esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### X-ray Irradiation  
X-ray irradiation in air was conducted at EB-Tech Co., Ltd. (Daejeon, Republic of Korea) using a high-energy linear accelerator (UEL V105, 7.5 MeV, 1 mA, 10 Kw). Target doses were monitored by dosimetry with an alanine pellet dosimeter (ES 200-2106, Bruker Biospin Co., Billerica, MA, USA). The target doses were set at 10, 30, 50, 70, 100, 150, and 200 Gy and were measured using a radiochromic film dosimeter (GEXGAF3002 DS, USA) [ISO/ASTM512752004(E)]. The range of absorbed irradiation doses is shown in Figure 1.  
Thirty female and thirty male _P. opercuella_ adults were placed in a breeding cage (30 \(\times\) 30 \(\times\) 60 cm) containing cotton soaked in a sugar solution (5%) with coarse filter paper attached to the ceiling. They were permitted to lay eggs for 12 h. The filter paper with attached eggs (0-12 h old) was then exposed to X-ray irradiation. Ten _P. opercuella_ larvae (3 rd and 5 th instars) were placed in a plastic Petri dish (\(\diameter\) 9 \(\times\) 4 cm) with a potato tuber (5 \(\times\) 1 cm) and exposed to X-ray irradiation. Ten _P. opercuella_ pupae (less than 1 day  
Figure 1: X-ray dosimetry.  
after pupation) were placed in a plastic Petri dish (\(\Osterrow\) 9 \(\times\) 4 cm) and exposed to X-ray irradiation. Ten _P. opercuella_ adults (5 females and 5 males, 0-24 h after emergence) were separately placed in circular plastic cages (\(\Osterrow\) 9 \(\times\) 8 cm) and exposed to X-ray irradiation. To investigate the lethal effects on various developmental stages, we studied the rates of egg hatching and emergence suppression. The rate of egg hatching was recorded in X-ray-irradiated eggs. In X-ray-irradiated 3 rd-instar larvae, the pupation rate, adult emergence rate, larval period, and larval mortality were recorded. In X-ray-irradiated 5 th-instar larvae, the pupation rate, adult emergence rate, larval period, larval mortality, and newly emerged adult longevity were recorded. In X-ray-irradiated pupae, the rate of new adult emergence and the longevity of newly emerged adults were recorded. Furthermore, the fecundity and \(F_{1}\) egg hatchability were recorded that adults emerged and copulated successfully from the irradiated pupae. In X-ray-irradiated adults (female and males), the longevity of irradiated adults, and the fecundity and \(F_{1}\) egg hatchability were recorded. Trials on the different stages of _P. opercuella_ were performed with three replicates.
## 3 Measurement Improvement by Time Aggregation
### An Analysis of Varying the Position of the Interharmonic Tone  
Figure 4 shows the RMS value measured at the 250 Hz spectral bar, in which a harmonic tone of 13.2 Vrms is kept fixed. This value depends on the frequency of a second variable tone of 9.8 Vrms. The individual values found after performing the DFT on each of the first four windows of 0.2 s (tw1-tw4) are shown in that figure, along with those computed after performing the time aggregation on the first three windows (aggregated over time (Aggreg.) tw1-tw3), and those using a higher number of windows (Aggreg. tw1-tw144).  
Figure 4b shows an enlarged area with the values obtained for the sweeping tone at 253.3 Hz. The time aggregation of three windows (black dotted line) provides the correct common RMS value (13.81 V) for that position, which is also obtained if another quantity multiple of three windows is aggregated (144 in this graph, black continuous line). However, the aggregation of three windows is not sufficient for other positions of the tone closest to the harmonic with which it interacts, as it takes longer aggregation time when both tones are closer.  
The most significant variations between values obtained in successive windows occur when the sweeping tone is close to the center of the space between spectral bars, as in those positions, the leakage produced is the highest. Additionally, in those positions, the sum of the vector components of both tones experiences abrupt changes because the rotation speed between the representative vectors of the tones is maximum, so the variations of the phase angles between them are very significant. As the sweep tone approaches the other tone, changes in values between windows become slower, as the phase angle variation is smaller. For small rotation angles (due to the interaction between nearby tones), the evolution of the cosine summation in (1) is slower, and that leads to a more extensive aggregation of windows to improve the calculation of the RMS value. Therefore, \(\cos(\varphi_{i})\) evolves more slowly for close tones or with low rotation speeds between them, as is observed in Figure 4b when the sweep tone is close to the fixed harmonic located at 250 Hz. In that case, there are smaller variations between the amplitudes obtained with the successive tw1-tw4 windows and a more significant difference between the aggregated value computed with only three windows and the correct RMS value (continuous black line, for a high number of aggregated windows).
