esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 SAT-Hadoop-Processor
### RS Data Integration and Storage: Hadoop Framework  
In this section, we explain how to create a Hadoop cluster for RS data integration and storage. In our work, we worked with the HortonWorks distribution launched in 2011. This version's components are open source and licensed from Apache to adopt the Apache Hadoop platform [31]. HortonWorks is a significant Hadoop contributor, and its economic model is not to sell a license but to support sales and training exclusively. This distribution is most consistent with Apache's Hadoop platform. More configuration details can be found in the following link: [[https://www.techrunn.com/how-to-install-ambari-in-centos-7-using-mysql/](https://www.techrunn.com/how-to-install-ambari-in-centos-7-using-mysql/)]([https://www.techrunn.com/how-to-install-ambari-in-centos-7-using-mysql/](https://www.techrunn.com/how-to-install-ambari-in-centos-7-using-mysql/)) (accessed on 7 November 2021). After the successful installation, deployment, and configuration, we can access the Ambari dashboard via the link IP-Server:8080 containing all the metrics and the cluster's customization tools.  
This study integrated and stored the pre-processed RSBD inside a Distributed File System (DFS) in a scalable way across a distributed Hadoop cluster. DFS is a virtual file system that affords data nodes' heterogeneity in various centers [32]. Thus, the DFS provides a standard interface for applications to manage data on different nodes that use the other OS. DFS can retain a replica of data further than one node; thus, the image is preserved and restored if needed in the event of a fault. DFS is scalable, where the number of compute nodes can be amplified to optimize the processing. Figure 5 shows the general paradigm to integrate and store pre-processed files stored in a CSV file to DSF, HDFS, HBase, and the Hive table.  
The first step makes the DFS and HDFS folder for storing, yielding access to the folder, copying the CSV file to HDFS, before importing the HDFS to HBase based on the primary column and the Column Family (CF), and lastly, generating an external Hive table for the HBase table. Accordingly, the CSV file is stored in Hadoop, which can be requested and retrieved using HiveQL language only and is comparable to the SQL language queries.
# Detecting the Speed Change Intention from EEG Signals:
## 2 Materials and Methods
### Equipment  
For the EEG data recording, a 32 electrodes system actiChamp (Brain Products GmbH, Germany) was used (see Figure 1). Signals were transmitted wirelessly by a Move transmitter to the actiHamp. The electrodes registered EEG activity through 27 noninvasive active electrodes following the international 10-10 system distribution (F3, FZ,FC1, FCZ, C1, CZ, CP1, CPZ, FC5, FC3, C5, C5, CP5, CP3, P3, PZ, F4, FC2, FC4, FC6, C2, C4, CP2, CP4, C6, CP6, P4). One of the electrodes was placed on right ear lobe for reference and an additional electrode acted as ground on the left ear lobe. The other 4 electrodes were placed to record electrooculography (EOG) activity in bipolar configuration (HR, HL, VU, VD). A medical rack was placed on the head to mitigate electrode and wire oscillation due to motion. Signals were registered at 500 Hz. Seven inertial measurement units (IMUs) (Tech MCS V3, Technaid, Spain) were placed for registering the walking parameters at 50 Hz sampling (Figure 1). Four of them, placed on shins and foots, were used for processing the actual speed change moment.  
For the closed-loop experiment, an H3 exoskeleton (Technaid, Spain) was used to assist the user in the speed change intention.
# Bridge Expansion Joint in Road Transition Curve: Effects Assessment on Heavy Vehicles
## 3 Methodology and Case of Study
### In Situ Test and Equipment  
The following tests were performed on the highway section including the joint:  
1. Precision geometric-topographic measurements, along with about 500 m-long branch: The survey was made using a precision theodolite (total station) and a rod, assuming the carriageway markings as the edges of the surveying area. The coordinate reference system was relative; just the elevations were linked to the absolute system. In the area closest to the joint, a \(1\times 1\) m mesh size was considered, while in the other distant zones, 3 m \(\times\) 3 m and 10 m \(\times\) 10 m meshes were created. This discretization allowed performing the global layout of the platform and, particularly, the carriageway markings and the road edges.
2. Evaluation of dynamic action due to the joint, with accelerometers installed on a heavy vehicle test: The measured accelerations were analyzed in the time and frequency domains. In particular, the equipment used was composed of: * Three-axle heavy vehicle, with an overall empty load equal to 16.04 t (P1 = 3.208 t; P2 = P3 = 6.416 t; see Figure 5); * Three concrete blocks whose weights were, respectively, 1.82 (C1), 2.04 (C2) and 2.18 t (C3); * Seven piezoelectric accelerometers: 4 accelerometers with a bottom scale \(\pm\)50 g (Type A) and 3 with a minimum full-scale range of \(\pm\)20 g (Type B). The Type B accelerometers were located on the right end of the axles connected to the vehicle frame, while three of the four Type A accelerometers were placed one on each vehicle axle. The last Type A accelerometer was located on the left side of the front axle to control the possible asymmetry of the transversal acceleration distribution.  
