esa-sceva/satcom-chunk-collection huggingface dataset:
# Modeling and Predicting Carbon and Water Fluxes Using Data-Driven Techniques in a Forest Ecosystem
## 2 Materials and Methods
### Model Evaluation  
The performance of developed data-driven models was evaluated on the basis of several statistical indices, including the coefficient of determination (\(R^{2}\)), Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE) and mean absolute error (MAE). The expressions of the abovementioned statistical indices are described as below:  
\[R^{2}=\left[\frac{\sum\limits_{i=1}^{N}{(Y_{o,i}-\overline{Y_{o}})(Y_{m,i}- \overline{Y_{m}})}}{\sqrt{\sum\limits_{i=1}^{N}{(Y_{o,i}-\overline{Y_{o}})^{2 }\sum\limits_{i=1}^{N}{(Y_{m,i}-\overline{Y_{m}})^{2}}}}}\right]^{2} \tag{2}\]  
\[\text{NSE}=1-\frac{\sum\limits_{i=1}^{N}{(Y_{o,i}-Y_{m,i})^{2}}}{\sum\limits _{i=1}^{N}{(Y_{o,i}-\overline{Y_{o}})^{2}}} \tag{3}\]  
\[\text{RMSE}=\sqrt{\frac{1}{N}\sum\limits_{i=1}^{N}{(Y_{o,i}-Y_{m,i})^{2}}} \tag{4}\]  
\[\text{MAE}=\frac{1}{N}\sum\limits_{i=1}^{N}{|Y_{o,i}-Y_{m,i}|} \tag{5}\]  
where \(Y_{o}\) and \(Y_{m}\) denote the observed and modeled values, respectively; \(\overline{Y_{o}}\) and \(\overline{Y_{m}}\) are the means of observed and modeled values, respectively; and \(N\) is the number of observed values.
# Pedestrian Behavior in Static and Dynamic Virtual Road Crossing Experiments
## 1 Introduction
Previous research has found that the quality of each simulator is associated with the capacity to induce in the participants the feeling of being present in the virtual environment and not just perceiving it as a digital image [35]. This, in turn, depends on the environment's realism and the simulator's usability, which is supported by the quality of the graphical representation, sound, and interaction possibilities. Still, it is not known if simulations in which the participant can walk have a measurable impact on participants' decision-making. Thus, the role of participants' free movement on their decision-making should also be assessed. The research carried out for this work aimed to compare pedestrians' crossing behavior using a perception-action task based on data extracted from static and dynamic virtual experiments. This main aim links to the question of the benefits of putting extra effort into performing a more realistic approach in which the participants were required to walk effectively along a semi-virtual crosswalk. The contributions of the work are not only methodological, introducing dynamic features in the virtual experiments, such as pedestrian movement and spatialized sound, but also behavioral. To reach the main objective, this study assessed how both the noise emitted by approaching vehicles and their movement patterns impact pedestrians' decision-making when crossing the street. It also examined factors related to vehicle speed and distance and experimental conditions (static and dynamic), which all influence crossing decisions and interactions with vehicles. Participant diversity and sample size are critical factors in research, especially when exploring human behavior across diverse demographic groups. In this study, efforts were made to include participants from various backgrounds, encompassing different age groups, genders, and cultural contexts. The authors recognize that individuals from different age groups may exhibit distinct cognitive abilities and risk perceptions. For example, younger participants may be more inclined toward risky behavior, while older participants often prioritize safety and caution. Although the authors acknowledge the limitations related to participant diversity and sample size, it is important to note that the sample size, though not large, is consistent with those used in similar studies in the field, as mentioned earlier. Taking advantage of the ability of the CAVE system to truly isolate the users from the real world and involve them in a traffic environment [39], a comparison was made between previously published results from an experiment conducted with static crossing evaluation conditions [41] and another experiment in which participants were confronted with a dynamic crossing evaluation condition, meaning that the crossing decision was made by walking along the virtual crosswalk.
# Concurrent Transmission Based on Distributed Scheduling for Underwater Acoustic Networks
## 3 Concurrent Transmission Based on Distributed Scheduling  
### System Description and Problems  
Consider a one-hop cluster in a distributed underwater acoustic network, where all nodes in the cluster are static, randomly distributed and can reach each other directly using an omnidirectional and half-duplex underwater acoustic modem. The clocks in all nodes are synchronous. A delay table that contains the inter-node propagation delays in the cluster is stored by each node, which is obtained in the network initialization stage by measuring the round-trip time or exchanging information with its neighbors.  
