esa-sceva/satcom-chunk-collection huggingface dataset:
# Astronomical Investigation to Verify the Calendar Theory of the Nasca Lines
## 5 Discussion and Conclusions  
The results suggest that the geoglyphs, as a whole, certainly cannot be interpreted as a calendar system. Nevertheless, the astronomical theory cannot be completely negated. Therefore, in the next step, the other types of lines and areas should be examined more closely. Extensive manual preparations are required for this. There are, for example, very long meandering lines. These must be broken down into individual line sections in order to be able to calculate the astronomical azimuth of each line section. The same applies to the other line types. It must be defined for each individual area whether the calculations should be carried out for the center line or for the edges of the area. Another item are the figures and piles of stones. Relevant alignments to the Sun have already been demonstrated here as well. In order to be able to make a certain relevant statement, further investigations must also be carried out for these items.  
One topic that has not yet been considered are geoglyphs, which have an orientation to the Moon. [PERSON] defined a relatively large number of lines as so-called moon lines. The review of these lines is still pending, but the corresponding software programs are already available.  
However, referring to the other pre-Columbian cultures, the orientation of geoglyphs towards the Sun seems the most likely and most promising. Therefore, these investigations will be in the foreground in the near future.  
All geoglyphs that have an astronomical orientation are provided with the appropriate attributes in NascaGIS. The coordinates, azimuths and elevation angles used for the calculation as well as the correlating celestial bodies with the corresponding time informationare recorded in the tables of the NascaGIS data model [16]. In the future, all data should be available in the WebGIS application. At the moment, only the vector data can be called up as Web Map Service (WMS) [28], since many attributes in NascaGIS are still incomplete.  
Conceptualization, B.T. and C.R.; methodology, B.T.; formal analysis, B.T. and C.R.; investigation, K.P., B.T. and C.R.; writing--original draft preparation, K.P., B.T. and C.R.; writing--review and editing, K.P., B.T. and C.R.; visualization, C.R.; supervision, B.T.; project administration, B.T. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Czech Technical University in Prague Grant number SGS20/053/OHK1/1T/11, and the APC was funded by the Czech Technical University in Prague, FCE, dept. of Geomatics\".  
Not applicable.  
The authors would like to thank the University of Applied Sciences (HTW), Faculty of Spatial Information, and the Faculty of Civil Engineering, CTU in Prague, for support.  
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 Auditory Perception Study of Sound Field in Closed Spaces with Different Structural Parameters
### Discussion  
When the position of the receiving point is not considered, the auditory perception changes caused by the volume, inner surface absorption coefficient, and shape are shown in Figure 9.  
It can be seen from Figure 9 that, for the flute music, when the volume changes, the cabin with a volume of 24 m\({}^{3}\) achieves the best auditory perception. When the wall absorption coefficient changes, the cabins with the thick pit sand mortar polished brick wall surface and the full sound absorption wall surface can impart better auditory perception. When the shape changes, the hemispherical cabin can impart better auditory perception. For violin music, when the volume changes, the cabin with a volume of 24 m\({}^{3}\) has better auditory perception. When the absorption coefficient changes, the cabin with a sound absorption coefficient of 0.5 and the full absorption wall have better auditory perception. When the shape changes, the hemispherical cabin has better auditory perception. For the symphonic music, when the volume changes, there is no significant difference among the cabins. When the wall sound absorption coefficient changes, the total reflection wall cabin has the worst auditory perception, while the other cabins have no significant difference. When the shape changes, there is no significant difference among the cabins.  
It can be concluded from the above observations that the flute and violin music are most suitable for playing in a hemispherical cabin with a small volume and a relatively large wall sound absorption coefficient in the various simulated cabin environments of this experiment, and that the symphony has no special requirements for the playing environment except for total reflection walls. That is to say, hemispherical cabin with a small volume and a relatively large absorption coefficient wall achieves better auditory perception for playing single instrument music such as the flute and violin. While multiple instruments music such as the symphonic has no specific requirement for playing except the extreme case of total reflection wall.
## 4 Discussion
### Characteristics of Urbanization and Carbon Accumulation Due to Urbanization  
Some common metrics such as distance from urban core [9], urban settlement times [21] and the impervious surface area fraction [51] were also used to represent the urbanization gradients. However, in China, the different ring roads were mainly used to determine the urban core or outskirts for public awareness. In our study, we divided the urbanization gradients by different human disturbance times and different ring roads, and testified that the ring roads produce similar results as the human disturbance times on forest C dynamics. This is helpful for citizens to understand the urbanization effects on forest soil C variations, and makes it easier to obey the government regulations about C cycles.  
