esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions  
Understanding the relationship between fluid contacts and pore pressure is crucial for hydrocarbon recovery and drilling operations. Overpressure and normal pressures affect the fluid contacts in the reservoir. The results showed a close correlation between fluid contact and pore pressure. The fluid contacts that are associated with overpressures are gas-water and oil-water contacts. Pore pressure seemed to increase where gas-water and oil-water contacts were detected. An increase in pore pressure can cause a displacement of fluid contacts, either vertically or laterally. Conversely, pore pressures decreased where gas-oil contact was detected. Decreased pore pressure results from gas expansion and increased gas volume.  
This study illustrates the significance of an integrated approach to predicting fluid contacts and pore pressure within reservoirs using geophysical well logs and RFT. The RFT and geophysical well logs offered useful information and assisted in improving the accuracy of pore pressure and identifying contacts by assessing their behaviors. Therefore, it can be concluded that integrating RFT and Eaton's method of developing a depth-dependent NCT using sonic and resistivity logs can aid in predicting pore pressure based on the type of fluid contact.  
Conceptualization, P.P.S. and M.M.; methodology, P.P.S.; software, P.P.S.; validation, P.P.S., M.M. and M.O.; formal analysis, P.P.S.; investigation, P.P.S.; resources, P.P.S. and M.M.; data curation, P.P.S.; writing--original draft preparation, P.P.S.; writing--review and editing, P.P.S. and M.M.; visualization, M.M. and M.O.; supervision, M.M. and M.O.; project administration, P.P.S., M.M. and M.O. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data are not publicly available due to the confidentiality agreement signed between the authors and the Petroleum Agency of South Africa.  
The Petroleum Agency of South Africa (PASA) is acknowledged for providing the data. Geoactive Limited is also greatly appreciated for providing Interactive Petrophysics (IP) software support.  
The authors declare no conflicts of interest.
## 2 Results
### Evaluation of Each VOC for Direct-Contact Nematicidal Activity against Meliologzyme hapla  
In order to verify the direct-contact nematicidal activity of the GJ-7 strain VOCs against _M. hapla_, the pure VOCs identified through GC-MS analysis were purchased to test the contact nematicidal activity against J2s and the direct-contact inhibition activity against egg hatching. The results showed that the LC90 values of 3-methyl-2-pentanone, 5-methyl-2-hexanone, and 2,5-dimethylpyrazine was 10-20 \(\mu\)L/mL at 24 h, and the LC90 values of 2-heptanone and 6-methyl-2-heptanone were 6.2 and 6.4 \(\mu\)L/mL, respectively. In addition, 3-methyl-1-butanol was the most active, displaying LC90 values of 2.8 \(\mu\)L/mL at 24 h (Table 2).  
Similarly, after continuous observation, the effects of each of the VOCs on egg hatching were recorded after 7 days of treatment. When the dilution concentration was 10 \(\mu\)L/mL, the hatching rate of eggs in the 3-methyl-2-pentanone treatment group was 42.08%, which represented no significant difference compared with the 51.42% of the control group (10 \(\mu\)L/mL DMSO). The hatching rate of the eggs treated with 3-methyl-1-butanol, 5-methyl-2-hexanone, 2-heptanone, 2,5-dimethylpyrazine and 6-methyl-2-heptanone was significantly lower than that of the control group, indicating that these five VOCs had a level of direct-contact inhibitory activity on the egg hatching of _M. hapla_. Remarkably, 2-heptanone, 2,5-dimethylpyrazine, and 6-methyl-2-heptanone had an inhibitory effect on egg hatching 2.5-7.5 times greater than other VOCs, showing strong egg hatching inhibition (Figure 3).  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Compound**} & **24 h** & **48 h** \\ \cline{2-3}  & **LC90 (\(\mu\)L/mL)** & **LC90 (\(\mu\)L/mL)** \\ \hline
3-methyl-1-butanol & 2.8 & 2.7 \\
3-methyl-2-pentanone & 20 & 18 \\
5-methyl-2-hexanone & 20 & 17 \\
2-heptanone & 6.2 & 6.1 \\
2,5-dimethylpyrazine & 12.7 & 10.8 \\
6-methyl-2-heptanone & 6.4 & 6.3 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Nematicidal activity of six commercial VOCs against second stage juveniles.  
