esa-sceva/satcom-chunk-collection huggingface dataset:
### Discussion  
#### 4.6.1 Relationship between Travel Time and Cumulative Survival Ratio (CSR)  
[PERSON] and [PERSON] [7] collected 5,424 ambulance attendance records for a six-month period from the emergency department of an injury center in a city with a population of 620,000, and calculated a mortality risk of 1.58% for reaction times \(>\)5 minutes and 0.51% for reaction times \(<\)5 minutes. Table 4 and Figure 17 present data for the relationship between EV travel time and deaths from their study. Cumulative death ratio (CDR\({}_{i}\)) is defined as the ratio of the number of deaths when EVs arrive at incident scenes within \(i\) minutes to the number of total deaths. For example, CDR\({}_{3}\) can be calculated as \(\frac{0+0+1}{71}\times\)100%\(=1.4\%\), indicating a CDR of 1.4% if EVs arrive at a specific scene within three minutes. Cumulative survival ratio (CSR\({}_{i}\)) is calculated as 1-CDR\({}_{i}\), with results used to estimate improvements from using each method.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Travel Time (s)** & **Death** & **CDR (\%)** & **CSR (\%)** \\ \hline
0–59 & 0 & 0 & 100 \\
60–119 & 0 & 0 & 100 \\
120–179 & 1 & 1.4 & 98.6 \\
180–239 & 2 & 4.2 & 95.8 \\
240–299 & 4 & 9.8 & 90.2 \\
300–359 & 16 & 32.3 & 67.7 \\
360–419 & 14 & 52.1 & 47.9 \\
420–479 & 11 & 67.6 & 32.4 \\
480–539 & 10 & 81.6 & 18.4 \\
540–599 & 7 & 91.5 & 8.5 \\
600–659 & 3 & 95.7 & 4.3 \\
660–719 & 3 & 100 & 0 \\
720+ & 0 & 100 & 0 \\ \hline \end{tabular}
\end{table}
Table 4: Relationships between travel time, cumulative death ratio (CDR), and cumulative survival ratio (CSR) from [PERSON] and [PERSON] [7].  
Figure 16: Travel times of simulation set #3 with real traffic data for the (**A**) short route and (**B**) long route.  
18.4%, 18.4%). When using path clearing with the same numbers of vehicles along the short route, travel time was reduced from (427, 517, 661) to (376, 472, 540) s and CSRs increased from (32.4%, 18.4%, 0%) to (47.9%, 32.4%, 8.5%). Long route travel times decreased from (623, 677, 716) to (612, 637, 686) s, and CSRs increased from (4.3%, 0%, 0%) to (4.3%, 4.3%, 0%). From Figure 18, we can observe that no matter which method was used, the CSR improvement is significant for the short route. In contrast, only traffic light preemption shows a great improvement in CSR for the long route. However, we can find that path clearing reduced the EV travel time by 30 s (from 716 to 686 s) for the long route with 2000 vehicles, but the CSR remains 0%. This shows us that reducing the EV travel time does not guarantee increases in CSR.