## 4 Mathematical Modeling
### Radiation Patterns of a GNSS Receiver's Antenna  
Earlier works have only modeled the radiation pattern in the \(X\!Z\) plane. To generalize the study, the radiation patterns must be modeled in the \(X\!Z\) and \(XY\) planes as mathematical models of E- and H-plane radiation patterns, respectively. The selected models are based on what was used in [13], but with some modifications. These models are  
\[g_{XZ}(\alpha) =\left|\frac{\sin(C_{XZ,MLFZ}\alpha)}{C_{XZ,MLFZ}\alpha_{SZX,Max}} \right|\left[C_{XZ,BS}\Big{(}e^{-|C_{XZ,S\tau R}-C_{XZ,SP\pi}|}+e^{-|C_{XZ,S\tau R }+C_{XZ,SP\pi}|}\Big{)}+C_{XZ,MLS}e^{-|C_{XZ,S\tau R}|}\right] \tag{3}\] \[g_{XY}(\beta) =\left|\frac{\sin(C_{XY,MLFZ}\beta)}{C_{XY,MLFZ}\beta_{XY,Max}} \right|\left[C_{XY,BS}\Big{(}e^{-|C_{XY,S\tau R}-C_{XX,SP\pi}|}+e^{-|C_{XY,S \tau R}+C_{XY,SP\pi}|}\Big{)}+C_{XY,MLS}e^{-|C_{XY,S\tau R}|}\right] \tag{4}\]  
In which \(C_{\theta,MLFZ}\), \(C_{\theta,BLS}\), \(C_{\theta,ST}\), \(C_{\theta,SP}\), and \(g_{\theta,max}\) are defined as detailed in [13], but within their plane of projection (the \(\#\) sign should be replaced with the \(XY\) or \(XZ\) terms). To assure the comparability of the results with those of earlier works, \(g_{XY}\) and \(g_{XZ}\) are modeled as described in [13], as listed in Table 2 and illustrated in Figure 2.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{1}{c}{**Scenario**} & \(C_{DF}\) & \(C_{PP}\) & \(C_{MA}\) & \(C_{CA}\) \\ \hline XZ Plane & Landing & 1.06 & 5.25 & 50 & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters to set the Direct Landing (DL) scenario.  
Figure 1: (**a**). A sample flight profile with its projections in the \(XY\) and \(X\!Z\) planes. (**b**). The projection of the same sample flight profile in two perpendicular planes.
# Underlying Security Transmission Design for Orthogonal Time Frequency Space (OTFS) Modulation
## 7 Conclusions  
In this paper, we have proposed a 2D permutation-aided OTFS secure transmission scheme that uses the GOST algorithm to perform disturbance control on the OTFS modulation domain. Furthermore, we have proposed an improved SLM algorithm, which can significantly improve the PAPR problem with very low complexity. We have carried out a comprehensive security analysis and simulation evaluation. Our results have shown that the transmission scheme can obtain a promising independence performance, ensuring the underlying security property of the OTFS. Furthermore, compared to the OFDM scheme, our proposed scheme can reduce the PAPR by 20% and significantly improve the BER. To facilitate practical implementation, future studies may consider the design of the OTFS secure scheme in non-reciprocal channel scenarios.  
Conceptualization, J.S. and X.L.; methodology, W.L.; validation, J.S., W.L. and J.H.; investigation, L.L.; writing--original draft preparation, W.L.; writing--review and editing, W.L.; funding acquisition, J.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Natural Science Foundation of China under Grant 61901327, Grant 61941105, Gants 62101450, in part by the National Natural Science Foundation for Distinguished Young Scholar 61825104, in part by the Fundamental Research Funds for the Central Universities under Grant JB210109, in part by the Shenzhen Science and Technology program under Grant JCYJ20210324121006017, in part by the Foundation of State Key Laboratory of Integrated Services Networks of Xidian University under Grant ISN22-03.  
Not applicable.  
The authors declare no conflict of interest.
