esa-sceva/satcom-chunk-collection huggingface dataset:
# Passive Radar-Based Parameter Estimation of Low Earth Orbit Debris Targets
## 5 Simulations
### Self-Mixing  
Figure 5a displays the single-snapshot FFT results for a self-mixing scenario in which two signals were generated according to Equation (7) where \(A_{dir}=1\), \(A_{ref}=0.35\), \(\omega_{0}=1.575\) GHz, and \(\omega_{D}=1.5\) Hz. As expected, a single peak at the Doppler frequency is displayed. In this case, \(A_{dir}A_{ref}=0.38\), which is only 8% off the expected value of 0.35.  
Figure 5b displays the results of a similar scenario with an additional target added. In this case, \(A_{ref,2}=0.25\), and \(\omega_{D,2}=2.5\) Hz. As expected from Equation (13), three peaks resulted: two peaks corresponding to the Doppler signals and the remainder corresponding to the Doppler-difference signal.
## 5 Experiments
### Ablation Study
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**LLMs**} & \multirow{2}{*}{**Dataset**} & \multicolumn{2}{c}{**ACC of SwapAlpha**} & \multicolumn{2}{c}{**ACC of SwapWord**} & \multicolumn{2}{c}{**ACC of CaseAlpha**} \\  & & **w/o HECP** & **Ours** & **w/o HECP** & **Ours** & **w/o HECP** & **Ours** \\ \hline \multirow{4}{*}{GLM4} & MMLU & 50.86 & 54.69 & 47.98 & 49.27 & 59.85 & 60.72 \\  & LogiQA-en & 29.91 & 40.03 & 29.13 & 32.40 & 39.56 & 46.26 \\  & LSAT & 40.80 & 43.81 & 31.74 & 32.51 & 47.26 & 48.27 \\  & SAT-en & 67.25 & 73.79 & 55.46 & 56.31 & 81.45 & 82.04 \\ \hline \multirow{4}{*}{Llama3.1} & MMLU & 47.51 & 50.85 & 47.75 & 48.07 & 54.01 & 55.42 \\  & LogiQA-en & 33.80 & 35.51 & 29.15 & 29.75 & 37.89 & 38.47 \\  & LSAT & 36.75 & 39.45 & 29.73 & 30.72 & 41.22 & 43.11 \\  & SAT-en & 54.94 & 59.71 & 47.49 & 48.06 & 63.68 & 64.08 \\ \hline \multirow{4}{*}{Qwen2.5} & MMLU & 59.18 & 61.80 & 53.43 & 54.37 & 66.14 & 66.37 \\  & LogiQA-en & 46.04 & 49.22 & 36.34 & 39.72 & 51.87 & 52.49 \\ \cline{1-1}  & LSAT & 48.27 & 51.34 & 37.26 & 37.66 & 54.41 & 54.81 \\ \cline{1-1}  & SAT-en & 75.24 & 79.61 & 59.31 & 60.19 & 83.92 & 84.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Response ACC comparison of the self-correction reflection (Ours) with the ablated variant (w/o HECP) across three perturbation types at 100% intensity, evaluated on four datasets using four LLMs.
# RBC Storage Lesion Studies in Humans and Experimental Models of Shock
## 9 Volume, Age and Washing Effect on RBCs  
We next examined the effects of transfusing subjects with washed or unwashed RBCs of varying volumes and age. Two-year-old purpose-bred beagles were inoculated intra-bronchially with _S. aureus_ and then were transfused with increasing volumes (5-10, 20-40, or 60-80 mL/kg) of either 7- or 42-day-old RBCs (n = 36) or 80 mL/kg of either washed or unwashed RBCs with increasing age of storage (14, 21, 28, or 35 days) (n = 40) [16]. At all transfused volumes studied (5-80 mL/kg), transfusion of 42-day-old units resulted in similar increases in iron, CFH, lung injury, and mortality rates. Transfusion of 80 mL/kg of RBCs stored for an intermediate duration of time (14, 21, 28 and 35 days) resulted in increased CFH and iron in between levels found when the freshest (7-day-old RBCs) and longest stored RBCs (42-day-old RBCs) were transfused. However, washing RBCs of intermediate ages (14-35 days) did not alter the levels of iron and CFH or change mortality rates. Thus, these preclinical data suggest that by contrast with the extremes of storage age, transfusion of washed blood stored for intermediate periods does not alter risks of transfusion. In contrast, washing any volume of RBCs stored for 42 days potentially decreases CFH and iron levels and decreases risks during established infection. In contrast, transfusion of even massive volumes of fresh RBCs stored for 7 days result in minimal increases CFH and iron levels and risks. Looked at another way, it is not until the last week of storage, week six, that RBCs are so fragile that washing them has net beneficial effects by removing a profound number of cells easily hemolyzed by the stress of washing or transfusion. This increased risk could also be alleviated by decreasing the allowable storage duration to only five weeks. At the National Institutes of Health (NIH), we have applied the results of these preclinical data and have reduced the maximum storage duration for all stored RBCs in the Clinical Center Blood Bank to 35 days.