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} AIUB & Astronomical Institute of the University of Bern \\ ADR & Active Debris Removal \\ BAU & Business-As-Usual \\ COSPAR & Committee on Space Research \\ CW & Clohesys-Wiltshire \\ DELTA & Debris Environment Long-term Analysis \\ DIFFRACT & De-Orbit, Formation Flight and Re-Entry Analytical Toolbox \\ DOCTOR & Display of Objects Circulating in Terrestrial Orbits \\ DSMS & Data Stream Management Systems \\ EKF & Extended Kalman Filter \\ ELISA & Experimental Lab for proxlmity operations and Space Situational Awareness \\ EnKF & Ensemble Kalman Filter \\ EOL & End-Of-Life \\ ESA & European Space Agency \\ ESOC & European Space Operations Centre \\ ESTEC & European Space Research and Technology Centre \\ FHR & Fraunhofer Institute for High Frequency Physics and Radar Techniques \\ GEO & Geostationary Earth Orbit \\ GNSS & Global Navigation Satellite System \\ HIL & Hardware-In-the-Loop \\ IADC & Inter-Agency Space Debris Coordination Committee \\ IFD & In Flight Demonstration \\ JSpOC & Joint Space Operations Center \\ KF & Kalman filter \\ LEO & Low Earth Orbit \\ LQR & Linear Quadratic Regulation \\ LUCA & Long-term Utility for Collision Analysis \\ MASTER & Meteoroid And Space debris Terrestrial Environment Reference \\ NEPTUNE & Networking/partnering initiative Ephemeris Propagation Tool with Uncertainty Extrapolation \\ NCS & Net Capture System \\ PMD & Post Mission Disposal \\ POD & precise orbit determination \\ PROOF & Program for Radar and Optical Observation Forecasting \\ PWM & Pulse Width Modulation \\ RSO & Resident Space Object \\ SCATTER & SpaceCratt ATtitude and Orbit numERical simulator \\ SPHERES & Synchronized Position Hold, Engage, Reorient, Experimental Satellites \\ SSA & Space Situational Awareness \\ SST & Space Surveillance and Tracking \\ TDT & Tether Dynamics Toolbox \\ TLE & Two-Line Elements \\ TRL & Technology Readiness Levels \\ UKF & Unscented Kalman Filter \\ UT & Unscented Transformation \\ \end{tabular}
# Trends from 30-Year Observations of Downward Solar Irradiance in Thessaloniki, Greece
## 3 Results
### Effects of the Solar Zenith Angle on SDR  
The solar zenith angle is a major factor affecting the SDR, as increases in SZA leads to enhancement of the radiation path in the atmosphere, especially in urban environments with human activities emitting aerosols [33]. In order to estimate the effect of SZA on the SDR trends, we grouped the data in bins of 1\({}^{\circ}\) SZA and calculated the overall trend for each bin separately for the daily periods before noon and after noon (Figure 4). Although there are seasonal dependencies of the minimum SZA (see Appendix A, Figure A3), these dependencies are not discussed further.  
For all-sky conditions, the brightening effect of SDR (positive trend) increases with SZAs (Figure 4a), ranging from about 0.1%/y to about 0.7%/y for the statistically significant trends. The trends in the morning and afternoon hours are more or less consistent with small differences at small SZAs, which can be attributed to effects on clear sky SDR from systematic diurnal patterns of aerosols during the warm period of the year, consistent with the results reported for China by [PERSON] et al. [33]. Note that SZAs less than 25\({}^{\circ}\) can only occur during the warm period of the year around noon when clear skies are more frequent. The increasing trend with SZA is likely caused by the increased attenuation of SDR with SZA. The effect is larger when aerosol and/or cloud layers are optically thicker; therefore, decreases in aerosol and clouds through the study period will result in larger positive trends of SDR at larger SZAs.  
Under clear skies (Figure 4b), the trends are smaller and less variable, ranging between 0.1 and 0.15%/y up to 77\({}^{\circ}\) SZA. At higher SZAs and in the afternoon hours, there is a sharp increase in the trend up to 0.3%/y, which may have been caused by the long path length of radiation through the atmosphere as discussed above for the all-sky conditions. The small differences in the trend between morning and afternoon between 35\({}^{\circ}\) and 60\({}^{\circ}\) SZA is likely a result of less attenuation of SDR in the morning hours due to lesser amounts of aerosols and a shallower boundary layer.  
For cloudy-sky conditions (Figure 4c), we cannot discern any significant dependence of the SDR trend with SZA, as the variability of irradiance is dominated by the cloud effects leading to insignificant trends. Statistically significant trends appear only in the afternoon and for SZAs larger than 60\({}^{\circ}\). The sharp increase of the trend at SZAs larger than \(\sim\)75\({}^{\circ}\)  
Figure 3: Cumulative sum plots of monthly SDR anomalies in (%) for different sky conditions after removing the long-term linear trend: (**a**) all skies; (**b**) clear skies; (**c**) cloudy skies.  
observed also for clear skies, is probably associated with stronger attenuation by clouds under oblique incidence angles, which also result in smaller variability.
# Predictive Scheduling with Markov Chains and ARIMA Models
## 5 Summary and Conclusions  
The execution of production processes is associated with the occurrence of various uncertainty factors. Disruptions generate problems that may have a marked effect on production schedules. Therefore, more effort is required in developing techniques and methods that affirm the relevance of uncertainty factors in manufacturing and propose viable solutions. Robust scheduling exhibits the required potential to cope with disruptions and, thus, should be studied further.  
