esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Recently, underwater wireless optical communication (UWOC) has attracted the attention of researchers due to its large bandwidth, high data rates, and lack of electromagnetic interference [1, 2]. Traditionally, underwater acoustic communication (UAC) and radio frequency (RF) communication are the two main methods of underwater wireless communication (UWC). Although UAC has the overwhelming advantage of long-distance transmission [3], it is hard to achieve high-speed communication because of the narrow bandwidth of the acoustic wave. Compared to UAC, RF communication can offer a larger bandwidth and a higher data rate. However, RF communication is limited to short-distance transmissions because of the high conductivity of seawater to radio frequencies [4, 5].  
As novel underwater wireless communication technologies, UWOC can balance long-distance transmission and high data rates [6, 7, 8, 9, 10, 11]. When targeting long-distance UWOC, it is possible to exploit the low-attenuation window in the electromagnetic spectrum, which locates in the visible spectrum the approximate peak wavelength of 522 nm, as shown in Figure 1. With the expansion of Internet-of-Things (IoT) technology, the ocean will be explored deeply by humans. Ocean buoys, satellites, aircraft, vessels, and vehicles have formed the satellite-terrestrial network, which will cover the ocean using the UWOC network in the near future [12].  
Despite UWOC having significant achievements, the complexity of the underwater environment still raises challenges for UWOC. There are a couple of unforeseen factors such as fish schools, seabed rocks, turbidity, and oceanic turbulence [13; 14; 15; 16]. These greatly degrade the performance of the UWOC links, which primarily utilize line-of-sight (LOS) communication [17; 18; 19; 20]. For example, seabed rocks block the communication link so that the UWOC transmission is interrupted, as shown in Figure 2. To keep UWOC links reliable and robust, many researchers have made some progress in non-line-of-sight (NLOS) UWOC [21; 22; 23; 24; 25; 26; 27]. [PERSON] et al. experimentally demonstrated a UWOC system at a data rate of 85 Mb/s within a transmission distance of 30 cm in emulated highly turbid harbor water by using an NLOS link [28]. [PERSON] et al. evaluated the proposed models of LOS and NLOS vertical underwater transmission links [20]. [PERSON] et al. discussed the path loss of NLOS on UWOC links [29]. [PERSON] et al. proposed an NLOS-scattering-channel model for the UWOC system [30]. In this paper, we demonstrated a novel NLOS UWOC link using the total internal reflection at the air-water interface and further investigated the impact on the UWOC links when the frequency and amplitude of the waves varied.
## 5 Results and Analysis
### Mechanism of the Nonlinear Effect of Built Environment Factors on Ridership
#### 5.4.5 Public Services  
Figure 12a-c show the partial dependence of public services on total and inbound and outbound weekday morning peak passenger flows, and the nonlinear effect of accessibility on them can be seen.  
It can be seen that public services have a nonlinear positive relationship on both total and inbound passenger flows and a nonlinear inverted U-shaped relationship on outbound passenger flows. For both total and inbound passenger flow, the total passenger flow saturates when the number of public services exceeds 1200 (as shown in Figure 8a,b).  
The pattern affecting outbound passenger flow shifts to an inverted U-shaped curve when the public service reaches between 850 and 900, with a brief peak at about 900 public services, followed by a decline (as shown in Figure 8c). This indicates that outbound passenger flows peak when the number of public services is moderate.  
Therefore, the frequency and capacity of metro services should continue to be strengthened in areas with high service (Number of public services > 1200) areas, and pedestrian and cycling feeder facilities should be optimised to ensure the convenience of the 'last kilometre' and to further enhance the metro's status as a major mode of travel. At the same time, in order to avoid the need for residents to travel long distances due to a lack of facilities, which would discourage outbound demand, or to reduce travelling efficiency due to overcrowding and redundancy (e.g., multiple competing facilities of the same type), a balanced layout should be emphasised in the planning of new public service facilities to ensure that the number and type of public services in each area meet the daily needs of the residents without wasting resources or over-concentrating them.