# Dynamic Network Formation for FSO Satellite Communication
## 3 Minimum Spanning Tree on Dynamic Graphs (DMST)
### Discrete Dynamic Graphs \(Mst\)
Available online: [[https://networkx.org/](https://networkx.org/)]([https://networkx.org/](https://networkx.org/)) (accessed on 24 October 2021). * [PERSON] (2020) Rhodes, B.C. PyEphem Astronomy Library. 2020. Available online: [[https://rhodesmill.org/pyephem/](https://rhodesmill.org/pyephem/)]([https://rhodesmill.org/pyephem/](https://rhodesmill.org/pyephem/)) (accessed on 24 October 2021). * [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Analysis of Inter-Satellite Link Paths for LEO Mega-Constellation Networks. _IEEE Trans. Veh. Technol._**2021**, _70_, 2743-2755. * [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON] StarPerf: Characterizing Network Performance for Emerging Mega-Constellations. In Proceedings of the 2020 IEEE 28 th International Conference on Network Protocols (ICNP), Madrid, Spain, 13-16 October 2020; pp. 1-11.
## 5 Conclusions  
Exposure to thirteen NORM-added negative-ion products has been investigated in terms of organ equivalent and annual effective dose. Products S05 and S13 recorded the greatest level of radioactivity, \({}^{238}\)U, \({}^{232}\)Th, and \({}^{40}\)K being found to be greater in sample S05. Estimation of organ dose equivalent and annual effective dose was obtained via Geant4 Monte Carlo simulations, leading to the conclusion that close contact with these products can infer annual effective doses of up to 2 mSv per year in excess of the dose constraint of 1 mSv y\({}^{-1}\) for members of the public. The products are advertised to contain touraline, monazite and zircon, all known to contain uranium and thorium. Although absent of any sound scientific support for the inclusion of radioactive components; nevertheless, these products are available for purchase in a number of countries, Malaysia included, and in the absence of any indication of the items containing radioactivity. It is suggested that the lead should be taken from EURATOM, and that such products should likewise be prohibited from being sold. We strongly recommend that consideration be given to the prohibition of the importation and sale of these undergarment products.  
Conceptualization, methodology, investigation, formal analysis, writing--original draft, H.J.H.; supervision, funding, conceptualization, investigation, writing--original draft, formal analysis, S.H.; conceptualization, investigation N.Z.H.A.H.; conceptualization M.F.R.A.H.; investigation, M.S.M.S.; writing--review and editing, D.A.B. and R.G.T.; funding, conceptualization, R.M.T. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Ministry of Science, Technology and Innovation (MOSTI) of Malaysia through Kumpulan Wang Amanah (KWA) Majlis Sains dan Penyelidikian Kebangsan (MSPK) (RJ130000.7317.4B658 and RJ130000.7317.4B659). The authors gratefully acknowledge the Ministry of Higher Education Malaysia and Universiti Tekhnologi Malaysia through Industry International Incentive Grant (No. 03M18). We acknowledge the cooperation with the project partners i.e., International Atomic Energy Agency and Atomic Energy Licensing Board, Malaysia for expert mission and procurement support through an IAEA TC program (MAL9018: Strengthening the Regulatory Infrastructure for Radiation and Nuclear Safety).  
\begin{table}
\begin{tabular}{c c c} \hline
**No.** & **Sample** & **Dose Rate (\(\mu\)Sv/h)** \\ \hline
1 & S01 & 0.11 \(\pm\) 0.01 \\
2 & S02 & 0.09 \(\pm\) 0.01 \\
3 & S03 & 0.12 \(\pm\) 0.02 \\
4 & S04 & 0.14 \(\pm\) 0.02 \\
5 & S05 & 0.24 \(\pm\) 0.03 \\
6 & S06 & 0.11 \(\pm\) 0.02 \\
7 & S07 & 0.09 \(\pm\) 0.01 \\
8 & S08 & 0.22 \(\pm\) 0.03 \\
9 & S09 & 0.17 \(\pm\) 0.02 \\
10 & S10 & 0.11 \(\pm\) 0.01 \\
11 & S11 & 0.09 \(\pm\) 0.01 \\
12 & S12 & 0.19 \(\pm\) 0.02 \\
13 & S13 & 0.23 \(\pm\) 0.03 \\ \hline \end{tabular}
\end{table}
Table 4: Dose rate (\(\mu\)Sv/h) of radioactivity in the undergarments, using a Survey Meter (IdentiFinder 2) portable detector.