## 1 Introduction  
Until now space missions have generally been either of short distance (Low Earth Orbit--LEO) or short duration (Apollo Lunar Missions). However, upcoming missions are looking to push the boundaries of space travel, with plans to travel for longer distances and durations than ever before. Both the National Aeronautics and Space Administration (NASA) and several commercial space companies (e.g., Blue Origin, SpaceX) have already started the process of preparing for long distance, long-duration space exploration and currently plan to explore inner solar planets (e.g., Mars) by the 2030s [1].  
Within the extraterrestrial environment, a multitude of exogenous and endogenous processes could potentially impact human health in several ways. Examples of exogenous processes include exposure to space radiation and microgravity while in orbit. Space radiation poses a risk to human health via a number of potential mechanisms (e.g., alterations of gut microbiome biosynthesis, accelerated atherosclerosis, bone remodeling, and hematopoietic effects) and prolonged microgravity exposure presents additional potential health risks (e.g., viral reactivation, space motion sickness, muscle/bone atrophy, and orthostatic intolerance) [2; 3; 4; 5; 6; 7]. Examples of endogenous processes potentially impacted by space travel include alteration of humans' natural circadian rhythm (e.g., sleep disturbances) and mental health disturbances (e.g., depression, anxiety) due to confinement, isolation, immobilization, and lack of social interaction [8; 9; 10]. Finally, the risk of unknown exposures, such as yet undiscovered pathogens, remain persistent threats to consider. Thus, prior to the emergence of long distance, long duration space travel it is critical to anticipate the impact of these varied environmental factors and identify potential mitigating strategies. Here, we review the available medical literature on human experiments conducted during space travel and summarize our current knowledge on the effects of living in space for both short and long durations of time. We also discuss the potential countermeasures currently employed during interstellar travel, as well as future directions for medical research in space.
# Lithium Battery SoC Estimation Based on Improved Iterated Extended Kalman Filter
## 2 Construction of Battery Model
### Equivalent Circuit Model Parameter Identification
#### 2.2.1 Fitting of OCV-SoC Curves  
Based on the data measured by the HPPC experiment, the open-circuit voltage data of the battery at the end of each step 3 is taken, and in this paper, the relationship between OCV and SoC is fitted using the cftool toolbox in MATLAB. After fitting, the root mean square error of the ninth-degree fitting is obtained as \(5.085\times 10^{-3}\), and the fitting effect is relatively good. Figure 2 shows the fitted ninth-degree polynomial fitting curve, whose ninth-degree polynomial is shown in Equation (4).  
\[\begin{array}{l}\text{OCV}(SoC)=&1674.8\times SoC^{9}-8204.2\times SoC^{8}+\\ 17,097.8\times SoC^{7}-19,767.3\times SoC^{6}+13,870.3\times\\ SoC^{5}-6082.3\times SoC^{4}+1660.2\times SoC^{3}-272.9\times\\ SoC^{2}+25.2\times SoC+2.50\end{array} \tag{4}\]
# Micromechanism of the Dispersion Behavior of Polymer-Modified Rejuvenators in Aged Asphalt Material
## 3 Results
### Toughness and Tencacity Analysis  
The toughness and tenacity curve for the CR rejuvenated asphalt binder is shown in Figure 10a. It has been well established that the shape of such curves reflects internal stress changes with tension. The aged asphalt binder in Figure 10a had the typical brittleness characteristic of the material and exhibited a rapid increase in stress and a direct fracture as the deformation increased. It was observed that the CR rejuvenator effectively softened the aged asphalt binder, which changed with the virgin asphalt binder (AH-70) type. Additionally, as shown in Table 6, an increase of the CR rejuvenator content was associated with a gradual reduction in the toughness of the asphalt binder, and an increase in the tenacity of the asphalt binder.  
As shown in Figure 10b, the shape of the toughness and tenacity curve for the MR-2 rejuvenated asphalt binder was similar to that of the modified asphalt binder (1-D). There are two obvious characteristics of the toughness and tenacity curve with increasing MR-2 content: (1) The height of the first peak was reduced; and (2) the yielding phenomenon became more evident. The shape of the first peak on the toughness and tenacity curve varied with the properties of the base asphalt binder, and the shape of the yielding region varied with the properties of the modifier [31; 32]. The results indicate that the rejuvenated component of MR-2 can soften the aged asphalt binder, and that the modifying components can improve its ability to resist deformation, especially when the MR-2 content was higher than 6%.  
