esa-sceva/satcom-chunk-collection huggingface dataset:
# Modalflow: Cross-Origin Flow Data Visualization for Urban Mobility
## 4 Materials and Methods
### Flow Map with Sinusoidal Encoding  
The flow map is the overlaying of a graph (where nodes are georeferenced points and flows are directed edges) on top of a geographic map. Its function is to reveal geospatial patterns, like sinks and sources of flows. However, as representing the flows for a whole city leads to a lot of clutter and low readability in the direction of flows, we developed a novel encoding for flows that uses a sinusoidal curve rather than an arrow or arc.  
[PERSON] conceptualized transport as \"a set of networks stitching together spaces and places, from which locations naturally emerge\" [47]. This metaphor of transport weaving the fabric of the city is evocative of a graph-like visualization of flows. Through it, we were inspired to design a new encoding to facilitate distinguishing incoming from outgoing flows, particularly over a geographic layout. Figure 4 schematically shows the two most common encoding alternatives for links in a graph, followed by our novel sinusoidal encoding. This encoding was designed, so that it brings a new symmetry into perspective, where directed links that go through a node get immediately divided into incoming and outgoing in the vertical dimension, which makes for an intuitive way to select them, as shown in Figure 4.  
Figure 4: Sinusoidal encoding design space and working schema. Left: Bidirectional flow encoding alternatives: (**a**) straight; (**b**) arched; and, (**c**) sinusoidal, which projects a third dimension into perspective, differentiating in- and outflows in the vertical dimension. Right: schematic view of incoming and outgoing flows at a certain node. Flow direction becomes quickly distinguishable thanks to the sinusoidal flow encoding.  
The sinusoidal encoding is achieved using a centripetal Catmull-Rom spline for each directed node-pair. The spline is defined by control points \(P_{0}\), \(P_{1}\), \(P_{2}\), and \(P_{3}\), where \(P_{1}\) and \(P_{2}\) are the position of the start node and end node, correspondingly, and  
\[P_{0}=(P_{1}x,P_{1}y+k*distance(P_{1},P_{2})),\]  
\[P_{3}=(P_{2}x,P_{2}y-k*distance(P_{2},P_{1})),\]  
where \(k\) is a constant that ponders the vertical elongation of the curves.  
As this new edge drawing technique does not get rid of the clutter, but rather tries to improve its visual organization, two known techniques to improve readability were also implemented in the rendering of flows: edge sorting (edges representing bigger flows are drawn on the front) and transparency (edges that represent less flow magnitude are less opaque).
# Effects of Nanoparticles on Algae: Adsorption, Distribution, Ecotoxicity and Fate
## 5 Factors Affecting Toxicity of NPs on Algae  
### Environmental Factors  
The toxicity of NPs on algae is influenced by various factors, particularly the characteristics and properties of the aquatic environment around algae, such as water chemistry, light and water temperature [23]. The hydrochemical conditions are important factors that influence the suspension of NPs, including dissolved natural organic matter (NOM), ionic strength and pH [8]. NOM can be adsorbed on NPs to alter the surface functional groups of NPs or form thin films, and enhance their migration and diffusion capabilities. NOM stabilized the particle size by covering the surface of NPs due to electrostatic repulsion [79]. The coating of NOM may limit the release of ions from NPs into the water [80], prevent NP aggregation [81] and reduce the toxicity of NPs on the algae [82]. The ionic strength and pH of natural water bodies can change the suspended state of NPs in water [83], which also influences the adsorption of NPs to NOM [84]. Water hardness is another important NP toxicity mitigator, promoting NP aggregation and decreasing dissolution [85]. In addition, water temperature, light and pollutant emissions will affect the toxicity of NPs. It is known that temperature directly affects aquatic ecosystem communities [86] since it is regarded as an important abiotic factor influencing the growth and production of primary producers such as algae. A higher dissolution rate of Ag NPs was obtained with an increased temperature [87]. Therefore, the toxicity of NPs to algae could be affected by temperature due to the change in the physiological status of algal cells and the existing state of NPs. Because some NPs are semiconductors with photocatalytic properties, NPs exposed to UV-light may cause a toxic effect on algae through the formation of highly reactive ROS [23], [PERSON] et al. [20] found that NPs were more toxic to algal cells irradiated with UV-C (a high energy radiation with a wavelength less than 280 nm) than those treated in dark and visible conditions.
