esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experimental Results  
In this section, we evaluate the performance of the synchronization procedure in the D&F relay node over 5G downlink signal in terms of error vector magnitude. After that, the KPIs of the proposed decode-and-forward protocol access hardware architecture in terms of bit error rate (BER) and throughput versus P\({}_{\textbf{BS}}\) (transmission power of base station) for 64-QAM and 256-QAM modulation schemes have been taken and analyzed. Note that the  
Figure 7: Overview of the testbench nodes and the experimentation scenario of the proposed D&F relay node co-operative 5G network.  
KPIs are evaluated from the downlink obtained through a gnodeB emulated employing the MatlabTM 5G ToolBox, where for each transmission (in this work 20), 80 frames were sent by the base station for each point of P\({}_{\textbf{BS}}\). Furthermore, we consider a 5G downlink signal (CP-OFDM modulator) with subcarrier spacing 15 kHz, a sampling rate of 7.68 MHz, and a carrier frequency of 3.5 GHz. The rest of the emulated gnodeB parameters are given in Table 1.
# Mdpj _sciences_
## 4 Comparative Analysis of Experimental and Simulation Approaches
### Experimental Analysis of \"In Situ\" Performance
#### 4.1.3 Livestock Farming Area Trials  
Four studies conducted experimental analyses within livestock farming areas. The pollutant types and concentrations in these areas differ significantly from those near busy roads or inside urban buildings. The site conditions are unique, necessitating a tailored mitigation strategy using vertical green systems.  
[PERSON] et al. [38; 39] installed a Windbreak Wall-Vegetative Strip System in a pig farm and a poultry house, respectively. These studies aimed to apply and validate the experimental filtration system. Near the technology (previously described under \"active green walls\"), measurements included total suspended particulate (TSP) concentrations, ventilation rate, temperature, fiberglass screen porosity, and differential pressure. The results showed that lower screen porosity increased PM capture but also increased counter-pressure due to screen clogging. The system reduced TSP emissions, ammonia emissions, and odor; vegetation and soil also captured nitrogen and sulfur.  
[PERSON] et al. [46] and [PERSON] et al. [47] studied the installation of vegetative environmental buffers in poultry houses. These systems, composed of rows of trees and hedges, control emissions from agricultural areas to the environment, reduce wind speed, and create acoustic and visual barriers. [PERSON] et al. [46] used lidar (light detection and ranging) to estimate particulate capture efficiency, which works by interacting infrared light pulses with air particles. [PERSON] et al. [47] measured concentrations using real-time aerosol monitors and laser photometric meters to detect PM.  
Table 5 summarizes the in situ experimental analyses conducted to evaluate the pollutant mitigation performance of various green systems in different settings, including indoor environments, outdoor urban areas, and livestock buildings. The studies investigated pollutants such as particulate matter (PM), VOCs, ozone (O\({}_{3}\)), nitrogen dioxide (NO\({}_{2}\)), carbon dioxide (CO\({}_{2}\)), carbon (C), nitrogen (N), and sulfur (S). The table details the type of  
green system used, the specific test site, and the pollutant detection methods employed. This comprehensive overview highlights the practical applications and effectiveness of green systems in real-world conditions, providing valuable insights into their potential for environmental pollution mitigation.
# Unusual Animal Behavior as a Possible Candidate of Earthquake Prediction
###### Abstract  
Short-term (with a lead time of about one week) earthquake (EQ) prediction is one of the most challenging subjects in geoscience and applied science; however, it is highly required by society because it is of essential importance in mitigating the human and economic losses associated with EQs. Electromagnetic precursors have recently been agreed to be the most powerful candidate for short-term prediction, because a lot of evidence has been accumulated on the presence of electromagnetic precursors (not only from the lithosphere, but also from the atmosphere and ionosphere) prior to EQs during the last three decades. On the other hand, unusual animal behavior associated with EQs, which is the main topic of this review, has been investigated as a macroscopic phenomenon for many years, with a much longer history than the study of seismo-electromagnetics. So, in this paper, we first summarize the previous research work on this general unusual animal behavior with reference to its relationship with EQs, and then we pay the greatest attention to our own previous work on dairy cows' milk yield changes. We recommend this unusual animal behavior as an additional potential tool for short-term EQ prediction, which may be a supplement to the above seismo-electromagnetic effects. Finally, we will present our latest case study (as an example) on unusual changes of cows' milk yields for a particular recent Tokyo EQ on 7 October 2021, and further propose that electromagnetic effects might be a possible sensory mechanism of unusual animal behavior, suggesting a close link between electromagnetic effects and unusual animal behavior.  
