esa-sceva/satcom-chunk-collection huggingface dataset:
# Hydropower Functional Zoning with Crowdsourced Geospatial Data: A Case Study in Sichuan Province
## 2 Materials and Methods
### Research Methods  
#### 2.3.1 Spatial-Clustering Algorithm  
The goal of spatial clustering was to divide data with similar spatial attributes into one class [40]. Getis-Ord Gi* and Moran's Index are spatial-clustering algorithms that take into account both the spatial relations and the thematic properties.  
Moran's Index is also a global spatial-autocorrelation index that is used to explore the spatial pattern of the study area. The single value was used to reflect the autocorrelation degree of the studied area, and a comparison of the similarity of the observed values at adjacent spatial positions was utilized to measure the global spatial autocorrelation:  
\[I=\frac{n\cdot\sum_{i}^{n}w_{ij}\cdot\Big{(}y_{i}-\overline{y}\Big{)}\Big{(}y _{j}-\overline{y}\Big{)}}{\Big{(}\sum_{i}^{n}\sum_{j}^{n}w_{ij}\Big{)}\cdot \sum_{i}^{n}\Big{(}y_{i}-\overline{y}\Big{)}^{2}} \tag{1}\]  
where \(w_{ij}\) denotes a weight matrix of relations among spatial objects. In this work, the basin locations were chosen to construct the spatial-weight matrix. If sub-basin \(i\) and sub-basin \(j\) are located in the same level 1 sub-basin and adjacent to each other, \(w_{ij}\) = 1; otherwise, \(w_{\bar{y}}\) = 0. The value range of Moran's Index was \([-1,\,1]\). If it is positive, there is a positive correlation between the attribute values of the objects in the spatial relationships. If it is negative, there is a negative correlation between the attribute values. If it is 0, there is no spatial correlation among the attribute values of objects. The \(p\)-value and Z-score are calculated from the statistical test. They are statistically significant when the \(p\)-value is less than 0.05 and the Z-score is greater than 1.96 (or lower than \(-1.96\)).  
Getis-Ord Gi* is a local spatial-autocorrelation index, also called the hotspot analysis method. Getis-Ord Gi* is defined as a local spatial-correlation index:  
\[G_{i}(d)=\frac{\sum_{j}^{n}w_{ij}(d)y_{j}}{\sum_{j}^{n}y_{j}} \tag{2}\]  
Figure 2: Hydropower-station-data preprocessing.  
\[U(G_{i})=\frac{G_{i}-E(G_{i})}{\sqrt{\text{var}(G_{i})}} \tag{3}\]  
When the local Getis-Ord Gi* value is higher than the mathematical expectation and such a difference is statistically significant, a hotspot region is formed.
## Results
### RT-qPCR Analysis of the Expression of Genes Involved in Aflatoxin Biosynthesis  
After the addition of the two test compounds to the _A. flavus_ growth medium, the expression levels of genes that were involved in the AFB\({}_{1}\) biosynthetic pathway and ergosterol were examined using RT-qPCR with nine gene primers (Figures 4 and 5). The examined genes express polyktetide synthase (_aflC_), reductase (_aflD_), nonsolorinic acid (NOR) reductase (_aflE_), P450 monooxygenase (_aflK_), and versicolorin B (VERB) synthase (_aflL_). Another three genes, _yap_, _aflR_, and _aflS_, are transcription factors for aflatoxin biosynthesis, and 18S rRNA was used to normalize the gene expression. A gene, _erg28_, was used to determine the expression of the ergosterol biosynthetic protein 28.  
Figure 3: Effects of \(t\)-cinnamaldehyde on aflatoxin production by _Aspergillus flavus_. AFB\({}_{1}\), aflatoxin B\({}_{1}\); AFB\({}_{2}\), aflatoxin B\({}_{2}\). Different letters above the same column indicate significant differences among the treatments. Data are presented as the mean \(\pm\) SD.  