The basic idea of the proposed method is to allow multiple handshakes and concurrent transmissions in one transmission cycle so that the channel resource can be used more effectively. There are two major problems in designing such a MAC protocol:  
* How to implement the scheduling algorithm in a distributed manner with the least overhead. Because there is no central node to broadcast the scheduling information, synchronizing the sending time of each source node to avoid collision is difficult.
* How to optimize the sending time of the source nodes to shorten the total data transmission time. The scheduling algorithm should ensure that a packet sent by an arbitrary source node will not overlap with other packets at its corresponding destination node (as a result, all destination nodes will receive their packets correctly), while ensuring the whole data transmission time is as short as possible. Note that overlaps of packets at their non-destination nodes are allowed.
## 3 Experimental Investigations of Hall Thruster Erosion  
Experimental investigations of Hall thruster erosion can be broadly grouped into two categories: thruster tests and material surface investigations. Thruster tests provide overall erosion and performance characteristics, whereas material surface investigations study sputtering yield and the impact of sputtering on surface structure. This section highlights important results found in both investigation types.
# Multi-Source Data Fusion for Vehicle Maintenance Project Prediction
## 1 Introduction
To the best of our knowledge, this paper represents the inaugural endeavor to predict vehicle maintenance projects and makes the following contributions:  
Figure 1: The number of common maintenance projects with different annual mileage. * To fully exploit the interdependencies among various maintenance projects, we introduce a novel correlation representation scheme for maintenance projects based on the co-occurrence matrix. * We develop a deep fusion network, endowed with an attention mechanism, to seamlessly integrate vehicle mileage and foundational vehicle information into the vehicle maintenance project prediction framework. * Extensive experiments conducted with real-world data demonstrate the superior performance of our model relative to contemporary baselines.
## 3 Results
### Factors Related to Contact between mandibular Second Molar Roots and Lingual Cortical Bone  
The ratio of L7-LCC was significantly different according to FHR and D7 MP (Table 6). The contact rate was the greatest in the hyperdivergent group (\(p<0.05\)) and the groups with small D7 MP (\(p<0.001\)).  
In a simple logistic regression, significant results were observed only at D7 MP, and when D7 MP increased by 1 mm, the probability of contact between the root and cortical bone decreased by 22% (\(p<0.001\), Table 7).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variable** & **Contact Rate (\%)** & **Number of Teeth** & \(p\) **Value** \\ \hline Sex & & & \\ Male & 32.1 & 168 & 0.381 \\ Female & 37.7 & 122 & \\ FHR & & & \\ Hypodivergent (\(>\)69\%) & 23.6 & 72 & 0.05 * \\ Normovergent (\(\geq\)61\%, \(<\)69\%) & 36.3 & 160 & \\ Hyperdivergent (\(<\)61\%) & 43.1 & 58 & \\ D7 MP & & & \\ Small (\(<\)12 mm) & 51.0 & 96 & 0.000 *** \\ Average (\(\geq\)12 mm, \(<\)15 mm) & 31.7 & 104 & \\ Large (\(\geq\)15 mm) & 20.0 & 90 & \\ ANB & & & \\ Class I (\(\geq\)0\({}^{\circ}\), \(<\)4\({}^{\circ}\)) & 32.9 & 170 & 0.653 \\ Class II (\(\geq\)4\({}^{\circ}\)) & 38.0 & 100 & \\ Class III (\(<\)0\({}^{\circ}\)) & 46.2 & 20 & \\ SNMP & & & \\ Hypodivergent (\(\leq\)27\({}^{\circ}\)) & 28.3 & 46 & 0.528 \\ Normovergent (\(\geq\)27\({}^{\circ}\), \(<\)37\({}^{\circ}\)) & 37.0 & 154 & \\ Hyperdivergent (\(\geq\)37\({}^{\circ}\)) & 33.3 & 90 & \\ PPMP & & & \\ Hypodivergent (\(<\)19\({}^{\circ}\)) & 30.0 & 50 & 0.671 \\ Normovergent (\(\geq\)19\({}^{\circ}\), \(<\)29\({}^{\circ}\)) & 36.4 & 176 & \\ Hyperdivergent (\(\geq\)29\({}^{\circ}\)) & 32.8 & 64 & \\ J-J/Ag-Ratio & & & \\ Low (\(<\)72\%) & 28.1 & 64 & 0.478 \\ Average (\(\geq\)72\%, \(<\)78\%) & 36.8 & 144 & \\ High (\(\geq\)78\%) & 35.4 & 82 & \\ \hline Chi-square test: * \(p<0.05\), *** \(p<0.001\). & & & \\ \end{tabular}
\end{table}
Table 6: Comparison of contact rate between the mandibular second molars and lingual cortical bone according to the clinical variables.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **M6** & **D6** & **M7** & **D7** & \(p\) **Value** \\ \hline Hypodivergent & 0 & 2 & 9 & 15 & 0.000 *** \\ (\(n=72\)) & (0\%) & (2.8\%) & (12.5\%) & (20.8\%) & 0.000 *** \\ Normovergent & 2 & 11 & 37 & 53 & \\ (\(n=160\)) & (1.3\%) & (6.9\%) & (23.1\%) & (33.1\%) & \\ Hyperdivergent & 0 & 7 & 16 & 25 & \\ (\(n=58\)) & (0\%) & (12.1\%) & (27.6\%) & (43.1\%) & 0.000 *** \\ \(p\) value & 0.441 & 0.115 & 0.082 & 0.024 * & \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of the contact rate between the roots of the mandibular molars and the lingual cortical bone.
