esa-sceva/satcom-chunk-collection huggingface dataset:
# Influences of Temperature and Substrate Particle Content on Granular Sludge Bed Anaerobic Digestion
## 4 Conclusions  
We carried out anaerobic digestion experiments using a lab-scale UASB reactor on two sets of samples with varying levels of suspended solids and digestion temperature. Our goals were to examine influences of temperature and particulate content on sludge bed anaerobic digestion. Based on the experiments and simulations carried out and the results obtained, we made the following conclusions:  
* An increase in temperature increased the overall biogas production in both high- and low-particulate-content substrates, but the temperature effect was stronger on high-particle-content substrates.
* Disintegration and hydrolysis of suspended solids were significantly enhanced by a temperature increase from 25 to 35 \({}^{\circ}\)C.
* Methane yield was significantly higher for the low-particulate sample (CF) than for the high-particulate sample (RF) at both 25 and 35 \({}^{\circ}\)C.
* Particulate and COD removal efficiencies were improved at a higher temperature. COD\({}_{\text{total}}\) removal efficiency improved from 44% at 25 \({}^{\circ}\)C to 73% at 35 \({}^{\circ}\)C for the high-particulate substrate and from 43% at 25 \({}^{\circ}\)C to 54% at 35 \({}^{\circ}\)C for the low-particulate substrate. COD\({}_{\text{soluble}}\) removal efficiencies were also improved at higher temperatures, but they were approximately similar for both high- and low-particulate substrates.
* Classifying particulates into fast and slow disintegrating and applying temperature-dependent disintegration constant values K\({}_{\text{dis}}\) fit the experimental data better than the traditional ADM1 method of simulation.  
Figure 8: Particulate content in Mode 2 simulation.  
Figure 7: Particulate content in Mode 1 simulation.  
**Author Contributions:** Conceptualization, F.A.T. and R.B.; methodology, F.A.T. and C.D.; software, F.A.T.; validation, F.A.T.; formal analysis, F.A.T.; investigation, F.A.T.; resources, F.A.T.; data curation, all authors; writing--original draft preparation, F.A.T.; writing--review and editing, all authors; visualization, F.A.T.; supervision, R.B. and W.H.B.; project administration, R.B.; funding acquisition, R.B. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was part of a PhD project funded by the European Regional Development Fund, Interreg BioGas2020.  
**Acknowledgments:** The authors would like to thank [PERSON] for his help during sample collection.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 3 Results and Discussion
### Expansion Measurement  
Figure 5 presents expansion data for mortar specimens with different lithium mica slag contents. The results of the test show that mortar specimens without lithium mica slag presented slight shrinkage with increased age. There was significant expansion when the lithium mica slag content was above 10%. As the content of lithium mica slag increased, the expansion of the specimens increased rapidly before 150 days. The expansion of the mortar specimens remained stable after 60 days. When the lithium mica slag content was 10%, the expansion of mortar specimens with 20% and 30% lithium mica slag increased at a slower rate from 28 days to 180 days compared to before 28 days, and the expansion of the mortar specimens remained relatively stable from 180 days to 240 days. When combined with the information reported in Section 3.6, it was observed that mixing lithium mica slag with mortar specimens during early production resulted in an increase in AFt. In a humid environment, the surface of AFt becomes negatively charged. This results in the adsorption of H\({}_{2}\)O by AFt, resulting in the swelling of concrete due to electrostatic attraction. The amount of early AFt also increases with the addition of lithium mica slag. Therefore, when mixed with 30% lithium mica slag, mortar specimens experience the most significant expansion. During the later stages of the hydration reaction, the lithium mica slag particles gradually fill the pore space, resulting in the weakening of the expansion process and gradual stabilization.
# A Survey on Intrusion Detection Systems for Fog and Cloud Computing
## 5 Intrusion Detection in Fog, Edge, and Cloud Computing
### Open-Successes for Fog Computing in the IoT Environment
#### 5.2.3 Uninterrupted Services  
The ability of fog computing to run independently can ensure the interruption of services even under conditions of fluctuating network connectivity to the cloud.
