esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Calculation Method of Main Cable Curve: Segmented Catenary Method  
### Single Segmented Catenary  
The single segmented catenary method assumes three points. First, the main cable material conforms to [PERSON]'s law. Second, the main cable is an ideal flexible cable, only bearing tension. Third, the change of cross-sectional area due to the elastic deformation of the main cable is ignored. Under these assumptions, due to gravity, the main cable shape is a curve, which can only bear the forces \(T_{A}\) and \(T_{B}\) along a tangent. When the suspension bridge is constructed, there is no horizontal force acting along the main cable, so that the horizontal force of the main cable \(H\) is a constant. In this study, a segment of a single main cable is taken as the research object, and the force situation is shown in Figure 1. According to [PERSON] (2007) [27], the calculation process of single-segment catenary equation of main cable system is shown below:According to [PERSON]'s law, the equilibrium equation of the segment element can be formulated as  
\[\sum y=0. \tag{1}\]  
Then, Equation (1) can be written as  
\[H\frac{dy}{dx}+\frac{d}{dx}\bigg{(}H\frac{dy}{dx}\bigg{)}dx+q(x)dx-H\frac{dy}{dx} =0. \tag{2}\]  
Additionally, Equation (2) can be derived as  
\[H\frac{dy^{2}}{d^{2}x}+q(x)=0. \tag{3}\]
# Mixed Reality Enhanced User Interactive Path Planning for Omnidirectional Mobile Robot
## 3 Mixed Reality System
### Microsoft HoloLens  
HoloLens is a head-mounted MR device with a Windows system installed, as shown in the Figure 2. It is equipped with a 32-bit central processing unit (CPU), a graphics processing unit (GPU), and a special holographic processing unit (HPU). The HPU can be used to process a large amount of holographic and sensor data, and achieve motion tracking, spatial positioning, and other functions, which are of great significance in the MR device. Various information fusions of the inertial measurement unit (IMU), the environment understanding camera, a depth camera, and an ordinary camera, enable the device to literally render the virtual environment, giving the wearer a better sense of immersion [32]. In addition, HoloLens has a clear advantage when interacting with robots. As a fully stand-alone device, it can be used independently without wired connection with other hardware during use, which is convenient for the wearer to move with the robot [33]. At the same time, a variety of interaction methods also make the robot control methods diverse.  
Figure 1: Diagram for the system of research.  
The development of the HoloLens requires the HoloToolKit development kit, Unity3D, and Visual Studio. The HoloToolKit provides some scripts and components necessary to develop it. Unity3D was used to design a mixed reality application suitable for HoloLens in combination with HoloToolKit, and then Visual Studio deployed the designed application in HoloLens.  
In this paper, HoloLens has two functions. One is to send control instructions and position of virtual obstacles to the mobile robot, to control the movement of the robot. The other is to receive the robot motion map and planning path, to master the robot motion information more comprehensively.
## 3 System Configuration
### Mid-Infrared Tunable Lasers
#### 3.1.3 Mid-Infrared Vertical-Cavity Surface-Emitting Lasers  
MIR VCSELs have been paid great attention in the past decade for their advantages of low power consumption, low beam divergence, narrow and single-fundamental-mode, high wavelength tunability, and on-wafer testing capability [45]. The buried tunnel junction (BTJ) concept yields high-performance VCSELs in the wavelength ranges of 1.3-2.6 \(\upmu\)m [75] and 2.3-3.0 \(\upmu\)m [76], respectively. An interband cascade VCSEL has achieved lasing to \(\lambda\)\(\sim\)3.4 \(\upmu\)m in pulsed mode at temperatures up to 70 \({}^{\circ}\)C [77], and a 4 \(\upmu\)m VCSEL has been developed by using a single-stage active region with eight type-II quantum wells combined with BTJ technology [78]. VCSELs operate with very low threshold currents of several mA and very low power consumption of milliwatts. They provide a single mode by distributed Bragg reflector with a moderate linewidth of tens of MHz. VCSELs are particularly suited for compact and battery-powered sensors.
