esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Case Studies
### Case Study: Composite Intelligent Learning Control of Strict-Feedback Systems with Disturbance
The researchers developed an improved logic virtual ship (LVS) principle considering the time-varying ocean environment. The USR with the proposed guidance principle can implement the waypoint-based path-following control mission in the presence of a random wind direction and a varying route reference. In the nearby area of waypoints, the sailboats can sail along the planned smooth arc path, preventing the sailboat from losing control due to a sudden change in course. A dynamic event-triggered mechanism is designed for the USR. The threshold parameter can adjust dynamically according to a dynamic rule in the presented event-triggered control, reducing unnecessary transmission burden and energy consumption. The mechanism also allows for more accurate control by asynchronously triggering the sail angle and rudder angle. The paper concludes that the improved LVS guidance principle and the dynamic event-triggered mechanism have significant benefits. The proposed guidance principle can complete the path-following mission, especially the route with a time-varying wind direction and the reasonable arc turning path. The simulated results show that the communication burden from the controllers to actuators can be reduced due to the dynamic event-triggered mechanism, enhancing transmission efficiency. These case studies illustrate the practical benefits of using Machine Learning in marine traffic management and prediction. They offer evidence of improved safety, efficiency, and sustainability in maritime systems through the application of these advanced techniques. The next section will explore the future prospects and potential advancements in this exciting field.
## 2 Related Work on Diacritics Restoration
### Transformer-Based Approaches  
The state-of-the-art techniques in the diacritics restoration, as in all NLP fields, employ transformer-based models.  
The multilingual BERT was successfully applied to 12 languages (Vietnamese, Romanian, Latvian, Czech, Polish, Slovak, Irish, Hungarian, French, Turkish, Spanish, and Croatian) [46]. The BERT embeddings, created on the undiacritized text, are fed into a fully connected Feed-Forward Neural Network (FFNN). The output of such a network is a set of instructions (as labels) that define the diacritization operation necessary for each character of the input token. The authors claim that their BERT-based approach outperforms all previous state-of-the-art models.  
The authors in [47] solve the character classification problem for the Vietnamese language by offering a novel Transformer Decoder method with the Penalty layer (TDP). The model is a stack of six decoder blocks. The encoder part is redundant since each input character corresponds to only one output character. The penalty layer restricts the output by only allowing the possible characters for each input character. The authors also performed comparative experiments, proving their approach is superior to those offered in [38].  
Another transformer-based technique was applied to 14 languages (Bosnian, Czech, Estonian, Croatian, Hungarian, Lithuanian, Latvian, Polish, Romanian, Slovak, Slovenian, Albanian, Serbian, and Montenegro) [48]. The core of the diacritization approach is the Marian Neural Machine Translation (NMT) system [49] with six encoder-decoder layers, which is applied to the frequently occurring character sequences. The research is especially interesting because it is performed in monolingual (training and testing on the same language) and multilingual (by either mixing the data of all languages or by mixing the data of all languages, but inserting language codes as the first token of each segment) settings. The authors experimentally determined that the monolingual experiments gave almost the same accuracy as the multilingual experiments with the language codes.
# Temperature Effects on the Natural Frequencies of Composite Girders
## 2 Temperature Effects on a Composite Bridge
### Impact of Temperature on the Size of Structures  
A temperature change in a composite bridge affects the size of its members as a result of thermal expansion, which results in variations in the moment of inertia. The change in length of a rectangular beam with temperature can be calculated using Equation (5) [5] as follows:  
\[L1=(1+\alpha\Delta T)L \tag{5}\]  
where  
\(L1\) is the beam length after temperature change,  
\(\alpha\) is the linear expansion coefficient,  
\(\Delta T\) is the temperature change, and  
\(L\) is the initial beam length.
## 4 Results
### Factors Controlling Acoustic Velocity
#### 4.6.3 Bioturbation Intensity and Burrow Infill  
Based on CT scan, bioturbation intensities in the studied samples range between 3 and 27%. The bioturbation intensity shows a very weak relation with the compressional velocity (VP) (Figure 13A) with correlation coefficient R2 < 0.1. However, fine-filled burrows display higher velocities than coarse-filled burrows (Figure 14B).  