## 2 Related Work  
Information-spreading analysis and the retweet-prediction task have been extensively studied by a number of researchers. There are many different ways to approach the problem of retweet prediction. It can be modelled as a binary or multiclass classification problem in which classes are defined according to the number of retweets, and the model should predict the class of a given tweet, as well as a regression/prediction problem in which the model should predict the number of retweets for a given tweet [23]. There are also some other approaches such as prediction a \(p\) value, which is the probability of a retweet of the given tweet by the given user [24] or users' retweet behaviour prediction [15], retweet time prediction [13] or the prediction of the size of retweet cascade size as in [25]. In the domain of complex networks, this task is usually described as the link prediction in the network of retweeting. From a broader perspective, spreading patterns have been studied in many fields ranging from disease spreading [26; 27] to information spreading on social networks [28].  
In all these approaches, one of the major research questions is related to the identification of the properties that affect the spreading. There are many possible factors that influence information spreading on a social network, ranging from linguistic features,personal information of users such as user profiles, user post history, user following relationships, network properties, etc. There are studies that try to predict retweeting based solely on text properties [29; 30] or based on topic and emotion extracted from text [31]. On the other hand, many authors use only network properties to predict retweeting [32; 33].  
Some recent studies show the advantages of combining features from different, heterogeneous sources: information content, network structure, dynamics of spreading, information metadata, and other properties that can be referred to as heterogeneous data sources [1; 13]. There are still some combinations of heterogeneous data sources worth exploring as predictors of spreading. One such approach is combining multilayer network features with text features proposed in this study. In the following subsections we give an overview of two research domains related to the proposed approach: (i) research studies that combine features from heterogeneous data sources in the task of retweet prediction, and (ii) research of the multilayer network approach.
# False Information Detection via Multimodal Feature Fusion and Multi-Classifier Hybrid Prediction
## 2 Related Work
### Multimodal-Based Approach  
Most of the existing multimodal-based methods use two kinds of modal information, text and picture, to detect false information. [PERSON] [22] et al. used BERT to extract text features and VGG19 to extract image features, which were concatenated as joint features for false information detection. [PERSON] [23] et al. proposed a multimodal fusion model based on multimodal decomposition bilinear pooling. This method can solve the problem that the simple concatenating of different features cannot determine the feature boundary, and the correlation between image feature and text feature cannot be found.  
Although the above studies have proposed different ideas in the fusion module, the input is only two modalities of text and image, ignoring the role of the other modalities. [PERSON] [24] et al. extract sentiment from text while extracting features from text, extract image labels when extracting image features and perform similarity calculation between image labels and text features. Through the processing of the above method, more information can be obtained from the text and images, and the utilization ratio of the information can be increased. However, it only performs feature fusion through simple concatenating, which fails to fully consider the correlation between different modalities. [PERSON] [8] et al. proposed semantically enhanced multimodal false information detection, which obtains image features, graph labels and text in the graph through a convolutional network and updates the text information by adding the text extracted from the picture to the text information. The graph labels, original text information and updated text information are used to extract features through enhanced representation from knowledge integration (ERNIE) [25]. The graph labels and graph feature vectors are updated through an attention mechanism using features extracted from the original text. Finally, the updated text features, the updated graph label features and the updated image features are concatenated as the final joint feature for detection.  
[PERSON] et al. [14] proposed a multimodal fusion model based on attention mechanism. The model first uses Bi-GRU to extract semantic features and uses convolutional recurrent neural network to extract the features of different levels of the picture and then uses the inter-modality attention and the intra-modality attention to fuse the multimodal information to obtain joint features. Finally, the text features, image features and joint features are fused through the attention mechanism to enhance the role of the original information.  
The above research works use simple splicing or attention methods to fuse text features and image features, and they only perform early fusion of the two features, ignoring the effect of later fusion [26]. At the same time, in the early fusion, the influence of noise on the fusion results is not considered [27]. In this paper, the above problems are studied, and a deep-autoencoder-based false information detection method is proposed.