## 2 Foundational Data Acquisition
### Data Interpretation  
A thorough bibliometric analysis is conducted in Section 3 to understand the diversity of the extracted material, categorize pertinent researchers, and examine issue statements in the area of IoT in agricultural disease detection. The study locations, the contributors' connections, the authors' names, and the journals where the research articles were published all show distinctiveness in the research field. The search analysis is carried out using the keywords found in the extracted material. The recovered information is frequently used to estimate the number of citations for each research paper and collaborative study.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Year** & **Publication Count** \\ \hline
2020 & 74 \\
2019 & 38 \\
2018 & 14 \\
2017 & 10 \\
2016 & 3 \\
2015 & 4 \\
2014 & 0 \\
2013 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Yearly publishing trends of IOT in crop disease detection.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category of Publications** & **Publication Count** & **Percentage** \\ \hline Article & 75 & 51.37 \\ Review & 36 & 24.65 \\ Conference Paper & 22 & 15.07 \\ Book Chapter & 8 & 5.49 \\ Book & 5 & 3.42 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Classification of Publications for IOT in agriculture.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Publication Language** & **Publication Count** \\ \hline English & 145 \\ Chinese & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Languages used for publishing on IOT in crop disease detection.  
Using a line chart to schematically portray Table 4, Figure 1 demonstrates that 2020, with a total of 74 documents published, is the most frequently occurring year for research document publication.
## 7 Conclusions  
This study addresses the issue that existing simulation systems overlook or only simulate the impact of two-dimensional ocean currents on ROV motion trajectories [28]. It also acknowledges that these systems' visualization of simulation results could be improved. Focusing on the ROV, a highly modular simulation system was built using MATLAB and Simulink to optimize these issues. The system primarily optimized the resistance matrix in the original simulation model, decomposing three-dimensional ocean currents into the \(X\), \(Y\), and \(Z\) directions. Simulations were performed on the relative velocity in each direction, enabling the simulation of ROV motion trajectories under ocean current interference. Additionally, to provide an intuitive display of simulation results and data, the model incorporated a 3D plotting module, allowing users to rotate the 3D view and observe the results.  
In contrast to traditional path planning simulations that often ignore the impact of current direction and magnitude, this study incorporated a complete 3D current model to replicate realistic underwater conditions better, which enhanced the validity of the simulation outcomes and provided a more comprehensive understanding of ROV trajectory behavior under various current alignments. Yaw dynamics and directional drift also improved upon prior simplified methods, making the results more applicable to real-world operations.  
Although this research has made some progress, many areas still warrant further exploration. Future studies may incorporate time-varying or turbulent currents and autonomous decision-making for real-time path correction. Additionally, game theory or distributed control methods could be introduced to extend the control of a single ROV to collaborative control and path planning for multiple ROVs. Artificial intelligence (AI) technologies, such as deep learning algorithms, could be integrated on the technical application front. Combined with deploying distributed sensor networks and a hardware/software simulation test platform, this could push advancements in the direction of intelligence and multi-functionality.  
**Author Contributions:** Conceptualization, Y.Z. and S.X.; Methodology, Y.Z.; Software, Y.Z.; Validation, S.X.; Investigation, B.X.; Resources, L.L.; Writing--original draft, Y.Z. and S.X.; Writing--review & editing, S.X. and X.Z.; Supervision, X.Z. and C.X.; Project administration, C.X. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by the Guangdong Ocean University Research Project Initiation Fund (360302042202) and the China National College Students Innovation and Entrepreneurship Training Program Funding Project (202410566040).  
**Data Availability Statement:** There were no new data created, and there were no particular data used during the research.  
**Conflicts of Interest:** The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 3 Proposed Approach
### Feature Extraction
#### 3.2.1 Geometric-Based Features  
Geometric features consist of tissue area, luminal border, and plaque component features. With regard to our previous work [45], the Close Lumen Border Tracing (CLBT) and Open Lumen Border Tracing (OLBT) algorithms trace the luminal border. The results for the lumen border obtained by the CLBT and OLBT algorithms are a sequence of \(n\) elements. To extract the luminal border features, the intensity value of each member is extracted. The amount of NC in contact with the lumen (\(f_{NCCL}\)) and DC in contact with the lumen (\(f_{DCCL}\)) are calculated based on the number of red and white pixels in the lumen border. To extract the plaque component features, three algorithms, including Extracting Confluent Components (ECC), Necrotic Core Layering (NCL), and Plaque Burden Assessment (PBA), are applied. The ECC algorithm extracts the confluent components, including the Confluent NC (CNC) and the Confluent DC (CDC). The DC images which do not belong to the CDC are considered to be Micro Calcification (MicroCa). The NC images which do not belong to the CNC are considered to be Scattered Necrotic Core (SNC). Furthermore, confluent NC in contact with the lumen (CNCCL) and confluent DC in contact with the lumen (CDCCL) are calculated. The area of CNC, CDC, MicroCa, SNC, CNCCL, and CDCCL are calculated as \(f_{CNC}\), \(f_{CDC}\), \(f_{MicroCa}\), \(f_{SNC}\), \(f_{CNCCL}\), and \(f_{CDCCL}\), respectively.  