Figure 3: Effects of direct contact of six VOCs on the egg hatching of _M. hapla_ after 7 days. Different lowercase letters indicate significant differences among treatments (\(p<0.05\)); bars indicate the standard error of the means (\(n=3\)).
## 2 The CNES PPP-WIZARD Demonstrator
### The User Side of the Demonstrator
#### 2.3.3 The PPP-Snapshot Concept  
On the user side, the OEUFS method has been implemented in the so-called PPP-Snapshot mode, taking its name from the fact that the ambiguity is reinitialized at each epoch and the Kalman filter does not exploit the fact that the carrier-phase ambiguity is constant over a single passage. AR is thus performed at each epoch without any knowledge of the previously resolved integer ambiguity. As shown in [41], the convergence of the receiver position is mainly driven by the number of frequencies used for AR. Hence, the benefit of using this configuration lies in the fact that the long convergence time due to the phase ambiguity parameter estimation in the filter disappears, and there is no need to detect or repair the cycle slips, as they are not estimated at each epoch any more. The other parameters of the Kalman filter, such as the ionosphere elongation, the troposphere delay, or the dynamical model, have to be estimated in the classical way by the filter. The ionospheric elongation can thus be maintained by the filter over the time, even in case of a gap in the measurements. Doing so greatly improves the ability of the Snapshot mode to estimate the ambiguities again without convergence at the end of the measurement gap.  
However, as a main drawback, this method suffers from the difficulty of solving for the narrowlane ambiguity, which leads to a possible degradation of the accuracy. On top of that, the compatible phase combinations are limited to Galileo E6 and Beidou-3 signals. The number of real-time compatible stations at the IGS is limited but increases over time, as seen in Figure 4.  
Figure 3: Instantaneous ambiguity resolution diagram. The optimal combination is to be understood as the extra-widelane combination leading to the smallest noise possible.
# Biological Production of 3-Hydroxpropionic Acid: An Update on the Current Status
## 3 Production of 3 HP from Sugars  
Glucose and other sugars (such as xylose) are another source of renewable raw materials for the cultivation of microorganisms when aiming to produce 3 HP. Commonly used sources of sugar include sucrose from sugar beet and sugar cane, and glucose from the hydrolysis of corn starch. Due to the fact that these sources of sugar can also serve as food and animal feed, the use of sugars from lignocellulosic presents an attractive alternative. Sources of lignocellulosic biomass include agricultural wastes and by-products, forest biomass, energy crops, and municipal waste [43; 44; 45]. The use of lignocellulosic materials as a source of fermentable sugars requires a pretreatment step (to disrupt the rigid structure of lignocellulosic biomass), followed by enzymatic hydrolysis of the insoluble carbohydrates in order to release soluble sugars. Several pretreatment methods have been proposed in the literature, which can be classified as physical, physicochemical, chemical, and biological [46]. The different pretreatment methods have shown varied efficiency against lignocellulosic biomass, with the source of the biomass affecting the chosen pretreatment parameters.  
Regarding the use of sugars (mainly glucose) as carbon source for the production of 3 HP, several different pathways have been proposed. Different research groups have made significant progress in this field by intensively studying some of these pathways. On the other hand, some other predicted pathways have turned out to not be efficient enough when transferred to host microorganisms.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Genes Transfered** & **Microorganism** & **Culture Conditions** & **Concentration** & **Productivity** & **Ref.** \\  & & & **(g/L)** & **(g/L-h)** & **(g/L-h)** & \\ \hline Mutation in the CRE upstream & _L. reuteri_ & Fed-batch bioreactor 3 L with resting cells, 1 L, pH 7, 37 °C, anaerobic, 500 rpm & 10.6 & 1.08 & [23] \\ \hline Mutation in the CRE upstream & _L. reuteri_ & Immobilized cells with fed-batch feeding, 12 mL, 37 °C, anaerobic, 100 rpm & 3.3 & 0.09 & [14] \\ \hline  & & Two-step cultivation: (1) anaerobic fed-batch bioreactor 3 L with _L. reuteri_ and & & & \\ - & _L. reuteri_ and & _G. oxydans_ & pH 5.5, 37 °C, (2) aerobic batch system 3 L with _G. oxydans_ resting cells, 1 L, pH 5.5, 28 °C, 0.33 vvm, 800 rpm & 23.6 & n.a. & [41] \\ \hline _dhuB, gdrAB_, and _puuC_ from _k. pneumoniae_, deletion of _glpk_ & _B. subtilis_ & Flasks with the addition of & & \\ - & & glucose, 37 °C, 200 rpm & 10 & n.a. & [42] \\ \hline  & & n.a.: not available. & & & \\ \end{tabular}
\end{table}
Table 3: Results of 3 HP production from glycerol using other host microorganisms.
