esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Chelating Activity of the Fe\({}^{2+}\) Ion  
The chelating capacity of Fe\({}^{2+}\) was tested using the ferrozine method [55]. Metal ion chelation has a crucial role in the inhibition of reactive oxygen species production [56]. A calibration curve was prepared by utilising aqueous solutions of FeSO\({}_{4}\) to measure Fe\({}^{2+}\) ions. First, an initial FeSO\({}_{4}\) solution with a Fe\({}^{2+}\) content of 0.53 mmol/L was prepared. Next, a ferrozine initial solution (concentration of 3.2 mmol/L). Then, 1000 \(\mu\)L of the initial FeSO\({}_{4}\) solution (final Fe concentrations of 3, 1.2, 0.6, and 0.3 mg/L) and 1000 \(\mu\)L of ferrozine were introduced into 10, 25, 50, and 100 mL volumetric flasks. The flasks were filled with distilled water, sealed firmly with a stopper, and left at room temperature for 10 min. The absorbance of the test solutions was measured using the Thermo Scientific GENESYS 50 equipment at the wavelength \(\lambda\) = 562 nm, resulting in a calibration curve for Fe\({}^{2+}\) ions (y = 0.4888x + 0.0064, R\({}^{2}\) = 0.999).  
In the following step, 1000 \(\mu\)L of the initial FeSO\({}_{4}\) solution, 100 \(\mu\)L of FSE, and 1000 \(\mu\)L of ferrozine were added to 10 mL volumetric flasks. The flasks were filled with distilled water, sealed tightly with a stopper, and allowed to incubate at room temperature for 10 min. The absorbance of the solutions was measured using a spectrophotometer at a wavelength of \(\lambda\) = 562 nm. Three independent tests were conducted.  
The chelating activity (\(ChA\)) of Fe\({}^{2+}\) ions was calculated using the following formula shown in Equation (3):  
\[ChA=\frac{\left[(C_{F2+b.s.}-C_{F2+t.s.})\cdot V_{s}\right]}{V_{FSE}}.100\% \tag{11}\]  
where:  
\(ChA\)--chelating activity of Fe\({}^{2+}\) [mg/L],  
\(C_{F2+b.s.}\)--concentration of Fe\({}^{2+}\) ions in the blank sample [mg/L],  
\(C_{F2+t.s.}\)--concentration of Fe\({}^{2+}\) ions in the tested sample [mg/L],  
\(V_{s}\)--total volume of solution introduced into volumetric flasks [L],  
\(V_{FSE}\)--volume of FSE introduced into volumetric flasks [L].  
We used the same methods to evaluate the stems extract for comparison. The extraction of stems was carried out using the ultrasonic method. For this purpose, 20.0 g of ground plant material (in the amount of 6.40%) was introduced into 300 mL of distilled water, and extraction was carried out using an ultrasonic bath at 40 kHz (for 20 min at 40 \({}^{\circ}\)C), after which the extract obtained was filtered using a pressure funnel through a Whatman paper filter (EEA03).
# Wireless Positioning in IoT: A Look at Current and Future Trends
## 2 Related Work  
At this moment, to the best of the authors' best knowledge, there are no comprehensive comparisons in the literature between different IoT protocols in terms of their positioning capabilities. There are, however, other studies that compare specific IoT technologies and which look at IoT from the communications point of view, as well as studies focusing on positioning with a particular technology, such as narrow-band IoT (NB-IoT) or BLE. In this section, we highlight the related work from literature studies.  
A survey of localization methods for 5G, having a short section also on IoT positioning has been recently published as a white paper in COST action CA15104 [1]. It has also been emphasized in this paper that localization will become a key component of future 5G systems and it has been pointed out that accurate future localization solutions in 5G should exploit the multipath and non-line-of-sight information and should put more emphasis on heterogeneous data fusion mechanisms. However, such advanced solutions would also increase the power consumption on the devices and are not well-suited for the majority of IoT systems. By distinction with the work in [1], our paper focuses mostly on low-cost low-power consumption IoT solutions.  
The authors in [2] focus on the Long-Term Evolution (LTE) Machine type communications (LTE-M) and Narrow Band Internet of Things (NB-IoT) protocols and their positioning capabilities. It was shown in [2] that at 46 dBm power of the transmit AN, positioning accuracy goes to around 10 m and that NB-IoT protocol supports better positioning accuracy than LTE-M protocol. A related study can be found in [3]. The focus in [3] is on indoor localization via improved received signal strength (RSS) fingerprinting in generic IoT devices. The results are based on 802.11\(n/b/g\) signals where location errors below 5 m are achieved in more than 50% of the studied cases.  
