esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Conclusions and Outlook  
With increasing use of electromagnetic radiation for mobile communication, extensive research is being performed on EMI shielding. Electrospun nanofiber mats with conductive and/or magnetic properties were shown to be often suitable especially for shielding of radiation in the X-band, partly also in the Ku-band and other bands. A broad range of approaches exists to tailor the shielding effectiveness of nanofiber mats, such as embedding conductive and/or magnetic nanoparticles, carbonization, coating with different methods and materials, or preparing composites with other materials.  
This review gives a brief overview of these possibilities, highlighting some of the most recent approaches, to stimulate further research combining and extending the most promising ideas of the state of research and technology.  
The increasing number of devices producing electromagnetic radiation especially in increasing frequency ranges, mostly related to communication, will make this research more and more important to protect humans and equipment from unnecessary electromagnetic irradiation, while at the same time not disturbing mobile phones or other communication devices. It can be assumed that textile shielding materials, based on absorption instead of reflection, will become more and more important due to their flexibility and drapability. Especially for these fabrics, it is necessary to develop reliable alternatives to the recently most often used ASTM D4935 to enable the faster screening of soft, flexible, potentially even elastic materials in order to accelerate EMI shielding tests.  
Conceptualization, T.B., A.H. and A.E.; investigation, T.B., A.H. and A.E.; writing--original draft preparation, T.B. and A.E.; writing--review and editing, all authors. All authors have read and agreed to the published version of the manuscript.  
This research was partly funded by the German Federal Ministry for Economic Affairs and Energy (grant no. KK5129710 KT1).  
Not applicable.  
The authors declare no conflict 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 Field Measurements
### Field-Measurement Results  
#### 3.2.1 Track-Geometry-Measurement System  
In this study, track irregularities were measured using a Track master. The targets of the track-irregularity measurements included the vertical profile, alignment, cross level, gauge, and twist. Relevant measurement results are presented in Figure 11.  
Figure 11: Cont.  
Figure 10: Measurements of track irregularities in the field-measurement section.  
As shown in Figure 11a, the measurements of the track irregularities of the HSR T1 track in the target section yielded maximum vertical profiles for the left and right rails of ~6.93 mm and ~7.41 mm, respectively. These exceeded the maintenance criteria by values in the range of 4-4.5 mm. In addition, it was found that the vertical profile was larger in the right compared with the left rail, and the right rail of the HSR T1 track was more vulnerable to the vertical profile due to the adjacent excavations.  
As a result of the alignment analysis, as shown in Figure 11b, the maximum alignments of the left and right rails were ~3.87 mm and ~5.04 mm, respectively, which exceeded the maintenance criteria by 1-2 mm. Additionally, a larger alignment occurred on the right rail compared with the left rail, and the right rail of the HSR T1 track was more vulnerable to alignment owing to the adjacent excavations.  
Regarding the cross level, the maximum cross level was ~5.16 mm, as shown in Figure 11c. This outcome exceeded the maintenance criteria by ~2 mm. The cross level  
Figure 11: Results of track irregularities measurements (HSR T1). (**a**) Ground conditions; (**b**) Alignment; (**c**) Cross level; (**d**) Gauge; (**e**) Twist.  
caused by adjacent excavation was analyzed to be \(\sim\)1.72 times greater than the maintenance criteria value.  
As shown in Figure 11d, the maximum gauge was \(\sim\)4.36 mm and exceeded the maintenance criteria value by \(\sim\)2 mm. Additionally, the gauge caused by adjacent excavations was analyzed to be \(\sim\)2.18 times larger than the maintenance criteria value.  
Regarding the twist, its maximum value was \(\sim\)4.62 mm, which exceeded the maintenance criteria by \(\sim\)1.5 mm, as shown in Figure 11e. The result confirmed that the gauge caused by the adjacent excavation was \(\sim\)1.54 times larger than the maintenance criteria value.  
As a result of the track-irregularity analysis with the use of the Track master, the track irregularities in the vertical direction were predominantly large at the tunnel construction section located at the center of the measurement section, and the range of the influence of the track irregularities was \(\sim\)20 m around the tunnel construction site.  
In particular, a clear trend of increase in the vertical profile was observed around the center of the measurement section at \(\sim\)150 m, which was the center of the tunnel construction, and the cross level, which represents the height difference between the left and right rails, was the largest at the position which was 25 m or more away from the center.
