esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Enhanced Mathematical Model with Atmospheric and Environmental Effects
### Free-Space Path Loss (FSPL) with Atmospheric Attenuation  
The FSPL model describes basic signal attenuation over a distance \(d\) in a vacuum, given by  
\[\mathrm{FSPL}(dB)=20\log_{10}\bigg{(}\frac{4\pi df}{c}\bigg{)} \tag{8}\]  
where \(f\) is the frequency, \(c\) is the speed of light, and \(d\) is the distance between the transmitter and receiver. To incorporate real-world environmental losses, we add atmospheric attenuation, particularly relevant at high frequencies. The FSPL with atmospheric attenuation FSPL\({}_{\text{atm}}\) is given by  
\[\mathrm{FSPL}_{\text{atm}}(dB)=20\log_{10}\bigg{(}\frac{4\pi df}{c}\bigg{)}+A _{\text{atm}}\cdot d \tag{9}\]  
where \(A_{\text{atm}}\) is the atmospheric attenuation factor in \(\mathrm{dB/km}\). Atmospheric attenuation, denoted as \(A_{\text{atm}}\), is primarily affected by two components: the dry air attenuation coefficient, \(\alpha_{\text{dry}}(f)\); and the water vapour attenuation coefficient, \(\alpha_{\text{wet}}(f)\). These components are frequency-dependent, and their combined effect over a distance \(d\) can be modelled by the equation  
\[A_{\text{atm}}(f,d)=\Big{(}\alpha_{\text{dry}}(f)+\alpha_{\text{wet}}(f) \Big{)}\cdot d \tag{10}\]  
where \(f\) is the signal frequency. Both \(\alpha_{\text{dry}}(f)\) and \(\alpha_{\text{wet}}(f)\) tend to increase with frequency, leading to higher attenuation levels as \(f\) rises. This relationship underscores the vulnerability of higher frequencies to atmospheric effects, especially over extended distances.
# Improvement of Position Repeatability of a Linear Stage with Yaw Minimization
## 3 Factors Affecting the Yaw Motion
### Controllable Parameters: Design, Manufacturing Conditions
#### 3.2.2. Center of Mass & Center of Stiffness
Figure 20 suggests that when the value of the _CS_ and _CM_ is maintained close to an _FO_ of 80%, the allowable yaw angle is achieved for a _PA_ of 10 \(\upmu\)m. Figure 21 shows that  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline _CM_[\(CS\)] & **0\%** & **20\%** & **40\%** & **60\%** & **80\%** & **100\%** \\ \hline
0\% & 5.96 & 5.38 & 4.19 & 2.39 & 0.0012 &  
At this point, it may be suggested that the values of the _CS_ and _CM_ need to be close to an _FO_ of 80%, while _PA_ may be maintained in the vicinity of 10 \(\upmu\)m. This will require the ratio \(k_{3}/k_{1}\) to be less than 0.1 and balancing weight to the platform for 80% of _CM_. In practice, it is difficult to accurately match the ratio \(k_{3}/k_{1}\) with commercially available LM Guides. One alternative is to choose \(k_{3}=0\) with a _CS_ of 100%. Keeping the blocks of rail number two simply supported in the \(z\)-direction without constraints in the \(x\)- and \(y\)-directions can be a practical solution, as illustrated in Figure 22.  
Figure 23 shows three yaw angle waveforms for the deceleration stage of the trapezoidal motion profile for the number four platform at 80% _FO_. The
## 3 Results and Discussion
### Crack Growth Trend Simulation
#### 3.2.2 Bridge Segment  
The constraint from cable bracings installed on the top of the specimen during fatigue testing is relatively weak. In reality, both ends of an anchorage segment can be deemed fixed because of the constraints from adjacent segments. Also, the type of extra stiffener added to the test specimen does not exist in the actual bridge. Therefore, a similar crack growth pattern analysis was performed for a more realistic bridge simulation. Analysis results of the crack propagation evolution are shown in Figure 15.  
Figure 15: Simulation of crack propagation path in bridge segment: (**a**) Location of fatigue crack initiation; (**b**) Crack growth under different analysis stages.  