In this investigation, the aim was to design a robust production scheduling method with the implementation of Markov chain theory and ARIMA models that will provide for the negative effects of technological machinery failure. The analyses reveal that the inclusion of machine failure in the production schedule results in the extension of the performance indicators, mean flow time, mean job completion time, as well as the central criterion describing the performance of the production system--the completion time of all jobs (makespan). However, the elongation remains within the reasonable limits given that the production is carried out according to failure-inclusive schedules. The simulations evidence that the robust schedules bear a closer similarity to the simulated production process than their nominal equivalents. In other words, the proposed model generates high-accuracy makespan while increasing the robustness and stability of the schedule.  
To extend our research in the future, we intend to develop improved models that will: provide for the management of other uncertainty factors in production scheduling (e.g., disruptions related to transport, availability of materials or employee absence), enable reactive scheduling of production jobs or extend the versatility of the proposed solutions over other manufacturing systems. Our current findings and methodologies should make a noteworthy contribution to the theory of production scheduling, as well as appeal to practitioners representing various manufacturing industries and different-sized enterprises.  
A.G. gave the theoretical and substantive background for the developed solution and conceived and designed the experiments, E.K. prepared and provided mathematical description of the method, L.S. prepared conception of proposed method and conducted experimental verification of the solution. All authors have read and agreed to the published version of the manuscript.  
Figure 4: Relative increase of makespan in LPT and SPT schedules.  
**Funding:** The project/research was financed from the Lublin University of Technology Project--Regional Initiative of Excellence from the funds of the Ministry of Science and Higher Education on the basis of a contract No. 030/RID/2018/19.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Application to the Case Study  
### The Spiral Staircase in the Fortified Tower of Nisida: Geometry and Construction  
Nisida is the smallest and closest island to Naples. A cylindrical watchtower was built on top of the island in the Angevin period. For several centuries, the pictorial view of Nisida has been characterized by the ancient tower, which is one of the most critical and prominent architectural buildings of the Phlegraean area. It was long-abandoned and reused as a prison in the early decades of the nineteenth century; it was then definitively abandoned after the Second World War.  
The tower structure has changed drastically, mainly due to the 19 th-century reformations and the 20 th-century partial demolition; all that remains of the coastal defense building today is the sole scarp The current access is through a spiral stair, located inside this scarp, dating back to the end of the 19 th century, and leading to the only remaining room on the upper floor.  
The analysis of the small spiral staircase with a central hole is the case study of the present work. It has a circular plan of 1.83 m in diameter, and it resides in a \"well\" (e.g., the circular perimeter structure containing the spiral staircase), a vertical void of 8.10 m in height. The perimeter wall is in tuff masonry covered with plaster. Along the staircase, there are two empty windows for lighting and ventilation (Figure 3). The stair consists of 36 steps that rest on the helical pillar and it rises by rotation, so that the transmission of loads through the central support is somehow compromised. The steps are made of cut stone with a rise of 21 cm, 61 cm wide without considering the part of the step embedded in the wall of the staircase cylinder [36].  
Figure 3: Helicoidal staircase of Nisida: (**A**) Photographs by the authors; (**B**) in silico geometrical model; (**C**) Helicoidal FE model of staircase.
# The Effect of Non-Transferred Plasma Torch Electrodes on Plasma Jet: A Computational Study
## 3 Results
### Case 1: Study of Cathode Shapes
#### 3.1.3 Temperature and Velocity Changes  
The result of ionization close to the cathode tip causes a sharp rise in both temperature and velocity in that region. Further, as the plasma moves downstream, these values gradually decline toward the outlet, mainly due to cooling by the anode. This pattern of temperature and velocity variation has been widely reported in previous studies using various analytical approaches [11; 15; 32].  
Figure 6a shows temperature profiles for different cathode shapes at a fixed power input of 14 kW using a cylindrical anode. It is worth noting that the current density required at the cathode tip to achieve 14 kW power is not uniform across all cathodes. To elucidate, the current density required at the cathode tip for the attainment of 14 kW power is as follows for the respective cathodes: cathode a (\(10^{6}\) A/m\({}^{2}\)), cathode b (\(8\cdot 10^{6}\) A/m\({}^{2}\)), cathode c (\(8\cdot 10^{5}\) A/m\({}^{2}\)), cathode d (\(1.5\cdot 10^{6}\) A/m\({}^{2}\)), cathode e (\(3\cdot 10^{6}\) A/m\({}^{2}\)), and cathode f (\(2\cdot 10^{6}\) A/m\({}^{2}\)), respectively. The figure highlights a strong dependence of cathode shape on  
Figure 5: Variations of the current density of the plasma arc.  
temperature near the tip, while outlet temperatures remain relatively consistent. Cathodes b, e, and f produce higher tip temperatures than d, a, and c.  