earthquake (EQ); EQ prediction; unusual animal behavior; cows' milk yield; the Tokyo EQ on 7 October 2021; electromagnetic precursors; sensory mechanism of animals
# Gap Analysis of Ambient Electromagnetic Noise Measurements Stored in the ITU Data Banks
## 2 Man-Made Noise Levels in P.372  
In P.372, the radio noise level is expressed as an ambient noise factor \(Fa\), which is the ratio of the power output \(P_{n}\) of a lossless reference antenna and the thermal noise power \(KTB\). In logarithmic form, expressed in decibels:  
\[F_{a}=P_{n}-10\times log_{10}\left(k\ T\ B\right) \tag{1}\]  
where \(k\) is Boltzmann's constant (1.38 \(\times 10^{-23}\) J/K), \(T\) is the temperature (assumed 290 K), and \(B\) is the bandwidth in Hz. The reference antenna is a ground-mounted short lossless vertical monopole, or a lossless resonant half-wave dipole antenna. The predicted median noise factors for man-made noise are given in Figure 1. They can also be found in the form of a formula and a table in Part 6 of the Recommendation. The value shown represents the relative power of the background radio noise, which is assumed to resemble AWGN. The power spectral density of this component is independent of the sensor bandwidth. Radio noise is measured with a Root Mean Square (RMS) detector, preferably in a bandwidth that allows separation of the background noise from radio signals [13]. Intentionally emitted radio signals are not noise and should not be included in the measurements. Four environmental categories are shown in Figure 1: City, Residential, Rural and Quiet Rural. According to P.372, the difference between City and Quiet Rural is 24 dB, the difference between Rural and Quiet Rural is 14 dB. A future revision of the standard will probably use new environment definitions proposed in Recommendation ITU-R SM.1753 [17], in which Remote Rural replaces Quiet Rural and a few new categories are added. The given values are for outdoor man-made noise.  
Especially the Quiet Rural category is important for spectrum management: this is the level of radio noise when few or no man-made noise sources are nearby. This may be considered the base-line radio noise level.
# SatGuard: Satellite Networks Penetration Testing and Vulnerability Risk Assessment Methods
## 4 Implementation and Results
### Problem Setup  
Task background: In June 2024, the SpaceX Starlink Generation 7 satellite network entered the global deployment phase. A newly built equatorial ground station (codenamed SGS-17) was found to have significant security risks during the system acceptance test due to rapid-delivery requirements. The core system of the software layer of the ground-station system architecture is a customized Linux 4.19 real-time operating system.  
Evaluation metrics: We measure the effectiveness of LLMs by whether the penetration test is successfully completed and the number of interaction rounds with the LLMs [26, 27, 28]. We use the success rate to calculate the number of successful attempts and calculate the average number of interaction rounds.  
LLMs used: In this study, the commercial OpenAI GPT-4 and the domestic DeepSeek-R1 LLM are selected as the objects of comparative research. They represent the current internationally leading commercial general-purpose model and the Chinese-language-domain-optimized professional model, respectively. The specific technical parameters are as follows:  
GPT-4 is called through the Azure API service and supports a 32K context window. It achieves dynamic activation of trillions of parameters through a mixture of experts (MoE) architecture. The training data are up to October 2023, and it integrates multimodal understanding capabilities.  