As shown in Figure 15, a crack appears in the girder's outer web at its connection with the upper support plate on the side of the anchor plate, where the stress distribution is most unfavorable under bridge operation conditions. At Step \(-1.5\), the crack is symmetric around the center of the upper support plate in the thickness direction, with a half crack size of 4 mm. As the analysis time increases, the crack gradually propagates along the path approximately perpendicular to the support plate toward the web stiffeners, symmetrically on both sides. Starting at Step \(-2.75\), as the upper tip approaches the neighboring stiffener, the growth of the lower crack tip accelerates. At Step \(-3.8\), because of continuous stress redistribution and damage accumulation, the crack propagates quickly toward the lower stiffener in the web.
# Numerical Insight into the Kelvin-Helmholtz Instability Appearance in Cavitating Flow
## 5 Conclusions  
Numerical simulation has provided additional insights into the formation of Kelvin-Helmholtz flow instabilities in the Venturi section. The process is being able to cause the shedding of cavitation clouds similar to the re-entrant jet or shockwave cases. Results conform well to the available experimental data.  
The formation of Kelvin-Helmholtz instabilities is determined by the large vertical variations in the shear stress, vapor fraction, and the different physical properties of liquid and vapor regions. The vapor with its much lower density and momentum is more impacted by the instabilities creation as the liquid region. This promotes perturbations and the development of the turbulent eddies in the vapor region. Turbulent eddy impingement point on the shear layer point marks the position of the large variation of the shear stress gradient. We observed the folding of the lines of constant vapor fraction within the shear layer even before any velocity changes were noticed. Thus, the vapor fraction properties may influence the Kelvin-Helmholtz instability formation process through the variation of the density and the transfer of the momentum. As instabilities grow further, adverse pressure gradient and velocity lead to the detachment of the cavitation cloud together with all instabilities.  
In both layers, Kelvin-Helmholtz instabilities for the case of cavitation in the Venturi section express less pronounced rolling motion and are less periodic and symmetric in comparison with their more well-known occurrences. This perhaps was the reason that Kelvin-Helmholtz instability was not recognized before as a possible source of the cavitating flow instabilities and cavitation cloud shedding.  
More experimental and numerical studies will be required in the future to better understand the formation of Kelvin-Helmholtz flow instabilities in cavitation flow and their role in the cavitation shedding process.  
Conceptualization, M.D. and P.P.; methodology, P.P., M.H. and M.D.; validation, P.P., M.H. and M.D.; Investigation, P.P., M.H. and M.D.; resources, M.H. and M.D.; writing--original draft preparation, P.P., M.H. and M.D.; writing--review and editing, P.P., M.H. and M.D.; visualization, P.P. and M.D.; supervision, M.H. and M.D.; funding acquisition, M.H. and M.D. All authors have read and agreed to the published version of the manuscript.  
European Research Council (ERC) under the European Union's Framework Program for research and innovation, Horizon 2020 (grant agreement n 771567--CABUM), the Slovenian Research Agency (Core funding No. P2-0401).
###### Abstract  
Assmarma wastewater treatment plant (WWTP) is the largest treatment facility in Jordan. Treated wastewater is discharged into the Zaroa River (ZR) and used to irrigate fodder and vegetables. ZR also includes surface runoff, stormwater, and raw wastewater illegally discharged into the river. This study examined pharmaceutically active compounds (PhAC) in water resources in the ZR basin. Samples of WWTP influent and effluent and river water from four sites along ZR were collected. Concentrations of 18 target antibiotics, one stimulant, and 15 other PhACs were determined in the samples. Five antibiotics were detected in WWTP influent (510-860 ng L\({}^{-1}\) for \(\sum\)Antibiotics) and six in the effluent (2300-2600 ng L\({}^{-1}\) for \(\sum\)Antibiotics). Concentrations in the effluent of all antibiotics except clarithromycin increased by 2- to 5-fold compared with those in influent, while clarithromycin concentration decreased by around 4- fold (from 308 to 82 ng L\({}^{-1}\)). WWTP influent and effluent samples contained 14 non-antibiotic PhACs, one stimulant, and six antibiotics at detectable concentrations. The dominant PhACs were paracetamol (74% of \(\sum\)PhACs) in the influent and carbamazepine (78% of \(\sum\)PhACs) in the effluent. At ZR sampling sites, carbamazepine was the dominant PhAC in all cases (800-2700 ng L\({}^{-1}\)). The antibiotics detected in WWTP effluent were also detected at the ZR sites. In summary, water in ZR is contaminated with PhACs, including antibiotics, and wastewater discharge seems to be the main pathway for this contamination. The occurrence of antibiotics and other PhACs in the irrigated soil requires investigation to assess their fate.  