## 5 Case Study: \"11.28\" Rockburst in Jinping II Drainage Tunnel
### Model Establishment and Mechanical Parameters  
A corresponding 3D tunnel excavation model considering a nearby rigid structural plane is established according to the project overview. The overall dimensions of the numerical model were 40 m \(\times\) 5 m \(\times\) 40 m, and the excavation diameter of the drainage tunnel was 7.2 m. To meet the requirements of block size and improve the calculation accuracy and efficiency, from the tunnel to the boundary, the mesh division gradually becomes larger, and the edge length of block size is set between 0.1 m and 1 m. The Mohr-Coulomb constitutive model is adopted for the rock block, and the rock mechanical parameters are determined according to the actual marble of Baishan formation (T2b) on the field, and Table 5 shows the specific macro mechanical parameter values [33]. The contact constitutive model adopts the Coulomb-slip model, considering that it is difficult to calibrate the specific contact parameters of the virtual joints and structural plane in the actual situation, it is assumed that the parameter settings of the structural plane are consistent with the parameters in Section 3.2. The stress boundary conditions are set based on the results of the ground stress test in the Jinping II drainage tunnel. Table 6 shows the specific parameter values, including \(\sigma_{\times}\), \(\sigma_{y}\), \(\sigma_{z}\), \(\tau_{xy}\), \(\tau_{yz}\), and \(\tau_{xz}\) that are the normal stress and shear stress acting on the \(x\), \(y\), and \(z\) planes along the \(x\), \(y\), and \(z\) directions, respectively.  
Figure 9: Schematic of “11.28” extremely intense rockburst location and structural plane structure: (**a**) Map of China and location of the station; (**b**) Location of the tunnels; (**c**) Location of “11.28” rockburst; (**d**) Layout of the structural plane.
## 4 Data Transmission
### DS-SS proposal
#### System description and results  
**Emitter.** The emitter block diagram is depicted in Figure 4.a. First an interleaver and a rate 1/3 turbo coder is applied to the raw data. The coded data is then divided in two blocks: one block of bits of length multiple of \(n\) is BPSK or QPSK modulated, the other block of bits of length multiple of \(m\) is used to determine the spreading code. In pure DS-SS signaling no modulation is done, _i.e._, \(n=0\). The transmitted frames consist of a preamble followed by the spread data multiplexed with channel estimation M-sequences. Let us recall that in pure DS-SS signaling no modulation is done, _i.e._, \(n=0\), therefore channel estimation is not required. Finally, the signal is filtered using a root raised cosine and delivered to the up-converters.  
**Receiver.** The receiver block diagram is depicted in Figure 4.b. As previously described, fine frequency synchronization is achieved by using the preamble information. Then an impulsive noise limiter is used to improve the receiver performance. Channel estimation is obtained by means of correlation of the input signal and a replica of the M-sequences multiplexed in the frame. Then the signal is despread, demodulated and decoded to obtain the information data. The SNR is estimated from this data in order to evaluate the performance of the configuration under test.  
**Results.** An example of the experimental results is depicted in Figure 5, where the scatterplot of the BER measured in a 972 coded bits frame (BER\({}^{{}^{\prime}}\)) versus the estimated SNR is shown. Every cross corresponds to the demodulation of a single frame. For the configuration under test, if the receiver was only limited by Gaussian noise all the crosses should lay between the two continuous lines with a 90% probability. However, most of the crosses are located outside that region, shifted to higher SNR.  
Figure 4: DS-SS signaling emitter (a) and receiver (b) block diagram.  
As expected, the implemented receiver exhibits lower performance due to mutlipath fading, nonlinear amplification, _etc._ Although the improvement of the receiver algorithms could increase the performance of the reception, a 3 dB loss of SNR is a realistic assumption when dealing with this ionospheric channel.  
Many different configurations have been compared, depending on the occupied bandwidth, the sequence length (processing gain) and the modulation, and a scatterplot has been obtained for each configuration under test. On the basis of these results, we concluded that DS-SS techniques are a successful choice for data transmission in very long distance ionospheric links. We showed that a 150 bps transmission can be achieved in a 3 kHz channel bandwidth with a signal to noise ratio of -5 dB. In those conditions, more than 90 % of the packets were received without errors. This speed is sufficient for the transmission of low rate data from most of the remote sensors in the SAS.