Although many previous studies considered urbanized SOC data, some reported high SOC content in downtown or old urban regions, while few of them reported the SOC accumulation rate. As in Chongqing, Southwest China, the areas developed from 2001 to 2010 had a lower SOCD than the areas built before 1988 [52] and in Shanghai, Southeast China, older parks had higher SOCD (201 t h\({}^{-1}\)) than younger parks (107 t h\({}^{-1}\)) [53]. Forest SOCD decreased from 4.24 kg C m\({}^{-2}\) to 3.99 kg C m\({}^{-2}\) from urban to suburban Boston, United States [9], and in west Georgia (United States), SOCD in 1974, 1980, and 1990 was 5.487 kg C m\({}^{-2}\), 5.492 kg C m\({}^{-2}\), and 5.518 kg C m\({}^{-2}\), respectively [8]. In Harbin city, forest soil was accumulating at a speed of 15.4 g C m\({}^{-2}\) year\({}^{-1}\)[21]. Our study reported an SOC increasing rate of 13.4 g C m\({}^{-2}\) year\({}^{-1}\), which was much lower than Harbin city.  
In addition to the increase in total SOC, old urbanized regions had more temperature-stabled SOC with longer turnover times than in new urbanized regions. The carbon stability calculated for the 1 st ring road was 6%, 7%, 13%, and 19% higher than that calculated for the 2 nd, 3 rd, 4 th, and 5 th ring roads, respectively. Carbon stability calculated for the human disturbance time of 114 years was 7%, 13%, 18%, and 15% higher than that calculated for 60, 24, 10, and 0 years, respectively. Therefore, SOC sequestration capacity might be even larger than expected in the above estimations, due to increasing SOC stability and longer SOC turnover time. The lower Q\({}_{10}\) value with urbanization meant a higher temperature stability and a lower soil basal respiration [54]. Therefore, greater carbon accumulation, longer carbon turnover time, and more stable carbon sequestration are the main features of urbanization-induced forest SOC accumulation.
## 2 The Measurement Principle of Mass Characteristic  
### Principles of Measurement of Mass Characteristics  
The test for determining the centroid is based on the principle of three-point measurement [24]. First, the measurement system uses a coordinate system (\(oxy\)), which is located at the center of rotation, as shown in Figure 2. Three weighing sensors, which are identified as \(A\), \(B\), and \(C\) (\(OA=OB=OC=200\) mm), are located in the \(x-y\) plane with an angle of 120\({}^{\circ}\) between them. Hence, the mass of the pico-satellite can be obtained:  
\[P_{A}=m_{4}-m_{1} \tag{1}\]  
\[P_{B}=m_{5}-m_{2} \tag{2}\]  
\[P_{C}=m_{6}-m_{3} \tag{3}\]  
\[m=P_{A}+P_{B}+P_{C} \tag{4}\]  
where, \(m_{1}\), \(m_{2}\), and \(m_{3}\) represent the measurement values of the total mass of the fixture tools and worktable of the three weighing sensors, \(A\), \(B\), and \(C\), respectively. \(m_{4}\), \(m_{5}\), and \(m_{6}\) represent the measurement values of the total mass of the fixture tools, worktable, and pico-satellite of the three weighing sensors \(A\), \(B\), and \(C\), respectively. \(P_{A}\), \(P_{B}\), and \(P_{C}\) are the satellite weights which are calculated according to \(m_{1}\), \(m_{2}\), \(m_{3}\), \(m_{4}\), \(m_{5}\), and \(m_{6}\) in \(A\), \(B\), and \(C\) three points, respectively. \(m\) is the total mass of the pico-satellite.  
Figure 1: A summary of the paper.  
Figure 2: Measurement coordinate system of the centroid.  
According to the principle of moments [9], when the moment is considered from the \(ox\)-axis, the centroid of the pico-satellite in the \(y\)-direction can be expressed as:  
\[y_{G}=(P_{B}y_{2}+P_{C}y_{3}-P_{A}y_{1})/m \tag{5}\]  
where \(y_{1}\), \(y_{2}\), and \(y_{3}\) are the distances from the \(x\)-axis, respectively.  