## 3 D2 HCP (Distributed Dynamic Host Configuration Protocol)
### Synchronization  
The synchronization is done by monitoring the routing table of the OLSR routing protocol [30]. The addition or departure of a node in the network is detected when OLSR adds a new route to its routing table, or deletes an existing one. By detecting the addition or departure of a node in the network, the _Free_IP_Blocks_ table is updated locally, and without exchanging any messages.  
For this reason, the following rules are obeyed:  
* The responsibility of recovering the IP addresses that a node leaving the network makes available is one that can be attached to the right of the free block. This will not be possible when the block to be collected contains the lowest address of the network. In that case, the node that picks the block up is one that can add to it to the left.
* By dividing the free addresses in two blocks to deliver one of them to a new node that joins the network, the node that acts as server delivers the sub-block, which does not contain its own IP address, to the client.  
When the node departure is detected, its entry must be removed, and an update of the corresponding node's now available IP address must be recorded.  
By detecting the joining of a new node, a new entry is created for it in the table, and the free address block of the node which supplied its IP address will be updated. In order to identify the node who acted as a server, it is simply necessary to find out which node has the IP address of the new node in its free address block.
# Utilizing Duplicate Announcements for BGP Anomaly Detection
## 3 Proposed Methodology  
The collected raw data, which is considered, is downloaded from the update message of the BGP routing protocol. These update messages consist of network prefixes and network layer reachability information. The raw data are collected from RIPE and Route View collection sites [2], which are open-source and standard datasets. The proposed methodology is shown in Figure 2 below.  
As shown in Figure 2, the proposed EMA model, in combination with Autoencoder, is applicable in detecting anomalies in BGP update messages by proposing duplicate announcements as the main implication. We have collected and prepared BGP datasets from RIPE and Route Views, which contain the network prefixes and routing information for in and around various anomaly events, such as the Slammer Worm Stuxnet worm, Helsinki blackouts, and WannaCrypt ransomware attack. In the preprocessing stage, data cleaning, normalization, and feature extraction are carried out, resulting in 37 features extracted that are divided into volume-based (e.g., no. of announcements, no of withdrawals, etc.) and AS-path-based metrics (e.g., edit distance, AS-path length, etc.). Connect the input and output through a T-SMOTE (Temporal-oriented Synthetic Minority Over Sampling Technique) to balance the training data (Synthetic Minority Over-Sampling Technique).  
Smoothing the time-series data and identifying trends containing abnormal behavior is performed using the Exponential Moving Average (EMA).  
Two deep learning models, namely autoencoder and long short-term memory (LSTM), are used for anomaly detection. We build the Autoencoder with three layers of encoding (128, 64, 32 neurons), a bottleneck layer (16 neurons), and a symmetric decoder, where we use activation ReLU and sigmoid activation out, respectively. For comparison purposes, the LSTM model consists of two LSTM layers, each with 64 units, and a dropout rate of 0.2 to mitigate overfitting. Both models are trained using Adam optimizer (learning rate = 0.001) for 30 epochs and a batch size of 32. The details of each block are provided in the following subsections.
## 3 Results and Discussion
### \({}^{210}\)Pb Dating  
The behaviour of \({}^{210}\)Pb over the analysed peat deposit has an almost exponential character with a slight fluctuation of activity in the upper part. The R-square determination coefficient for the entire data series \(ln\) (\({}^{210}\)Pb\({}_{\text{uns}}\)) is 0.96, which is acceptable for the CF dating model (CRS) used by us and indicates an insignificant effect of migration on \({}^{210}\)Pb [64].  