In [4], the authors investigate a time-domain based positioning with additional frequency hopping for the NB-IoT system. The obtained positioning accuracy is down to 30-50 m under strong signal-to-noise ratio conditions, and it deteriorates quickly for medium and low signal-to-noise ratios.  
A study complementary to our work is found in [5], where IoT positioning is looked at from the perspective of security, privacy and robustness of the localization technology. No positioning resultswere reported in the study. Another complementary study is found in [6] in which the authors focused on existing and emerging software and hardware platforms for IoT applications, but positioning was not part of that study. IoT positioning has recently been considered in [7] from the point of view of spoofing resistance in time of arrival (TOA) ultra-wideband (UWB) for IoT systems.  
Other complementary comprehensive studies, focusing solely on the communication aspects of IoT, are found for example in [8; 9].
# A Comparative Analysis of IMUs and Optical Systems in Layup Shot Biomechanics
## 4 Discussion  
This study evaluated the accuracy and reliability of IMUs (Xsens) in capturing basketball layup kinematics. The goal was to assess their suitability for performance analysis in representative environments, such as the basketball court, compared to an optical motion capture system (Vicon). The findings demonstrated strong agreement for global metrics such as jump height and take-off angle but highlighted significant RMSD for joint-specific measures, particularly in the flexion-extension joint angle of the shoulder. This aligns with numerous validation studies that indicate task-specific and anatomical plane-dependent performance of IMUs [11, 29]. Furthermore, a between-condition analysis revealed an ability of Xsens to detect relative changes in joint angle kinematic adjustments when task-relevant condition constraints were incorporated that was comparable to Vicon. These results emphasise the potential of IMUs as portable alternatives for field-based biomechanical assessments while identifying limitations in capturing detailed joint-level kinematics.  
The findings of the present study demonstrate a high level of agreement between the Vicon and Xsens systems for measuring jump height and take-off angle. The paired-samples \(t\)-test showed no significant differences between the systems, highlighting the comparability of outputs. Specifically, the mean jump height values were identical (jump height (Table 1), with a minor mean offset of 0.025 m. Similarly, take-off angle (Table 1) showed minimal divergence with a mean offset of 1.5\({}^{\circ}\), confirming the systems' consistency in measuring key metrics for dynamic movements, such as the basketball layup. These two metrics, derived from the system-calculated COM location, demonstrate reliable tracking of the COM. This aligns with previous studies highlighting that COM displacement and jump height are less influenced by drift and alignment errors compared to joint-specific measures [30, 31]. The excellent reliability scores for jump height and take-off angle (ICC = 0.97-0.96) indicate strong consistency, ensuring observed variations reflect performance differences rather than measurement error.
## 3 Preliminaries
### Network Model  
The network model of the proposed scheme in 5G-enabled vehicular networks comprises a trusted authority (TA), some fixed 5G base stations (5G-BS), and mobile vehicles equipped with OBUs, as illustrated in Figure 1. The details of the components are described below.  
* Trusted authority (TA): the TA has a large storage capacity and computing power. TA is in charge of issuing system parameters and secret keys for each corresponding vehicle in 5G-enabled vehicular networks. In addition, the TA is responsible for generating sensitive data for each domain. Each network has a group of duplicate TAs to avert bottlenecks and a single point of failure. Therefore, the entire 5G-enabled vehicular networks are segmented into many geographical areas, and each area has a TA in the proposed scheme [40].
