esa-sceva/satcom-chunk-collection huggingface dataset:
# Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion
## 3 Framework for System Design and Experimentation
### Data Collection and Preprocessing  
To the best of the authors' knowledge, no data consisting of thermal images and gas sensors for the representation of gas has yet been collected and available in the open domain for direct use. Hence, in this work, data of the sensors and thermal imaging camera is collected manually for model training and validation purposes.  
The experimental data is collected through an array of 7 gas sensors as well as using the Seek Thermal Camera. The gas sensors were placed at 1 mm apart.  
In the experimentation, two specific gas sources are identified, namely, the gases originating from perfumes and gases emitted by incense sticks. The experimentation setup and workflow for the data collection is shown in Figure 4.  
Sensor readings and thermal images are recorded for each of these two gas sources were collected at a time interval of 2 s continuously for one and a half hours. In this time, gas was sprayed with an interval of 15 s for the first 30 min, with 30 s intervals for the next 30 min and 45 s intervals for the next 30 min. A few representative samples for three classes (no gas, perfume, and smoke) with the thermal image and corresponding gas array data are shown in Table 2. The sensors provide the analog voltage equivalent to the gas  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Sensor** & **Sensitive Gas** \\ \hline MQ2 & Methane, Butane, LPG, Smoke \\ MQ3 & Alcohol, Ethanol, Smoke \\ MQ5 & Natural Gas, LPG \\ MQ6 & LPG, Butane Gas \\ MQ7 & Carbon Monoxide \\ MQ8 & Hydrogen Gas \\ MQ135 & Air Quality (Benzene, Smoke) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Gas sensors and sensetive gases.  
Figure 4: Experimental Setup for data collection.  
concentration. The analog value is converted to the 10-bit digital value using an analog to digital converter. These 10 bits of digital values are shown for representation purposes in Table 1. Each sensor is sensitive to more than one gas, and hence sensors are calibrated appropriately. A data set in total consists of 6400 samples where 1600 samples belong to perfume, 1600 samples belong to image, 1600 samples belong to mixture of perfume and smoke and 1600 samples belong to neutral environment (No gas).
## 4 Experiment
### Ablation Study  
We further conducted an ablation study to verify the validity of each module in our model. The result is in Table 5. In the ablation experiment, we removed the dependency tree (dep), constituent tree (con), aspect-aware attention (aaa), and multi-head attention (mha) for comparison and verification.  
First, removal of the dependency tree (dep) leads to a drop in accuracy of 0.73%, 0.91%, and 2.65% on the Restaurant, Laptop, and Twitter dataset, respectively, which demonstrates that the dependency tree is important for extracting syntactic information. Then, with the removal of the constituent tree (w/o con), the model performance decreases by 0.9%, 1.26%, and 1.19%, respectively. It is shown that the constituent tree can effectively supplement the syntactic information extracted from the dependency tree. After, the removal of aspect-aware attention (w/o aaa) causes a decay in the accuracy of 0.37%, 0.31%, and 0.59%. As for 'w/o mha', the accuracy decreases by 1.17%, 1.75%, and 1.5% on the Restaurants, Laptop, and Twitter datasets, respectively. As a result, the ablation experimental outcomes confirm the contribution of both components.
# A Greedy Algorithm for Neighborhood Overlap-Based Community Detection
## 2 Terminology and Examples
### Neighborhood Overlap and Weak Ties  
The neighborhood overlap (NOVER) of an edge \((u,v)\)[11; 13] is defined as the number of vertices who are common neighbors of both \(u\) and \(v\) divided by the number of vertices who are neighbors of at least one of the two vertices \(u\) or \(v\) (excluding each other). Quantitatively,  
\[NOVER(u,v)=\frac{c_{uv}}{k_{u}+k_{v}-2-c_{uv}}\]  
where \(k_{u}\) and \(k_{v}\) are, respectively, the degrees of nodes \(u\) and \(v\), and \(c_{uv}\) is the number of common neighbors of both \(u\) and \(v\). The factor of 2 in the denominator is to account for excluding vertices \(u\) and \(v\) who are neighbors of each other. It is obvious that the NOVER values range from 0 to 1. The convention followed in the literature until now [11] is that edges with NOVER value below a threshold are classified as weak ties and the rest of the edges are classified as strong ties. An appropriate choice for this threshold value is very difficult to be fixed and depends on several characteristics (like the degree distribution of the nodes and the edge-to-node ratio, as seen in our simulation results) of the underlying network considered. Figure 1 illustrates an example to calculate the NOVER scores for the edges in a graph and their classification (as weak or strong ties) based on a threshold NOVER score of 0.50.