## 6 Matching User Preferences to Network Response
### Combining Evaluation Metrics for Comparison
#### 6.1.2 Weighting by Relative Importance  
To influence the solution scores to represent the desires of the application a weighting regime is imposed. This will add a weight to each of the criteria as per the needs of the application. Should an applications dictate a high requirement for latency, a weight will be applied increasing the effect of latency on the overall score. The solution with the best latency will thus enjoy an improved score over the other solutions. A weighing scheme using relative importance is used on application preferences. A relative importance weighted scheme is easily achieved with quantitative value criteria. The application simply places an importance in terms of a number from 1-100 on each of the criteria. If all criteria are of equal importance the application could place an importance value of 100 on them all. The weighting factor is derived directly from the importance value with an importance value of 36 receiving a weight of.36 and an importance value of 78 receiving a weight of 0.78 and so on.  
Figure 8: Scaling factor for the reliability criterion.  
The result of these processes is a set of scores which are representative of the quality the solution provides but also reflect the application goals within the network. From these scores a clear winner is easily chosen. The winner is the communication solution which is most likely to achieve the best fit with the application requirements within the current environment.
# Estimation and Evaluation of Zenith Tropospheric Delay from Single and Multiple GNSS Observations
## 3 Data Collection
### ERA5 Data  
The ERA5 provides NWM products for atmospheric research. Currently, data are available from 1940 up to one week behind the real-time epoch [42]. Compared with previous ECMWF ERA-Interim reanalysis, the ERA5 has introduced significant improvement, such as hourly sampling, the increase in the spatial resolution from \(\sim\)80 to \(\sim\)25 km, and the temporal resolution from 6 to 1 h [43; 44]. In this study, ERA5 layer products, downloaded from the ECMWF public dataset ([[https://cds.climate.opernicus.eu/cdsapp#f/dataset/](https://cds.climate.opernicus.eu/cdsapp#f/dataset/)]([https://cds.climate.opernicus.eu/cdsapp#f/dataset/](https://cds.climate.opernicus.eu/cdsapp#f/dataset/)), accessed on 2 February 2023), provide hourly temperature, geopotential, and specific humidity at 37 pressure levels with a horizontal resolution of 0.25\({}^{\circ}\). Geopotential height was converted to geodetic height in order to achieve the same height unit [45; 46; 47]. The ERA5 ZTD can be obtained using the index of refractivity at each geopotential layer of the ERA5 data by the integration method [48].
## 3 Results and Discussion
### Optimal Process Parameters for Injection Molding  
After the geometric optimization, the cooling channel with the highest cooling efficiency for the mold and the most even temperature distribution for the lens surface was adopted. Thus, the RGA-optimized cooling channel layout was selected for the DOE to determine the most suitable molding conditions. The optimal process parameters were selected on the basis of the signal/noise (S/N) ratio response. The optical properties of the lenses were compared before and after performing the DOE. Figure 17 illustrates the calculation results of the S/N ratio response from the DOE module of Moldex3D. The total S/N ratio response was obtained by adding the S/N ratio responses from three quality factors under four control factors and five levels (Figure 17d). A high S/N ratio  
Figure 16: Temperature difference between the inlet and outlet for: (**a**) the upper cooling channel and (**b**) bottom cooling channel.  
Figure 15: (**a**) Reference numbers and locations of the 18 measured nodes on the lens; (**b**) total thermal warpage values measured using the upper nodes (1–8); and (**c**) total thermal warpage values measured using the bottom nodes (9–16).  
indicates low noise (external influence). According to the Taguchi method, the level with the maximum S/N ratio was selected as the optimal condition [16; 29]. Therefore, the optimal combination of control factors, reported in Table 1, and their corresponding levels was A4B2C4D1. The optimal control factor level settings were A4 (melt temperature: 285 \({}^{\circ}\)C), B2 (mold temperature: 89.75 \({}^{\circ}\)C), C4 (filling time: 0.99 s), and D1 (packing time: 6 s). This combination of process parameters (A4B2C4D1) was used in the injection molding simulation. The optics module of Moldex3D was adopted to predict the birefringence and fringe pattern of the lens. After the DOE analysis, the birefringence of the lens considerably decreased (Figure 18a), which indicated that the residual stress within the material also diminished [16]. Moreover, after the processing optimization, the fringe pattern on the lens resembled concentric circles (Figure 18b). The distributions of the fringe pattern on the optimized molded lens were rarefied near the gate, which implied that the optical properties of the lens had been improved.  