# Underground Mine Road Detection Using Deep Learning Technique
## 3 Experiment and Results
### Experimental Evaluation Index  
In order to quantitatively analyze the segmentation effect of the algorithm, mean intersection over union (mIoU), pixel accuracy rate (PA--pixel accuracy), and Dice coefficient were used as the evaluation indicators of the road segmentation model. The indicators are defined as follows:  
mIoU: the ratio of the intersection and union of the predicted value set and the real value set is calculated, the IoU on each category is calculated, and the mean value is taken to be the mIoU. The calculation method is as follows:  
\[\text{mIoU}= \frac{1}{\text{k}+1}\sum_{i=0}^{\text{k}}\frac{\text{TP}}{\text{FN}+ \text{FP}+\text{TP}} \tag{6}\]  
Among them, TP is the number of pixels that are correctly classified as foreground, TN is the number of pixels that are wrongly classified as foreground, FP is the number of pixels that are wrongly classified as background, and FN is the number of pixels that are correctly classified as background.  
Pixel accuracy rate PA: refers to the proportion of the predicted correct pixel amount to the total pixel amount. The calculation method is as follows:  
\[\text{Accuracy}= \frac{\text{TP}+\text{TN}}{\text{TP}+\text{FP}+\text{FN}+\text{ TN}} \tag{7}\]  
Dice similarity: Dice similarity is also known as F1 metric, which is determined by two parameters, precision and recall, and is used to calculate the similarity of two sets. When the Dice value is high, it means that the experimental method is more effective. The calculation method is as follows:  
\[\text{Dice}= \frac{2}{\frac{1}{\text{P}}+\frac{1}{\text{R}}}=\frac{2\times\text{ P}\times\text{R}}{\text{P}+\text{R}} \tag{8}\]  
where R is the recall rate, which refers to the ratio of the number of pixels that are correctly predicted as foreground to the total number of pixels that are actually foreground; P is the precision, which refers to the number of pixels that are correctly predicted as foreground and the number of pixels that are predicted to be foreground ratio.
# Drilling Fluid and Cement Slurry Design for Naturally Fractured Reservoirs
## 2 Determining the Location of the Thief Zone and the Classification of Fluid Loss
### The Classification of Fluid Loss  
The best approach to cure lost circulation is to assess the severity of fluid loss (drilling fluid or cement slurry) in the loss zone and match the remedial material and technique to it, both in terms of the size of the material and its function. According to the severity of fluid loss, lost circulation can be classified into four categories: seepage loss, partial loss, complete loss, and severe complete loss [5]. The severity of loss is best determined by the amount of loss and the static mud column height (see Table 2).  
From the data shown in Table 2, it can be concluded that during drilling through fractured formations, and depending on the size of the fracture, partial losses, and even more often, complete (total) mud losses can occur.  
Different classifications can be found in literature according to the severity of losses and with different values of the loss rate (see Table 3). Also, the rate of loss is stated differently depending on the conditions as static loss rate (occurs in static conditions) and flowing loss rate (occurs in dynamic conditions) [4; 9; 11; 43; 44]. Some authors and companies also base the distribution of losses on the type of mud and state lower values for oil-based muds (OBM) than for water-based muds (WBM) [45; 46].  
Based on the data shown in Table 3, it can be concluded that most authors and companies agree on the definition of seepage (_minor losses_; <1.6 m\({}^{3}\)/h) and total losses (no drilling fluid returns to the surface). Defining partial (_moderate/medium losses_; from 1.6 to even 80 m\({}^{3}\)/h) and severe (_massive/complete_; from 3.2 to more than 80 m\({}^{3}\)/h) losses differs significantly.  