# Sphingolipidoses and Retinal Involvement: A Comprehensive Review
## 3 Ophthalmological Examination: A Key Tool in the Diagnosis and Management of Sphingolipidoses
### Fundus Photography  
Fundus imaging is a core technique for capturing detailed images of the retina. This is achieved using specialized camera systems that can be integrated into slit lamps or designed as standalone ultra-high-resolution devices. Some of these systems incorporate ultra-widefield technology, allowing for the acquisition of extensive retinal images in a single capture [20].  
Fundus photography is instrumental in tracking retinal disease progression by enabling comparative analysis of structural changes over time [20,21]. The integration of artificial intelligence further enhances its capacity for detecting pathological retinal features with increased precision [21]. In sphingolipidoses, fundus photography is useful for follow-up to monitor anatomical retinal changes that may occur during the course of the disease, or to assess potential modifications during pharmacological treatment. The main limitation is that it is not significantly useful in the preclinical phase before ophthalmoscopic retinal pathologic signs appear.
## 4 Electrochemical Sandwich Assays Combining Aptamers and Antibodies
The protein streptavidin was first bound to the IDE using 1,1-carbonyldimazole and then used to capture the biotinylated aptamer. The binding of IGF1 would result in a current increase upon a voltage sweep from 0-2 V across the 10 um IDE gaps. A detection limit of 10 fM was found and the formation of the sandwich structure was seen to increase the current levels. This sensor design involved a sandwich structure and electrodes but is not an actual electrochemical sensor. A summary of the results from these electrochemical assays using aptamers together with antibodies is presented in Table 3. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Analytic** & **Components of Sandwich Assay** & **Method of Detection** & **Linear Range** & **Limit of Detection** & **Ref.** \\ \hline H5N1 avian influenza virus protein & Screen-printed carbon electrode/Au nanoparticles/apatamer/H5N1/antibody alkaline phosphatase conjugate & Differential pulse voltammetry & 100 fM–10 pM 25–100 pM & 100 fM & [74] \\ \hline Lysozyme & Screen-printed carbon electrode/benzoic acid/apatamer/lyozyme antibody/alkaline phosphatase conjugate & Differential pulse voltammetry & 1 fM–5 nM & 4.3 fM & [75] \\ \hline Protein tyrosine kinase-7 (PIX) & Screen-printed electrodes/Au nanoparticles/apatamer/PIX/antibody labeled with alkaline phosphatase & Differential pulse voltammetry & 100 fM–10 pM & 100 fM & [76] \\ \hline Vascular endothelial growth factor-165 (VEGF) & Interdigitated gold electrodes/apatamer and triconine/VEGF/antibody-conjugated magnetic beads & Non-Faradaic impedance spectroscopy & 5 pg/mL–1 ng/mL & 5 pg/mL & [78] \\ \hline Amyloid \(\beta\)-oligomers & Glassy carbon electrode/apatamer/amyloid \(\beta\)/apatamer and triconine-modified Au nanoparticles & Differential pulse voltammetry & 0.5–30 nM & 100 pM & [79] \\ \hline Tau-381 protein & Au electrode/mercaptoethanol monolayer/anti-tau antibody/tau-381/Au nanoparticles with aptamer and submarine, Fe(CN)\({}_{3}\)-\({}^{3-4}\) in solution. & Differential pulse voltammetry & 0.5–100 pM & 0.5 pM & [80] \\ \hline Human immunoglobulin E (gE) & Gold electrode/antibody/apatamer-modified Au nanoparticles with methylene blue & Differential pulse voltammetry & 1–10,000 ng/mL & 0.52 ng/mL & [81] \\ \hline C-reactive protein & Glassy carbon electrode/Au nanoparticles/apatamer/silica microspheres with Au nanoparticles and Zn\({}^{3}\). & Square-wave voltammetry & 0.005 ng/mL–125 ng/mL & 0.0017 ng/mL & [82] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Electrochemical Sandwich Assays Combining Aptamers and Antibodies.