* 5G base station (5G-BS): The 5G-BS is a wireless communication device located at intersections or hotspots. The 5G-BS is a transceiver with wide-area coverage and super-fast transmission and is usually security-hardened to prevent compromise. However, it is only an intermediary transmission medium between TA and vehicles; therefore, it does not have any storage and does not execute any verification process.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Notations** & **Definitions** \\ \hline \(P\) & The generator of the cycle additive group \(G\) \\ \(P_{pub},s\) & The key pairs of the system \\ \(sk_{i},r_{i}\) & The random values from the group of multiplicative \(Z_{q}^{*}\) \\ \(H_{1},H_{2},H_{3}\) & The three secure one-way hash functions \\ \(PW_{i}\) & The login password for a driver \\ \(DID_{i},ID_{i}\) & The real identity of driver and vehicle \\ \(A_{i},B_{i}\) & The two secret authentication parameters \\ \(V_{i}\) & The i-th vehicle \\ \(s_{d},P_{pub}^{d}\) & The key pairs of an updated domain \\ \(ET_{i}\) & The valid period of this domain key \(s_{d}\) \\ \(M_{i}\) & The safety message \\ \(T_{i}\) & The current timestamp \\ \(1_{i}\) & The multiplication inverse \\ \(\overline{\sigma_{i}}\) & The message signature \\ \(AID_{i}\) & The pseudonym ID for each vehicle \(V_{i}\) \\ \(vbs_{i}\) & The variables \\ \(||,\oplus\) & The concatenation operation and exclusive OR \\ \(\equiv\) & The congruent modulo \\ \hline \hline \end{tabular}
\end{table}
Table 1: Notations.  
Figure 1: The network model of 5G-enabled vehicular networks.  
Vehicles: Vehicles in the proposed scheme are the terminal nodes in 5G-enabled vehicular networks that enjoy all types of applications. A realistic TPD is usually fitted on the vehicle's OBU. Vehicles can exchange data with each other or local TAs using the 5G protocol.
# A Study of Multi-Step Sparse Vessel Trajectory Restoration Based on Feature Correlation
## 2 Related Work
### Traditional Mathematical Modeling Methods  
Traditional methods for vessel trajectory data restoration rely on an in depth understanding of the data and accurate modeling, which detects abnormal points and repairs sparse trajectories by building complex mathematical equations and models describing the vessel's operation. These methods usually establish a functional relationship between latitude, longitude, and time and use interpolation methods to build the restoration model.  
To realize the reconstruction of vessel trajectories in different sailing states in a port, [PERSON] et al. [18] constructed a multi-state vessel trajectory reconstruction model based on linear regression and a spline interpolation method based on the quantitative analysis of the quality of the AIS data, which fit and reconstructed vessel trajectories based on the identification of the sailing states of the vessels in the port area. [PERSON] et al. [19] address the previous algorithms that do not consider the dynamic information of vessel operation; it is difficult to repair the curve of the ship trajectory, resulting in low accuracy, so they improved the linear interpolation algorithm and proposed a two-way iteration and weighted average of the trajectory repair iterative algorithm, which effectively takes into account the dynamic information of the ship, thus improving the restoration of the trajectory accuracy and at the same time compressing the algorithm execution time. [PERSON] et al. [20] focused on single-ship AIS data and proposed a trajectory anomaly identification and repair method, which utilizes the parameter information of the AIS data itself to determine the anomalies and then repairs the trajectory anomalies by using the cubic spline interpolation method, which is effective in eliminating the abnormal data mutations of the parameters to make the repaired trajectory changes smoother. Also, [PERSON] et al. [21] proposed a vector analysis-based vessel trajectory anomaly detection and track repair method, which analyzes the characteristics of AIS raw data to establish the trajectory basis vectors, uses the basis vectors as the basis for classifying the vessel trajectory categories, and finally reconstructs the trajectory according to the unused trajectory line type categories by using different interpolation methods, respectively.  
Although traditional methods can achieve better restoration results, when faced with too many missing and abnormal trajectory points or complex navigation environments, these methods adopt the processing method of screening out sparse and abnormal trajectory points, which often makes it difficult to achieve higher accuracy in the restoration results. Therefore, it is necessary to screen the sparse and abnormal trajectory data points and modify the trajectories by interpolation methods without abandoning them and to label them to improve the restoration accuracy.
# Weighted Cluster-Range Loss and Criticality-Enhancement Loss for Speaker Recognition
## 4 Experiments and Results
### Input Feature  
Following the experience in [9], we adopt log Filter-bank (Fbank) coefficients as the input feature for the neural network. Given an utterance from a speaker, it is first framed by the Hamming window with a duration of 25 ms and a shift of 10 ms. After that, silent frames are removed, and we extract log Fbank coefficients for each frame with the dimension being 64. Then, a fragment of continuous 320 frames is randomly selected from the sequence. Thus, for each utterance, an input feature of 320 \(\times\) 64 is given.