## 4 Implementation and Discussion
### Performance Analysis  
#### 4.2.1 No Single Point of Failure  
PoF based medical decision achieving scheme is distributed in nature while a centralized system is used by other schemes [2; 3]. P, D, I\({}_{\text{c}}\), and C\({}_{\text{P}}\) also have full control over their decisions, sensitive information (PII, PPII), and identities. Blockchain stores data securely in multiple physical locations, thus no single point of failure presents. A single node cannot modify data independently to hinder overall integrity. The validity of the exchanged data and associated entities are rightly preserved.
# Biomedical Applications of Polymeric Cryogels
## 3 Cryogels in Medical Applications
### Immobilization of Biomolecules  
In affinity-based separation and purification of biomacromolecules a specific ligand is immobilized onto cryogel matrices. The immobilization of ligand in cryogel matrices can be applied with two approaches; (i) covalent coupling of the ligand to the prepared cryogel matrix and (ii) physical attachment of ligand in during the polymerization [24]. The low-pressure drop and lack of diffusion resistance are the main advantages of cryogels that causes to apply viscous samples.  
Antibody immobilized cryogel matrices provide a selective removal of specific antigen from a complex mixture. In autoimmune diseases such as rheumatoid arthritis, plasma exchange treatment has been used to remove of autoantibodies produced during these diseases. The disadvantages of plasma exchange treatment can be altered by using affinity adsorption therapy for plasma exchange. For example, in a study, poly(2-hydroxyethyl methacrylate) (PHEMA) cryogel carrying protein A was used for the removal of immunoglobulin M (IgM) from human plasma [25]. The PHEMA cryogel was prepared by bulk polymerization, which proceeds in an aqueous solution of monomer frozen inside a plastic syringe. As seen in Figure 2a, the PHEMA cryogel has a continuous matrix with 10-200 um pores. Pore volume in the PHEMA cryogel was 71.6%. Protein A was covalently immobilized onto the PHEMA cryogel via cyanogen bromide activation. The PHEMA cryogel was contacted with blood in vitro system for the determination of blood-compatibility (Figure 2b). IgM adsorption capacity decreased significantly with the increase of the plasma flow rate. An increase in the flow rate reduced the plasma volume treated efficiently until breakthrough point and therefore decreased the retention time of the PHEMA cryogel column. The maximum IgM adsorption amount was 42.7 mg/g. IgM could be repeatedly adsorbed and eluted without noticeable loss in the IgM adsorption amount. Separation of target molecule with high specificity and yield provide advantages to cryogels immobilized with monoclonal antibodies. [PERSON] et al. coupled anti-CD34 monoclonal antibodies to protein A-PVA cryogel beads for capturing human acute myeloid leukemia KG-1 cells expressing the CD34 surface antigen on the surface [26].  
Figure 2: Scanning electron microscopy (SEM) images of the PHEMA cryogel **(a)**, Flow behavior of whole blood through a PHEMA cryogel column **(b)**[25].  
In another study, apoproteinB100, a ligand against the main protein component of low-density lipoprotein (LDL) was used for the selective removal of harmful LDL without decreasing useful high-density lipoprotein (HDL) in hypercholesterolemia. [PERSON] et al. prepared protein A immobilized cryogels carrying Anti-LDL antibody. They successfully removed approximately 59% of the initial LDL from the hypercholesterolic plasma [16].
# Quality-of-Service-Linked Privileged Content-Caching Mechanism for Named Data Networks
## 5 Results and Discussion
### Content Store Size and Hit Rate
#### 5.3.2 Content Store Size and Hit Rate for Overall Traffic  
The simulation evaluates the content store hit rate corresponding to the size of a content store size of QoS nodes for the overall traffic, including priority content (20%) and non-priority content of the entire network. The results are depicted in Figure 6, which are compared with EQPR, PRR, probability cache, and LFU and LFF schemes. QLPCC outperforms the EQPR scheme in the range of 8% to 14%, the PRR scheme in the range of 4% to 9%, the probability cache scheme in the range of 12% to 18%, the LFF scheme in the range of 16% to 22%, and the LFU scheme in the range of 24% to 26%. The results are consistent when the network nodes are scaled from \(|M|\) = 500 to \(|M|\) = 1000. The content store size ranges from 50 MB to 250 MB, as shown in the X axis of the graphs in Figure 6.