## 4 Results and Analysis  
To comprehensively investigate the attenuation of terahertz waves in fog and rain, this section first compares and analyzes the impact of radiation and advection fog on terahertz wave attenuation for diverse temperatures and visibility conditions and compares the findings with those of [18]. Secondly, fog attenuation under different visibility conditions is analyzed based on Mie theory. Finally, an analysis of rain attenuation in terms of frequency, rainfall rate, and raindrop distribution is presented.
###### Abstract  
Surfaces of unpaved roads are subjected to dust PM10 (particulate matter < 10 \(\upmu\)m) emission by wind process regardless of vehicles (wheels) transport. However, there is little quantitative information on wind-induced dust emission from unpaved roads and the efficiency of diverse dust control products. The study aimed to fill this clear applied scientific gap using wind-tunnel experiments under laboratory and field conditions. The wind-tunnel complies with aerodynamics requirements and is adjusted to dynamic similitude by appropriately scaling all variables that affect dust transport. The results of the control sample (no-treatment) clearly show that dust emission by wind from unpaved road could be a substantial contribution to mass transfer and air pollution, and thus should be considered. Diverse dust control products of synthetic and organic polymers (Lignin, Resin, Bitumen, PVA, Brine) were tested. In the first stage, the products were tested under controlled-laboratory conditions. The results enabled quantitative assessment of the product efficacy in wind erosion without the impact of vehicle transport. In the second stage, the products were tested in field experiment in an active quarry, in which the products were applied on plots along the road. The field experiment was conducted after transportation of the quarry-haul trucks in two time points: several days after the application, and several weeks after the application. The results show that in most of the plots the dust emission increases with the wind velocity. PM10 fluxes from the road surface in each plot were calculated to determine the effectiveness of the dust control products. Some products significantly reduced dust emission from quarry roads, especially when using the Hydrous magnesium chloride (Brine). Additional experiments revealed that such Brine can be applied with reduced amounts and still keeping on low emission.  
wind erosion; dust; suppressants; PM10; wind tunnel; lignin; resin; bitumen; PVA; brine +
Footnote †: journal: Applied Physics Letters
# DNA Barcoding as a Plant Identification Method
## 3 Nuclear Genome DNA Barcodes  
### ITS (Internal Transcribed Spacer)  
Nuclear ribosomal DNA (rDNA) genes have been widely used in plant molecular taxonomy; more specifically, the rDNA cistron contains a multigene family that consists of the _18S_, _26S_, and _5.8S_ coding regions that encode the rRNA core of the ribosome. These genes are separated by the internal transcribed spacer (_ITS_) consisting of two subregions, namely, _ITS1_ and _ITS2_. So far, the _ITS_ has been used as a DNA barcode to identify more than 21,000 plant species [31; 33; 34].  
_ITS_ is a powerful phylogenetic marker because of its widespread distribution and the greater evolutionary rate it presents, which enables the comparison of relative divergent taxa. Moreover, as it is a non-coding region, it exhibits more variation because of a presumed reduction of functional constraints [20; 31; 32; 33].  