Figure 2: Effects of 1,8-cineole on aflatoxin production by _Aspergillus flavus_. AFB\({}_{1}\), aflatoxin B\({}_{1}\); AFB\({}_{2}\), aflatoxin B\({}_{2}\). Different letters above the same column indicate significant differences among the treatments. Data are presented as the mean \(\pm\) SD.  
Following treatment with 1,8-cineole, the expression levels of two genes, _aftE_ and _aftL_, were strongly downregulated from the two treatment concentrations (Figure 4). These two genes express NOR-reductase and VERB synthase. Interestingly, the transcription factors _aftR_ and _aftS_ increased slightly or were unchanged, respectively. The expression of other genes (_aftC_, _aftD_, _aftG_, and _aftK_) that are involved in aflatoxin biosynthesis exhibited no change at all of the treatment concentrations. However, _erg28_ expression was about two-fold higher in the 1,8-cineole-treated samples than the control.  
For _t_-cinnamaldehyde, no genes involved in aflatoxin biosynthesis were differentially regulated in comparison to the control, except for the _aftR_ gene, a transcription factor for aflatoxin biosynthesis (Figure 5). At the treatment concentration of 10 ppm, the expression levels of _aftL_, _aftK_, and _aftE_ were upregulated by about 200-fold, 40-fold, and 25-fold, respectively, in the _t_-cinnamaldehyde-treated _A. flavus_ when compared to the control. However, there was no effect on _erg28_ gene expression. Therefore, only the _aftR_ gene was expressed differently, indicating that this gene might play an important role in the reduction of aflatoxin biosynthesis during _t_-cinnamaldehyde treatment.  
Figure 4: Expression of genes (_aftC_, _aftD_, _aftE_, _aftK_, _aftL_, _aftR_, _aftS_, and _yap_) involved in aflatoxin biosynthesis in _Aspergillus flavus_ treated with 1,8-cineole. An ergosterol biosynthetic gene, _erg28_, was comparatively measured after treatment with 1,8-cineole. Different letters above the same column indicate significant differences from the control group (_p_ < 0.05).
## Appendix B Measurements and Modelling Parameters
### Model Parameters Used for Hydrolight-Ecolights  
For most of the experiments, Ecolight's 2-component IOP model was used to generate \(R_{rs}(\lambda)\). The \"clearest natural water\" IOPs were selected for Component 1 (water). IOPs for component 2 (everything else) were precomputed in Matlab from the EAP phytoplankton IOPs and additional \(a_{gd}(\lambda)\) and \(b_{map}(\lambda)\) contributions as required.  
Fluorescence quantum efficiency \(\phi\) was approximated by Chl \(a\) concentration:  
\(<\)10 mg/m\({}^{3}\) = 1%  
10-50 mg/m\({}^{3}\) = 0.6%  
50-100 mg/m\({}^{3}\) = 0.2%  
\(>\)100 mg/m\({}^{3}\) = 0.1%.  
These values are based on MODIS \(\phi_{sat}\) climatologies [101], and measurements [102] to characterise the reduction in \(\phi\) as eutrophication increases.  
A constant set of generalised atmospheric conditions was selected for all experiments. An annual average for solar irradiance and a solar zenith of 30\({}^{\circ}\) was used in lieu of time and location.