TCFA is categorised into two classes: single and multiple confluent NC layers [78]. The NCL algorithm determines the NC layering (\(f_{NCL}\)) and DC layering (\(f_{DCL}\)). Quantifying the plaque burden is crucial in terms of diagnosing vulnerable plaque [79]. Therefore, the PBA algorithm measures the plaque burden features, including plaque area (\(f_{PA}\)), vessel area (\(f_{VA}\)), lumen area (\(f_{LA}\)), and plaque burden (\(f_{PB}\)). Therefore, each VH-IVUS image has three different types of geometric feature: tissue plaque area, luminal border, and plaque component features referred to as geometric features \(GF\) = {\(f_{NC}\), \(f_{DC}\), \(f_{FI}\), \(f_{FF}\), \(f_{NCCL}\), \(f_{DCCL}\), \(f_{CNC}\), \(f_{SNC}\), \(f_{CDC}\), \(f_{MicroCa}\), \(f_{CNCCL}\), \(f_{CDCCL}\), \(f_{NCL}\), \(f_{PDL}\), \(f_{PA}\), \(f_{VA}\), \(f_{LA}\), \(f_{PB}\)\(\_\)ENREF\(\_\)1\(\_\)ENREF\(\_\)1.
## 3 Results and Discussion
### Antioxidant Effects  
Several investigations have reported the antioxidant potential of _C. officinalis_. As an example, the ethanol extract of _C. officinalis_ flower showed to reduce Fe\({}^{3+}\) to Fe\({}^{2+}\) (ferric reducing antioxidant power or FRAP assay) [27]. Ethanol extract of _C. officinalis_ flower scavenged 2,2\({}^{\prime}\)-azino-bis(3-ethylbenzothazoline-6-sulphonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals at an IC\({}_{50}\) of 6.5 and 100 ug/mL, for respective assays [28]. In the present study, the flower extracts showed highest radical scavenging and reducing potential (Table 3). In general, the Soxhlet extract of _C. officinalis_ flower (37.58, 57.69, and 63.43 mg TE/g, for DPPH, ABTS, and FRAP assays, respectively) showed highest equivalent values, meaning highest activity. The radical scavenging properties of natural compounds are often related to their ability to quench free radicals. As such, rutin and nictotiforin, and isoquercitrin, identified in higher concentration in _C. officinalis_ flower have been shown to scavenge free radicals [29]. Extracts of _C. officinalis_ roots were the least active. _C. officinalis_ leaf extracts showed highest chelating activity. Relevantly, isoquercitrin, identified in high level in _C. officinalis_ leaf Soxhlet extract (24.907 mg/g extract), has been reported to show remarkable chelating potential [30]. The pivotal role of oxidants in the onset, progression, and exacerbation of human diseases has rendered antioxidant determination crucial for the development of novel drug candidates. In fact, the ability of a molecule to exhibit antioxidant potential as well as interacting with other biological pathways is an attractive therapeutic strategy. We observed some results for antioxidant properties of _C. officinalis_. For example, [PERSON] et al [25] reported antioxidant properties of infusion and decoction from flowers of _C. officinalis_ via different chemical methods such as DPPH, ABTS, FRAP, and cupric reducing power (CUPRAC) and the authors noted that the extracts exhibited moderate efficiency. Also, [PERSON] et al [24] reported moderate activity of _C. officinalis_ on ABTS and DPPH assays. [PERSON] et al [31] studied the antioxidant activities of hydroalcoholic and infusion of _C. officinalis_ flowers with DPPH and FRAP assays and the hydroalcoholic one exhibited stronger ability when compared infusion. [PERSON] et al [32] also reported antioxidant properties of hydroalcoholic extract from _C. officinalis_ flowers. These findings could provide that the alcohol could be useful for the preparing novel products from _C. officinalis_, to increase efficiency.
