esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluating Creativity: Can LLMs Be Good Evaluators in Creative Writing Tasks?
## Appendix A ANOVA and Post Hoc Analysis for Evaluator Type and Evaluation Criteria  
To examine differences in evaluator type and evaluation criteria, an ANOVA was conducted on both human and GPT-4 writings, as shown in Table A1. The results show that in human writings, both evaluator type (\(F\ =5.106\), \(p<0.01\)) and evaluation criteria (\(F=7.671\), \(p<0.001\)) had significant effects, indicating that different evaluators scored human-written texts differently and that certain evaluation criteria were rated higher than others. However, post hoc [PERSON]'s HSD analysis revealed that no significant differences existed among individual evaluator groups (\(p\)-values ranged from 0.181 to 1 for all pairwise comparisons), suggesting that while evaluator variation had an overall effect, no specific group differed significantly from the others.  
For AI-generated writing, the evaluator effect was not significant (\(F=1.845\), \(p=0.160\)), while differences across evaluation criteria remained significant (\(F=8.353\), \(p<0.001\)), suggesting that AI texts were assessed more consistently across evaluators, but differences among evaluation criteria were still evident. Post hoc comparisons further confirmed that elaboration was rated significantly higher than specific creativity strategies (\(p<0.05\)) and usefulness (\(p<0.001\)) in AI-generated writing.  
These findings suggest that human writing is influenced by both evaluator variation and evaluation criteria, while AI-generated writing is mainly shaped by differences in evaluation criteria rather than by who evaluates it. This may be because AI-generated texts follow learned patterns, making evaluator differences less noticeable. In this study, AI-generated writing was assessed by both human evaluators and four different language models, raising concerns about potential biases in AI-based evaluation. Since LLMs evaluate text based on patterns learned from pre-trained data, they may favor familiar structures andreinforce existing biases rather than objectively assessing creativity. These results highlight the importance of evaluation criteria in assessing creative writing and the need to carefully examine AI's role as an evaluator.
# Perpendicular Electrical Conductivity in the Topside Ionosphere Derived from Swarm Measurements
## 1 Introduction
Their results suggested that particle precipitation is responsible for the enhancement of \(\sigma_{\parallel}\) in the cusp region and in correspondence with the nocturnal main trough. Finally, [PERSON] et al. [59] quantified the power density dissipated by FACs, namely \(\mathbf{J}\cdot\mathbf{E}\), taking advantage of local calculations of \(\mathbf{J}\) and \(\sigma_{\parallel}\) with Swarm data. To our knowledge, no one has ever characterised the electrical conductivities perpendicular to the magnetic field, \(\sigma_{P}\) and \(\sigma_{H}\), in the topside ionosphere via in situ measurements. This is mainly due to their lower magnitude compared to the parallel conductivity in the topside ionosphere. Nevertheless, although small, \(\sigma_{P}\) and \(\sigma_{H}\) are not null. Therefore, the application of intense electric fields, which were actually observed at those altitudes [60; 61] in the direction perpendicular to the geomagnetic field, may lead to the onset or amplification of perpendicular ionospheric currents. The intensity and direction of these currents are influenced by the local structure of conductivity. This is even clearer if one rewrites Equation (1) for the case of a three-dimensional anisotropic medium characterised by the conductivity tensor, \(\underline{\sigma}\), as follows [62]:  
\[\mathbf{J}=\underline{\sigma}\mathbf{E}^{\prime}= \begin{pmatrix}\sigma_{P}&- \sigma_{H}&0\\ \sigma_{H}&\sigma_{P}&0\\ 0&0&\sigma_{\parallel}\end{pmatrix} \mathbf{E}^{\prime}. \tag{2}\]  
In Equation (2), \(\mathbf{E}^{\prime}\) is the electric field in the plasma frame of reference with components \(E^{\prime}_{i}=E_{i}+(\mathbf{u}\times\mathbf{B})_{i}\), and we assume that \(\mathbf{B}\) is directed along the versor \(\mathbf{\hat{z}}\), the component of \(\mathbf{E}\) perpendicular to \(\mathbf{B}\) is directed along \(\mathbf{\hat{x}}\), and the versor \(\mathbf{\hat{y}}\) is perpendicular to both \(\mathbf{B}\) and \(\mathbf{E}\) in a left-handed Cartesian coordinate system. Therefore, the knowledge of the conductivity tensor is crucial for reconstructing ionospheric currents, whatever their intensity, and possibly quantifying their dissipation even at Swarm altitude, i.e., between 450 and 500 km. In this paper, we extend our previous works [55; 56] and, for the first time, compute \(\sigma_{P}\) and \(\sigma_{H}\) in the topside ionosphere from in situ satellite measurements, which is preparatory to an empirical model for \(\underline{\sigma}\). This paper is organised as follows: In Section 2 we describe the data set used and the methods employed for the calculation of \(\sigma_{P}\) and \(\sigma_{H}\). Section 3 is devoted to the description of results, which are discussed in Section 4 considering the previous literature. Finally, in Section 5, we summarise the key points of the work and come to conclusions by indicating future perspectives.