When the moment is taken from the \(oy\)-axis, the centroid of the pico-satellite in the \(x\)-direction can be expressed as:  
\[x_{G}=(P_{B}x_{1}-P_{c}x_{2})/m \tag{6}\]  
where \(x_{1}\) and \(x_{2}\) are the distances from the \(y\)-axis, respectively.  
After the measurement system rotates by a \(90^{\circ}\) angle, \(z_{G}\), the centroid of the pico-satellite in the \(z\)-direction can be obtained.
## 2 Materials and Methods
### Aqueous Matrices for Adsorption Experiments  
In this work, adsorption experiments were first carried out in ultrapure water (conductivity = 55 \(\upmu\)S\(\cdot\)cm\({}^{-1}\), resistivity = 18.18 M\(\Omega\).cm and pH = 6.9 at 25 \({}^{\circ}\)C), which was sourced by a Milli-Q purification system. Then, aiming to assess the possible utilisation of the considered adsorbents in tertiary waste water treatment, experiments on the adsorption of pharmaceuticals from real waste water were carried out. For this purpose, the secondary effluent from the municipal waste water treatment plant (WWTP) of Leon (Spain) was collected. This WWTP consists of a primary stage, followed by a secondary stage treatment. The primary stage comprises screening, sand removal,  
\begin{table}
\begin{tabular}{c c c} \hline
**Absorbent** & **GPP20** & **Sepabeads SP207** \\ \hline Matrix & Coal based steam activated carbon & Styrene-divinylbenzene copolymer \\ Colour & Black carbon & Yellowish opaque beads \\ Specific surface area (m\({}^{2}\) g\({}^{-1}\)) & 1000 & 650 \\ Mean particle diameter (mm) & 0.04 & 0.4 \\ \hline \end{tabular}
\end{table}
Table 1: Physical properties of adsorbents used for diclofenac acid adsorption.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Pharmaceutical** & **Structure** & **Mw (g mol\({}^{-1}\))** & **Sw * (mg L\({}^{-1}\))** & **pKa** & **Log K\({}_{\text{ow}}\)** & **PSA (A\({}^{2}\))** & **HBAC** \\ \hline
**Ibuprofen Sodium** & & & & & & \\ (G\({}_{3}\)H\({}_{7}\)NaO\({}_{2}\)) & & 228.26 & 100,000 & 4.91 & 3.8 & 40.1 & 2 \\ \hline
**Acetaminophen** & & & & & & \\ (G\({}_{6}\)H\({}_{8}\)NO\({}_{2}\)) & & 151.17 & 14,000 & 9.48 & 0.46 & 49.3 & 2 \\ \hline \end{tabular} PSA = Polar Surface Area, HBAC = Hydrogen Bound Acceptor Count, \({}^{\text{a}}\) Sw = water solubility (25 \({}^{\circ}\)C).  
\end{table}
Table 2: Physico-chemical properties of the pharmaceuticals used in this study (Source: Chemspider and Chemicalize).  
fat removal, and primary clarification treatments. Then, the secondary stage involves a plug-flow activated sludge with nitrification/denitrification followed by a secondary clarification. After the secondary clarification, the effluent is directly discharged at the Bernesga river, which has a length of 77 km, and is a tributary of the Esla river. The WWTP was designed to treat the waste water of 330,000 equivalent inhabitants, and has an inflow of 123,000 m\({}^{3}\) day\({}^{-1}\), with a hydraulic retention time (HRT) of about 6 h.  
Waste water quality parameters, namely pH, conductivity, total suspended solids (TSS), biological oxygen demand at five days (BOD5), chemical oxygen demand (DQO), NTK, N-NH4, N-NO3, N-NO2, total P-PO4, were determined according to Standard Methods [33]. The determined parameters are shown in Table 3, together with European regulations on the discharge of this sort of effluents, which, as may be seen, are fulfilled.