Figure 4: Pavement condition of the area surrounding the BEJ.  
Inside the vehicle cab, a signal control exchange and a PC were located to record and verify collected data and to re-calibrate the equipment if necessary.  
Four different loading conditions were considered to examine the phenomenon. They represent various heavy vehicle configurations (Table 2) and various dynamic increments, because the phenomenon is sensitive to both the speed and load condition of heavy vehicles, as reported by [PERSON] et al. [34]. The considered speed and load combinations gave to the BEJ energy values comparable to those reached on the structure under real service conditions.
## 2 Materials and Methods  
### 2.1 Linear Energy (\(y\))  
To describe radiation effects in subcellular structures (like DNA, nucleosomes, or chromosomes), microdosimetric quantities must be used, since they consider the finite range of secondary ejected electrons and the energy-loss straggling effect [32]. A widely used microdosimetric quantity to characterize radiation quality is the lineal energy (\(y\)), which is defined as the ratio of the imparted energy in a volume from a single event (\(\varepsilon_{1}\)(i.e. from the primary particle and all its secondary particles) by the mean chord length (\(\bar{l}\)) of that volume. Due to the stochastic nature of energy deposition, biophysical RBE models typically use the fluence-averaged lineal energy (\(y_{\text{F}}\)) and the dose-averaged lineal energy (\(y_{\text{D}}\)) given by  
\[y_{\text{F}}=\int_{0}^{+\infty}y\,f(y)\ dy, \tag{1}\]  
\[y_{\text{D}}=\frac{\int_{0}^{+\infty}y^{2}\ f(y)dy}{\int_{0}^{+\infty}y\ f(y) \ dy}=\frac{1}{y_{F}}\int_{0}^{+\infty}y^{2}\ f(y)dy, \tag{2}\]  
where \(f(y)\) is the probability distribution of \(y\).
# Arsenic: A Review on a Great Health Issue Worldwide
## 7 Arsenic Epigenetic Modifications
The authors found a negative correlation between AS3 MT and miR-548c-3p, as well as between the expression of miR-548c-3p and many relative mRNAs. AS3 MT and miR-548c-3p may regulate arsenic methylation in arsenic metabolism. DNA methylation pattern in mammals is the most epigenetic modification studied in relation to arsenic exposure. DNA methylation of cytosine-rich region, known as CpG dinucleotide islands, is a covalent addition of a methyl group to cytosine to form 5-methylcytosine (5-McC). CpG islands can be found in the promoter region of about half of human genes [73]. Methylation of CpG cytosine is allowed by DNA methyltransferase (DNMT) in the presence of SAM (S-adenosyl methionine) as a methyl donor. Actually, five members of DNMT family are known in mammals (DNMT1, DNMT2, DNMT3a, DNMT3b, and DNMT3L); but mammal methylation is mediated only by DNMT1, DNMT3a, and DNMT3b [74]. Arsenic can reduce the activity and the expression of DNMT and the availability of SAM in the methylation of CpG. Literature studies have shown arsenic methylation levels of DNA and several cancer gene promoters both in in vitro cell cultures and in vivo people exposed to arsenic. Gene silencing by CpG methylation directly affects the affinity of transcription factors for binding site of their DNA. [PERSON] and [PERSON] [75] reported that in vivo or in vitro both hypo- and hyper-methylation at various genetic loci are associated with arsenic exposure. Moreover, both DNA hypo- and hyper-methylation in the promoter region of tumor suppression genes are often associated with carcinogenesis and cancer. [PERSON] et al. (2013) [76] showed that arsenic exposure during gestation develops congenital malfunctions and disease consequences including cancer. The authors identified DNA methylation of cord blood-derived DNA from 134 infants (New Hampshire, England) exposed to low levels of arsenic, and methylation to individual CpG loci. Their studies demonstrated that, among 44 CpG islands, 75% of them showed higher methylation levels in infants exposed to high arsenic compared to that exposed to low arsenic. It must also be remembered that sex-specific DNA methylation pattern after arsenic exposure have been studied. [PERSON] et al. (2012) [77] demonstrated that in a prenatally exposed population of Bangladesh exposed to arsenic in drinking water (up to 660 ug/L), global CpG methylation decreased in females and increased in males. [PERSON] et al. (2015) [78] searched the effect of arsenic (up to 300 ug/L in drinking water) on global DNA methylation in an adult population of Bangladesh. Results of the authors indicated that there was no association between arsenic exposure and DNA methylation in females, while in males they found a positively association between arsenic and global DNA methylation.