# Multi-Scale Twin Networks for Coastal Zone Change Detection in Remote Sensing Imagery
## 3 Principles and Methods
### Contextual Information Integration
#### 3.2.1 Feature Fusion  
There are significant differences in spatial resolution and the receptive field between multi-scale features, and feeding them directly into the SDAM module could introduce redundancy and increase the model's computational burden [21]. Therefore, we resized the feature maps from three different scales of the same branch to a common scale and then fused them element-wise. This effectively integrates information from different scales, reducing redundancy and allowing subsequent modules to process the features more efficiently and focus on extracting useful information. By resizing the feature maps to the same scale, the fused feature map removes scale differences, enabling unified processing of input features in subsequent modules. This helps capture changing area information more accurately.  
In addition, changes in coastal zones typically manifest as features of various types and scales, such as localized geomorphological changes and global land-use patterns. High-scale features capture global semantic information, while low-scale features retain rich local details. Feature fusion improves both global and local semantic representations of the model, and element-wise fusion preserves the benefits of all scales in the feature map [22]. This gives a distinct advantage when dealing with diverse changes in the coastal zone.
## 2 Experimental Setup and Materials  
### Device Design  
We assembled an experimental setup in accordance with the optical scheme shown in Figure 1, which is a laser scatterometer sensing the fat content of milk. The radiation of a laser diode with a wavelength of 532 nm and a power of 5 mW undergoes diffuse scattering in milk flowing through a transparent cylindrical quartz tube (outer diameter 15 mm, wall thickness 1 mm). The ends of the tube are terminated with fittings for connecting milk hoses. The angular distribution of the scattered light intensity is recorded by a set of eight photodiodes arranged around a circle with an angular step of 18\({}^{\circ}\). The photodiodes have a silicon photosensitive element of 3 \(\times\) 3 mm\({}^{2}\) area with a plastic molded lens. The radius of this circle is chosen to correspond to the focus of an imaginary cylindrical lens, into which the tube would turn when filled with water. The photodiodes P1-P8 are divided by gaps into three groups covering the angular ranges of forward scatter (0\({}^{\circ}\), 18\({}^{\circ}\), 36\({}^{\circ}\)), side scatter (72\({}^{\circ}\), 90\({}^{\circ}\), 108\({}^{\circ}\)), and backscatter (144\({}^{\circ}\), 162\({}^{\circ}\)). Before reaching the photodiodes, the scattered light field is limited by rectangular diaphragms 1 mm wide, made in a plastic ring. The photodiodes operate in the photoconductive mode. Being amplified, the photodiode signals are digitized by an ADC ADS 1256 connected to an Arduino Leonardo microcontroller. The microcontroller switches on the laser module in the square-wave mode.  
Figure 2 shows a photograph of a prototype device that implements the scheme in Figure 1.  
Figure 1: Optical scheme of the laser scatterometric sensor: (1) laser diode with a wavelength of 532 nm; (2) cylindrical tube of 15 mm diameter filled with flowing milk; (3) axial photodiode array P1-P8; (4) ring with rectangular diaphragms.  
The plastic parts of the device were made using FDM 3D-printing technology.
# Reflection Propagation Law of Electromagnetic Waves in U-Shaped Roadway
## 3 U-Shaped Roadway Model and Reflection Path Validity
### Reflection Path Validity
#### 3.2.1 Four-Time Valid Reflection Paths  
Figure 6 shows the two-dimensional four-time valid reflection paths, where the combination of secondary reflection from point T to point P and secondary reflection from point P to point \(R\) as an example.  
Figure 5: Calculation of reflection point.  
* Create a primary mirror image of the emitting point T with respect to plane \(m_{1}\) and obtain the primary mirror point I\({}_{1}\).
* Set point I\({}_{1}\) as the base point, create a secondary mirror image in plane \(m_{2}\), and obtain a secondary mirror point I\({}_{12}\).
* Connect point I\({}_{12}\) with point P, and the intersection point of plane \(m_{2}\) is A\({}_{12}\).
* Connect point A\({}_{12}\) with point I\({}_{1}\), and the intersection point of plane \(m_{1}\) is point A\({}_{1}\).
* Points T, A\({}_{1}\), and A\({}_{12}\) are connected sequentially to form a secondary valid reflection path.
2. A primary mirror of relay node \(P\) is made with respect to plane \(m_{5}\) to obtain the primary mirror point I\({}_{5}\), and a secondary mirror in plane \(m_{2}\) is made based on this point to obtain the secondary mirror point I\({}_{52}\).
* Connecting point I\({}_{52}\) with point \(R\), the intersection point in plane \(m_{2}\) is A\({}_{52}\).