Similarly, the velocity-porosity cross plot (Figure 14) shows that the bioturbation intensity (BI) has no major control on velocity, where samples with higher bioturbation intensities (15-30%) have a wide range of porosities (5-20%) and about 1 km/s velocity difference at the same porosity (at 5.5% porosity in Figure 14A). Similarly, samples with medium BI (10-15%) have a wide scatter of velocity at the same porosity; compare velocities at about 15% porosity in Figure 14A. Likewise, samples with low bioturbation intensities (BI < 10%) show similar velocities although they have 10% porosity difference; compare values at about 5.5 km/s Vp in Figure 14A. Nevertheless, when adding the burrow filling material parameter, the results show that fine-filled burrows have lower porosity and permeability values (\(\mu\) = 6.56%, 0.66 mD), and higher velocity values (\(\mu\) = 5.46 km/s), relative to the coarse-filled burrows (\(\mu\) = 14.44%, 0.56 mD, and 4.52 km/s) (Figure 14B).  
Figure 12: Pore types impact on the compressional velocity (Vp). Samples dominated with fractures and interparticle pores have the lowest velocities, while samples dominated by vug pores (open burrows) have the highest velocity.  
Figure 13: (**A**) Compressional velocity (\(\rm V_{P}\))–biorturbation intensity cross plot showing the weak relation. (**B**) \(\rm V_{P}\)–biorturbation intensity relation with burrow filling material superimposed, and showing that fine-filled burrows have higher velocities than coarse-filled burrows.
# Innovative Strategies for Combining Solar and Wind Energy with Green Hydrogen Systems
## 5 Discussion
### Renewable Energy Sources
#### 5.1.2 Wind-Powered Hydrogen Production System  
Wind energy is not more efficient than solar energy owing to the wind's unpredictable nature. As a result, the amount of electricity generated by wind turbines varies over time. Excess electricity might be stored as H\({}_{2}\) gas utilizing wind energy in a W/H\({}_{2}\) system, as illustrated in Figure 10. During low wind speeds, the produced H\({}_{2}\) can be converted to energy using a fuel cell; during high wind speeds, a portion of the H\({}_{2}\) may be sold or stored, while the remainder is converted to electricity [84]. Thus, a wind turbine's efficiency can be enhanced by integrating it with an electrolytic unit and a fuel cell to create a sufficient green energy source [85].  
There is theoretical and numerical research on the wind/H\({}_{2}\) system, in addition to the experimental investigations. In actuality, a model for electrolysis has been created utilizing four numerical models [86]. The suggested models have demonstrated good performance under the wind speed outcome conditions. Additional studies have looked into how to use a novel approach and control technique to enhance the wind/H\({}_{2}\) system's efficiency [87]. To reduce the cost of producing H\({}_{2}\) under the wind/H\({}_{2}\) system, many strategies and procedures have been developed. It has been noted that the expenses are influenced by both the original outlay and the locations of the wind and H\({}_{2}\) systems. A sample of some global locations and the associated costs of an electricity-based wind energy system and H\({}_{2}\) generation are provided in Table 5.  
Figure 10: Wind/H2 system for hydrogen and electricity production.  
When H\({}_{2}\) is generated using renewable energy sources, it is stored and transferred. High-pressure tanks are used to properly store H\({}_{2}\)[56]. The most serious issue that can arise is the escape of compressed gas at high pressure, which could result in an explosion. On the other hand, the storage system is one of the most important elements influencing H\({}_{2}\) production costs. Various installation strategies for wind and H\({}_{2}\) systems have been studied to lower production costs [88]. The cost of producing H\({}_{2}\) and transporting it by pipeline is around 5.71 USD per kilogram. A study was carried out on the integration of H\({}_{2}\) and methane generation, which allows for an increase in the system's overall efficiency [89]. A low-cost H\({}_{2}\) manufacturing method was discovered employing a wind turbine in the location with the highest potential wind power in Southern Algeria [90]. The lowest price of roughly 1.214 USD/kg was found in Adrar City.