## 2 Samples and Research Methods  
GaSe:S crystals were grown from melts using the vertical Bridgman method with thermal field rotation. The detailed description can be found elsewhere [49]. The atomic inclusion of sulfur was determined using an energy-dispersive X-ray spectrometer in combination with a scanning electron microscope. Direct chemical analysis measurements were performed on the cleaved surface of a GaSe:S single crystal, analogous to the work [19] and confirmed by the variation of the absorption edge with relative sulfur content [25]. The samples were cut into two thicknesses: \(\sim\)1 mm to study the optical properties and \(\sim\)0.3 mm to measure THz detection efficiency in accordance with the \(L_{\rm coh}\) calculated below. The samples were glued into the metal diaphragm, and the surface was then prepared to a high optical quality by exfoliation using adhesive tape. The refractive index of the samples was measured at a wavelength of 1547 nm using a Metricon 2010 system (Metricon, USA). According to the device manual, the absolute measuring error is \(\pm\)0.003.  
The terahertz refractive index of the samples was measured using a THz-TDS developed at the IA&E SB RAS. It has a bandwidth of 0.1-2.6 THz, with a maximum dynamic range of \(>\)70 dB achieved at the frequency of 0.3 THz. The spectral resolution was \(\sim\)20 GHz. A detailed description of this spectrometer and experimental conditions is given in [50; 51].
## 2 Materials and Methods
### Course of the Study
#### 2.5.1 Questionnaires  
Previous studies indicate that individuals diagnosed with chronic migraine have a diminished ability to recognize emotions, expression difficulties, heightened levels of depression and anxiety, and increased central sensitization [19; 39]. Consequently, the following three questionnaires were added to this study: The Toronto-Alexithymia-Scale 20 Items (TAS-20), the Depression-Anxiety and Stress Scale (DASS), and the Central Sensitization Inventory (CSI).  
Toronto-Alexithymia-Scale 20 Items (TAS-20). The TAS-20 records alexithymia, i.e., so-called emotional blindness, using a questionnaire with a total of 20 items. The German translation of the original English scale [40; 41] showed adequate validity and reliability in a sample analysis [42]. The scale is recommended for the assessment of alexithymia [43]. However, in the course of an investigation into the psychometric properties in the application of the scale in somatoform pain disorders, the originally propagated 3-factor model was not recommended, and only the use of the total values was recommended for interpretation and recording [44].  
Depression Anxiety Stress Scales (DASS). The DASS is a self-report instrument designed to measure three related negative emotional states, namely depression, anxiety, and stress. Each of these states is assessed by a set of 14 items, for a total of 42 items. The questionnaire uses a 4-point severity/frequency scale to assess the extent to which an individual has experienced each state over the past week. Overall, the DASS is both reliable and valid and is recommended in its short form for patients with persistent pain [45; 46].  
Central Sensitization Inventory (CSI). This questionnaire is available in a validated German version and contains 25 items, which are rated with a range of 0-4 points. The cut-off value for the hypothesis of the existence of a central sensitization of pain is 40 points. In an empirical study on the validity of the German tool called \"Zentrale Sensibilisierung Screeningtool\" (ZSS), the Neck Disability Index (NDI) was used as a comparable gold standard in a population that suffered from persistent, non-specific neck pain. The Spearman rank correlation showed a statistically significant correlation between NDI and ZSS of \(\rho\) = 0.557 (\(p\) < 0.01). With a Cronbach's alpha of \(\alpha\) = 0.867 and a total of 25 items, the internal consistency of the ZSS can be rated as good, confirming its validity [47].
## 2 Multilevel Edge Network Task Offloading Model
### Offloading Node Resources
#### 2.2.4 Integrated Offloading Function  
As shown above, the model focuses on time and energy consumption costs. The integrated cost function of time delay \(T\) and energy \(E\) is defined as follows:  
\[E=\{E_{u},E_{UAV-Z},E_{GMEC-Z}\}, \tag{27}\]  
\[T=\{T_{U},T_{UAV-Z},T_{GMEC-Z}\}. \tag{28}\]This model seeks to consider the energy and time delay problem synthetically. However, the unit and order of energy and time are different and cannot be compared. In this study, the energy and time functions are normalized [24]. The normalization function is as follows:  
\[H(x_{\min},x_{mid},x_{\max},\alpha,x)=\left\{\begin{array}{ll}0&x<x_{\min}\\ \frac{\left(\frac{x}{x_{mid}}\right)^{a}}{1+\left(\frac{x}{x_{mid}}\right)^{a} }&x_{\min}<x<x_{mid}\\ 1-\frac{\left(\frac{x_{\max}-x_{mid}}{x_{max}-x_{mid}}\right)^{a}}{1+\left( \frac{x_{\max}-x}{x_{mid}}\right)^{a}}&x_{mid}<x<x_{\max}\\ 1&x>x_{\max}\end{array}\right., \tag{29}\]  
where \(x\) is the variable value and \(x_{\min}\), \(x_{\max}\), and \(x_{\rm mid}\) are the minimum, maximum, and median values of a variable, respectively. \(\alpha\) determines the slope of the utility function for the shape parameter. As the value of \(\alpha\) increases, the slope becomes steeper.  