## 4 Conclusions  
In this paper, we have presented an improved multi-temporal PolSAR image change detection approach. A test statistic based on MLE and improved K&I were used to deal with the problem of change detection of a complex urban area containing bridges, water bodies, and buildings. Multi-temporal data of Wuhan, China, were used to assess the performance of the proposed method. The main advantages of the proposed method are (1) the use of fully polarimetric information, (2) the use of the GGM to choose the PolSAR threshold, and (3) the computational simplicity and stability. Because obtaining the CI map is the key step in unsupervised change detection, the log-ratio method using single-channel information and CVA using linear computation of multi-channel information cannot generate a high-quality CI map, which directly influences the precision of the change detection map. The proposed method using fully polarimetric information is better able to detect slight differences and can effectively distinguish between changed and unchanged areas. The use of a test statistic is appropriate for PolSAR images, and it can be used to obtain an accurate CI map. The use of K&I to automatically choose the threshold under the assumption that the PDF of the CI follows a Gaussian distribution does not accurately match the aforementioned conditional densities of classes. We therefore use the improved K&I algorithm based on the GGM to choose the threshold. Using the proposed method, we were able to accurately detect the changes associated with the construction of a tunnel on East Lake from 2011 to 2016, as well as the changes in water bodies caused by the heavy rainfall in July 2016. The experimental results obtained on the multi-temporal PolSAR images of Wuhan confirmed the effectiveness of the proposed approach.  
**Acknowledgments:** The authors would like to thank the National Natural Science Foundation of China (grant no. 91438203, no. 61371199, no. 41501382, no. 41601355), the Public Welfare Project of Surveying and Mapping Interest (201412002), the Hubei Provincial Natural Science Foundation (no. 2015 CFB328, no. 2016 CFB246), the National Basic Technology Program of Surveying and Mapping (no. 2016 KJ0103), and the Technology of Target Recognition Based on GF-3 Program (no. 03-Y20A10-9001-15/16). [PERSON] would also like to thank China Scholarship Council for funding his study at Southern Methodist University.  
**Author Contributions:** [PERSON] defined the research problem, proposed the method, undertook most of the programming in MATLAB and VS2010, and wrote the paper. [PERSON] gave some key advice. [PERSON] gave useful advice and contributed to the paper writing. [PERSON] provided the RADARSAT-2 data and some useful advice. [PERSON] collected the data and processed the datasets in ENVI, PolSARpro, and NEST software. [PERSON] obtained the ground-truth map.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Materials and Methods  
The levels of electric field were recorded in all areas where crew members and passengers gather in all three levels of the ship: (i) the upper deck, Level 1 (the area where the passengers spend some of their time); (ii) the bridge deck, Level 2 (central to where the bridge operation stations are located and the crew members' working position); and (iii) the bridge roof, Level 3 (where all of the transmitters and antennas were located), as in Figure 1. Please note that the bridge roof is not accessible to the general public (e.g., passengers). The shipboard radio transmitter and the antenna systems that we used in this study are described in Table 1. The position numbers or measuring locations in Table 2 correspond to the numbers in Figure 1.  