\begin{table}
\begin{tabular}{c c c} \hline
**Severity of Loss** & **Rate of Loss** & **Type of Formation** \\ \hline \multirow{3}{*}{Seepage} & \multirow{3}{*}{0.16 to 1.6 m\({}^{3}\)/h} & Any permeable formation type when the bridging agents are not large enough to form a seal, or when there are no fine particles to complete the seal. \\  & & Highly porous or fractured formations, gravel, small natural fractures and barely opened induced fractures. \\  & & Long, open sections of gravel, long intervals of small natural fractures, large natural fractures (caverns, vugs) or open induced fractures. \\ \hline \multirow{3}{*}{Severe complete} & mud level at 152 to 305+ m below wellhead & Large, open natural fractures, caverns, and open induced fractures. \\  & & \\ \hline \end{tabular}
\end{table}
Table 2: Classification of mud loss according to its severity [5].
# Research on Phase Stabilization Algorithm of Femtosecond Timing System
## 5 System Testing  
### Signal Phase Test Without Automatic Control  
A timing system prototype has been developed based on structural divisions, as illustrated in Figure 8. In particular, Figure 8 depicts the physical prototype of the timing system, while Figure 8 presents the schematic representation of the continuous-wave laser unit. The fiber length is 0.5 m, and the frequency of the high-frequency reference signal is 499.8 MHz.  
Figure 8: (**a**) Physical schematic diagram of femtosecond timing system; (**b**) Physical schematic diagram of continuous wave laser.  
Figure 7: Algorithm flow chart.  
In the absence of the phase correction module and algorithms, the phase delay of the high-frequency reference signal and the ambient temperature over time are shown in Figure 9. From the figure, it can be observed that after 8 h of continuous testing, the temperature fluctuation reached 1 \({}^{\circ}\)C, under which the maximum phase offset was 2484.75 fs, with an average offset of 1374.104 fs.
# Towards DC Energy Efficient Homes
## 3 Factors for DC Installations
### Standardization of DC Connectors  
Due to the wide range of applications, DC connectors can be of different types. From the well-known USB, and its power delivery extension of up to 100 W, to Ethernet, also up to 100 W, there is a wide array of options; for example, different types of USB (type A, type B, type C, type D, and also the mini and micro versions, mini A, micro A, mini B, and micro B), lightning, thunderbolt, etc. Currently, USB connectors are used to charge the batteries of electronic devices (smartphones, tablets, laptops, wearables, etc.), to supply power to some peripherals (scanners, webcams, headsets, speakers, etc.), and to supply power to small size devices, such as fans, handheld vacuum cleaners, juicer machines, mixers, etc. [75, 86]. However, the limit of power does not presently allow to connect every device, although research and development in the mobile industry will soon allow phones to be charged at 125 W with an efficiency of 98% [87], and so it is possible that load powers will be extended in the coming years. In fact, in the market, combined AC and USB sockets are available, due to their generalized use, and also USB sockets can be found in public access places, such as parks, squares, bus stops, shopping centers, etc.  
The different DC voltage levels can be easily obtained or maintained with a buck-boost converter. These types of converters can increase or reduce voltage levels when necessary through two main parts, the buck converter, which reduces the voltage, and the boost converter, which increases the voltage. The efficiency of buck-boost converters is 98% and they are widely used in consumer electronics, control applications, or power amplifiers [88].
###### Abstract  
This study aimed to perform a qualitative synthesis of the available in vitro evidence on the microleakage of commercially available conventional glass ionomer cements (GICs), resin-modified glass ionomer cements (RMGICs), and modified glass ionomer cements with nano-fillers, zirconia, or bioactive glasses. A systematic review was conducted according to the PRISMA 2020 (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement standards. The literature search was performed in Medline (via PubMed), Embase, Web of Science, and Scopus to identify relevant articles. Laboratory studies that evaluated microleakage of GICs, RMGICs, and modified glass ionomer cements with nano-fillers, zirconia, or bioactive glasses were eligible for inclusion. The QUIN risk of bias tool for the assessment of in vitro studies conducted in dentistry was used. After the study selection process, which included duplicate removal, title and abstract screening, and full-text assessment, 15 studies were included. A qualitative synthesis of the evidence is presented, including author data, year of publication, glass ionomer materials used, sample characteristics, microleakage technique and values, and main outcome measures for primary and permanent teeth. Although no statistically significant differences were found in numerous studies, most results showed that RMGICs exhibited less leakage than conventional GICs. All studies agreed that leakage was significantly higher at dentin margins. It was also higher at the gingival margin than at the occlusal margin. Nano-filled RMGICs Ketac N100, Equia Forte, and Zirconomer appear to have less microleakage than conventional GICs and RMGICs. Further investigations using a standardized procedure are needed to confirm the results.  