# Wire-Grid and Sparse MoM Antennas: Past Evolution, Present Implementation, and Future Possibilities
## Why MoM?
### MoM Antennas
Consequently, there is no need to solve the entire problem at each iteration in the optimization process. This is because in each iteration step, only a few rows and columns are added or removed from the matrix system used in the previous iteration step. Since this procedure greatly reduces the computation time, it becomes possible to evaluate, in real time, the effects caused by the changes in geometry that are made during the design process to improve system performance.
## 1 Introduction
The first derivative method was used to extract the information of the spectral change rate in the original spectral data. The permutation entropy method was used to extract the extremes of the spectral change rate, and the partial least square method was used to establish COD prediction model. With the aim to improve the accuracy of turbidity compensation, a dual-wavelength method (DWM) and a new turbidity compensation method were proposed. Experimental results demonstrate the hybrid strategy can improve the detection accuracy of COD with turbidity interference and has stability. This paper is organized as follows: In Section 2, we describe materials used in this article and FDPE_PLS algorithm, DWM, and a new turbidity compensation method. We present the experimental methodology and the results in Section 3. Finally, we draw conclusions and indicate directions for future research in Section 4.
# Unsupervised Temporal Adaptation in Skeleton-Based Human Action Recognition
## 2 Related Work  
Skeleton data encode the dynamics of human movement over time by depicting the trajectories of the human body's skeleton joints. In this context, a human action can be represented by a sequence of skeleton frames that is trimmed to cover only the series of body movements that compose a specific action from the beginning to the end. By benchmarking the human action recognition task on a variety of large-scale skeleton-based datasets such as NTU RGB+D [8] and the PKU Multi-Modality Dataset [9], Graph Convolution Networks (GCNs) have attracted significant attention in recent works [5; 6; 7]. The concept of a GCN is to construct a graph upon skeleton frames in which each node corresponds to a human body joint and the edges correspond to the spatial connectivity among the joints, allowing the network to interpret the topological features of skeleton data. For instance, [PERSON] et al. [12] introduce actional-structural directed graph neural networks (AS-GCNs) to model the temporal dependencies among skeleton joints. [PERSON] et al. [5] define spatial-temporal graph convolutional networks (ST-GCNs) to capture both spatial and temporal information in skeleton data, achieving competitive results in action recognition. [PERSON] et al. [6] propose a framework (CTR-GCN) with the goal of interpreting relationships between joints.  
However, the generalization of action recognition models in real environments is still challenging [13] due to the data distribution shift caused by variations in sensory configuration, e.g., camera views, heights, orientations, locations, and variations in data collection [8]. Skeleton contrastive learning [7; 14] is an effective way to overcome the need for annotation on large volumes of data while demonstrating pivotal competency in learning invariant representations from unlabeled skeleton data for downstream tasks such as action recognition. These methods involve skeleton augmentation while constructing self-supervised contrastive learning pretext tasks, such as similarity measurement [15], which contrast positive pairs against negative pairs from a pre-defined dynamic dictionary [16; 17].