Figure 9: DSR analysis results for CR and MR-2 rejuvenated binders at different contents: (**a**) curves of complex modulus as a function of temperature; (**b**) curves of phase angle as a function of temperature.
## 3 System Model
### System Propagation Model
#### 3.3.2 Free Space Loss Model of Satellite Channel  
Figure 3a shows that packets are transmitted through different beams of one satellite. In different beams, the distance between the user and the satellite can be regarded as the same. Different beams use different carrier frequencies for transmission. According to Figure 4a, we can see when the distance between the user and the satellite is 1500 km, the free space fading generated by beam 1 with 28.1 GHz and beam 2 with 28.2 GHz is 245.5 dB and 245.7 dB, respectively. In order to better show the influence of the distance on free space fading, doppler shift, and transmission delay, we have underlined the free space fading, doppler shift, and transmission delay values of satellites located at 1500 km and 1700 km in Figure 4. The red line indicates the free space fading, doppler shift, and transmission delay of the satellite \(s_{1}\) with a height of 1500 km. The black line indicates the free space fading, doppler shift, and transmission delay of the satellite \(s_{2}\) with a height of 1700 km. Figure 3b shows that packets are transmitted through different beams of multiple satellites. In different beams, the distance between the user and the satellite is quite different. At the same time, different beams use different carrier frequencies for transmission. It can be seen in Figure 4a that when the distances between satellites and users are 1700 km and 1500 km, the free space fading of beams with the same carrier frequency of 28.1 GHz is 248 dB and 245.5 dB, respectively. The free space fading can be expressed as:  
\[PL_{pathloss,\sigma_{q}^{c}s_{p}b_{p}}=\left(\frac{4\pi}{c}\right)^{2}\frac{ L}{G_{t}G_{r}}d_{\sigma_{q}^{c}s_{p}}^{2}f_{c}b_{p}{}^{2}, \tag{2}\]  
where \(c\) is the velocity of light. \(G_{t}\) and \(G_{r}\) are gain of transmitter and receiver, respectively, which we set to 1. \(L\) is system loss parameters. \(d_{\sigma_{q}^{c}s_{p}}\) is the distance between the satellite and the user, which can be get from Equation (3). \(f_{c}b_{p}\) is the carrier frequency. The carrier frequency of different beams is different. As the distance \(d_{\sigma_{q}^{c}s_{p}}\) between the satellite \(s_{p}\) and the user \(u_{q}\) and the carrier frequency \(f_{c}b_{p}\) of the beam \(b_{pj}\) increases, The free space fading \(PL_{pathloss,\sigma_{q}^{c}s_{p}b_{p}}\) of the beam \(b_{pj}\) of the satellite \(s_{p}\) transmitted the packet \(a_{qi}^{c}\) increases.  
\[d_{\sigma_{q}^{c}s_{p}}=\sqrt{R_{e}^{2}+r^{2}-2R_{e}rcos\theta}, \tag{3}\]  
where \(cos\theta=cos\left(\theta_{\sigma_{q}^{c}}-\theta_{s_{p}}\right)\bullet cos \varphi_{\sigma_{q}^{c}}\). \(\theta\) is the angle between \(R_{e}\) and \(r\). The range of \(\theta\) is \([-\frac{2\pi}{3},\frac{2\pi}{3}]\). \(\theta_{\sigma_{q}^{c}}\) and \(\varphi_{a_{qi}^{c}}\) are the longitude and latitude of the user \(u_{q}\) that generates the packet \(a_{qi}^{c}\), respectively. \(\theta_{s_{p}}\) is the longitude of the satellite \(s_{p}\). \(R_{e}\) is the radius of the earth. \(r\) is the orbit radius of the satellite.
## 4 Numerical Experiment
### Influence of the Release Time of the Shipper on Routing Optimization  
The MTW of the receiver is predetermined based on the post-transportation processing schedules and is thereby difficult to change flexibly. However, the release time of containers at the origin can be negotiated between the shipper and receiver and is thus adjustable. In this section, we discuss how the release time influences the routing optimization where the receiver prefers a high RT.  
In this case, we set the optimization levels as 0.9 and 1.0 and the release times as 6, 9, 12, 15, and 18, to obtain the TCs of the PIMRs under different combinations these parameters. The results are illustrated in Figure 9.  
Figure 8: Pareto solutions to the BOO for the GIMRPMTWIFCCTR under the optimization level of 0.7.  
Figure 9: TCs of PIMRs under different combinations of optimization level and release time.  