All electric field measurements were recorded under similar conditions with (i) a NARDA NBM 520 with probe (EF 1891), frequency range 3 MHz-18 GHz and sensitivity 0.8-1,000 V/m, and (ii) a NARDA NBM 550 with probe (EF 0391), frequency range 100 kHz-3 GHz, sensitivity 0.2 V/m for the electric field and a detection range 0.2-320 V/m (Narda Safety Test Solutions, Germany), to measure the electric field levels in this study. Both broadband and narrowband (frequency selective) instruments can be used for measuring RF fields. In our study, the NARDA meters provide the broadband measurements, and the electric field probes provide isotropic (non-directional) measurements. The data acquisition time of the NARDA meters is 2 s-5 min. Each position undertook two types of measurements, \"spot measurements\" and \"continuous measurements\". Each set of electric field measurements was taken for 6 minutes at each position until a steady-state value was obtained; average values were then recorded. All probes were oriented vertically during the data collection, and the auto-zeroing function was used to exclude the effects of temperature on the results. Since the field distribution is not homogeneous, the spatial averaging function was used in both meters. The transmission directions of directional antennas did not change during the data collection period. Figure 1: Measuring locations (No. 1–12) of the marine ship. The electric field (EF) measurements were recorded in all areas where people (crew members and passengers) gather in all 3 levels of the ship: (i) the upper deck (Level 1, the area where the passengers and crew members spend time); (ii) the bridge deck (Level 2, the crew members’ working position); and (iii) the bridge roof (Level 3, all the transmitters and antennas were mounted). Please note that the bridge roof is not accessible to the general public (e.g., passengers).
# A Modified Bearing Capacity Model for Inclined Shallow Anchor Cable with Experimental Verification
## 3 Validation by Model Experiment
### Experimental Material  
Due to sedimentary and loading histories, most natural soils are of cementing structures at the particulate level [33; 38]. Consequently, the ground in the test was prepared by mixing the sand, cement mortar, and water at a ratio of 1450:55:310. The cement slurry with a water-to-cement ratio of 0.5:1 was employed as the grouting material for the anchor cable. The anchor cable was composed of four twisted steel wires, each with a diameter of 1.5 mm.  
During the ground preparation, the grouting hole was reserved for installing the anchor cables. Additionally, standard specimens of the ground (\(\Phi\)50 mm \(\times\) 100 mm) were prepared for uniaxial and triaxial compression tests to determine the basic properties, including cohesion, internal friction angle, elastic modulus, Poisson's ratio, and density.  
The mechanical parameters of the sample were obtained by triaxial compression tests, and the corresponding Mohr's circles were plotted to emulate the cohesion (9.85 kPa) and internal friction angle (39\({}^{\circ}\)), as shown in Figure 4a. The elastic modulus and Poisson's ratio were calculated based on the load-displacement curve of the uniaxial compression tests, as shown in Figure 4b. Table 2 shows that the average elastic modulus was 124.5 MPa and Poisson's ratio was 0.37. The average density was 1.77g/cm\({}^{3}\), as shown in Table 3. Table 4 presents the ground properties. It shows that the ground exhibited an initial friction angle of 39\({}^{\circ}\) and a cohesion of 9.85 kPa.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Diameter \(d\) (mm)** & **Inclination Angle \(\alpha\) (\({}^{\circ}\))** & **Fixed Anchor Length \(l_{fixed}\) (mm)** & **Burial Depth \(h_{\alpha}\) (mm)** \\ \hline
20 & 30 & 120 & 70 \\
20 & 40 & 120 & 70 \\
20 & 50 & 120 & 70 \\
20 & 60 & 120 & 70 \\
20 & 70 & 120 & 70 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Test scheme.  
Figure 4: Result of uniaxial and triaxial compression tests: (**a**) Mohr’s circles of triaxial compression tests; (**b**) load–displacement curve of uniaxial compression tests.