## 3 Results
### Availability of Five-System Integration
In contrast, there is also a typical region extending from 165\({}^{\circ}\)W to 45\({}^{\circ}\)E in the east-west direction, and from 60\({}^{\circ}\)N to 60\({}^{\circ}\)S in the north-south direction. The number of visible satellites is significantly reduced in this region, with an average number of 33.9. It is clear that the number of visible satellites decreases with the increasing distance from the diamond-shaped area, which is caused by the GEO and the IGSO satellites. Under ideal conditions, the average number of visible satellites on a global scale can be 38.9, with a minimum statistic of 29.7, implying that the reliable PPP time transfer can be ensured even at locations with limited sky view. For further analysis, the actual number of visible satellites and time dilution of precision (TDOP) values at stations BRUX, ROAG, and SPT0 on DOY 254, 2021, are presented in Figure 3. The smaller TDOP values are beneficial for the high-accuracy time transfer. In addition to the five-system integration (GREC), the GPS-only (GPS), GLONASS-only (GLO), Galileo-only (GAL), and BDS-only (BDS) cases are also provided in Figure 3. In terms of the actual satellite number, it is generally less than 15 for each GNSS single-system case, while the average satellite number at stations BRUX, ROAG, and SPT0 under the five-system combination is 32.0, 29.7, and 36.4, respectively. For the TDOP, the average value at three stations is 0.87, 0.96, and 0.86 for the GPS-only case, 1.53, 1.83, and 1.82 for the GLONASS-only case, 1.53, 1.35, and 1.25 for the Galileo-only case, and 0.91, 0.99, and 0.71 for the BDS-only case, respectively. Notably, the TDOP value of the GLONASS-only and Galileo-only cases is extremely unstable and has a wide range of variation due to the relatively smaller number of available satellites. In contrast, the average TDOP value at three stations under the five-system combination case is 0.42, 0.44, and 0.40, respectively. Thus, compared with the GNSS single-system cases, the five-system combination can significantly increase the number of visible satellites, reduce the TDOP values, and improve the stability of the time series of epoch-wise TDOP values, which will definitely benefit the PPP time transfer. In addition, the average number of visible satellites for the five-system combination at station TID1 on DOY 254 of 2021 can be 42.3. In conjunction with the results shown in Figure 2 as well as the information of stations provided in Table 1, it is indicated that the actual satellite numbers are roughly close to the theoretical ones. This verifies the correctness of our theoretical analysis about the availability of five-system integration. Figure 2: Average number of visible satellites of the five-system combination on DOY 254, 2021.
## 2 Carbon Isotope Detection Principle and Absorption Line Selection
### Absorption Line Selection  
The high-resolution transmission (HITRAN) molecular absorption database is a worldwide standard for calculating or simulating atmospheric molecular transmission and radiation [22; 23]. It covers a wide spectral region from microwave to ultraviolet radiation. In the infrared band, the absorption spectra mainly comprise vibrational and rotational spectra, and each gas has multiple absorption bands. The HITRAN absorption spectra of 10 ppmv CO\({}_{2}\) and 1% H\({}_{2}\)O at a gas pressure of 20 Torr with a 24-m effective optical path length are depicted in Figure 1.  
The selection of the absorption line pair of \({}^{13}\)CO\({}_{2}\)/\({}^{12}\)CO\({}_{2}\) is especially critical for obtaining high sensitivity and precision. The absorption line pair was chosen at 2315.10 cm\({}^{-1}\) and 2315.36 cm\({}^{-1}\) with appropriate spacing, as it does not overlap with other chemical substances, such as methane or sulfuretted hydrogen. The absorption lines are strong, resulting in a better signal-to-noise ratio and avoiding the need for a larger absorption cell, which is beneficial for the miniaturization of the sensing system. Due to the similar low energy levels of absorption line pairs, the detected isotopic stability is less dependent on temperature. In particular, there is no water vapor absorption line between the line pairs; thus, the sensing system does not need to over-consider the influence of ubiquitous water vapor.  
Using the selected absorption line pair, the parameters shown in Equation (8) can be determined as follows: Boltzmann constant \(B=1.328\times 10^{-23}\) J\(\cdot\)K\({}^{-1}\), \(\Delta E=4.76\times 10^{2}\) cm\({}^{-1}\), \(k=1.9865\times 10^{-23}\) J\(\cdot\)cm, and the target temperature \(T=300\) K. For the target CO\({}_{2}\) isotope \(\delta^{13}\)C value of 0.6%, the temperature change amount \(\Delta T\) should be less than 0.127 K. If the calculation of the MDL according to Allan variance can reach lower than \(\sim\)0.01%, it will meet the requirement of deep-sea NGH exploration.  
Figure 1: The high-resolution transmission (HITRAN) absorption spectra of 10 ppmv CO\({}_{2}\) and 1% H\({}_{2}\)O at a gas pressure of 20 Torr with a 24-m effective optical path length.
## 3 Optical Properties
### Microdisk Lasers Based on QWDs
#### 3.5.2 Dynamic Characteristics and Data Transmission
All measurements were carried out at 300 K.  