As indicated by Figure 9, the release time of containers influences the GIMRPMTWIFC-CTR. Under the condition that the receiver prefers a high RT and accordingly requires a high optimization level, the TCs of the PIMR become lower the earlier the containers are released at the origin. When changing the release time from 18 to 6, the TCs of the PIMR are reduced by 6.7% for the confidence level of 0.9 and 3.3% for the confidence level of 1.0.  
Therefore, an earlier container release time helps the receiver to reduce the TCs of the PIMR with a high RT to a certain degree. In this case, the shipper and receiver should negotiate effectively to enable the shipper to release the containers of the transportation order quickly, allowing a PIMR with lower costs and higher RT to be provided to the receiver by the IMO.
# HIPPP: Health Information Portal for Patients and Public
## 2 Materials: The HIPPP IT System for PPI
### HIPPP-AI: The Evaluation Pipeline Environment
#### 2.2.7 Incremental Learning  
Several studies created corpora of WBHI and evaluated the quality of the contained information through one of the QUEST, HONCode or DISCERN frameworks: 269 samples were considered in [15], 200 samples in [16], and 35 samples in [17]. However, these are tiny sample sets, leading to insufficiently small corpora. These data sets are not comprehensive enough to create truly generalised and robust models.  
Given this scarcity of available suitable corpora, we explored the idea of creating such an exhaustive data set for this task. The first task was to identify \"gold standard\" information sources. We consider government entities (such as hse.ie) and advocacy groups (such as cancer.ie) as reliable and relatively straightforward to find via search engine queries. However, aside from those most obvious content providers, determining where else to look in order to find real examples of the kinds of information sources that people engage with is a non-trivial exercise. The reason is the complexity of the information propagation channels on the internet. On top of this, there is the social media layer, where the information served to an individual is personalised based on a plethora of factors unknown to anyone just using or accessing social media.  
In this context, it would be extremely difficult, if not infeasible, for a small group of researchers to source and gather a collection of samples of sufficient quantity and representative quality to train high-quality models before making the pipeline accessible to the public. As a result of this initial data scarcity, the strategy was devised to use the HIPPP system itself to serve as a crowd-sourcing tool for gathering real-world samples of WBHI that real portal users do access on the internet. So, along with providing the user with an evaluation of the user input samples, the HIPPP will also serve as a data collection tool for information sources that are then labelled either automatically or manually through the expert portal.  
This approach enables _incremental learning_ through the process of adding new training data over time to extend the model's knowledge while retaining the knowledge learned from existing data. Given that we have access to a network of physicians who specialise in cancer research, we can leverage their domain knowledge to label \"hard samples\", i.e., those which did not meet the confidence threshold described above. The labelled data can then be used to extend the knowledge of the various models in the pipeline and to improve their performance.  
It is important to note that many of the tasks undertaken in the pipeline, such as coreference resolution and tone detection, are well-established research areas and therefore data scarcity is not an issue. Although available training data for these tasks is not specific to the domain of medical information, transfer learning [18] can be undertaken with a small volume of domain-specific data to tune the models.
# Potentials for Pressure Gain Combustion in Advanced Gas Turbine Cycles
###### Abstract  
Pressure gain combustion evokes great interest as it promises to increase significantly gas turbine efficiency and reduce emissions. This also applies to advanced thermodynamic cycles with heat exchangers for intercooling and recuperation. These cycles are superior to the classic Brayton cycle and deliver higher specific work and/or thermal efficiency. The combination of this revolutionary type of combustion in an intercooled or recuperated gas turbine cycle can, however, lead to even higher efficiency or specific work. The research of these potentials is the topic of the presented paper. For that purpose, different gas turbine setups for intercooling, recuperation, and combined intercooling and recuperation are modeled in a gas turbine performance code. A secondary air system for turbine cooling is incorporated, as well as a blade temperature evaluation. The pressure gain combustion is represented by analytical-algebraic and empirical models from the literature. Key gas turbine specifications are then subject to a comprehensive optimization study, in order to identify the design with the highest thermal efficiency. The results indicate that the combination of intercooling and pressure gain combustion creates synergies. The thermal efficiency is increased by 10 percentage points compared to a conventional gas turbine with isobaric combustion.  
Keywords:pressure gain combustion; advanced cycles; intercooling; recuperation; gas turbine performance; cycle optimization +
Footnote †: journal: Applied Sciences