Figure 17: S/N ratios for: (**a**) shear stress at the end of the filling stage; (**b**) shear stress at the end of the packing stage; (**c**) total warpage; and (**d**) sum of responses from (**a**) to (**c**).
# An Overview of Vehicular Communications
## 3 Vehicle-To-Infrastructure  
Unlike the V2V communication model, which allows the exchange of information only among vehicles, the V2I enables vehicles in transit to interface with the road system. These components include RFID readers, traffic lights, cameras, lane markers, street lamps, signage, and parking meters [46]. Commonly, V2I communications are wireless, bidirectional, and similarly to V2V, using Dedicated Short-Range Communication (DSRC) frequencies to transfer data [47]. This information is sent from the elements of the infrastructure to the vehicle, or vice versa, through an ad-hoc network. In the ITS, V2I sensors can acquire infrastructural data and provide travelers with real-time advice, sending information on road conditions, traffic congestion, any accidents in the roadway, the presence of construction sites and the availability of parking spaces. Likewise, traffic supervision and management systems can use the data collected from the infrastructure and vehicles to set variable speed limits and adjust the Signal Phase and Timing (SPaT) to achieve fuel savings and facilitate traffic flows [48]. The hardware, software, and firmware that make communication between vehicles and infrastructure reasonable are a fundamental starting point for the development of autonomously driven cars.  
In January 2017, the US Department of Transportation issued V2I guidelines for the Federal Highway Administration (FHA), aimed at improving safety and mobility, accelerating the implementation of communication systems [49]. These guidelines are designed to help state governments in preparing V2I initiatives and managing the data needed to support them. For the realization of these projects, as already mentioned, the problems of financing and obtaining resources arise from governments. Since these costs cannot be sustained only by the income of the states, coming from fuel taxes and motorway tolls, a partnership is needed with the primary vehicle's manufacturers, which could benefit for their commercial purposes of big data used in communications.
## 3 Results and Discussion
### Stage III
#### 3.3.5 Flowability  
The 2 FI model allowed the significant prediction (_p_-value \(<\) 0.05) of HR of model MD powders. A satisfactory fit of the model to the data verified experimentally was noted, which was confirmed by the relatively high value of the determination coefficients (R\({}^{2}\) = 0.7510) and the insignificant result of the lack of fit test (_p_-value \(>\) 0.05) (Table A2). Based on the estimated parameter values (Equation (8)) and response surface plots (Figure 12), it can be concluded that increasing IAT and FC had a positive effect on HR, while increasing IAH had a negative effect. The effect of IAH was larger than IAT and FC; however, as ANOVA showed, IAH and FC had a significant influence on HR, while IAT term was not significant (_p_-value \(<\) 0.05).  
It was found that with increasing IAT, powders were more cohesive and less flowable, and increasing humidity resulted in the formation of powders with better flowability. Thus, the powder obtained at the lowest temperature (80 \({}^{\circ}\)C), and the ambient humidity with the low maltodextrin concentration (10%) in the feed solution, is considered the most satisfying in terms of flowability (Table A1). At the same time, [PERSON] and [PERSON] (2019) also found that the decrease in IAT (from 190 to 150 \({}^{\circ}\)C) resulted in better flowability properties for the microencapsulated cream powders ([PERSON] _et al._ (2025). [PERSON] et al. (2025) noted as well that when the spray drying of milk powder with curcumin _Cissus quadrangularis_ (CQ) extract lowered IAT from 200 to 160 \({}^{\circ}\)C, the powders' flowability improved ([PERSON] _et al._, 2020).  
\[HR=1.10+0.1444\cdot IAT-0.4503\cdot IAH+0.1163\cdot FC+0.1413\cdot IAT\cdot IAH-0.0431\cdot IAT\cdot FC+0.1362\cdot IAH\cdot FC \tag{8}\]
# Combating Web Tracking: Analyzing Web Tracking Technologies for User Privacy
## 3 Countermeasures against Web Tracking
### Tracking Prevention
#### 3.2.2 Adding a Noise or Randomization  
JavaScript APIs that output multimedia elements can vary based on the user's hardware and environment settings, making it possible for trackers to extract a unique fingerprint through these APIs. Therefore, to thwart fingerprinting, one can incorporate a random value into the output or employ a technique that shows a non-specific value. This makes it impossible to accurately depict the real user's environment through the direct or indirect output of the API.  