# Design and Test of Real-Time Detection System for Cleaning Loss of Rapeseed Harvester
## 2 Materials and Methods
### Signal Processing Circuit Design
#### 2.3.4 Triple Voltage Comparison Circuit  
The voltage comparison circuit is a circuit that discriminates and compares the input analog signals and finally outputs a digital signal. Through the design of the integration circuit, it was found that the integration results of the kernels and the two categories of impurities were distributed in three different threshold intervals, so the triple voltage comparison circuit was designed to distinguish the different integral voltage ranges of the three categories of signals. Each voltage comparison circuit is connected in parallel with two other voltage comparison circuits. Each voltage comparator in the triple voltage comparator  
Figure 6: In-phase integral circuit.  
was designed according to the principle of series voltage division, and each connection is completely independent and they do not interfere with each other. The difference between each voltage comparator is that the voltage value adjusted by the adjustable potentiometer is different, and the voltage value is determined by the integration results of the different categories of impact signals.  
The input signal of the comparison circuit is the integration voltage value of the output of the in-phase integral circuit. The design method was to set three different voltage thresholds by adjusting the three resistance parameters of R19, R22 and R25, so as to distinguish the different voltage ranges after integrating the signals of the kernels and impurities. The design diagram of the triple voltage comparison circuit is shown in Figure 7.  
The designed triple voltage comparison circuit selects the threshold value for the output voltage of the integration circuit and automatically selects the threshold interval of the signal according to the different integration results of the signals generated by kernels and impurities and converts them into three different pulse signals at the same time.  
The three threshold intervals of the triple voltage comparison circuit are as follows: If the output voltage value of the signal after integration is greater than the voltage value of U8 but less than the voltage value of U7, the signal was formed by the impact of a carob shell on the inductive plate, and the output pulse signal is characterized by only one falling edge; if the output voltage value of the signal after integration is greater than the voltage value of U7 but less than the voltage value of U3, the signal was formed by the impact of a kernel on the inductive plate, and the output pulse signal is characterized by two falling edges; and if the output voltage value of the signal after integration is greater than that of U3, the signal was formed by the impact of a short stem on the inductive plate, and the output pulse signal is characterized by three falling edges.  
Figure 7: Triple voltage comparison circuit.
# Optimization of Pico-eNB Tx Power and the Effects of Picocell Range Expansion in Multiband HetNet
## 4 Optimization of Pico-eNB Tx Power
### Analysis of Use Rate of Modulation Methods  
Figure 10 shows an analysis of the use rate of each modulation method used in the downlink MCS as a function of the pico-eNB Tx power. No significant changes occur for the pico-eNB Tx power. However, the use rate of QPSK reaches minimum for a pico-eNB Tx power of 37 dBm. This result can be obviously explained based on the results shown in Figure 6. When the pico-eNB Tx power is 37 dBm, the use rates of both the 256- and 1024-QAM are 21%, although the use rate of QPSK is almost 36%. When the pico-eNB Tx power is 28 dBm, the use rates of both the 256- and 1024-QAM are 18%, and the use rate of QPSK is almost 40%. Accordingly, a pico-eNB Tx power of 37 dBm was able to improve the use rates of higher modulation methods compared with those at powers of 28 and 46 dBm.