d 2024 14 1729. [[https://doi.org/10.3390/app14051729](https://doi.org/10.3390/app14051729)]([https://doi.org/10.3390/app14051729](https://doi.org/10.3390/app14051729))  
1
# A Review on Styrene Substitutes in Thermosets and Their Composites
## 2 Traditionally Crosslinkable Monomers
### Vinyl Monomers
#### 2.1.2 Other Vinyl Monomers  
More recently, two new types of vinyl monomers, i.e., NVP and TDE, were selected to replace styrene in UPE resins for the production of hemp fiber reinforced composites, respectively [29]. As given in Table 1, NVP has a C=C bond that links with nitrogen, giving the C=C bond with a high reactivity due to the electronegativity of nitrogen. TDE has two C=C bonds, which has more opportunities for crosslinking with UPE (Table 1). The results indicated that both monomers could effectively dissolve solid UPE, reduce the entanglement of UPE chains, and significantly reduce the viscosity of the resulting resins (from 50 to 500 mPa-s at room temperature). NVP-based resin composites showed comparable tensile and higher flexural properties with styrene-based resin composites because NVP is a highly reactive monomer.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Monomers** & \begin{tabular}{c} **Molecular Weight** \\ **(g/cm\({}^{3}\))** \\ \end{tabular} & \
\begin{tabular}{c} **Boiling** \\ **Point (\({}^{\circ}\)C)** \\ \end{tabular} & **Toxicity** & **Chemical Structure** \\ \hline \hline \multirow{2}{*}{
\begin{tabular}{c} Styrene \\ Divinylbenzene (DVB) \\ \end{tabular} } & 104.15 & 145–146 & acute toxicity \\  & 130.19 & 195 & acute toxicity \\  & 118.18 & 165–169 & acute toxicity \\  & 122.14 & 67 & - \\  & 118.18 & 169–171 & acute toxicity \\  & 111.14 & 92–95 & acute toxicity \\  & 111.14 & 92–95 & acute toxicity \\  & 111.14 & 202.25 & 120–126 & - \\  & 1202.25 & 120–126 & - \\ \hline \hline \end{tabular} Note: The data were obtained from the data sheet provided by Sigma-Aldrich (St. Louis, MO, USA).  
\end{table}
Table 1: Characteristics of commonly used vinyl monomers as reactive diluents (RDs).  
Following this work, NVP was further utilized as a RD for AESO resins for preparing the hemp fiber reinforced AESO composites with high performance [30]. It was found that NVP-AESO resins had better processability than styrene-AESO resins, and hemp fiber-reinforced NVP-AESO composites achieved superior static and dynamic mechanical properties when compared to styrene analogues. To improve the crosslinking degree of AESO matrix and its interfacial adhesion with hemp fibers, isophorone diisocyanate (IPDI) was further incorporated into the hemp fibers/AESO composite system [31]. Due to the chemical characteristic of AESO, the IPDI could serve as two functions in the composite system: one is crosslinker within AESO resin for increasing its crosslinking density; the other is coupling agent between hemp fibers and AESO thus giving rise to the interfacial bonding of the composites. The comparison on tensile-fractured surfaces of composites intuitively showed that the addition of diisocyanate improved the interfacial adhesion between fibers and resins. The tensile and flexural properties, storage modulus, and glass transition temperature of the composites were accordingly increased by significantly enhanced interface and crosslinking density.
# A Traffic Information Detection Method at Single Intersection Based on Wi-Fi Data
## 2 Theoretical and Technical Foundations
### Key Technology
#### 2.2.2 K-Means Clustering  
This method still maintains high efficiency and scalability when processing extensive data. Due to its simplicity and speed, this method is effective for recognizing urban cross-traffic information [38].  