# RIS-Assisted Network Slicing Resource Optimization Algorithm for Coexistence of eMBB and URLLC
## 6 Summary  
This paper aims to solve the resource allocation problem in the coexistence scenario of eMBB and URLLC services by combining RIS technology. The problem is described as two optimization problems, i.e., the eMBB allocation problem and the URLLC allocation problem. To overcome the nonconvexity of these problems, we propose a two-stage eMBB allocation algorithm based on alternating iterations and a heuristic URLLC allocation algorithm based on a preconfigured RIS phase shift matrix, respectively. Simulation results show that the proposed algorithm has lower time complexity than other scheduling methods when the URLLC packet reception rate reaches about 95.5%. And the larger the URLLC load is, the more prominent its superiority is. In addition, as the network scales up, the RIS scheme chosen in this paper is well suited to achieving the tradeoff between maximizing URLLC reception and minimizing eMBB loss compared to non-deployed RIS. In the future, we will try to apply the algorithm to the resource allocation problem of heterogeneous vehicle networks, the power resource planning and allocation problem, etc.  
Figure 7: Traversal achievable rate assisted by different number of RIS reflection elements.  
**Author Contributions:** Conceptualization, X.S. and Z.Z.; methodology, X.S.; software, Z.Z.; validation, Z.Z., X.S., and X.L.; formal analysis, X.L.; investigation, X.L.; resources, X.S.; data curation, Z.Z.; writing--original draft preparation, Z.Z.; writing--review and editing, Z.Z.; visualization, X.S.; supervision, X.S.; project administration, X.S.; funding acquisition, X.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was partly funded by the National Natural Science Foundation of China (Grant no. 61961010), Guangxi Science and technology major special projects (Grant no. AA19046004), Natural Science Foundation of Guangxi (Grant no. 2021 AC19255), and Innovation Project of Guangxi Graduate Education (Grant no. YCSW2022314).  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Application of Dynamic Time Warping (DTW) in Comparing MRT Signals of Steel Ropes
## 2 Materials and Methods  
### MRT Methods  
Information about the current technical condition of the rope is obtained during non-destructive testing using the MRT magnetic method. Measurement data from MRT tests are recorded by the measurement path containing (Figure 3) the following:* A measuring head with
* the circuit of longitudinal magnetization of a fragment of a steel rope based on permanent magnets and magnetoguides;
* two searching coils on the E-core, wrapping the tested rope in two different ways, which generate LF1 and LF2 signals (also marked in the literature as LD1 and LD2, local defect) proportional to the speed of changes in the magnetic flux (features of magnetic anomalies) and the location of the defect in the cross-section of the rope, taking into account the influence of the structural features of the E-core and the rope magnetization circuit on the signal spectrum;
* two Hall sensors with a magnetic field concentrator located between the coils, which record the scattering field around the rope and generate a resultant LMA signal proportional to the strength of the magnetic field.
* A defectograph in which
* the influence of changes in the speed of rope scanning (type from 0.15 m/s to 4 m/s) on the amplitude of LF1 and LF2 signals using the signal from the encoder is compensated;
* signals LF1, LF2, LMA and recording time \(t\) are sampled in parallel with a set frequency in the TIMER mode or the resolution of the rope displacement scan in the ENCODER mode;
* measurement data discrete in time are saved on a non-volatile memory carrier;
* the course of the recorded time series is illustrated on the screen;
* measurement data are pre-processed (filtration and calculation of additional variables--rope scanning speed in ENCODER mode, LF1 integrals, defined diagnostic estimates);
* a simplified analysis of measurement data is carried out according to preset criteria in the time domain or order, including visual comparison of the results with the previous recording (reference result);
* the function of printing test results on a thermal printer or an external printer is available;
* data transfer to an external computer (for extended data analysis and data archiving) is carried out using a standard RS-232 or USB 2.0 port.