## 2 Materials and Methods
### Data Collection  
Prior to data collection, infrared reflective markers were placed bilaterally on the anterior and posterior superior iliac crest, mid-lateral femoris (one marker slightly superior to the other), lateral femoral epicondyle, anterolateral mid-shaft of tibia, lateral malleolus, 2 nd metatarasophalangeal joint, and calcaneus. This placement was consistent with the recommended Vicon plug-in gait placement and enabled bilateral collection of the hip, knee, and ankle joint motion. All collection procedures were performed by well-trained and experienced doctoral students under the supervision of the two senior authors. The participants then mounted a motorized treadmill (Bertee(r), Columbus, OH, USA) and were secured in an overhead harness that prevented falls but did not provide postural support during walking. A static calibration was then obtained. To determine the participants' comfortable walking speed, the task began with the treadmill speed set to 0.1 m/s and was gradually increased by 0.1 m/s until the participants began to display signs of discomfort such as facial and hand motions, or vocalizations, or when the parents indicated the speed should be reduced. The speed was then reduced by 0.2 m/s and was labeled as the participants preferred speed. Once the preferred speed was identified, participants walked for two minutes to acclimate to the treadmill. After a brief rest, data collection was initiated and continued during three minutes of walking. The kinematic data were collected at 100 HZ using a Vicon(r) 16-camera motion (Vicon, Oxford, UK) capture system and processed with the Nexus v2.15 plug-in gait data processing software. A representation of the data collection environment including the treadmill, harness, and marker placement is displayed in Figure 1.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Participant** & **Biological Sex** & **Age** & **Syngap Genetic Mutation** \\ \hline
1 & M & 9 & c.3718C-T (p.R1240X) \\ \hline
2 & F & 9 & c.3190C-T (p.Q1064X) \\ \hline
3 & M & 8 & c.3583-9G-A (IVS16-9G-A) \\ \hline
4 & F & 12 & c.1677-2A-C (IVS10-2A-C) \\ \hline
5 & F & 4 & c.659T-C (p.F220S) \\ \hline
6 & F & 17 & c.3541\_3557 del (p.K1181 Aspfs*3) \\ \hline
7 & F & 5 & c.3535A-T (p.K1179*) \\ \hline
8 & F & 5 & c.3535A-T (p.K1179*) \\ \hline \hline \end{tabular} \({}^{*}\)stop codon.  
\end{table}
Table 1: Participant biological sex, age, and genetic mutation.
## 2 Latest Developed Biosensors for COVID-19
### Surface Plasmon Resonance (SPR)/Localised Surface Plasmon Resonance (LSPR) Biosensor
#### 2.2.1 SPR/LSPR Biosensor for COVID-19
[38] extended the previous PTAPS method by introducing a novel concept of thermoplasmonic-assisted dual-mode transducing (TP-DMT), as shown in Figure 3C. This dual-mode system combines (1) an amplification-free direct viral RNA detection and (2) an amplification-based cyclic fluorescence probe cleavage (CFPC) detection to provide self-validating biosensing readout for quantifying the SARS-CoV-2 sequences within 30 min. The first LSPR signal was based on the hybridisation between the target viral sequences and the functionalised thiol-DNA receptors. The amount of captured sequence  
Figure 3: SPR and LSPR biosensor for SARS-CoV-2 detection. (**A**) Graphene-based multiple-layer coated (\(\text{Bk}_{7}/\text{Au}/\text{P}\text{Ste}_{2}/\text{Graphene}\)) SPR biosensor. Reprinted with permission from [35]. (**B**) Dual-functional PPT enhanced LSPR biosensing system. Reprinted with permission from [37]. Copyright 2020, American Chemical Society. (**C**) Thermoplasmonic-assisted dual-mode transducing (TP-DMT) biosensing system. Reprinted with permission from [38]. Copyright 2021, American Chemical Society. is directly proportional to the virus concentration in the sample, and the limit of detection (LOD) was as low as 0.1 \(\pm\) 0.04 pM. In the CFPC detection, endonuclease IV (site-specific nuclease) was utilised to cleave the apurinic/apyrimidinic (AP)-site modified fluorescent probe from the target viral sequence under local PPT heating. The released fluorescent probe was used to quantify the concentration of the virus, which improved the LOD to 0.275 \(\pm\) 0.051 femtomolar (fM). This dual-mode sensing method employed two interdependent yet different tests on the AuNI chip, and provides two sensitive readouts of viral sequence to yield remarkably low limits of detection in pM and fM, respectively. When the final readout of the direct viral hybridisation detection exhibited a weak response, the CFPC method was used for verification and it could even detect a trace amount of virus in the sample.