The dating data for the ISO-1 peat column are presented in Figure 5. Based on the fact that below the horizon 22-24 cm excess lead is not detected, the model is limited to a layer of 20 cm, the date of formation of which corresponds to 1896. The age of the horizons below 22 cm is more than 150 years old and beyond the \({}^{210}\)Pb dating method.  
A comparison of data on the distribution of the independent marker of man-made \({}^{241}\)Am indicates the existence of an activity peak in the 12-14 cm horizon, which according  
Figure 5: The plot of \({}^{210}\)Pb chronology of the ISO-1 peat core under the CF (CRS) model.  
to the CF dating model (CRS) corresponds to the age of 1963 (Figure 6), the period of maximum atmospheric \({}^{241}\)Am arrival to the earth's surface [65; 66; 67].  
The consistency of these data indicates the correctness of the chosen model and the adequacy of the dating results in relation to the ISO-1 peat core.  
During the dating of the ISO-1 profile, the linear rate of peat accumulation \(s\) (SAR) was calculated (Figure 7).  
Figure 6: The graphs of total activity concentration (**a**) and unsupported (**b**) \({}^{210}\)Pb, \({}^{241}\)Am (**c**) for the ISO-1 peat column.  
Figure 7: The plot of the linear rate of peat accumulation in the ISO-1 peat core by depth.  
Thus, the linear accumulation rate varies from 0.05 \(\pm\) 0.03 to 0.24 \(\pm\) 0.02 cm/year, the mean value is 0.15 \(\pm\) 0.02 cm/year. At the same time, for the previously studied ISNO-1 core sampled at the site with a natural hydrological regime, \(s\) values varied in a wider range (from 0.09 \(\pm\) 0.02 to 1.3 \(\pm\) 0.05 cm/year), and the average accumulation rate was more than three times higher than 0.48 \(\pm\) 0.08 cm/year. Obviously, this is due to changes in the hydrological regime at the ISO-1 profile sampling site due to drainage, in which there is significantly less accumulation of peat biomass and compaction of the peat.  
The calculated meaning of the atmospheric flux of \({}^{210}\)Pb to the peatland surface was 77 \(\pm\) 4 Bq/m\({}^{2}\cdot\)yr, which is comparable to the above data from the [64,68] and our earlier data for the European subarctic (zone) of Russia for an ISNO core, a value was 69.13 \(\pm\) 10 Bq/m\({}^{2}\cdot\)year [29].
## 5 Performance Evaluation
### Model Validation and System Implication  
The analytical model is validated by MATLAB-based simulation. This simulation tool is selected due to its availability and credibility. In simulation, we consider large-scale path loss model, path loss component, distance, and small-scale Rayleigh fading. To obtain good samples of data, the simulation was run longer to reach the steady state condition to avoid  
Figure 8: Sum throughput of all DUEs vs. transmit power of D2D pairs.  
Figure 9: Sum throughput of all DUEs vs. minimum QoS requirement.  
biased results. For instance, we consider 1000 different seed values to have results with a confidence level of 95%. We create a more realistic simulation scenario with \(-174\) dBm/Hz as noise power spectral density and 7 dB as noise figure. In the proposed DRL model, we consider DUEs instead of training eNBs/SCeNBs which help to make better coordination between network elements. A learning rate of 0.001, a discount rate of 0.9, a greedy rate of 0.1, a training memory size of 2000 MB, and a mini-batch size of 32 are used in the deep reinforcement learning algorithm. The DQN model is trained based on Algorithms 1 and 2.  
Implementing D2D technology in a cellular network is challenging due to its several known issues. First, for a small-sized network where overheads are comparatively low, a centralized approach can be used. No matter what strategies are used, network performance degrades significantly with the increasing number of users as the network grows. In a D2D-enabled cellular HetNet where interference management is a major challenge; the proposed distributed DRL method can be useful to network designers to implement the system in a large-scale network scenario. So, our DRL approach can be used to design the network with desired throughput and QoS requirements for both cellular and D2D users with proper mode selection and controlled interference manner.