* Connecting point A\({}_{52}\) with point I\({}_{5}\), the intersection point in plane \(m_{5}\) is A\({}_{5}\).
* The connecting points P, A\({}_{5}\), A\({}_{52}\), and R form a secondary valid reflection path in that order.  
The transmitting point T to the relay node \(P\) has six reflecting surfaces, and each surface theoretically has a primary mirror point. There are, therefore, a total of six primary mirror points, and each one has five secondary mirror points in addition to its own reflective plane. The transmitting point T to the relay node \(P\) therefore has 30 secondary mirror points, that is, 30 reflection lines. The relay node \(P\) to the receiving point \(R\) therefore also has 30 secondary mirror points, that is, 30 reflection lines. This combination, therefore, has a total of 60 points and 900 reflection lines. Similarly, for the combination where there is one reflection from the transmitting point T to the relay node \(P\) and three reflections from the relay node \(P\) to the receiving point \(R\), and the combination where there are three reflections from the transmitting point T to the relay node \(P\) and one reflection from the relay node \(P\) to the receiving point \(R\), there are theoretically 156 mirror points and 900 reflection lines. Therefore, all combinations of the four-time reflection paths theoretically have a total of 372 mirror points and 2700 reflection lines.
# Plate Size Effects in Gravelly Soil Based on In Situ Plate Load Tests and Finite Element Analysis
## 2 Geotechnical Profile and Soil Parameter  
### Geotechnical Profile  
The Kahaluo Jinsha River Bridge [15], situated at the boundary between the Sichuan and Yunnan provinces in China, is a highway suspension bridge. Geological surveys indicate that the slope on the Sichuan side of the bridge site consists of a thick overburden layer made up of breccia, gravel, boulders, pebbles, and silty clay, classified as medium to hard soil. The overburden is stratified as follows from top to bottom: Quaternary Holocene landslide deposits, primarily composed of silty clay with gravel, breccia, and boulders, with a drilling-revealed thickness of 4.0 to 14.0 m, mostly in a slightly dense state. The Quaternary Upper Pleistocene landslide deposits, reaching a maximum thickness of 145 m, are composed of silty clay mixed with gravel, breccia, and boulders, underlain by coarse sand from the Upper Pleistocene alluvial deposits, creating a steep soil slope. The weathering of rock in this layer weakens gradually from top to bottom, while the overall density increases, consisting mainly of medium-dense to dense gravelly soil and boulders. The Quaternary Upper Pleistocene alluvial deposits are partially interspersed with pebbles and cobbles, with drilling showing a thickness of about 22 m and a lenticular distribution. The geological profile is shown in Figure 1.  
Figure 1: Geological profile.  
Based on Chinese code DL/T 5356-2006 [16], the particle size distribution analysis of the geotechnical mass revealed that it consists of well-graded gravel. Particles with sizes between 20 mm and 100 mm constitute 20% to 25% of the total mass, with 20 mm particles being predominant.
# Molecular Mechanisms of Topography Sensing by Osteoblasts: An Update
## 2 Influence of Topography on Cells
### Unordered Topographies
[PERSON] and colleagues showed that implants made of rough titanium produced by sandblasting and acid etching led to a higher bone/biomaterial contact area and a higher push out force required to remove the implant, demonstrating an increased osseointegration of the biomaterial [19]. The induction of bone production by biomaterials can also be achieved through the commitment of MSCs to the osteogenic lineage. There again, roughness seems to favor the osteogenic differentiation and behavior of MSCs. These cells cultured on rough titanium produced by sandblasting and acid etching exhibit a higher ALP activity, OCN levels and Runx2 expression, although the differential remains somewhat modest [26]. Titanium etched by Reactive Ion Etching (RIE) to generate a nanoroughness also increases ALP expression of MSC cultures. Interestingly, increase in calcium and phosphate signal as measured by Energy-dispersive X-ray spectroscopy (EDX) confirmed that the osteogenic commitment of MSC results in higher deposition of mineralized matrix on the rough surface as opposed to the smooth control [37]. Recently, [PERSON] and colleagues (2021) showed that titanium implants modified by acid etching and anodizing had similar effects both in vitro and in vivo. It enhanced cell proliferation and osteoblast differentiation in vitro, and increased bone production in vivo [38]. [PERSON] and colleagues also found similar osteogenic results in vitro and in vivo incorporating strontium oxide to titanium surfaces [39]. These confirm that unordered surfaces can be a good inductor of osteoblast differentiation.