The 3-dB bandwidth (\(f_{\text{3 dB}}\)) is shown versus bias current in Figure 19. Examples of the SSM responses are depicted in the inset to this figure. The maximal \(f_{\text{3 dB}}\) of 6.7 GHz was obtained for the 23 \(\upmu\)m in diameter microlaser at a bias current of 21 mA. The roll-over of the 3-dB bandwidth at high currents is attributed to the self-heating of the device. To study the large signal modulation characteristics, the MD laser emission was coupled to the lensed fiber. Note that only 2.5% (32 \(\upmu\)W at 25 mA) of the entire MD output power was fed into the fiber. Certain arrangements were undertaken to overcome the effects due to the photodetector noise and to measure the true dynamic performance of the MD lasers [89]. To obtain the eye diagrams, ten 2\({}^{7}\)-1 pseudo-random bit sequences (PRBSs) were transmitted through the fiber. Figure 20b-e shows the eye diagrams at 30 \({}^{\circ}\)C ambient temperature for the optimum pumping regime. The received power was -15 dBm. The eye stays open up to bitrate \(B_{\text{max}}\) = 12.5 Gbit/s. This result is in good agreement with the obtained maximal 3-dB bandwidth \(f_{\text{3 dB, max}}\) = 6.7 GHz (Figure 19) that suggests the estimation of \(B_{\text{max}}\approx 2f_{\text{3 dB, max}}\) = 13.4 Gbit/s. The dependence of bit error rate (BER) on the received optical power at 30\({}^{\circ}\)C is depicted in Figure 20a. Thus, the QWD MD lasers are applicable for 10 Gbit/s error-free data transmission (BER = 10\({}^{-12}\)). In case the output power of the QWD MD laser is increased by for instance, coupling to a bus ridge waveguide, e.g., like in Ref. [84], the data transmission speed can be further enhanced. Figure 19: Dependence of 3-dB bandwidth (\(f_{\text{3 dB}}\)) on injection current. Inset: examples of small signal modulation responses at different bias currents. The line is a guide to the eye.
## 2 Materials and Methods
### DNA Extraction, PCR Amplification and 165 rRNA Sequencing  
Total DNA was extracted using the NucleSpin(r) Food (MACHEREY-NAGEL GmbH & Co.KG, Duren, Germany), following the manufacturer's instructions. The isolated DNA was quantified using a Nanodrop 2000c Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). A PCR reaction targeting the V3 region of the 16S rDNA gene was carried out for each sample, using the primers 5\({}^{\prime}\)-ACTGAGACACGGTCCAGACT-3\({}^{\prime}\) (F) and 5\({}^{\prime}\)-GTATTACCGCGCTGTG-3\({}^{\prime}\)(R). For each reaction, 100 ng of DNA were mixed with 10 \(\upmu\)L of Kappa HiFi HotStart ReadyMix (Roche, Basel, Switzerland), 4 \(\upmu\)L of primers (final concentration 0.2 \(\upmu\)M) and proper volume of Nuclease Free water to reach a final volume of 20 \(\upmu\)L. PCR was carried out under the following conditions:--Initial denaturation at 95 \({}^{\circ}\)C (5 min), followed by 25 cycles of denaturation at 95 \({}^{\circ}\)C (30 s), annealing at 58 \({}^{\circ}\)C (30 s) and extension at 72 \({}^{\circ}\)C (15 s). PCR products were checked in a 2% \(w/v\) agarose gel and then purified using magnetic Agencourt AMPure XP beads (Beckman Coulter,CA, USA) according to the manufacturer's instructions. An amount of 75 ng of purified PCR products was used for the preparation of the libraries with the Ion Plus Fragment Library Kit (Thermo Fischer Scientific). The libraries were then quantified and prepared for sequencing by the Ion Torrent GeneStudio(tm) S5 (Thermo Fischer Scientific).  
Raw sequencing data were analyzed to filter out low-quality reads. Data analysis for amplicon sequencing was performed using Mothur (v.1.45.3) [23]. OTUs (Operational Taxonomical Units) were defined by clustering reads at 3% divergence (97% similarity), using the Greengenes (v.13\(8\)99) database. Normalization, taxonomic-binning of OTUs in phyla and genera levels and the calculation of [PERSON]'s and Simpson's indices were performed using the Rhea platform [24].