[PERSON] et al. [39; 40] developed Blink and FPRandom. Blink automatically reconfigures user platforms consisting of diversified platform components (DPCs) such as font, plugins, browsers, operating system, and CPU architecture, and uses virtual machines for this purpose. The disadvantage of Blink is that it relies on components that occupy a large amount of disk space, and it can be difficult to use virtual machines on low-performance computers. FPRandom modifies Firefox's code and adds a random value to the value derived by the browser function to deliver a different return value between each browsing session. Plugins and font lists were two main attributes of identifying devices, but researchers considered canvas, AudioContext, and JavaScript property orders due to changes in fingerprinting techniques at the time.  
[PERSON] et al. [38] developed FPGard by modifying the Chromium browser to randomize elements like canvas and font, which can be used for fingerprinting. In addition, since each API has its own characteristics, researchers proposed a randomization method that fitted the characteristics of APIs.  
[PERSON] et al. [42] developed PriVaricator. In order to randomize to a realistic value, PriVaricator takes a method such as selecting an arbitrary number within an appropriate numerical range or adding an in-range noise to the original value. Through this, researchers proposed a method for minimizing the phenomenon of site breaking and returning a more realistic value in the randomization process.  
[PERSON] et al. [41] developed Disguised Chromium Browser. It complements the methods used in traditional FPRandom and PriVaricator (which continuously disable or randomize system and browser parameters) and is a solution developed in such a way that the values of elements change from session to session, randomizing features to more realistic values and preventing continuous changes to system parameters. It considers elements such as canvas, user-agent, screen size, etc., among browser history, navigator, and JavaScript APIs.
## 4 Digital Domain Processing
### Physical Layer Frame Format  
For the hierarchical data transmission in underwater packet-based communication systems, the frame format of the physical layer is designed as depicted in Figure 4. At the beginning of each frame, a preamble having a length of 4 octets and the value 0 xAAAAAAAA is inserted to recognize the existence of a frame and obtain symbol synchronization at the receiver. The following field is SFD, indicating the end of the preamble. In this application, one octet is allocated for SFD and its value is 0 xFF. The preamble and SFD are often called a synchronization header (SHR) because they are used for frame and symbol synchronization. After SHR, a frame length field is inserted to inform a receiver of the length of physical layer payload. Frame length field itself constitutes the physical layer header (PHR). The last field is the physical layer service data unit (PSDU). Since the length of the frame length field is one octet, the maximum length of PHY payload amounts to 255 octets. All of the abovementioned field types and lengths could be varied according to the underwater channel environment, maximum data rate of the acoustic modem, and desired underwater applications.
## 2 Materials and Methods  
### General  
The \({}^{1}\)H-NMR spectra were obtained by 400 or 600 MHz spectrometers (Bruker, Billerica, MA, USA). The \({}^{1}\)H chemical shifts are described as \(\delta\) values in ppm relative to acetone-d\({}_{6}\) (2.05 ppm), DMSO-d\({}_{6}\) (2.50 ppm), CDCl\({}_{3}\) (7.26 ppm), and tetramethylsilane (1H, 0.00 ppm). The \({}^{13}\)C NMR spectra were obtained by a Bruker 600 MHz spectrometer. The \({}^{13}\)C chemical shifts are described as the \(\delta\) values in ppm relative to acetone-d\({}_{6}\) (29.84 ppm), DMSO-d\({}_{6}\) (39.52 ppm), and CDCl\({}_{3}\) (77.16 ppm). The \({}^{31}\)P-NMR spectra were recorded by a Bruker 500 MHz (202 MHz for \({}^{31}\)P). The multiplicity and qualifier abbreviations are as follows: s = singlet, d = doublet, t = triplet, q = quartet, quin. = quintet, sept. = septet, m = multiplet, br = broad. The electrospray ionization (ESI) mass spectra were recorded using a BioTOF II mass spectrometer or APEX III (Bruker Daltonics, Bruker, Billerica, MA, USA). The matrix-assisted laser desorption/ionization (MALDI-TOF) mass spectra were recorded Autoflex speed mass