## 1 Introduction
The results showed that the wind pressure distribution on the surface could be accurately calculated by using the unstructured mesh system [35]. [PERSON] and [PERSON] adopted an unstructured mesh with tetrahedral cells in the simulation of complex high-rise residential buildings to evaluate the comfortable outdoor-wind levels for pedestrians [1; 36]. The polyhedral mesh has the advantage of achieving better simulation results with relatively fewer meshes. Some scholars analyzed the calculation speed and accuracy of polyhedral meshes and verified the accuracy of the simulation results. For instance, [PERSON] et al. proposed a new method for computational domain discretization based on polyhedral meshes and compared the simulation results generated by three mesh types (i.e., hexahedral, polyhedral, and tetrahedral). It was found that the polyhedral mesh was a reliable choice for computational domain discretization. Moreover, this method could reduce the numerical diffusion of the meshes and the calculation time [37]. Previous research in this field mainly focused on the influence of different turbulence models and parameter settings on the simulation results, and there is no comprehensive study on the accuracy of the simulation results in low- and high-wind-speed areas around high-rise buildings. Some requirements about wind speed were included in the design guidelines for green buildings. For example, \"Green Building Evaluation Standard\" (GB/T50378-2019) requires that the maximum wind speed is less than 5 m/s at the pedestrian level (1.5 m above the ground) around buildings in winter and that there are no static wind areas in playgrounds in summer [38]. However, the methods of predicting outdoor wind environment and the choices of turbulence models were not suggested in this standard. To fill the gap, this study shed light on the wind flow around a high-rise building using various k-\(\epsilon\) turbulence models (e.g., SKE, RKE, etc.) based on polyhedral meshes. The simulation results were cross-compared with the wind tunnel experiment results to verify the accuracy of the simulation under different conditions. It is expected that this study can provide a benchmark for future work and improve the accuracy of predicting the wind environment around a high-rise building.
## 5 Discussion
### Characterisation of the Fracture Network
These comparison wells exclusively penetrate the rocks of the AG block and reveal the sheared zones inside the tens-of-metre-thick amphibolite sequence. Nevertheless, the wells to the South penetrated only a massive amphibolite. As previous studies [16; 19] have revealed, the presence of an SG block can be inferred below the AG block, separated by wide (\(\sim\)10-20 m) fault zones throughout the Szeghalom Dome. Such an arrangement suggests that the shear zones inside the AG block can be spatially extended and have a south-dipping position parallel to the major thrust sheet that separates it from the underlying SG block. Wells both to the East and West also have rocks of SG and OG blocks below the AG block. In harmony with the structural evolution of the area [16; 19; 20], these regions represent elevated horsts separated by normal faults from an AG-dominated block between them (Figure 14). Based on their position and lithological characteristics, the brecciated amphibolite layers in the A-1 well and its neighbouring wells can be assumed to relate to the overthrust zone between the SG and AG blocks at smaller scales. From this viewpoint, the structures revealed by the A-1 well can be interpreted as minor fault zones accompanying the larger fault zone within the hanging wall (i.e., AG block). The near-well fracture network models based on the geometric parameters of the fractures measured along with the A-1 well indicate communicating fracture systems in two of the three well-deformed depth intervals (\(\sim\)2075 and 2065 m; Figure 11). In contrast, the zone at \(\sim\)2052 m most likely contains individual fractures, which do not define a connected network. At these points, the output of all 10 independent simulations reveals fracture patterns with identical behaviour, a result sufficiently stable to be accepted. Nevertheless, the connectivity of the fracture system outside the two well-developed layers is more ambiguous, with some models exhibiting communication between the two highly fractured zones and others indicating two entirely isolated fracture systems (Figure 11). The reason behind such unpredictable behaviour is that outside the two brecciated zones, the fracture network is probably geometrically close to the percolation threshold [51], meaning that the communication between the two highly fractured zones is limited [52]. Combining the results of the well-log interpretation and fracture network modelling, three intensively tectonised intervals can be outlined inside the AG body. Because of the mutual  
Figure 14: Block model representing the structural position of the A-1 well and its surroundings. The two highly fractured zones inside the AG block with good reservoir properties are denoted. interconnection of the fracture network resulted by the DFN models (Figure 11), two of them probably exhibit substantial lateral extension. Whether or not they communicate hydrodynamically can hardly be predicted using the fracture system simulation approach.
## 4 Network Architecture and Parameter Optimization
### Dataset Partitioning  
In this study, we randomly divided the dataset into training sets and test sets, of which 80% (197 groups) were training sets and 20% (50 groups) were test sets. In the specific process of training the model, a five-fold cross-validation method was utilized to optimize each training process; that is, the training sets were divided into five parts, four of which were used for training in turn, and the remaining part was used for verification.