Keywords:Asamra WWTP; caffeine; carbamazepine; irrigation; ofloxacin; paracetamol; pharmaceuticals; Zaroa River +
Footnote †: journal: Applied Sciences
## 6 Case Study
In tests whose spectra present harmonics surrounded by abundant interharmonics, of relatively large amplitudes and comparable to those of harmonics and close to them (as, for example, occurs in the test corresponding to Figure 10a), large differences were observed between the values found in each individual window for rates such as THD (blue graphs in Figure 11a). This is because the leakage produced by these interharmonics is also large, and when absorbed by nearby harmonics, vectorially adding to them, gives rise to variable amplitudes, and therefore, more aggregation time would be needed, as indicated in the previous sections. Thus, it was observed how the aggregated values obtained in the Figure 11a test were stabilized for a time greater than 3 s, which would justify  
Figure 11: Time evolution of: (**a**) the THD current rate of the PowerFlex inverter, and (**b**) the THD voltage rate of the Altivar inverter, for the same tests shown in Figure 10.  
Figure 10: Low part of the frequency response of the supply signals from two inverters connected to an induction motor: (**a**) current with PowerFlex, (**b**) voltage with inverter Altivar. the use of longer aggregation times. On the other hand, the rate measured in Figure 11b reached a stable value more quickly, due to the lower interharmonic content of the analyzed signal (Figure 10b), in which case the aggregation time of 3 s was sufficient. These tests prove experimentally that the aggregation time required for some parameters measured at the output of inverters may be greater than the 3 s indicated in the standard, and considerably less than the 10 min indicated in the same IEC standard for the next recommended time grouping.
## 2 Materials and Methods
### Extraction and Determination of Volatile Compounds  
Volatile compounds were extracted via a method referred to in a previous study with slight adjustments [20]. Tea powders (5.0 g) were first placed in a 100 mL glass by adding 10 \(\upmu\)L ethyl caprate (100 mg/L) as an internal standard. After adding 50 mL boiling deionized water, the vial was immediately sealed with a cover and equilibrated for 5.0 min at 60 \({}^{\circ}\)C. Next, a DVB/CAR/PDM coating fiber (50/30 \(\upmu\)m; 1 cm; Supelco, Inc., Bellefonte, PA, USA) was inserted into the vial to adsorb the volatile compounds for 50 min. Finally, the volatile compounds were desorbed at 240 \({}^{\circ}\)C for 3 min for GC-MS analysis. The GC-MS analysis was carried out using a GC system (7890A, Agilent Technologies, Santa Clara, CA, USA) coupled with an MS detector (5975C, Agilent Technologies, Santa Clara, CA, USA). The column was an HP-5 MS type (30 m \(\times\) 250 \(\upmu\)m \(\times\) 0.25 \(\upmu\)m, AgilentTechnologies; Santa Clara, CA, USA), and the carrier gas was helium (99.999%) with a constant flow of 1.0 mL/min. The GC temperature-rise procedures were as follows: 50 \({}^{\circ}\)C held for 5 min, slowly increased to 180 \({}^{\circ}\)C at 3 \({}^{\circ}\)C/min, and then increased to 250 \({}^{\circ}\)C at 10 \({}^{\circ}\)C/min and held for 3 min. The splitless injection mode was applied. The MS conditions were as follows: the ionization mode was EI; the ion source temperature was 230 \({}^{\circ}\)C; the quadrupole temperature was 150 \({}^{\circ}\)C; the mass scan scope was 50-550 m/z; the electron impact ionization was \(-\)70 eV. The concentrations of volatiles were calculated using the following formula: _Ce_ (\(\mathrm{\mu g/L}\)) = (_PA_/_PAIS_) \(\times\) 10 \(\mathrm{\mu L}\)\(\times\) 100 mg/L, where _Ce_, _PA_, and _PAIS_ represent the concentrations of the examined compound, peak area of volatile, and peak area of IS, respectively. The limit of detection (LOD) was 0.3 \(\times\) 10\({}^{-11}\) g/L, and the limit of quantification (LOQ) was 1 \(\times\) 10\({}^{-11}\) g/L.