## 3 Inspection Robot Platform and Data Resources  
### Inspection Robot Platform  
This study relies on an integrated real-time target detection platform for inspection robots to efficiently monitor and intelligently recognize personnel safety attire. The platform incorporates functionalities such as image acquisition, intelligent analysis, and safety alerting and can operate reliably in complex industrial environments. The platform is built around an autonomous mobile inspection robot with an embedded computing unit, high-definition camera, and wireless communication module. The robot autonomously navigates along a predefined path within the factory, capturing real-time images of personnel and quickly identifying whether workers wear safety vests and helmets and triggering alerts when necessary. As shown in Figure 1, the inspection robot platform utilizes a two-wheel differential drive mechanism, achieving a maximum speed of 1 m/s. It supports both manual remote operation and autonomous navigation. A high-definition camera mounted on a gimbal enables real-time object detection. We include images of workers in various working postures in the dataset to ensure high detection precision across different body positions. In addition, we perform repeated detection over short intervals to reduce the probability of false positives and missed detections. When the system identifies improper safety attire, it issues warnings through voice prompts or broadcasting and stores the corresponding detection results as evidence for future review. If multiple violations occur within a single inspection process, the platform sends alerts via the factory's internal communication network. Safety managers then assess the severity of the violations and decide whether to initiate manual inspection.
# A Comparative Analysis of Active Learning for Rumor Detection on Social Media Platforms
## 3 Methodology
### Active Learning Query Strategy  
As mentioned before, the critical challenge in the workflow cycle of active learning lies in selecting an appropriate query strategy, known as a selector. The query strategy evaluates the \"worthiness\" of unlabeled samples using a specific criterion and determines whether a sample is worthy of annotation based on its suitability. Therefore, choosing the right query strategy is pivotal in enabling the model to converge effectively with minimal training data. The choice of query strategy holds significant implications in active learning.  
To date, numerous strategies have been proposed in the literature for querying unlabeled instances. These query strategies can be categorized into three main groups based on the nature of the instances they select: informative-based, representative-based, and both of these in combination. Informative-based strategies focus on the informativeness of unlabeled instances, prioritizing those with higher information content for labeling by the oracle. Typically, the informativeness of unlabeled data is assessed based on the model's uncertainty. However, informative-based strategies may overlook relationships among unlabeled instances, and often lead to the selection of multiple instances of a similar type.  
On the other hand, representative strategies aim to make efficient use of the structure within the unlabeled data when selecting candidate query instances. Additionally, they strive to address the challenges encountered by informative query strategies. Representative strategies can help to alleviate issue of sampling bias by selecting instances from diverse regions within the input space. Combining informative and representative strategies can strike a balance between measures of informativeness and representativeness. It is worth noting that an increase in the informativeness of a selected instance may come at the cost of reduced representativeness.  
In the following subsections, we provide a detailed description of the strategies employed in this paper.
## 1 Introduction
### Risk Warning eHMI Penetration in Vehicle Platoon  
Real-world traffic environments are inherently complex; however, existing eHMI research has predominantly focused on simple interactions between a pedestrian and a single AV, e.g., [9; 10; 28; 29; 30], with relatively less attention given to interactions involving multiple vehicles. One such traffic condition involving multiple vehicles is the vehicle platoon. A vehicle platoon refers to a sequence of vehicles passing consecutively, each potentially traveling at different speeds and having varying TTA, e.g., [11; 13; 14; 22].  