## 4 Discussion
When analyzing the results of rheological parameters, a decrease in erythrocyte aggregation parameters, an extension of the half-life of complete aggregation (AI, T1/2), and a decrease in fibrinogen concentration were observed [36]. In a study by [PERSON] et al., the effects of a12-week resistance and aerobic training program were examined in a group of elderly men. It was found that training caused changes in RBC deformability and aggregation [37]. In the study by [PERSON] et al., the influence of long-term physical training on hemorheological parameters was examined in a group of elderly people. Following training, a slight decrease in HCT was observed, while significant reductions in blood viscosity and plasma viscosity were noted. The red blood cell aggregation indices and deformability parameters increased significantly [38]. Rheological blood tests, when considered alongside morphological blood parameters, provide valuable insights into the health status of elderly patients. Any changes in morphological parameters, as well as alterations in blood and plasma viscosity, may indicate underlying health issues. Practical Applications:  
It is worth emphasizing the role of hemorheology in the diagnosis and prevention of diseases such as atherosclerosis, hypertension, diabetes, thrombosis, and hyperlipidemia. The results of our studies show the benefits resulting from changes in morphological and rheological blood parameters when using smovey(r) training. These exercises are safe for elderly people and improve the circulatory system. Introducing regular smovey(r) training sessions to facilities where seniors stay (retirement homes) and which they use as part of their active leisure time (universities of the 3 rd century) would improve their psycho-physical condition and quality of life, which could ultimately contribute to successful aging. Study limitations:  
This study has some limitations that should be considered. One key limitation is the relatively small number of participants in the experimental group, as well as the restriction to elderly individuals. The small sample size may reduce the statistical power. Future studies should include larger and more diverse groups of participants to provide more comprehensive insights into changes in morphological and rheological blood parameters.
## 2 Integration of Quantum Nodes and Systems in the Current Network  
### SDN Controller  
To optimize the transmission of quantum and classical signals over a network and to manage the key relay for longer distances, it is necessary to integrate QKD systems with network control at both the physical and logical levels. This can be achieved by describing the capabilities of QKD devices to the network controller using the YANG modeling language [6; 7; 8; 9; 10]. The purpose of this information model is to simplify the management of QKD resources by implementing an abstraction layer in YANG, which will allow for the efficient creation and usage of QKD-derived keys through the use of a central element, the SDN controller, which has a global view of the network.  
An SDN-enabled QKD node (SD-QKD node) is a collection of one or multiple QKD modules that connect to an SDN controller using standard protocols, allowing it to be remotely and dynamically configured by the controller to create, remove, or update key associations between remote locations, either through a quantum channel or multi-hop routing with trusted nodes.
## 3 Proposed Dataset  
### Image Acquisition  
At present, in the field of pavement distress detection, some researchers have acquired images with cameras or smartphones [17; 48]. Although this approach allows one to acquire pavement images of different environments, with different illumination levels and shooting angles to improve the diversity of the data, it is quite inefficient. Unmanned aerial vehicles (UAVs) equipped with HD cameras have also been used to collect pavement images [49; 50]. In order to obtain clear images of the road surface, the flight altitude and speed of UAVs are limited, so a suitable scenario for their application is an urban street with a low traffic volume. An automatic road measurement vehicle can collect road images at normal traffic flow speeds, and the high-resolution CCD sensor and LED illumination system ensure the uniformity of the captured images, so these have been applied by road authorities in several countries [3].  
The images used in this study were obtained by a road measurement vehicle and collected from the Hulunbuir section of the Suiman Expressway in the Inner Mongolia Autonomous Region, China, as shown in Figure 1. A line scan industrial camera was mounted on the rear of the vehicle. The camera has a CCD sensor resolution of 3024 pixels and scans a road width of 3 m, with 1 pixel representing approximately 1 mm of road. A rotary encoder mounted on the rear axle of the vehicle generates pulses as the wheels move, and this pulse signal triggers the line scan camera to take a picture of the road surface for every 1 mm of vehicle movement. Therefore, 1 mm\({}^{2}\) of the road surface area corresponds to approximately 1 pixel in the image. In the process of road image collection, the vehicle's driving speed is between 80 km/h and 120 km/h, and the camera can photograph the road surface uniformly at different vehicle speeds. In order to ensure that the images captured in different environments are balanced and uniform, a powerful integrated LED set is used  
In this study, we collected 106,792 images with a resolution of 3024 \(\times\) 1889 on a 15 km length of road. As mentioned in [17; 51], we decided to crop the original images to a resolution of 600 \(\times\) 600 pixels, meaning that each image represents a pavement area of approximately 0.36 m\({}^{2}\).