# Space Object and Background Polarization Models and Detectability Analysis
## 2 Basic Theory of the Polarization Bidirectional Reflection Distribution Function Model
### Bidirectional Reflection Distribution Function Model Based on Microlanes
The expression of polarization can then be deduced as:  
\[DOP=\frac{\sqrt{\left(k_{s}f_{sp_{0}}\right)^{2}+\left(k_{s}f_{sp_{2,0}} \right)^{2}}}{k_{s}f_{sp_{0,0}}}=\frac{\frac{k_{s}}{16\pi\sigma^{2}\cos^{4} \alpha}\cdot\frac{\exp\left(-\frac{\tan^{2}\alpha}{2\sigma^{2}}\right)}{\cos \theta_{i}\cos\theta_{r}}\cdot G\left(r_{s}-r_{p}\right)}{\frac{k_{s}}{16\pi \sigma^{2}\cos^{4}\alpha}\cdot\frac{\exp\left(-\frac{\tan^{2}\alpha}{2\sigma^ {2}}\right)}{\cos\theta_{i}\cos\theta_{r}}\cdot G\left(r_{s}+r_{p}\right)+ \frac{\cos\theta_{r}}{\pi}\rho_{d}} \tag{23}\]  
As can be seen from the Formulas (19) and (23), the polarization value of a rough surface material is determined by five physical characteristics of the material, namely \(n,k\), \(\sigma\), \(k_{s}\), and \(\rho_{d}\). The degree of polarization and other information about the target material are typically directly obtained by polarization imaging. Experiments cannot be used to directly measure the five aforementioned parameters. In order to generate the five physical parameters needed for the model, this research will use methods to invert the degree of polarization information obtained from experiments.
## 3 Results and Discussion
### Phase Analysis of CuO-CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\)  
Figure 3 shows the XRD results for the catalyst. The CeO\({}_{2}\) and CuO diffraction patterns match the characteristic peaks of the fluorite structure of CeO\({}_{2}\) (PDF# 75-0151) and the monoclinic structure of CuO (PDF# 80-1916), respectively. There were no diffraction peaks for the CuO on the CuO/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) and CuO-CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) catalysts. A study by [PERSON] et al. [20] demonstrated that the capacity of CuO dispersed in the monolayer on the surface of \(\gamma\)-Al\({}_{2}\)O\({}_{3}\) is 0.75 mmol/100 m\({}^{2}\) Al\({}_{2}\)O\({}_{3}\); in the highly dispersed state, Cu\({}^{2+}\) occupies octahedral and tetrahedral vacancies on \(\gamma\)-Al\({}_{2}\)O\({}_{3}\). Related studies by [PERSON] et al. [21] reveal that when the Cu loading is less than 0.6 mmol/100 m\({}^{2}\) Al\({}_{2}\)O\({}_{3}\), CuO is highly dispersed on the surface of \(\gamma\)-Al\({}_{2}\)O\({}_{3}\) and no crystalline CuO are formed. For the CuO/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) and CuO-CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) prepared in this experiment, the Cu loading is 0.35 mmol/100 m\({}^{2}\) Al\({}_{2}\)O\({}_{3}\), which is within the range described in the literature. Therefore, the high dispersion of CuO components on the surface of \(\gamma\)-Al\({}_{2}\)O\({}_{3}\) explains the absence of CuO diffraction peaks in the three catalysts spectra. There were no diffraction signals for the Ce component of CuO-1% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\). CuO-5% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) shows characteristic diffraction peaks of CeO\({}_{2}\) crystals at 28.5\({}^{\circ}\), 33.1\({}^{\circ}\), and 56.3\({}^{\circ}\) (PDF# 75-0151). The CeO\({}_{2}\) diffraction peaks for CuO-10% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) have greater intensity, and the peak widths at half height are smaller, indicating the formation of larger CeO\({}_{2}\) grains. There is no diffraction signal for the Ce component of CuO-1% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), because the Ce component is also a highly dispersed amorphous species, whereas there is a CeO\({}_{2}\) crystal on the CuO-5% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) grain. When considered in combination with the performance evaluation results, CuO-1% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) did not demonstrate significantly better thermal catalytic decomposition of DMMP than CuO/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), whereas CuO-5% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) performed significantly better. These results indicate that the key to improving the catalyst performance maybe the size of the CeO\({}_{2}\) grains, rather than the highly dispersed Ce species. This may be due to the catalysis of the specific crystal plane of CeO\({}_{2}\) or the Cu component entering the crystal lattice of CeO\({}_{2}\) as a dopant atom, resulting in an increase in the number of oxygen defects [22; 23]. In