DeepSeek-R1 can be deployed through the Alibaba Cloud Machine Learning Platform PAL. It adopts the Transformer-XL architecture with an improved attention mechanism. It  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dimension** & **CVSS** & **Proposed Method** & **Practical Implication** \\ \hline Domain & & & Tailored solutions for satellite-specific \\ Applicability & General IT systems & Satellite networks & risks, enhancing security \\  & & & in space infrastructure. \\ \hline \multirow{2}{*}{Core Parameters} & Linear combination of & & \\  & exploitability/impact metrics & Nonlinear amplification of impact (I), & Prioritizes high-impact, low-probability \\  & (AV, AC, PR, UL, C/1/A) & likelihood (L), and measurability (M) & threats critical to mission success. \\ \hline \multirow{2}{*}{Dynamic Adjustment} & \multirow{2}{*}{Temporal multipliers (E, RL, RC)} & Exponential time decay (8(t)) with & Provides time-sensitive risk \\  & & patch-state differentiation and & quantification, crucial for managing \\  & & confidence calibration (C) & long patch cycles. \\ \hline \multirow{2}{*}{Environment Customization} & \multirow{2}{*}{Modifies base metrics (MAV, MAC) and} & \multirow{2}{*}{Hierarchical segment weights} & Aligns risk evaluation with the \\  & security requirements (CR, IR, AR) & (\(\omega_{x}\) = 1.5-1.0) & operational criticality of different \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparative analysis of CVSS and proposed method.  
has a proprietary Chinese scientific literature training set (with a scale of 800 B tokens) and supports knowledge enhancement in vertical fields such as finance and biomedicine.
## 4 Conclusions and Future Work  
This paper considered the modeling of the small-scale and low-stiffness floating ring SFD bearings commonly used in the aeroengine rotor support system. Based on the perspective of theory and simulation, the oil film pressure distribution, fluid-structure coupling dynamic characteristics, and elastic ring support stiffness of the ring SFD-rotor system were identified. The main research contents and conclusions are as follows:  
1. The inner and outer oil film pressure distribution of the floating ring was investigated: the maximum oil film pressure keeps increasing with the increase in eccentricity,  
Figure 19: The minimum oil film clearance. (**a**) Minimum oil film clearance of floating ring 1; (**b**) minimum oil film clearance of floating ring 2.  
Figure 18: The flow rate of the oil hole channel.  
and it increases linearly with small eccentricity and increases non-linearly with large eccentricity exceeding 0.5. The bearing capacity of the oil film increases with the increase in eccentricity. The squeeze effect of the oil film is significantly enhanced, showing a strong nonlinear effect. The deflection angle decreases linearly with the increase in eccentricity. With the increase in the aspect ratio, the maximum oil film pressure increases linearly. The bearing capacity of the oil film also increases linearly with the increase in the aspect ratio.
2. In the balanced state, compared with the rotor speed, the floating ring rotates in the oil cavity at a very small speed. The results of the shaft trajectory and floating ring trajectory changes during the rotor start-up speed-up process show that the ring SFD has a significant effect on regulating rotor vibration, and the rotor shaft trajectory quickly converges to a balanced state and then whirls slightly in the ring. These results may encourage further work based on enhancements of the theoretical model in test.
3. The conclusions will be used to verify the theoretical results, and the influence of other parameters of SFD will be evaluated in the future. To comprehensively and deeply study the nonlinear dynamic behavior of the small-scale and low-stiffness ring SFD, the structural parameters of the ring SFD should be carefully selected to acquire a good vibration reduction performance.  
M.S.: Conceptualization, methodology, validation, data analysis, investigation, writing--original draft. Y.Y.: Writing--review and editing, supervision, funding acquisition. W.D.: Validation, formal analysis, project administration. J.W.: Data curation, validation, formal analysis. C.F.: Data curation, project administration. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China, grant number 11972295, and the Key Laboratory of Aero-engine Vibration Technology, Aero Engine Corporation of China, grant number KY-1003-2020-0037.  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
# Fact-Checking Reasoning System for Fake Review Detection Using Answer Set Programming
## 3 Why Reasoning System for Fake Review Detection Is Important?  
As mentioned in Reference [26], 90 percent of customers who remembered reading online reviews claimed that positive online reviews impacted their buying considerations. At the same time, 86 percent of them said negative online reviews affected their buying decisions. Additionally, around 40 percent of all online reviews on Amazon are fake ([[https://www.brightlocal.com/research/local-consumer-review-survey/](https://www.brightlocal.com/research/local-consumer-review-survey/)]([https://www.brightlocal.com/research/local-consumer-review-survey/](https://www.brightlocal.com/research/local-consumer-review-survey/)) ((accessed on 31 May 2021)). Thus, the need to have a reasoning system that is able to detect such reviews is in high demand specially when taking the following points in consideration:  
1. Fake reviews deceive customers of being fully aware of all the information about the product they are buying.
2. Some fake reviews are written in order to distract customers from positive rating of the product.
3. A lot of fake reviews are written to promote or even to demote the product.
4. Pure supervised learning approaches could not be a proper choice due to the lack of training data that considers the behavioral patterns of users/reviewers. The provided approach uses supervised learning for sentiment analysis of the review, which is considered in one rule in the KB.