_ITS_ can be easily PCR-amplified with conserved primers; alternatively, _ITS1_ and _ITS2_ with the joining of _5.8S_ loci can be used as barcodes [31; 33]. The CBOL Plant Working Group does not suggest its use as a universal plant DNA barcode, but as a supplementary locus for taxonomic groupings [30; 32]. Several limitations hinder the use of _ITS_ as a universal DNA barcode; gene paralogues, and the existence of secondary structural problems that result in difficulties in amplification and sequencing, are major drawbacks [29; 35; 36]. Despite these problems, _ITS_ has been used to identify flowers, parasitic plants, and algae very well [21; 32; 35; 37]. Interestingly, a study of the _ITS_ region as a candidate for plant DNA barcoding suggested that, in general, it is superior to chloroplast DNA barcodes, having better discriminatory power and universality [3; 31; 35].
# Detecting and Mitigating Attacks on GPS Devices
## 6 Countermeasures and Their Comparison
### Countermeasures for GPS Jamming
#### 6.1.2 Signal Processing Approaches  
Several approaches exist in the literature based on reducing/removing unwanted interference through signal processing methods, focusing on some form of notch filtering, some of which are summarized in Table 13.  
Other research papers have studied the effects of various hardware components on jamming rejection performance, such as the automatic gain control (AGC) function within the GPS receiver [109], in which they performed frequency domain analysis to isolate the desired GPS signal from the jamming signal. This frequency domain method can effectively capture GPS signals and begin processing when the AGC interference-to-noise ratio is at least 37 dB, corresponding to a GPS SNR of approximately 14 dB. These signal-processing approaches are typically effective against only specific types of jamming waveforms; however, they are relatively lightweight in terms of computational or hardware complexity and are likely feasible across many hardware platforms.  
Most proposed techniques primarily address narrowband jammer types, such as CW and narrowband chirp jamming. Limited signal processing-based approaches in the literature address wideband jamming threats. Wideband jamming techniques are generally less effective than narrowband techniques, likely due to the spread spectrum nature of the GSM waveform, suggesting that the lack of wideband methods is not a critical gap; however, studies have indicated that partial-band swept noise can be highly effective in disrupting GPS signal reception. Current literature does not address mitigating this type of jamming.
## 5 Challenges and Future Work for SWE
### Increasing Interoperability  
While SWE has proven its applicability in a wide variety of projects and applications, it is still not yet widely used in productive systems. One reason for that is the generic nature of the standards which is required to be applicable for a broad range of domains. The SOS (Section 3.3.2), as an example, is intentionally defined for all kinds of sensor resources, ranging from thermometers to satellites. The required flexibility allows on the one hand the integration of heterogeneous sensors, but on the other hand it leaves certain elements generic to fulfil the flexibility requirement. An example is the type of the observation result which is not restricted to a specific type in the basic O&M model (Section 3.2.2). This makes it difficult to implement generic and interoperable clients capable of dealing with different SOS implementations as the result type is not known _a priori_ and not restricted to a certain subset. A useful approach to tackle this problem is to define domain specific profiles. The Water Markup Language 2.0 (WaterML 2.0) [119] is such a profile for the hydrological domain. It restricts the result of an observation to a time series type and defines several other restrictions on sensor types, phenomenon types and allowed types for the feature of interest. In future, further profiles need to be defined to enhance interoperability within domains.  
Though the SWE standards can be used in complex scenarios, most of the currently available deployments are providing data from fixed _in-situ_ sensors. For those simple kinds of sensors, a lot of the above described flexibility in the standards is not needed. Thus, a _lightweight SWE profile_ for stationary _in-situ_ sensors would ease the implementation and would enhance interoperability.
## 4 State-of-the-Art COVID-19 Detection Using Anal Swab-Based Diagnosis  
The outbreak of COVID-19 has adversely impacted the whole world with a massive death rate. In late December 2019, China was the epidemic center just before the spring festival [75]. However, with this perspective, the Chinese government has taken strict precautions to overcome the spread of the virus. Some of the best strategies deployed by China to combat this pandemic are given below.  
1. Stop traveling from in and out of China to control the transmission.
2. Developed quarantine centers for suspected cases to get the best treatment.
3. China developed mobile apps for tracking suspected, confirmed cases, and interaction with individuals having COVID-19 symptoms.
4. Develop public awareness regarding self-protection, epidemiologic investigation, cleaning, and disinfecting the environment.
5. The government installed many intelligent based systems to monitor the public temperature, such as airports, metro stations, hospitals, communities.  