## 2 Literature Review
### Advanced Technologies  
In aviation maintenance, several attempts have been made to either aid the operator or fully automate the inspection and repair process by introducing new technologies such as artificial intelligence in combination with robots [15, 16, 17, 18, 19] or drones [20,21] for defect detection of aircraft wings and fuselage structures [22, 23, 24, 25, 26, 27, 28], wing fuel tanks [29], tires [30] and composite parts [22, 31, 32, 33, 34]. The inspection and serviceability of engine parts such as shafts [35, 36], fan blades [26, 37], compressor blades [38, 39] and turbine blades [40, 41, 42, 43, 44, 45] is of particular interest as they are safety-critical, and thus unsurprisingly the most rejected parts during engine maintenance [46]. From a hardware perspective, the automation of inspection and repair processes is commonly done using robots. For in situ operations, recent developments focused on continuum robots, i.e., snakelike robots that combine the functionality of a borescope and a repair tool, comparable to endoscopic surgery in the health sector. The use of these continuum robots has been successfully demonstrated on coating repairs in the combustion chamber using thermal spraying [18, 19] and blending,  
Figure 1: Two types of engine blade inspections: (a) in-situ borescope inspection, (b) on-bench piece-part inspection.  
i.e., smoothing of edge defects on engine blades such as nicks and dents [16, 17]. The following literature review focuses on studies that compared the performance of humans and advanced technologies. Advanced technologies are often referred to as machines [47, 48, 49], software [50], computers [51], artificial intelligence [52, 53, 54], neural networks [55, 56], deep learning [57, 58, 59, 60], machine learning [61, 62], image processing [63], technological support [64] or automation [65], depending on the nature of the approach and underlying principles. In this paper, we use the term 'advanced technologies' representatively for image processing and artificial intelligence software and 3D scanning, being the main methods under examination.
## 1 Introduction
Finally, the Lattice Discrete Particle Model (LDPM) was used to investigate UHPFRC fracture behavior by focusing on the synergistic fiber pull-out and bridging effects, which raised the energy-absorbing capacity and ability of crack propagations [9]. These experiments collectively indicate that the effectiveness of fibers is due to a variety of interrelated mechanisms: (1) crack bridging, which redistributes stress over crack surfaces and delays crack widening; (2) fiber pull-out, which contributes frictional resistance to crack opening; (3) micro-cracking under control, which spreads damage over a larger area; (4) plastic deformation of the matrix material around the fibers; and (5) debonding at interfaces, which requires energy to separate fibers from the matrix. The synergistic functions of such mechanisms significantly enhance the energy absorption capacity of fiber concrete compared to plain concrete. Understanding these mechanisms is essential in maximizing the fiber-reinforced, high-strength, and ultra-high-performance concrete design, particularly for applications involving energy absorption and crack resistance to seismic and impact loading. By preventing uncontrolled crack propagation and promoting distributed damage, fibers ensure that the material can withstand higher deformation levels while dissipating more energy. In addition, studies conducted on two-layer beams demonstrated that the application of steel fiber high-strength concrete (SFHSC) in the compression zone and normal-strengthconcrete (NSC) with reinforcement in the tension zone significantly enhances structural ductility, energy absorption, and cracking resistance [10,11]. Steel fibers' ability to improve toughness is well established, as they increase strain at peak stress, and also increase the secant modulus of elasticity [12]. Furthermore, the content of fibers can be managed to improve ductility levels, which makes FRC extremely suitable for seismic-resistant designs [10]. FRC compressive behavior depends on several parameters encompassing the strength of concrete, fiber content, and fiber aspect ratio. Studies show that increasing the fiber content increases the strain at peak compressive strength, and the elastic modulus reduces marginally [13]. This work expands previous studies by further investigating the crack growth, extension, and energy dissipation behavior in fiber-reinforced concrete using more advanced modeling techniques and available experimental data. This study is focused on numerical modeling of the steel fiber-reinforced compressed zone behavior based on the results of previous work on two-layer beams [10,11]. Specifically, we focus on optimizing fiber content at the compressed zone. The design utilizes materials' properties and optimizes structural performance with higher cracking resistance in cyclic loading conditions.
## 1 Introduction
Once we have identified the most conservative antenna patterns both for L1 and L5 (in Section 5), we focus on the elevation at which the signals are received during the full MTO; such a study can provide useful information for the design of the receiver antenna, specifically for the mission considered. Furthermore (in Section 6), we investigate the relationship between the signal's availability at the receiver's position and the angle from the transmitter antenna's boresight at which the same signal was transmitted. As specified in this manuscript (in the beginning of Section 6), this relation is of interest since the prediction of the elevation at which the signal is transmitted, as well as the elevation at which the signal is received, combined with the knowledge of the transmitter and receiver antenna patterns, can be used to aid the acquisition process and better attribute the available tracking channels. Similarly (in Section 7), we also analyze the relationship between the angle at which the signals are transmitted from the GPS satellites and their relative geometry with respect to the receiver, which can also be exploited to aid in the signal acquisition process. Finally, Section 8 gives a summary of the conclusions obtained during this work.