Similarly, Figure 6b presents plasma jet velocity for the same conditions. Again, cathodes b, e, and f show higher velocities, suggesting that flat cathodes enhance energy transfer and jet momentum. In contrast, conical or tapered cathodes with smaller tip areas tend to produce lower plasma temperatures and velocities.
###### Abstract
Other types of non-DSB lesions, such as clustered oxidized bases, are considered to be resistant to the repair process and more susceptible to DSB formation through their repair processing [34]. Throughout the last decade, Monte Carlo (MC) codes have proved to be a useful tool for assessing DNA lesions in a cell exposed to IR, since they have been constructed to simulate damage induction at the DNA scale [35; 36]. Radiation risks for an individual exposed to IR depend on different factors. One factor of great importance is the overall dose of radiation absorbed by the human body, while another equally important one is the dose distribution within it. In our study, we have used a serial combination of two MC codes with different roles in order to estimate the number of induced lesions (SSBs and DSBs) per cell of a person exposed to IR from a radioactive source (\({}^{137}\)Cs) placed in the ground, as a remnant from a hypothetical nuclear accident. These lesions were assessed for different values of surface activities and exposure times of the radioactive material to make conclusions about the health risk in such exposures. We have developed an efficient computational method with the combination of a small-scale MC biophysical model (MCDS), with a larger-scale and general-purpose MC transport code (MCNP) to reproduce the results induced in the cell environment after such an exposure. Specifically, we have used the general-purpose MC N-particle (MCNP) radiation transport code to estimate the absorbed dose and secondary electron spectra of \({}^{137}\)Cs irradiation in cell DNA. Subsequently, we combined the estimates of the secondary electron spectrum and the absorbed dose acquired from MCNP with MCDS simulations in order to calculate the initial DNA Damage. In synopsis, we have developed a computational method to study the potential biological effects on cell DNA after IR exposures. It is crucial to know the absorbed dose after the radiation exposure because, based on the recording of this magnitude and the analysis of the effects of radiation in living organisms (DNA damage), we can estimate the severity of each exposure. Ultimately, this information may help medical personnel to respond appropriately to such cases with individuals exposed to IR after a radiological incident.
# Biosorption Potential of Sargassum for Removal of Aqueous Dye Solutions
## 4 Discussion  
Methylene blue (MB) is a cationic thiazine dye that is largely used as a model of cationic dyes for adsorption studies. Algae were shown to be a low-cost and efficient alternative biomaterial to remove dyes due to the functional groups present. FTIR analysis of the brown seaweed, _S. muticum_, ascribed effective biosorption to the cell wall structure containing functional groups such as amino, hydroxyl, carboxyl and sulphate, which can act as binding sites via electrostatic attraction, ion exchange and complexation [39]. Both anionic dyes investigated showed no or little affinity for the Sargassum biomasses. In addition to the interactions mentioned above, hydrophobic attractions, chemical bonding, hydrogen bonds and physical adsorption interactions are also likely to occur between a biosorbent and dyes. Hence, the ionic charge of the dye will directly affect the adsorption capacity of the biomass.  
Chemical characterisation of many Sargassum species showed that metal content (in particular arsenic) severely hampers the prospects of using Sargassum species for food or feed. However, this seaweed's high metal sorption ability could offer a feasible and economical approach for removing industrial heavy-metal-bearing wastewaters that require efficient and cost-effective treatment [40]. Other non-conventional low-cost adsorbents were reviewed by [PERSON] et al. [41]. The effect of biosorption dosage on methylene blue dye removal was investigated (0.01\({}^{-1}\) g) using an 80 mL dye solution (10 mg L\({}^{-1}\), room temperature).  