The common performance indicators of clustering algorithms are the sum of squared error (SSE) and the silhouette coefficient. The sum of the squares errors is an important objective function in the iteration of the clustering algorithm, and can directly reflect the quality of the clustering effect, as in (1). The smaller the sum of squares error, the better the clustering effect. Generally, the sum of squares error gradually decreases with an increase in the number of clusters, but blindly increasing the number of clusters increases the computational complexity.  
The average silhouette coefficient is the average value of the silhouette coefficient of all samples in the clustering process, which can fully reflect the degree of cohesion and  
Figure 1: Architecture diagram of Wi-Fi data acquisition system.  
separation of each sample in the clustering result, as shown in (2). The value interval of the average silhouette coefficient is \([-1,1]\). The larger the value, the better the result. When the value is close to zero, the clustering result samples overlap. A negative value indicates that a large number of samples are assigned to clusters that do not meet the expectations.  
\[SSE=\sum_{i=1}^{K}\sum_{p\in C_{i}}\left|p-m_{i}\right|^{2} \tag{1}\]  
Among them, \(K\) is the specified initial cluster number, \(Ci\) is the \(i\)th cluster, \(p\) is the sample point in \(Ci\), and \(m_{i}\) is the central point in \(Ci\).  
\[\overline{S}=\sum_{i=1}^{n}\frac{b_{i}-a_{i}}{\max(a_{i},b_{i})}/n \tag{2}\]  
where \(\overline{S}\) is the average silhouette coefficient and \(n\) is the number of cluster samples. \(a_{i}\) is the average Euclidean distance between the \(i\)th sample and other samples in the same cluster, which reflects the cohesion of the sample. \(b_{i}\) is the average Euclidean distance between the \(i\)th sample and other samples in different clusters, which reflects the separation degree of the sample.
# Analysis of New Orthogonal Transforms for Digital Watermarking
###### Abstract  
The paper focuses on the application of new orthogonal transforms in digital watermarking. Novel types of transforms and their characteristics are presented. Potential methods for watermark embedding and recovery are also proposed. They assume embedding hidden information in the transform domains using the luminance channel of the original image. Image spectra are obtained by dividing the original image into smaller blocks that then are further processed by performing the forward transform operation. A watermark is embedded by modifying the spectral coefficients with relatively low values. Since there are various types of transforms, the latter process is realized in an adaptive manner. The proposed solutions were evaluated by measuring the level of visual distortion with respect to the total size of the inserted data. Additionally, the bit error rate (BER) in the recovery phase is also analyzed. The elaborated methods seem to be useful for applications in digital signal and image processing where high imperceptibility and low BER are of great importance. New orthogonal transforms were proved to be useful in watermarking tasks, and in some cases, they can even outperform the classic DCT approach.  
watermarking; image protection; steganography; multimedia systems; image processing 202  
(DWT) [10; 11], and Walsh-Hadamard transform [12]. In addition, transform-based methods can be used jointly with other techniques, such as, e.g., discrete fractional random transform (DFRNT) [3] or singular value decomposition (SVD) [13].  
Usually, the aforementioned transform types are modified and enhanced in order to improve some aspects of the already known watermarking approaches. On the other hand, sometimes, even completely new transforms are proposed and tested as far as their applicability in various tasks is concerned. As an example, Periodic Haar Piecewise-Linear (PHL) transform was evaluated and confirmed to be useful for watermarking purposes by achieving promising results and even outperforming classic DCT transform in some aspects [14]. Another attempt was presented in [15], where multiparameter discrete transforms based on discrete orthogonal polynomials are used for watermark embedding.  
In this paper, another set of recently introduced orthogonal transforms has been investigated with regard to their applicability in digital watermarking [16].  
The paper is organized as follows. The following section presents the transform types that are analyzed. Section 3 describes the watermark embedding methods used for the assessment of the usability of the transforms being examined. Section 4 contains the experimental results and comparisons of the proposed solutions with the DCT approach. Finally, Section 6 presents the conclusions and future work.