# A Compact Broadband Planar Inverted-F Antenna with Dual-Resonant Modes
###### Abstract
With the slots loaded, the current path of the TM\({}_{3/2,0}\) mode is increased, thereby its resonant frequency can be shifted downward to combine with the TM\({}_{1/2,2}\) mode, leading to a widened bandwidth. Meanwhile, the slots change the radiation current distribution of both the two modes, improving their radiation patterns. On this basis, another pair of vertical slots is loaded onto the radiation patch, which is beneficial for achieving good impedance matching. In addition, a single-layer substrate with high permittivity is used to obtain a simple and compact antenna structure. The proposed antenna features a wide bandwidth, a compact size, and stable broadside radiation patterns, making it suitable for 5G terminals.
# Planar Array Diagnostic Tool for Millimeter-Wave Wireless Communication Systems
## 6 Antenna Array Diagnosis from Measured Data
### Antenna Array Diagnosis from Simulated and Measured Far-Field Radiation Patterns  
There are differences between the simulated and measured antenna patterns due to measurements errors, uncontrollable array fabrication errors, and experimental set-ups that give different conditions from the simulations. For example, in our design, a finite flange was employed to feed the ground plane. Hence, the induced current on flange rescattered and redistributed somehow against the very large ground plane which was used for the simulations. Antenna array diagnosis procedures based on simulated radiation pattern (such as References [3; 16; 17; 18; 27; 35]) may not be reliable and accurate, except when tested with the corresponding measured data. Although, in this work, simulation and measurement data exhibit little difference in field intensity of the identified faulty elements (in Figures 14 and 19, respectively) caused by the electromechanical coupling effect. In general, the proposed BCS-based approach shows good reliability and accuracy against both simulated and measured far-field radiation patterns.
# Selecting a Proper Microsphere to Combine Optical Trapping with microsphere-Assisted Microscopy
## 3 Experiments and Analysis  
### Experiment Setup  
After selecting the PS and MF microsphere, in order to experimentally realize super-resolution imaging assisted by an optically trapped microsphere, we construct the experimental setup. The schematic of the optical system is shown in Figure 3, including the optical trapping system and imaging system with an upright objective lens. For the optical trapping part of the system, a continuous wave laser (wavelength of 1064 nm, 1.5 W, linear polarization) is used. Deionized water  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Microsphere** & **Optical Trapping** & **Super-Resolution Ability** \\ \hline SiO\({}_{2}\) & \(\surd\) & x \\ PS & \(\surd\) & \(\surd\) \\ Melamine formaldehyde (MF) & \(\surd\) & \(\surd\) \\ Barium titanate glass (BTG) & x & \(\surd\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Optical trapping performances and super-resolution ability of four microspheres in water.  
(\(n_{m}\sim 1.33\)) is used to immerse PS microspheres (\(n\sim 1.59\), D-10 \(\upmu\)m, BaseLine ChromTech Centre, Tianjin, China) and MF microspheres (\(n\sim 1.68\), D-10 \(\upmu\)m, Huacortek Microtek Co., Ltd., Wuhan, China). For the illumination part, Kolher illumination is conducted, in which a broadband LED (central wavelength of 600 nm) with an adjustable intensity is utilized, and we can adjust the condenser diaphragm (CD) and the field diaphragm (FD) to improve the image quality [36]. The objective (100\(\times\), NA = 0.9) is provided by Olympus Corporation, which under our conditions, gives a lateral resolution of 306 nm based on the equation \(0.61\lambda/NA/n_{m}\). A silicon nanostructure grating (SNG), consisting of 139 nm stripes with 139 nm separations is used as the sample which cannot be resolved by the objective. The imaging processing is conducted by a high-resolution CCD camera (acA2040, Basler). Firstly, we prepare the solution by diluting PS or MF spheres with deionized water in a proportion. Then, the sample is covered by a thin solution layer, and a few spheres are contained in this solution layer. The expanded laser beam is highly focused by the objective lens and then traps a sphere in the vicinity of its beam waist. The focused laser beam can be used to trap the sphere of interest. The optically trapped PS/MF microsphere is kept motionless and the position of the sample is adjusted by the 3-axis stage until the CCD captures magnified images of the measured surface in different positions. The optically trapped PS/MF microsphere is close enough to the sample and collects the sub-diffraction-limit frequencies of the sample. A short-pass filter (cut-off wavelength 800 nm) is used to eliminate the focused laser spot's influence on imaging.