## 4 Results of The Analysis
### Spatial Configuration Analysis Results
#### 4.2.2 Neighborhood-Level Analysis Results
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Location** & **Axis** & **MD (Average)** & **Spatial Configuration** & **Land-use Pattern** \\ \hline The market and its vicinity & Axis 1 & 6.22–787 (7.13) & Long street passing through a highly modernized commercial area, buffer area, and the traditional market & Activation of commercial business functions along the street \\ The boundary of the district & Axis 4 & 6.32–7.99 (6.92) & \begin{tabular}{c} The boundary of the district where \\ bus stops are continuously arranged \\ along the main road \\ \end{tabular} & Operation of public transport on the axis \\ The modernized area & Axis 5 & 6.70–7.77 (7.02) & Inside the modernized area, the \\ area & & & -west road that meets three long north–south streets (axes 1, 3 and 4) \\ The boundary & & & - On the boundary between the \\ between the & & & - modernized area and the buffer area, \\ modernized area & Axis 6 & 6.19–7.61 (6.59) & \begin{tabular}{c} The long east–west street intersecting \\ three north–south axes mentioned \\ above (axes 1, 3 and 4) \\ \end{tabular} & \begin{tabular}{c} Used as a specialized \\ street filled with many \\ street filled with many \\ street filled with many \\ stores selling mainly \\ \end{tabular} \\ and the buffer area & & & - Inside the buffer area, the long \\ The buffer area & Axis 7 & 6.30–7.58 (6.78) & \begin{tabular}{c} Inside the buffer area, the long \\ east–west street intersecting four \\ (axes 1 to 4) \\ \end{tabular} & \begin{tabular}{c} Used as a specialized \\ street filled with many \\ street filled with many \\ stores selling mainly \\ \end{tabular} \\ The buffer area & Axis 8 & 6.33–7.52 (6.79) & \
\begin{tabular}{c} Inside the buffer area, the long \\ east–west street intersecting four \\ north–south axes mentioned above \\ (axes 1 to 4) \\ \end{tabular} &
\begin{tabular}{c} Used as a specialized \\ street filled with many \\ stores selling various \\ types of furniture \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Spatial configurations and land-use patterns at the neighborhood level. Commerce was active along the long north-south street axes (axes 1 to 3) connecting the modern commercial area, the buffer area with old independent stores (usually one or two stories) and accommodations and the traditional market. There were bus stations along the major road at the area's eastern boundary axis near the market (axis 4) that provided public transit along the axis. Yukgeori Market's street network had three north-south street axes (axes 1 to 3) that extended beyond the market and were intersected by four highly integrated east-west street axes (axes 5 to 8).
###### Abstract  
Previous studies have shown mouse antigenotoxic and chemoprerentive potential with the administration of _Citrus paradisi_ juice (GJ). To evaluate another activity, the aim of the present report was to determine the beneficial effect of GJ on male mouse reproductive damage induced by cadmium chloride (CC). Seven groups of mice were intragastrically (IG) administered for 11 days. A control group was administered purified water daily, three groups were administered GJ daily (4.1, 16.6, and 33.2 \(\mu\)L/g), plus a single administration of CC (3 mg/kg) on the fifth day of the assay, another group was treated daily with 33.2 \(\mu\)L/g GJ, and a positive control group was treated with 3 mg/kg of CC on day 5 of the experiment. The results with the high GJ dose on the CC-treated mice showed a mean reduction of 88% in sperm quality endpoints (viability, motility, malformations) and a 94% sperm concentration increase. With the same dose, we also determined an 81% reduction in the DNA breaking potential and in the number of micronucleeli in the spermatids. We also found an 87% decrease in lipoperoxidation and a 68% decrease in protein oxidation with respect to the CC damage, and a strong DPPH scavenging ability. Our results suggest the potential involvement of the GJ antioxidant in the observed effect.  