There are different criteria for suspected, confirmed, asymptomatic, mild, and critical cases. All these cases were diagnosed and cured by following management criteria to diagnose COVID-19. Moreover, China's current positive cases have dropped to a few or even zero [76]. However, the pandemic situation goes on critically in other countries. Noticeably, China's policy implemented special preventive and diagnostic measures to control the deadly virus transmission and spread with more individuals testing. Oropharyngeal, nasopharyngeal swabs are primarily used for nucleic acid sampling [77].  
According to [PERSON] (Deputy Chief Physician of the department of respiratory and infectious disease of Beijing You'an Hospital), oropharyngeal swab tests are widely used and most appropriate for large-scale sampling. Nevertheless, the nasopharyngeal swab test accuracy is higher than the oropharyngeal swab tests, but the nasopharyngeal swab test is not convenient as oropharyngeal, and a person feels uncomfortable while sampling. On the flip side, China has started anal swab testing in Beijing to enhance infected people's detection rate and minimize unpredictable diagnoses. The sample collection method for anal swabs is to insert a cotton-tipped swab about 1-2 inches into the rectum to detect the virus. However, the sample collection of the anal swab is not so appropriate as of oropharyngeal swab. Therefore, anal swab sample collection is limited to high-risk areas such as quarantine centers. It was observed that the virus lives a long time in the anus than the upper respiratory tract. Therefore, the anal swab tests remain positive in infected cases after giving negative results in the oropharyngeal swab [7]. Noticeably, it is concluded that anal swab tests could accurately identify the virus than any other swab tests. The significant purpose of anal swabs is to increase the detection rate and increase accuracy in identifying COVID-19 positive cases.
## 4 Results and Discussion
### Effect of Turbulence
#### 4.2.1 Pressure Distribution Analysis of the Train Surface  
The pressure variation trend around the train body is the main cause of the pneumatic load variation. Figure 10 shows the averaged pressure distribution curves at five cross-sections of the train body surface under different conditions, where the center of the windward surface is the \(\theta\) origin. The variation in lift coefficient mainly depends on the is reduced, and the roof pressure coefficient no longer drops in a zigzag fashion (as shown in Figure 10a,b) but in a straight line (as shown in Figure 10c-e) the trend of pressure coefficient variation on the top and bottom surfaces (45-135\({}^{\circ}\), 225-315\({}^{\circ}\)). From S1 to S5 cross-section, the influence of the streamlining of the head car, the head length increases, and the pressure coefficient difference between the bottom of Case 3 and Case 1 (225-315\({}^{\circ}\)) is obvious (as shown in Figure 10a,e). The longer the head length, the greater the negative pressure at the bottom and the greater the negative peak at the corner (\(\theta\) = 225\({}^{\circ}\)). Except for the top and bottom of the tail car, the increase in turbulence intensity is not very obvious to the change in the mean pressure coefficient, which explains the reason why the lift force of the tail car is more affected by the nose length.  
Figure 10: Time-averaged surface pressure coefficient in the five cross-sections of the train: (**a**) S1; (**b**) S2; (**c**) S3; (**d**) S4; (**e**) S5.  
The variation in side force coefficient and overturning moment coefficient is mainly influenced by the trend of pressure coefficients on the windward and leeward sides (0-45\({}^{\circ}\), 315-360\({}^{\circ}\)). From S1 to S5 cross-section, the windward side is reduced by the streamlined shape of the head, and the pressure coefficient at the roof (0-45\({}^{\circ}\)) no longer drops and then rises (as shown in Figure 10a,b) but remains more stable (as shown in Figure 10c-e). With the increase in head length, the negative pressure of pressure coefficient difference between Case 3 and Case 6 windward side of 10 m head becomes lower (as shown in Figure 10c-e). the negative pressure on the windward side of Case 3 is greater than that of Case 6, while the positive pressure on the leeward side is basically the same. Therefore, we conclude that increasing turbulence reduces the \(Cs\) of the tail car. The negative pressure on the top surface of Case 6 is greater than that of Case 3, while the negative pressure on the bottom surface of Case 3 is greater than that of Case 6, see Figure 10e. Thus, we conclude that increasing turbulence increases the \(C_{L}\) of the tail car. However, for the leeward side of the tail car, the increase in turbulence intensity is not very obvious to the change in pressure coefficient mean value of the leeward side of the remaining cross-section, and the increase in turbulence instead reduces the peak negative pressure of the windward side. The above also explains the reason why the side force coefficient of the tail car is more influenced by the nose length of the tail car.