###### Abstract  
We carefully investigated the effects of La-Co co-substitution and magnetic field pressing (MFP) on the structural and magnetic properties of SrM hexaferrites. Samples composed of Sr\({}_{1-x}\)La\({}_{x}\)Fe\({}_{12-x}\)Co\({}_{x}\)O\({}_{19}\) were sintered at 1230 \({}^{\circ}\)C for 2 h in air with sintering additives composed of 0.7 wt% CaCO\({}_{3}\) and 0.7 wt% SiO\({}_{2}\). A single M-type phase was confirmed to exist up to \(x=0.3\). Rietveld refinement revealed a slight decrease in lattice parameter \(a\) and the unit cell volume (\(V_{cell}\)) with an increasing \(x\), while parameter \(c\) showed a significant decrease. The saturation magnetization (\(M_{\rm s}\)) values increased from 70.90 to 72.40 emu/g with an increasing \(x\) from 0.0 to 0.15 and then decreased to 71.38 emu/g with further increasing of \(x\) to 0.3, while the anisotropy field (\(H_{\rm d}\)) increased from 17.7 to 25.9 kOe, leading to a continuous increase in the intrinsic coercivity (\(H_{\rm d}\)), from 3.52 to 5.00 kOe, respectively. Using the MFP process, the \(c\)-axis of M-type hexaferrite grains could be effectively aligned to the applied field direction, which significantly affected the microstructures and, thus, magnetic properties of samples. Unlike non-MFP samples, exhibiting a significant increase in the average grain size (\(d_{\rm agg}\)) but almost unaltered average thickness (\(t_{\rm agg}\)) with an increasing \(x\) from 0.0 to 0.3, MFP-processed samples exhibited almost unaltered \(d_{\rm agg}\) values but a continuous decrease in \(t_{\rm agg}\). Consequently, the variation in remanent flux density (\(B_{\rm r}\)) versus \(x\) followed that of \(M_{\rm s}\) versus \(x\) and thus exhibited the highest \(B_{\rm r}\) of 4.05 kG for \(x=0.15\), leading to the highest maximum energy product (\([BH]_{\rm max}\)) of 3.62 MOGe. With an increasing \(x\) from 0.0 to 0.3, the \(H_{\rm d}\) values continuously increased from 3.14 to 3.84 kOe mainly due to a continuous increase in \(H_{\rm d}\), although they were significantly lowered in comparison with those of non-MFP samples because of a large increase in \(B_{\rm r}\) for a given composition \(x\). A higher \(M_{\rm r}/M_{\rm s}\) ratio always resulted in a larger \((BH)_{\rm max}\) in our samples regardless of \(x\). A careful comparison of the microstructures and magnetic properties between MFP and non-MFP samples provided valuable insights into a broad area of permanent magnet optimization.  
Keywords:SrM-type hexaferrites; La-Co substitution; saturation magnetization; magnetic anisotropy field; permanent magnet; magnetic field pressing +
Footnote †: journal: Applied Sciences
# Estimating Tetrachloroethene Sorption Coefficients Based on Soil Properties in Organic-Poor Soils
###### Abstract  
In the context of contaminated site remediation, the fate of chlorinated solvents in the subsurface and subsequent groundwater contamination is influenced by soil properties governing sorption. The solid-water distribution coefficient (\(K_{\mathrm{d}}\)) is a key parameter for modeling contaminant distribution and transport, essential for risk assessment and remediation planning. This study evaluated tetrachloroethene sorption isotherms in 34 low-organic-carbon soils from the Czech Republic, assessing the influence of soil properties on \(K_{\mathrm{d}}\). Soil samples exhibited variability in organic carbon content (<0.05-0.81%), with clay ranging from 0% to 64.9%, silt 5.1% to 71.2%, and sand 5.2% to 88.9%, specific surface area (0.41-64.39 m\({}^{2}\) g\({}^{-1}\)), particle density (2.05-4.09 g cm\({}^{-3}\)), and porosity (43.5-67.3%). Batch experiments were conducted using standard procedures, with \(K_{\mathrm{d}}\) values ranging from 0.379 to 2.272 L kg\({}^{-1}\). Statistical analysis grouped the soils into three textural classes: sandy, clayey fine, and silly loam. The findings reveal that organic carbon content and specific surface area are the primary predictors of \(K_{\mathrm{d}}\), while clay and sand also play a significant role in shaping sorption behavior. Multivariate regression models explained 63.6% to 98.5% of \(K_{\mathrm{d}}\) variability with high accuracy, as indicated by low root means square error (0.070-0.329) and mean absolute percentage error (3.8-28.8%) values. These models offer reliable predictions of sorption behavior, providing valuable tools for risk assessment and remediation strategies.  