\[x_{mid}=\frac{(x_{\min}+x_{\max})}{2}. \tag{30}\]  
Using the above functions, (25) and (26) are normalized respectively, as follows:  
\[H(t_{\min},t_{\rm mid},t_{\max},\alpha_{t},t)=T_{0}, \tag{31}\]  
\[H(e_{\min},e_{\rm mid},e_{\max},\alpha_{e},e)=E_{0}, \tag{32}\]  
where \(E_{0}\) and \(T_{0}\) represent the utility functions of the normalized energy and delay, respectively. \(e\) and \(t\) represent the energy and delay function values before normalization, respectively. Meanwhile, \(e_{\min}\) and \(t_{\min}\) are the minimum values of energy and delay, respectively. \(e_{\max}\) and \(t_{\max}\) are the maximum energy and delay, respectively. \(\alpha_{e}\) and \(\alpha_{t}\) are the shape parameters of the energy and delay, respectively. Finally, the integrated cost function is identified:  
\[E_{0}=\left\{E_{u,0},E_{UAV-Z,0},E_{GMEC-Z,0}\right\},T_{0}=\left\{T_{U,0},T_ {UAV-Z,0},T_{GMEC-Z,0}\right\}, \tag{33}\]  
where \(E_{u,0},E_{uav-z,0}\), and \(E_{GMEC-Z,0}\) are normalized into \(E_{u}\), \(E_{uav-z}\), and \(E_{GMEC-Z}\), respectively. \(T_{u,0}\), \(T_{uav,0}\), and \(T_{GMEC,0}\) are normalized into \(T_{u}\), \(T_{uav}\), and \(T_{GMEC}\), respectively.
# Battery Management System Hardware Concepts: An Overview
## 4 Measurement
### Data Transfer  
As already mentioned, communication between individual BMS-modules, as well as between BMS and the overall system, is required. Nowadays, the CAN bus is one of the most prominent buses used in vehicle environments because it is very flexible regarding the number of bus members, as well as offering a good noise resistance. The simpler Local Interconnect Network (LIN)-bus, which is also widely used e.g., has the disadvantages that it is slower, less flexible and non-differential, but, on the contrary, also is less expensive due to reduced hardware efforts [54]. Other buses that are mostly used on short distances, such as chip to chip communication (see above), is the SPI interface, I\({}^{2}\)C interface or the Onewire bus. Due to their non-differential signals, they are not robust against disturbances on a longer, more exposed line, such as inter-module buses. For the latter task, the previously mentioned CAN bus is a good choice. If the CAN bus at its highest speed of 1 Mbps is too slow, or the demand for real-time deterministic capability exists, then the FlexRay bus seems adequate. An Ethernet connection is also sometimes used to connect the battery system with the application, especially when high communication speed and large data volumes required.
# An Efficient Time-Variant Reliability Analysis Method with Mixed Uncertainties
## 5 Numerical Examples
### Time-Variant Reliability Analysis of the Structure of a Mechanical Part
In Table 2, when \(t=1000\), the maximum error is 0.62%, and when \(t=4000\), the minimum error is 0.27%, which is within the engineering allowable range. The results of the proposed method are very close to those of MCS method, which indicates that the proposed method is effective and feasible. In this study, the limit state function only needs to be called 72 times, while it needs to be called 9,984,164 times through MCS method. The running time of the MCS method is 300.82 s, while the running time of the current method is 0.089s. The total number of calls to limit state functions in this method is many orders of magnitude less than that in the MCS method.
# AWMC: Abnormal-Weather Monitoring and Curation Service Based on Dynamic Graph Embedding
## 4 AWMC Description
### Design  
#### 4.1.1 Back-End Design  
The architecture of the back-end is shown in Figure 1. The back-end of the AWMC system comprises three components: a data processor, a graph embedding model, and an anomaly detector. The data processor compensates for missing values in the original dataset, and the graph embedding model builds the embedding space and maps each day's weather data as an embedding vector. Lastly, the anomaly detector applies the existing anomaly detection algorithm to the embedding space and calculates the anomaly score for each day.