spectrometer and a laser at 337 nm in the negative mode using 3-hydroxypicolinic acid as the matrix or in the positive mode using 2,5-dihydroxyboxbenzoic acid as the matrix. Thin-layer chromatography (TLC) was performed using silica gel 60 F\({}_{254}\) pre-coated plates. Column chromatography was performed using silica gel 60 N (spherical, neutral, 100-210 \(\mu\)m, Kanto Chemical, Tokyo, Japan). Flash chromatography was performed using Kanto Chemical silica gel 60 N (spherical, neutral, 40-50 \(\mu\)m). The ultraviolet-visible (UV-vis) absorption spectra were recorded using a DU800 spectrometer (Beckman Coulter, Brea, CA, USA). The ODN synthesis was carried out using an automated DNA synthesizer (392 DNA/RNA synthesizer, ABI, Foster City, CA, USA) following the standard phosphoramidite chemistry. High performance liquid chromatography (HPLC) was performed using a Cosmosil SC18 MSII column (4.6 or 10 \(\times\) 250 mm, NACAlai Tesque, Kyoto, Japan), a PU-986 pump (JASCO, Tokyo, Japan), JASCO 2075 UV detector and a JASCO 2067 column oven. pH measurements were measured by a Seven Easy pH meter (Mettler Toledo, Columbus, OH) using an 8220 BNWP electrode. The denaturing polyacrylamide gel plates were visualized and quantified using a FLA-5100 Fluor Imager (Fujifilm, Tokyo, Japan). Anhydrous methanol, DMF, THF, CH\({}_{2}\)Cl\({}_{2}\), dioxane, pyridine, DMSO, CH\({}_{3}\)CN, toluene and THF were purchased from Wako Pure Chemical Industries, Ltd. (Tokyo, Japan). Unless otherwise noted, all the synthetic reactions were carried out at ambient temperature. The reactions requiring anhydrous conditions were achieved under an argon atmosphere in flasks dried under 1-3 mmHg. Commercially available reagents were obtained from Wako Pure Chemical Industries, Ltd., TCI, Inc., (Tokyo, Japan), Sigma-Aldrich Co. LLC (St. Louis, MO) and Kanto Chemical Co., Inc (Tokyo, Japan) and used without further purification. Human DNA (cytosine-5) methyltransferase (DNMT1) was obtained from New England Bio Labs Japan, Inc. (Tokyo, Japan)
## 3 Results and Discussion
### PAH Concentrations in the Sediments
PAH concentrations determined in the sediments of Kastela Bay are shown in Figure 4. T-PAH concentration ranged from 278.64 \(\upmu\)g kg\({}^{-1}\) to 2888.9 \(\upmu\)g kg\({}^{-1}\). The highest T-PAH concentrations during the two campaigns were measured at station KB3, which is located near the industrial port of Split and the shipyard area. C-PAH were the dominant PAH compounds, with concentrations ranging from 151.62 \(\upmu\)g kg\({}^{-1}\) to 1798.8 \(\upmu\)g kg\({}^{-1}\). Predominance of C-PAH fraction at each station of Kastela Bay indicate that PAH pollution in this area is mostly contributed by petrogenic sources [2]. PAH concentrations in Kastela Bay are similar to the concentrations reported for the urban, coastal areas of the Mediterranean Sea, although they are lower than the PAH concentrations measured in the sediments of big harbour cities in the Mediterranean Sea, such as Toulon and Barcelona [8; 26; 27; 30]. Concentrations of specific groups of PAH, determined in the sediment of Sibenik Bay, are shown in Figure 5. T-PAH concentrations ranged from 8280.8 \(\upmu\)g kg\({}^{-1}\) to 28,662 \(\upmu\)g kg\({}^{-1}\). The concentrations of the unsubstituted parent compounds were higher than the concentrations of C-PAH at every station. The highest concentrations of PAH were measured at station SB4A, which is closest to the area where a ferroalloy plant operated from 1880 to 1990. The high concentrations of PAH observed at station SB4 during both sampling periods can also be attributed to past industrial activities, as this station is only 100 m away from SB4A. A high proportion of the C-PAH fraction in the total concentrations of PAH was observed at station SB1, in February. Since this station is located near a tourist marina, the elevated concentrations of C-PAH can be explained by accidental leakage of petroleum derivatives during ship maintenance, which usually occurs during the winter season. The lowest concentration of T-PAH was observed at station SB5, which is farthest from shore. No seasonal trend in the concentration of PAH was observed. The very high PAH concentrations measured at each station in Sibenik Bay are similar to concentrations measured in the sediments of highly industrialized areas, such as Venice, Toulon, Barcelona, Mexico Bay and other coastal areas worldwide [8; 19; 28; 30; 31].