Additionally, vehicle platoons may undergo a transition period from partial AV penetration (AVs and traditional vehicles (TVs) sharing the road) to full AV penetration, along with a corresponding shift toward full eHMI penetration (where all AVs are equipped with eHMI) within these platoons, e.g., [11; 31; 32; 33]. Previous studies have shown that under full eHMI penetration conditions, the use of risk-warning eHMI with a single-level low risk information [22]; a single-level high risk information [13] and three-level low-medium-high risk [11; 14] improves pedestrians' crossing decision. However, Ref. [11] examined the use of three-level low-medium-high risk eHMI under partial eHMI penetration conditions and found that pedestrians' crossing decisions tend to be less safe when encountering TVs without eHMIs. In our earlier study [34], we extended the work of [11] by examining the cognitive effects of three-level low-medium-high eHMIs, and found that partial eHMI penetration condition significantly increased pedestrians' MW and decreased SA compared to full penetration.  
Building on these considerations, this study aims to investigate how eHMI configurations affect pedestrians' cognitive and behavioral responses in vehicle platoon scenarios, under both partial and full eHMI penetration conditions. The goal is to identify the most effective eHMI configurations that facilitate communication across different stages of AV deployment.
# Artificial Intelligence-Based System for Retinal Disease Diagnosis
## 2 Materials and Methods
### Fuzzy Model and Rule-Based Decision Making
\begin{table}
\begin{tabular}{c c c c} \hline
**Variable** & **Description** & **Value** & **Range of Value** \\ \hline \multirow{6}{*}{O1} & \multicolumn{3}{c}{Output Variables} \\  & \multicolumn{3}{c}{proliferative diabetic} \\  & \multicolumn{3}{c}{tri retinopathy, non-proliferative} \\  & \multicolumn{3}{c}{diabetic retinopathy, no} \\  & \multicolumn{3}{c}{diabetic retinopathy, no} \\  & \multicolumn{3}{c}{pathology} \\  & \multicolumn{3}{c}{dry age-related macular} \\ O2 & Age-related macular degeneration & \multicolumn{3}{c}{degeneration, wet age-related} \\  & \multicolumn{3}{c}{macular degeneration, no} \\  & \multicolumn{3}{c}{pathology} \\  & \multicolumn{3}{c}{hereditary retinochsis} \\ O3 & Retinochisis & \multicolumn{3}{c}{(\(\chi\)-chromosomal), primary} \\  & \multicolumn{3}{c}{retinoschisis, secondary} \\  & \multicolumn{3}{c}{retinoschisis, no pathology} \\  & \multicolumn{3}{c}{dytrophic retinal detachment,} \\ O4 & Retinal detachment & \multicolumn{3}{c}{traumatic retinal detachment,} \\  & \multicolumn{3}{c}{secondary retinal detachment,} \\  & \multicolumn{3}{c}{pathology absent} \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._  
Figure 5: Fuzzy model structure. Figure 6: _Cont._  
The decision-making rule base for retinal pathology diagnostics is defined as what-if production rules. Some rules from more than 150 are presented below. * If (I3 is 1) and (I4 is 5-10) and (I16 is low) and (I34 is below normal) and (I28 is under normal), then (O1 is non-proliferative diabetic retinopathy). Figure 6: Membership functions for input and output variables: (**a**) I\({}_{5}\); (**b**) I\({}_{2}\); (**c**) I\({}_{37}\); (**d**) O\({}_{3}\). * If (I1 is 21-40) and (I3 is 1) and (I11 is myopia) and (I19 is greater than normal) and (I25 is normal), then (O1 is non-proliferative diabetic retinopathy) and (O4 is dystrophic retinal detachment). * If (I10 is yes) and (I12 is yes) and (I16 is decreased) and (I18 is under normal) and (I20 is under normal), then (O3 is secondary reinoschisis). * If (I1 is less than 20) and (I2 is f) and (I16 is normal) and (I18 is normal) and (I20 is normal), then (O3 is no pathology). * If (I5 is normal) and (I10 is no) and (I14 is no) and (I32 is normal) and (I33 is normal), then (O4 is no pathology). Fuzzy inference is formed according to all the rules using the max-disjunction operation. The defuzzification procedure uses the gravity method.