graefruit; cadmium; reproductive damage; antigenotoxicity; antioxidant; mouse +
Footnote †: journal: Applied sciences  
Article
# Reliable and Energy-Efficient LEO Satellite Communication with IR-HARQ via Power Allocation
## 1 Introduction
### Outline  
The rest of the paper is organized as follows. In Section 2, the system model and the energy efficiency of different IR-HARQ methods are introduced. In Section 3, the NI-FFT method is proposed to calculate the outage probability of the IR-HARQ and the VPA-GA scheme is presented to maximize the energy efficiency. Simulation results are provided in Section 4. Finally, the conclusion is drawn in Section 5.
###### Abstract  
Laser trackers are instruments used to measure the three-dimensional coordinates of objects with high precision. It is necessary to study calibration methods to identify geometric errors of laser trackers so as to compensate for errors and improve measurement accuracy. Among the offsets, tilts, and eccentricity errors in the system, the transit tilt and offset errors play important roles and have an essential effect on the measurement accuracy, which need to be calibrated and compensated for. Current methods for detecting geometric errors between the transit and standing axes are complex and time-consuming. In this paper, a fast and novel calibration method is proposed, which can be easily operated with high precision. Two test rods are coaxially mounted on the ends of the transit axis to extend the hidden transit axis. Then, a telecentric measurement system is used to record the projection images of the test rods and identify the position of the transit axis. The transit offset and tilt errors were thus obtained by comparing the central axis positions of the two test rods before and after the standing axis rotated 180 degrees. Moreover, a numerical analysis method was proposed based on the least square circle fitting method to calibrate the installation eccentricity errors of the test rods. Experimental results verify that the measurement accuracy of the laser tracker can be improved after error compensation using the calibrated transit offset and tilt errors. The measurement error of the laser tracker can be reduced from 161 \(\upmu\)m to about 73 \(\upmu\)m after compensation at a distance of 5 m, while the error can be decreased from 143 \(\upmu\)m to about 108 \(\upmu\)m at a distance of 10 m.  
transit offset error; transit tilt error; laser tracker; calibration method Article
# A Hybrid Neural Network Model for Predicting Bottomhole Pressure in Managed Pressure Drilling
## 5 Trend Analysis  
Overall trend analysis can systematically assess the strength of the proposed model and make sure of how effectively the proposed model captures the physical phenomenon [16]. In this work, synthetic datasets were created, where in the dataset only one input parameter well depth was varied from its minimum to maximum values while all other parameters were kept constant at their average values. Figure 10 shows the effect of increasing well depth with three different drill fluid densities of 1.1, 1.15, and 1.2 g/cm\({}^{3}\). It can be seen that in the horizontal direction, as the well depth is increasing, the BHP has a slowly increasing trend. Vertically, the bigger drilling fluid density makes a higher BHP. At the same time, observing the \(Y\)-axis, it is found that when the well depth reaches 5608 m, the drilling fluid density is changed from 1.1 to 1.2 g/cm\({}^{3}\), and the BHP increases from 58.388 to 58.474 MPa, which proves the robustness of the model. This trend can also be further demonstrated by the momentum equation. To sum up, the trend analysis shows that the CNN-LSTM hybrid model can capture the correct physics behind the data and has a certain stability.
###### Abstract  
Prognostics and Health Management technologies are useful for early fault detection and optimization of reliability in mechanical systems. Reciprocating compressors units are commonly used in industry for gas pressurization and transportation, and the valves in compressors are considered vulnerable parts susceptible to failure. Then, early detection of faults is important for avoiding catastrophic accidents. A feasible approach for fault detection consists in measuring the vibration signal for extracting useful features enabling fault detection and classification. In this research, a test-bed composed by two-stage reciprocating compressor was used for simulating a set of 13 different conditions of combined faults in valves and roller bearings. Three accelerometers were used for collecting the vibration signals for extracting three different types of features. These features were analyzed furthermore by using two random forest models to classifying the different faults. The first set of features was obtained by applying the symbolic dynamics algorithm, which provides the histogram of a set of symbols. This set of symbols was obtained by subdividing a 2D Poincare plot into angular regions and counting the intersection of the phase trajectories on each of regions. The second type of features corresponds to the complex correlation measure which is calculated as the addition of the areas of triangles belonging to a Poincare plot. Additionally, a small set of classical statistical features was also used for comparing their classification abilities to the new set of proposed features. The three sets of features enable highly accurate classification of the set of faults when used with random forest classification models. Notably, the ensemble subspace k-Nearest Neighbors algorithm provides classification accuracies higher than 99%.  