# A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
## 2 Localization Techniques
### Signal Measurements  
The range-based localization techniques rely on the different types of signal measurements for first estimating the distance between the nodes, such as time-based (i.e., time of arrival (ToA), time difference of arrival (TDoA), round trip time (RTT)), angle-based (i.e., phase of arrival (PoA), angle of arrival (AoA)), and channel-based (i.e., received signal strength (RSS), link quality indicator (LQI), channel state information (CSI)). In this section, we describe how the various signal measurements are employed for estimating distance, while a comparison of the different methods is provided in Table 2.
_Energies_**2015**, \(8\), 7084-7099; doi:10.3390/en8077084  
_Article_  
Characterization of Anion Exchange Membrane Containing Epoxy Ring and C-Cl Bond Quaternized by Various Amine Groups for Application in Fuel Cells  
**[PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] ***  
Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea; E-Mails: [EMAIL_ADDRESS] (S.K.J.); [EMAIL_ADDRESS] (J.S.L.); [EMAIL_ADDRESS] (S.H.W.); [EMAIL_ADDRESS] (J.A.S.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +82-2-2123-2757; Fax: +82-2-312-6401.  
Academic Editor: [PERSON]  
_Received: 26 May 2015 / Accepted: 7 July 2015 / Published: 14 July 2015_  
**Abstract:** Anion exchange membranes were synthesized from different compositions of glycolidyl methacrylate (GMA) and vinylbenzyl chloride (VBC), with constant content of divinyl benzene (DVB) by radical polymerization using benzoyl peroxide (BPO) on non-woven polyethylene terephthalate (PET) substrate. Polymerized membranes were then quaternized by soaking in trimethylamine (TMA), triethylamine (TEA), tripropylamine (TPA), and 1,4-diazabicyclo [2.2.2] octane (DABCO). Characteristics of membranes were confirmed by Fourier transform infrared spectroscopy, water uptake, ion exchange capacity, ion conductivity, thermal, and alkaline stability. The results revealed that membranes quaternized by TPA and DABCO showed high affinity when GMA content was 15 wt% and 75 wt%, respectively. IEC and ion conductivity of membranes quaternized by TPA were 1.34 meq\(\cdot\)g\({}^{-1}\) and 0.022 S\(\cdot\)cm\({}^{-1}\) (at 60 \({}^{\circ}\)C), respectively. IEC and ion conductivity of membranes were quaternized by DABCO were 1.34 meq\(\cdot\)g\({}^{-1}\) and 0.021 S\(\cdot\)cm\({}^{-1}\) (at 60 \({}^{\circ}\)C), respectively. The results indicate that the membrane containing GMA 15 wt% quaternized by TPA showed the highest thermal stability among membranes and exhibited high ion conductivity compared to existing researches using GMA, VBC, and DVB monomers.  
**Keywords:** fuel cell; glycolidyl methacrylate; divinyl benzene; vinyl benzyl chloride; anion exchange membrane
## 1 Introduction
### Angle Diversity Receivers in VLC Systems  
ICI is a major problem that seriously degrades the overall performance of indoor VLC systems [33; 34]. Due to this issue, the SINR of the optical receivers would be considerably low, which is mainly caused by the existence of strong interference. To address this problem, the ADR based solutions are introduced for the first time to improve the efficiency of indoor MIMO-VLC systems in [24]. The ADRs can achieve a high-rank channel matrix by decorrelating the optical channel efficiently. The PDs are used with different FoVs to reduce the channel correlation in VLC systems. Furthermore, the concept of ADRs is also used to reduce the ICI and SINR fluctuations in indoor multi-cell systems, as evidenced by relevant studies [18; 19; 22; 25; 35; 36; 37]. In these investigations, the benefits of using ADRs in VLC systems as well as the general design of ADRs are analyzed to optimize the communication capacity. Among the general schemes of ADRs analyzed are those of pyramidal and hemispherical geometry along with their mathematical models, optimized location of the PDs, use of signal selection and combination schemes, and general tests in indoor VLC systems [38; 39; 40; 41]. Despite growing research on ADRs, the existing benchmark schemes do not optimize the structure of ADRs, and its performance is not fully explored. Other works focus on increasing the capacity and spectral efficiency of the system area; however, an analysis of the maximum data rate that these ADRs can reach has not been performed. Finally, the most important aspect that is relevant to our work is that these schemes have not yet been tested in underground mining VLC environments; therefore, to the best knowledge of the authors, this is the first time that solutions of this type are implemented in VLC mining environments.