prediction model; soil; sorption; sorption coefficient; tetrachloroethene
# Minimum-Cost Offloading for Collaborative Task Execution of MEC-Assisted Platooning
## 6 Numerical Analysis
### Application Profile  
We evaluate the efficiency of our algorithm in a cellular network composed of a BS with an MEC server. The distance between the leader and BS is \(\eta=0.5\) km. The distance between the adjacent vehicular transmitter and the receiver is \(\mu=0.008\) km. The platoon consists of nine members (i.e., \(m=9\)) and the distance between vehicles is fixed in the platoon. Assume that the antenna position of each vehicle is the same. Assume that the antenna position of each vehicle is the same. The communication mode is deployed in accordance with the relevant rules of IEEE 802.11p standard and LTE-V. The bandwidth and transmission power for V2V and V2I communications in the simulation are set according to the reference papers [31; 36]. The parameters of computation resource are set as follows: \(f_{0}=3000\) MHz, \(f_{1}=100\) MHz, \(f_{2}=650\) MHz, \(f_{3}=600\) MHz, \(f_{4}=620\) MHz, \(f_{5}=700\) MHz, \(f_{6}=800\) MHz, \(f_{7}=660\) MHz, \(f_{8}=1000\) MHz, \(f_{9}=550\) MHz. The other parameters in the simulation are summarized in Table 1.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline The number of platoon members & 9 \\ Bandwidth for V2V communication & \(B_{1}=20\) MHz \\ Bandwidth for V2I communication & \(B_{2}=100\) MHz \\ The noise power & \(\mathrm{N_{0}}=-174\) dBm/Hz \\ The transmission power of vehicle & \(g_{v}=23\) dBm \\ The transmission power of BS & \(\mathrm{\zeta_{MC}}=46\) dBm \\ The distance between the adjacent transmitter and the receiver & \(\mu=008\) km \\ The distance between the leader and BS & \(\eta=0.5\) \\ the computation resource cost of vehicle & \(a_{v}=1\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters.
## 3 Reclassification of Emergency Messages Dissemination Approaches
### Model System for PhEMS4 VN  
Contrary to any approach reviewed in Section 2, to make as many entities aware as possible in the whole environment, or to route packets through contiguous entities from points to other regions in the environment and/or exclusive entities, we propose that the communication enable collaborative behaviors among entities that pursue a common task and are in specific regions spatially close and recent in time in relation to where and when data are created and, thus, describe that part of the environment with more accuracy than other data. A feasible solution, as anticipated in Section 1, PhEMS4 VN is a bio-inspired communication approach with a focus on achieving a common task through exchange of messages under space-time constraints based on stigmergy found in social insects colonies,  
Figure 2: Proposed classification for message dissemination in VANETs [8, 19, 20, 21, 22, 24, 25, 28, 29, 30, 31, 32, 33, 34, 39, 40, 41, 42, 43, 44]. more specifically ants' pheromones. Therefore, in our mechanism, the messages are consumed only by entities that are coupled in space-time with a pheromone. The pheromone contains space-time data about incidents, provoked by entities with sudden stops that might endanger the occupants of other entities. The operation of PhEMS4 VN in a basis case is summarized as follows:  
* A vehicle experiencing an undetermined failure stops and an incident begins. * The failed vehicle periodically segregates messages and sends them to the closest RSU in order to indirectly inform other vehicles of the incident for as long as the incident lasts. * The fixed entity or RSU acquires the message and creates a pheromone to be sent, also periodically, to those vehicles coupled in space-time with the incident so that they can be made aware of it. * Vehicles around the location of the incident while it lasts consume pheromone messages and, if the planned route is obstructed by the incident, they will be instructed to take a detour. * Note that the pheromones sent are the emergency messages disseminated to the mobile entities coupled in space-time with the incident. * Entities not coupled in space-time are never aware of the incidents, as they probably are if broader other mechanisms are applied. * If the incident ends and messages stop being produced, the pheromone will decay and die, thus delimiting its lifetime.