reciprocating compressor; fault detection; valve fault; random forest; Poincare plot; symbolic dynamics; complex correlation measure; statistical features +
Footnote †: journal: Applied Sciences
# Transmitters and Receivers for High Capacity Indoor Optical Wireless Communication
## 3 Receiver for Optical Wireless Communication
### WDM OWC Receiver with a Single Surface Grating Coupler  
#### 3.4.1 Introduction  
The photodiodes used for OWC are limited in their ability to receive only the signal amplitude. In order to overcome this, light collection needs to be decoupled from light detection, as previously mentioned. PICs can facilitate this concept. OWC PIC-based receivers can use surface grating couplers as light collection and waveguide photodiodes for light detection. Additionally, the functionality of PIC-based receivers can be expanded with e.g., WDM demultiplexing, coherent detection, or separation of SDM beams. In this section, we present the combination of the IMOS surface grating coupler with AWGR to receive a WDM signal, which was previously shown in [34]. Wavelength Division Multiplexing can significantly increase the throughput of optical links. The AWGR allows the splitting of wavelengths and processing them separately. OWC WDM can be used in applications which require very high-capacity transmission, e.g., in outdoor OWC between buildings or in top-of-rack switches in data centers.  
In this part of the work, a PIC with surface grating couplers is used together with commercially available AWGR to create a WDM receiver for OWC. The grating couplers used here were designed for fibre-to-chip coupling. Their dimensions are 15 \(\upmu\)m \(\times\) 15 \(\upmu\)m. This is a proof-of-concept demonstration. Further optimization and integration are necessary.
# The Influence of Fatigue Loading on the Durability of the Conveyor Belt
###### Abstract
One of the most important parameters that can be monitored during exploitation is the elongation of the belt. Dynamic condition monitoring of the belt using a neural network model could enable a response from an intelligent belt condition monitoring system [13]. The mechanical resistance of the belt end joint is defined by two components--ultimate tensile strength and fatigue limit. During the tension test, the joint tears without delamination of the layers. On the other hand, during dynamic tension testing, delamination occurs first, i.e., adhesion fracture between the supporting layers occurs first. Therefore, it is important to study the fatigue resistance of adhesion between layers [14]. The fatigue behavior of the joint, i.e., the number of loading cycles until the belt layers delaminate, is affected by the modulus of elasticity of the belt, the ultimate tensile strength of the belt, and the adhesive strength of the belt joint [15]. Testing the belt specimens without a joint, i.e., the belt itself, has been a significant aim of recent research. The elongation of the specimens under the reference loading is influenced by the type of material of the carcass, the number of carcass layers, and the tensile strength of the material of the carcass [16]. The material of the carcass and the number of plies affect the ultimate tensile strength of the belt [17]. During exploitation, the belt loses its mechanical properties. Degradation of tensile strength occurs, flexibility of the belt decreases, while resistance to delamination decreases significantly, in certain cases up to 100% [18]. Innovative methods of monitoring the condition of the belt specimen during experimental tests have been developed. One of the most promising is the method of recording the belt specimen with computer tomography. As a result, a 3D model of the specimen is obtained in which the damage caused during the test can be clearly seen [19]. Through computer tomography, it is possible to monitor the change in the distance between the fibers of the carcass, which indicates damage, and it is possible to spot critical points in time [20].