# A Review of Irrigation Information Retrievals from Space and Their Utility for Users
## 5 The User Perspective: Observation Requirements and Current Obstacles
### Current Practices Versus Current Satellite Capabilities  
#### 5.2.1 Management Systems  
To understand to what degree satellite observations can help in the monitoring and the management of irrigation, we first asked the organizations whether they are already using any system for the management and measurement of irrigation applications. The answers varied from no system at all to fully automated, remotely controlled systems. Of those who do use management systems, most use point-scale in situ soil moisture measurements, while nobody mentioned the use of remote sensing observations. Furthermore, sometimes, there are in situ measurements that are not accessible to some stakeholders. For instance, the basin authority may not have access to the existing water accounting system within the irrigation district (they just track what has been delivered through the main canal). Additionally, there can be illegal uses of irrigation water that are unmetered. This happens in some Mediterranean areas [139] and remote sensing can play an important role in quantifying these water withdrawals. In summary, we believe that there is space for remote sensing observations and methods that integrate remote sensing information to provide useful tools for optimal irrigation and water resource management.
## 4 Results and Discussion  
### Verification Results for Fourier Series-Based Homogenization Theory  
To verify the proposed the Fourier series (FS)-based homogenization theory, the numerical analysis was performed for the unit-cell established in Section 3.1. Here, the fiber volume fraction, phase contrast combination amount and resolution were 13%, \(\zeta=44\) and 125, respectively. [PERSON] et al. [44] confirmed that the higher the resolution, the smaller the phase contrast ratio and the smaller the deviation range of the result. For the GDL fiber network of this paper, the phase contrast combination amount satisfies the condition that the reliability is secured with \(\zeta=73.7\) and resolution = 100.  
Numerical analysis was performed based on FS theory for the unit-cells using the commercial software ABAQUS. The user run-script was developed using a homogenization technique based on the FS to compute equivalence properties. Figure 5 compares the equivalent properties obtained from the Fourier series-based homogenization method developed in this paper, with the results from the conventional homogenization methods which have been already verified by several studies [44] such as the fast Fourier transformation (FFT), the mean field generalized self-consistent (MF-SC) and mean field interaction direct derivative (MF-IDD). Assuming that the result obtained by the FS-based homogenization theory is 100%, the degree error of the results from the conventional methods can be identified by comparing the referenced results [44] with the longitudinal elastic moduli (\(E_{11}\) and \(E_{22}\)). The results of the FS-based homogenization theory are relatively intermediate of the properties obtained from the FFT, MF-IDD and MF-SC theories.
###### Abstract  
Non-ionizing millimeter-waves (MMW) interact with cells in a variety of ways. Here the inhibited cell division effect was investigated using 85-105 GHz MMW irradiation within the International Commission on Non-Ionizing Radiation Protection (ICNIRP) non-thermal 20 mW/cm\({}^{2}\) safety standards. Irradiation using a power density of about 1.0 mW/cm\({}^{2}\) 50 cells/\(\mu\)L samples of _Saccharomyces cerevisiae_ model organism resulted in 62% growth rate reduction compared to the control (sham). The effect was specific for 85-105 GHz range and was energy- and cell density-dependent. Irradiation of wild type and _Arad52_ (DNA damage repair gene) deleted cells presented no differences of colony growth profiles indicating non-thermal MMW treatment does not cause permanent genetic alterations. Dose versus response relations studied using a standard horn antenna (\(\sim\)1.0 mW/cm\({}^{2}\)) and compared to that of a compact waveguide (17.17 mW/cm\({}^{2}\)) for increased power delivery resulted in complete termination of cell division via non-thermal processes supported by temperature rise measurements. We have shown that non-thermal MMW radiation has potential for future use in treatment of yeast related diseases and other targeted biomedical outcomes.  
non-ionizing radiation; millimeter waves; novel biomedical applications; yeast; non-invasive devices +
Footnote †: journal: _Sci. 2021_, 11, 6635. [[https://doi.org/10.3390/app11146635](https://doi.org/10.3390/app11146635)]([https://doi.org/10.3390/app11146635](https://doi.org/10.3390/app11146635))