# A Framework for Assessing the Interference from NGSO Satellite Systems to a Radio Astronomy System
## 4 Simulation Results
### Simulation Parameters  
This section analyses the interference of the NGSO satellite constellation with the RAS telescope. The satellite constellation configuration was mainly based on the OneWeb constellation. The satellite constellation is a Walker constellation with an orbital inclination of 90 degrees. The detailed constellation parameters are shown in Table 1, and the RAAN of the first orbit is zero degrees.  
In addition to the NGSO constellation configuration parameters mentioned above, other parameters were needed for the simulation. These included transmission parameters for the NGSO satellites, reception parameters for the RAS telescope, and protection criteria. The details of these parameters can be found in Table 2. The RAS telescope parameters were taken from ITU REC. RA 769 and included the interference thresholds and relevant RAS frequency bands. The 2% allowable probability of exceeding the EPFD threshold is a protection criterion for a single NGSO satellite system, and for all NGSO satellite systems worldwide and other communications systems in adjacent frequencies, the probability of the aggregate EPFD exceeding the EPFD threshold does not exceed 5%. Verifying that the aggregate EPFD protection criteria are met is very difficult and this paper currently only considered the protection criteria for individual NGSO satellite systems.  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Number of Satellites** & **Number of Planes** & **Orbit Inclination (deg)** & **Phase Factor** & **Range of RAAN (deg)** \\ \hline
720 & 18 & 90 & 9 & 0\(\sim\)180 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Configuration of the NGSO constellation.
## 3 Results and Discussion
### Adsorption Study
#### 3.2.4 Impact of Process Temperature  
The impact of temperature on MB removal efficiency was also investigated at different temperatures (25, 35, and 45 \({}^{\circ}\)C). As shown in Figure 5d, the removal of MB increased from 86.4 \(\pm\) 0.05% to 97.0 \(\pm\) 0.05% as the temperature was increased from 25 to 45 \({}^{\circ}\)C. On the other hand, a state of equilibrium was reached within 60 min at 45 \({}^{\circ}\)C as compared to the adsorption process conducted at 25 \({}^{\circ}\)C (240 min). In this research study, maximum MB removal was obtained at the highest temperature of 45 \({}^{\circ}\)C, which was consistent with the result of previously reported studies [42]. The diffusion rate of MB molecules through the internal pores of nZVISLP and the external boundary layer may be slightly increased by increasing the temperature.
## 4 Results and Discussion
### Software Analysis-Optimization and Cost Analysis
#### 4.5.3 Cost Analysis
[61] conducted a study addressing concerns that waste scattered around and left in unsanitary conditions could lead to diseases. They developed an automatic garbage bin monitoring system that alerted authorities via a signal when the bins were full, thus preventing waste from being left out in the open. The system automatically detected the garbage level using an ultrasonic sensor/humidity sensor and sent notifications via SMS to an Android phone. The presence of an automatic detection system in waste facilities to prevent disease highlights the advantages of this study. However, the failure to separate waste at the source through a chute system, the deviation from a sustainable circular economy model, and the collection of mixed waste, which impedes higher-quality recycling and increases labor costs, can lead to unsanitary conditions--a disadvantage of the study. Additionally, the lack of measures to protect the health of both the users and workers during pandemics and disease conditions also stands out as a limitation. The presence of these improvements in the renewed refuse chute system presented in this paper indicates that it fills this gap in the existing literature.
## 2 Materials and Methods
### Statistical Analysis  
Aphid mortality (%) was analyzed using the generalized linear mixed model method, with logit link and binomial distribution: Mortality\({}_{ijk}\ =\ \mu+\textit{treatment}_{i}+\textit{experiment}_{j}\), where \(k\) indicates plant (replicate). Treatment was modelled as a fixed effect and experiment was modelled as a random effect. The estimation method was maximum likelihood with Laplace approximation. Significance of the fixed effect (Treatment) was evaluated using the F-approximate test (\(\alpha\) = 0.05) and means from the different treatments were compared to the control using the Dunnett's test (\(\alpha\) = 0.05). Mortality data obtained from these experiments were also subjected to Kaplan-Meier survival analysis [29] to calculate Average Survival Time (AST) values in days and compared by the Log-rank test.  