## 2 Testing Samples and Experimental Setup
### Experimental Setup  
Electrical and optical characteristics such as operating voltage, lumen output, luminous efficacy, CCT, CRI were measured up to six thousand hours with period of one thousand hour using integrating sphere measurement system with diameter of two meter as shown in Figure 1a. Recently, international commission on illumination (CIE) published the international standard for measurement method of OLED product used in general lighting [16]. All electrical and optical characteristics of OLED panels and luminaires are measured according to this international standard CIE S 025-SP1/E: 2019: Test Method for OLED Luminaires and OLED Light Sources. During the operation OLED samples were in the temperature controlled chamber with temperature of 25 \({}^{\circ}\)C as shown in Figure 1b. In case of OLED luminaire, control gear to supply rated operating voltage was integrated in the luminaire. Thus additional power supply was not necessary to operate the OLED luminaire.
# Classification of OCT Images of the Human Eye Using Mobile Devices
###### Abstract  
The aim of this study was to develop a mobile application for Android devices dedicated to the classification of pathological changes in human eye optical coherence tomography (OCT) B-scans. The classification process is conducted using convolutional neural networks (CNNs). Six models were trained during the study: a simple convolutional neural network with three convolutional layers, VGG16, InceptionV3, Xception, Joint Attention Network + MobileNetV2 and OpticNet-71. All of these models were converted to TensorFlow Lite format to implement them into a mobile application. For this purpose, three models with the best parameters were chosen, taking accuracy, precision, recall, F1-score and confusion matrix into consideration. The Android application designed for the classification of OCT images was developed using the Kotlin programming language within the Android Studio integrated development environment. With the application, classification can be performed on an image chosen from the user's files or an image acquired using the photo-taking function. The results of the classification are displayed for three neural networks, along with the respective classification times for each neural network and the associated image undergoing the classification task. The mobile application has been tested using various smartphones. The testing phase included an evaluation of image classification times and score accuracy, considering factors such as image acquisition method, i.e., camera or gallery.  
OCT; retina; smartphone app; Android Article
## 2 Related Works  
In this section, we refer readers to a few related works that considered the scheduling problem with network coding. Additional literature on the problem formulation and solution are described along the main body of the paper.  
Network coding is a great fit for wireless networks. [PERSON] _et al._[5] study the case of applying network coding in wireless networks in many aspects. These include throughput, reliability, mobility and management. Several key challenges are proposed, as well.  
There are many researchers working on the topic of scheduling in network coding settings. However, most of them focus only on MAC-layer scheduling. The method usually gives \"higher priority\" to coding nodes. [PERSON] _et al._[6, 7, 8, 9] give examples of this kind.  
In addition to MAC-layer scheduling, there are other novel solutions that involve scheduling. [PERSON] and [PERSON] [10] propose an opportunistic scheduling algorithm. The links between the intermediate nodes and receiver nodes are subject to channel fading. When this fading is time-varying, the authors propose an opportunistic network coding scheme to determine how many and which packets are coded. It is shown that such an opportunistic scheme can provide higher throughput than any coding scheme that involves a fixed number of packets. [PERSON] _et al._[11] discuss the optimal physical-layer transmission rate in the MIT _Roofnet_platform. The basic idea is that a lower rate gives rise to a longer transmission range or a higher delivery ratio. Furthermore, the distances from the intermediate node to the two recipients may not be the same. Therefore, their delivery ratios would be different. In 802.11b, if 5.5 Mbps or 11 Mbps is used, the total expected coded transmission time (ECT) can be different.  
Most network-coding schemes are agnostic about the PHYand MAC layer. They assume a greedy algorithm to enforce network coding. However, [PERSON] and [PERSON] [12] advocate that exploiting every opportunity to enforce network coding may downgrade the overall throughput of the system. The statement is demonstrated using a scenario where interference is incorporated into the analysis. Hence, a specially tailored MAC-layer scheduling algorithm is proposed in order to achieve the expected throughput gain.  
[PERSON] and [PERSON] [13] consider the joint scheduling problem for MIMO and network coding (MIMO-NC) in wireless networks. A network in which each node is equipped with two antennas is analyzed. In order to achieve higher throughput, the authors propose a packet scheduling algorithm, which in essence matches all source-destination flows into pairs. When a pair is discovered, MIMO-NC is applied to reduce the number of transmissions. However, this approach requires the full knowledge of the network and traffic patterns. In addition, it is highly dependent on the traffic pattern. When the prescribed pair is not available, the power of MIMO is then wasted.