###### Abstract  
The geochemical background value of chromium (Cr) serves as a pivotal factor in environmental assessments and mineral exploration endeavors. Traditionally, geochemical background values have been determined using statistical parameters derived from dataset analysis, though this method may possess inherent limitations. In this study, we introduce a novel equation to calculate the geochemical background value of Cr, based on the premise that major elements can effectively delineate the geochemical background for trace elements. Using a dataset encompassing 791 abundance records from rocks, soils, and sediments, we derived and fitted the equation. Our findings revealed that when treating these 791 records as representative of background samples, approximately 95% of the records lie within a logarithmic error of \(\pm\)0.2 from the calculated values. Based on this observation, we propose adopting a logarithmic error threshold of \(\pm\)0.2 as a criterion for identifying background samples. To further validate the equation, we tested background samples from diverse regions with varying degrees of weathering. Among the 138 samples analyzed, only two exhibited background values with a logarithmic error exceeding \(\pm\)0.2 from the measured values, although all samples fell within a \(\pm\)0.3 error margin. We subsequently applied this equation to the orthopyroxenite and dunite zones within the Pados-Tundra complex, located in the western Kola Peninsula, Russia. According to the \(\pm\)0.2 logarithmic error criterion, mildly altered orthopyroxenite samples could be deemed as background Cr samples, where certain altered orthopyroxenite samples exhibited a logarithmic error in the \(\pm\)0.2-\(\pm\)0.3 range. In contrast, altered and mineralized samples in the dunite zone showed a significant deviation beyond the \(\pm\)0.2 error range, indicating that they should be classified as anomalous Cr samples. This innovative methodology offers a refined approach for background determination and anomaly identification, thereby enhancing mineral exploration and Cr environmental quality assessments.  
e +
Footnote †: journal: Applied Sciences  
_Article_
## 4 Discussion and Conclusions
### Smart Server  
The Smart Server was successfully used to collect data from various types of sensor and to communicate the results to an operative at ground surface level. It is simple to see how this idea can be expanded to network level where a number of Smart Servers work together to collect and transmit data for a large network of pipes. The server used in this project was a prototype, but it is obvious that it can be further developed and miniaturised using bespoke integrated circuit technology to make it smaller, more efficient and easier to deploy.
## 5 Case Study
### Modeling of the Water Disposal System  
Figure 9 gives the architecture and models of the water disposal system. In the figure, (1) is the architecture of the system and (2)\(\sim\)(7) are the timed automata for each component of the system. The system consists of five components: Actuator, Controller (CtrlWithAct and CtrlWithCon), Heater, Sensor and Configuration. In addition, we add an Attacker which executes command injection attacks to the system. The Attacker (Figure 9(8)) can simulate a message (a malicious command) sending to the Controller like the Configuration. The maximal water level is set as 100. The Configuration can set the range of the water level:in order to ensure safety, the highest water level is 90 (i.e., \(SH\) = 90) and the lowest water level is 10 (i.e., \(SL\) = 10). If this range is exceeded, the system is not safe. The Controller checks up on the real-time water level to make sure that the water level is within the normal range (i.e., \(L\) = 40 \(<\) water level \(<H\) = 60) and sometimes sends controlling messages to the Actuator. The Actuator opens or closes the valve according to the messages from the Controller and gives the current water level to the Sensor periodically. If the valve is opened, the water level can increase by 4 every time unit. The water level always drops by 1 every time unit regardless of the valve status. The Sensor receives the data from the Actuator and then sends them to the Controller at once. The components of the system operate independently and communicate with each other if necessary. We use the interleaving [10] to combine the components as a whole system model: System = Heater \(|||\) Sensor \(|||\) CtrlWithAct \(|||\) Actuator.  
The Attacker sends error messages to the Controller periodically. It changes the values of the normal range of the water level (i.e., change \(H\) to 95 and \(L\) to 5) such that the values exceed the safe water line. There will be an accident if the system does not find it in time. In order to solve this problem, the Controller detects whether the values of \(H\) and \(L\) are abnormal periodically: if so, it sends a request to the Configuration to obtain the correct values. Then the Configuration sends the right values to the Controller (with the assumption that the values in the Configuration are unmodifiable). The complete system is shown as follows: SystemWithAttacker=Attacker \(|||\) Configuration \(|||\) CtrlWithAct \(|||\)  
Figure 9: Architecture and timed automata models of water disposal system.  
CtrlWithCon \(|||\) Actuator \(|||\) Heater \(|||\) Sensor. In addition, the variables, the constants and the channel declarations of the system are shown in Figure 10.