## 4 Conclusions  
We compared the levels of heavy metals and major As species in seaweeds with those in other marine organisms. The concentrations of heavy metals such as Pb and Cd in most seaweeds were below the standard values recommended by international regulations and those of the Korea Food Code. The total As content in _Sargassum_ spp. of brown seaweeds was relatively higher than that in other seaweeds, and they contained considerable amounts of inorganic As, As(V) in particular. Therefore, _Sargassum_ seaweeds are classified as a high-risk food group around the world due to concerns related to the high toxicity of inorganic As. Fortunately, most _Sargassum_ spp. are inedible, and although _S. fusiforme_ (_hijiki_) is a widely known edible seaweed, the mean daily intake is quite low according to the statistical data on Korean and Japanese diets, where it is recognized that the ingestion of seaweeds is relatively higher than that in other countries. Therefore, if seaweeds such as _Sargassum_ spp.  
are carefully used within the proper intake range, they can be considered a healthy food that contains an abundance of dietary fiber, minerals, and vitamins.  
In this study, the number of samples used for monitoring heavy metals and arsenic in seaweed was insufficient to perform an in-depth evaluation of food safety. Therefore, additional studies such as evaluating the risk of inorganic As in seaweeds using internationally authorized methods like BMD and statistical relationships studies between the contents of As species in seaweeds and diverse marine organisms are necessary. These additional approaches will provide useful guidelines for seaweed consumption.  
Conceptualization, K.J.L., M.Y. and J.H.K.; Data curation, K.J.L., M.Y., H.Y., S.H.J. and J.H.K.; Formal analysis, K.J.L., E.H.K., M.Y., M.R.J. and S.H.J.; Funding acquisition, K.T.S.; Investigation, K.J.L., E.H.K., M.Y., M.R.J., H.Y. and S.H.J.; Methodology, K.J.L., E.H.K., M.Y., M.R.J., H.Y. and J.H.K.; Resources, K.T.S.; Supervision, K.T.S.; Validation, K.J.L., E.H.K., M.Y. and M.R.J.; Writing-original draft, K.J.L.; Writing-review and editing, K.J.L., M.Y., H.Y., K.T.S., S.H.J. and J.H.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a grant from the National Institute of Fisheries Science in Republic of Korea (R2022065).  
Not applicable.  
The authors declare that they have no potential conflict of interest.
## 2 Background
### HVAC Modeling Techniques
#### 2.1.2 Data-Driven Models  
Data-driven models leverage empirical data and employ machine learning techniques such as artificial neural networks, fuzzy networks, and genetic algorithms to establish relationships between features and target variables. These approaches are highly dependent on the quality and quantity of the available training data and can account for disturbances in the data, such as variability in occupancy, the usage of electronic devices, and other environmental factors. However, they capture the physics of the process to a minimal extent. [PERSON] et al. [3] successfully integrated an MLP with MOPS framework, achieving energy savings of 12.4-17.4%. Similarly, [PERSON] et al. [5] applied a multi-objective optimization model in combination with an evolutionary computation algorithm, resulting in energy savings of 21.4-22.6%. Additionally, [PERSON] et al. [7] utilized an ANN model to capture thermal interactions in multi-zone buildings, demonstrating that comfortable temperatures can be maintained with a 28% reduction in daily energy consumption and an estimated 10% savings when the model is extended over a month.