Optimal biosorption dosages can be used to predict the overall cost of biomass per unit of the dye solution to be treated. The optimal biosorbent dose for either _S. muticum_ or mixed Sargassum species was 0.05 g/80 mL, corresponding to \(Q_{c}\) values of 157 mg g\({}^{-1}\) (120 min) for _S. muticum_ and 115 mg g\({}^{-1}\) (120 min) for the mixed Sargassum sample. Likewise, contact times over 120 min were investigated, indicating that biosorption (>75% for mixed Sargassum and >78% for _S. muticum_) occurred in the initial 15 min. The maximum adsorption capacity of MB on _S. muticum_ at the optimal pH was reported to be 279 mg g\({}^{-1}\)[28].  
Figure 6: Biosorption of congo red over 120 min by _Sargassum muticum_ (SM) and mixed _Sargassum_ spp. in 0.1 g and 10 mg L\({}^{-1}\) (80 mL) dye solution. Standard deviation n = 3.  
The pH was not adjusted in this study, which could have caused the lower values obtained in this study. Chemical treatment with CaCl\({}_{2}\) improved the adsorption capacity, which is in line with those previously reported for other types of biomaterial [42].
# Torque Characteristic Analysis of a Transverse Flux Motor Using a Combined-Type Stator Core
## 4 Three-Dimensional Finite Element Analysis of TFM
### Permanent Magnet Flux Linkage  
The permanent magnet flux linkage waveform in armature winding is shown in Figure 7a, and the harmonic analysis result is shown in Figure 7b. It can be seen that the waveform of permanent magnet flux linkage is close to sinusoidal, the amplitude of PM flux linkage is 0.19 Wb, and the total harmonic distortion (THD) is 0.41%.
# A New Methodology for Type Synthesis of Planar Linkages for Exoskeletons up to Five Angular Outputs
## 6 Results
### Example-2  
For leg rehabilitation motion presented in [20], the angles at the hip and knee joints are illustrated in Figure 8d [20]. As walking is a cyclic motion, a crank-rocker mechanism is preferred for the hip output. A similar angular output is required for the knee joint.  
Figure 7: Using eight-bar linkage as exoskeleton for finger rehabilitation. (**a**) Selected graph from presented database; (**b**) corresponding linkage diagram; (**c**) equivalent exoskeleton linkage introduced by [21]; (**d**) desired motion for finger introduced by [21]; (**e**) resulting eight-bar linkage introduced by [21].  
Therefore, an exoskeleton linkage having two angular outputs are required for hip and knee joints. These angular outputs can be obtained by six-, eight-, ten- and twelve-bar mechanisms. A planar single DOF eight-bar linkage is proposed to realize the required movement. Thus, Figure 6, generated by series connection, can be used to select a proper eight-bar topology such as the topology labeled by '01' shown in Figure 8a. According to Section 4.4, the corresponding linkage diagram can be sketched as illustrated in Figure 8b. This linkage is equivalent to the proposed linkage by [20] as shown in Figure 8c.  
Therefore, the proposed database, illustrated in Table 1, is a reliable tool that can be used to select a suitable exoskeleton linkage or other robotics applications with up to five angular outputs as a type synthesis. Then, a further dimensional synthesis is needed for each design case to detect links and joints orientation as shown in Figure 7e [21] and Figure 8e [20].  
However, exoskeleton design procedures can be summarized in the flow chart shown in Figure 9. The main concern of the present study is the type synthesis procedure. The flow chart illustrates how the proposed results can be used during the design process.  
Figure 8: Using eight-bar linkage as exoskeleton for leg rehabilitation. (**a**) Selected graph from presented database; (**b**) corresponding linkage diagram; (**c**) equivalent exoskeleton linkage; (**d**) Lower limb joints.
# Leveling Control of Hillside Tractor Body Based on Fuzzy Sliding Mode Variable Structure
## 5 Test Analysis
### Composition of Auto-Leveling Test Bench  
The auto-leveling test bench comprises three parts: a road spectrum excitation system, control system, and simulated vehicle body (Figure 14a). The spectrum excitation system can simulate two types of collected gravel transportation and field operation slope data; the control system utilizes an industrial computer that hosted the LABVIEW software to compile the sliding mode variable structure control algorithm program based on fuzzy switching gain adjustment, which in turn controls the angle of the drive axle leveling hydraulic cylinders. There are, in total, four leveling hydraulic cylinders on the front and rear drive axles of the simulated vehicle body, which are used to perform auto-leveling under the control system to verify whether the leveling capability meets the design requirements.