The number of nymphs produced each day per aphid was analyzed using a linear mixed model for repeated measures to evaluate main effects and interactions between treatment and day:  
\[\textit{No. of nymphs per aphid}_{ijk}\ =\ \mu+\textit{treatment}_{i}+\textit{day}_{j}+ \textit{treatment}\times\textit{day}_{ij} \tag{2}\]  
Correlation between repeated measures was modelled as an autoregressive covariance matrix. Each replicate (plant), denoted by \(k\), was the experimental unit for repeated measures. Treatment and day were modelled as fixed effects. The factor experiment was initially included in the model as a random effect, but it was not significant and, therefore, was removed from the model and the two experiments were combined in the same analysis. The linear mixed model was estimated using the restricted maximum likelihood (REML) method, and means were compared using the [PERSON]'s test (\(\alpha\) = 0.05) [30].  
Aphid choice (between endophytically-colonized and control plants) was analyzed using a Pearson Chi-square test (\(p\leq\) 0.05) to determine whether the observed frequencies were significantly different to the expected ones (50% : 50%). Data on volatile compounds were analyzed using [PERSON]'s and [PERSON]'s tests to evaluate linear model assumptions (normality and homogeneity of variance) and analysis of variance (ANOVA) applied at a significance level of 0.05. Mixed models were analyzed with proc GLIMMIX-SAS 9.3 [31]; Pearson Chi-square, Kaplan Meier and linear models were analyzed with SPSS 24.0 [32].
## 2 Materials and Methods
### Computer Vision Software for Image Processing  
#### 2.3.1 Application of Qt-Creator/OpenCV for Color Sampling of Californian Black Olives  
Images captured by the camera are streamed to a standard PC and displayed by custom software written in C++/Qt-Creator 4.2.0 (Community) with OpenCV 3.4.3 functions [25,33]. The application allows the operator to define a region of interest (ROI) that excludes problematic areas where olives never appear, and it verifies the correctness of the erosion-dilation sequence--given a user-selected set of parameters--by overlaying the original frame with its binarized version. The same interface controls the electronic subsystem and provides a live visual inspection of the process, distinguishing five scene categories: empty (no olive), normal (properly oriented olive), boat (olive perpendicular to the awl), olive fragment, and double olive.  
Frames can also be downloaded to the hard drive for offline analysis. In the present study, a statistically representative set of 1638 raw images was acquired and later reduced to normal and boat cases in order to analyze only the caliber and orientation distributions.  
The class distribution obtained during the trial is summarized in Figure 6: normal = 96.46%, tilted = 2.44%, boat = 1.10%, and other cases = 0.61% (1 638 olives in total). Other cases--empty frames, double olives, and loose fragments--occur only when the mechanical alignment of the line is severely out of tolerance; in regular production, they are actively avoided by the maintenance team that continuously monitors the machine. Tilted olives (20\({}^{\circ}\)\(\leq\) 0 \(<\) 80\({}^{\circ}\) or 100\({}^{\circ}\)\(\leq\) 0 \(<\) 160\({}^{\circ}\)) fall within the manufacturer's acceptable orientation envelope and therefore do not cause misfeeds. By contrast, boat olives (80\({}^{\circ}\)\(\leq\) 0 \(\leq\) 100\({}^{\circ}\)) appear even with a perfectly adjusted machine and constitute the main source of defective feedings. Consequently, and in order to avoid an extreme class imbalance problem, the subsequent analysis focuses on discriminating the boat class from the rest, as this is the only orientation that degrades product quality under normal operating conditions.  
Figure 5: Image of a boat error case in an oxidized black Gordal olive just before pitting.  
Thus, the final digital inspection consists of 1628 color images of oxidized black Gordal olives in.png format, sized 320 \(\times\) 240 pixels (Figure 7), which are representative for the extrapolation of the results to an infinite population over the system's lifespan, with a Type I error below 5%.