## 3 Results
In Figure 4, expected discriminant features are correctly highlighted by Grad-CAM heatmaps for each class: grainy texture throughout the whole OCTA image for no AMD images (Figure 4A,B), flow deficits/nonflow areas for intermediate AMD images (Figure 4C,D), and high flow vascular networks (CNV) for advanced wet AMD images (Figure 4E,F,G,H). This is further supported by the CNN predicted probabilities for each image. Regarding no AMD images (Figure 4A,B), the CNN predicted high probabilities were 0.94 and 0.97, respectively, and were attributed to no AMD class. Predicted probabilities for intermediate AMD images (Figure 4C,D) were 0.70 and 0.99, respectively, and were attributed to the correct class. Finally, regarding advanced wet AMD images (Figure 4E,F,G,H) predicted probabilities were 0.99 for images Figure 4E,G,H and 0.63 for image Figure 4F, correctly attributed to CNV. On the other hand, non-discriminant CNV features are highlighted by Grad-CAM heatmaps in Figure 5I,J, including the flow deficits/nonflow areas or regions in Figure 5I and grainy texture in Figure 5J. The CNN predicted probabilities reinforce this observation where image Figure 5I is predicted as intermediate AMD with 0.84 probability and image Figure 5J as no AMD image with 0.90 probability. Regarding the Figure 5K, non-discriminant drusen features are highlighted by Grad-CAM heatmap, grainy texture is highlighted as discriminant features showing the CNN prediction as no AMD with 0.59 of probability against 0.41 for intermediate AMD. Conversely, Figure 5L represents a healthy CC (no AMD) image predicted as intermediate AMD with 0.58 of probability against 0.42 for no AMD. The Grad-CAM heatmap supports these probabilities by highlighting only drusen features as discriminant rather than those from grainy texture of no AMD images. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Ground Truth Class**} & \multicolumn{4}{c}{**Predicted Class**} \\ \cline{2-4}  & **CNV** & **DCCI** & **HCC** \\ \hline CNV & 58 & 19 & 1 \\ DCCI & 2 & 62 & 14 \\ HCC & 0 & 2 & 76 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Confusion matrix of the original VGG19 prediction on a balanced test dataset of 234 OCTA images (78 images for each class). CNV: choroidal neovascularization, DCCI: drusen/choriocapillaris impairment, HCC: healthy choriocapillaris. Figure 4: Grad-CAM visualizations for correct predictions by the proposed VGG19 modified model. Below each OCTA image, the corresponding Grad-CAM visualization of the CNN prediction. (**A,B**) Healthy choriocapillars—no AMD. (**C,D**) Drusen/Choriocapillars impairment-intermediate AMD. (**E–H**) Choroidal Neovascularization—advanced wet AMD.
# Comparative Study on Load Monitoring Approaches
## 5 Discussion  
In the previous sections of the paper, the advantages and disadvantages of each of the different approaches to load monitoring were presented. Intrusive load monitoring (ILM) and non-intrusive load monitoring (NILM) are two approaches for which the purpose is to monitor and analyze household electricity consumption. While ILM provides much more accurate results than NILM, this accuracy is still dependent on users correctly labelling their appliances. Furthermore, this accuracy in results is also dependent on a significant amount of effort to install the measuring devices, as physical modifications to the building's electrical system are mandatory. The maintenance of such devices requires, among other things, expert hands in electricity, in order to avoid accidents that could occur, as well as the discomfort that this would produce for the occupants of the buildings. Table 1 provides a summary of the key points of each of the approaches presented.