# Synchronization and Application of a Novel Hyperchaotic System Based on Adaptive Observers
###### Abstract  
This paper explores the synchronization and implementation of a novel hyperchaotic system using an adaptive observer. Hyperchaotic systems, known for possessing a greater number of positive Lyapunov exponents compared to chaotic systems, present unique challenges and opportunities in control and synchronization. In this study, we introduce a novel hyperchaotic system, thoroughly examining its dynamic properties and conducting a comprehensive phase space analysis. The proposed hyperchaotic system undergoes validation through circuit simulation to confirm its behavior. Introducing an adaptive observer synchronization technique, we successfully synchronize the dynamics of the novel hyperchaotic system with an identical counterpart. Importantly, we extend the application of this synchronization method to the domain of secure communication, showcasing its practical usage. Simulation outcomes validate the effectiveness of our methodology, demonstrating favorable results in the realm of adaptive observer-based synchronization. This research contributes significantly to the understanding and application of hyperchaotic systems, offering insights into both the theoretical aspects and practical implementation. Our findings suggest potential advancements in the field of chaotic systems, particularly in their applications within secure communication systems. By presenting motivations, methods, results, conclusions and the significance of our work in a more appealing manner, we aim to engage readers and highlight the innovative contributions of this study.  
hyperchaotic systems; adaptive observers; synchronization; secure communication +
Footnote †: journal: Applied Sciences
_Algorithms_**2014**, \(7\), 295-327; doi:10.3390/a7030295  
_algorithms_  
**ISSN 1999-4893**  
www.mdpi.com/journal/algorithms  
_Article_  
Solving the Examination Timetabling Problem in GPUs  
**[PERSON] 1,*, [PERSON] 1, [PERSON] 2, [PERSON] 3 and [PERSON] 1**  
1 Computer Systems Laboratory, Department of Electrical and Computer Engineering,  
University of Patras, GR-26504 Patras, Greece; E-Mails: [EMAIL_ADDRESS] (G.G.); [EMAIL_ADDRESS] (E.H.)  
2 Technological Educational Institute of Epirus, GR-48100 Preveza, Greece; E-Mail: [EMAIL_ADDRESS]  
3 Technological Educational Institute of Western Greece, GR-30020 Antirio, Greece; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +30-2610-962436.  
_Received: 27 March 2014; in revised form: 22 May 2014 / Accepted: 12 June 2014 / Published: 3 July 2014_  
**Abstract:** The examination timetabling problem belongs to the class of combinatorial optimization problems and is of great importance for every University. In this paper, a hybrid evolutionary algorithm running on a GPU is employed to solve the examination timetabling problem. The hybrid evolutionary algorithm proposed has a genetic algorithm component and a greedy steepest descent component. The GPU computational capabilities allow the use of very large population sizes, leading to a more thorough exploration of the problem solution space. The GPU implementation, depending on the size of the problem, is up to twenty six times faster than the identical single-threaded CPU implementation of the algorithm. The algorithm is evaluated with the well known Toronto datasets and compares well with the best results found in the bibliography. Moreover, the selection of the encoding of the chromosomes and the tournament selection size as the population grows are examined and optimized. The compressed sparse row format is used for the conflict matrix and was proven essential to the process, since most of the datasets have a small conflict density, which translates into an extremely sparse matrix.  
**Keywords:** evolutionary algorithms; examination timetabling problem; GPU computing; CUDA
# A Novel STDM Watermarking Using Visual Saliency-Based JND Model
## 4 STDM Watermarking Using Visual Saliency-Based JND Model
### Watermark Detection Procedure  
Watermarked images are likely to be subjected to some signal processing attacks during propagation such as salt and pepper noise, Gaussian noise, and JPEG compression. At the detection, the specific steps of the watermark extraction process are as follows:  
1. Calculate the saliency value of each pixel in the carrier image, according to Equations (13)-(17), and binarize the gray scale image according to the threshold to obtain a region of \"saliency\" area and \"non-saliency\" area of the image.
2. Divide the carrier image into eight by eight blocks and perform DCT transform to determine the DCT coefficients. The coefficients are scanned by zig-zag arrangement. Then select the four to ten DCT coefficients (in zig-zag-scanned order after the eight by eight block DCT on each image) to form a single vector which denoted as the host vector \(y\).
3. The JND coefficients are calculated according to Equation (4). According to step (1), the JND coefficients belonging to the \"saliency\" or the \"non-saliency\" area are multiplied by the different modulation factors to obtain the coefficients and form the visual redundancy vector \(s^{\prime}\).
4. The host vector \(x\) and the perceptual slack vector \(s^{\prime}\) are projected onto the given projection vector \(u\), which is set as the \(KEY\) to generate the projections \(x^{\prime}_{u}\) and \(s^{\prime}_{u}\). Then we can obtain the quantization step size \(\Delta\) via \(s^{\prime}_{u}\), which can be multiplied by the embedding strength in practice.
5. Use the STDM detector to extract the watermark message \(m^{\prime}\) according to Equation (3).
## 4 Discussion
### Manufacturing  
The only reported socket manufacturing process was molding, and the anthropometric measurement processes were molding (50%), molding combined with manual anthropometric measurements (41.67%) and 3D scanning (8.33%). These results evidence that, although 3D-printed prosthetics have emerged in recent years, the method of applying 3D scanning to take morphology measurements is still in its early implementation and development stages for upper limb prosthetics. The observed low 3D scanning rates could be correlated with the reported manufacturing processes, which were only molding-based. The importance of 3D scanning techniques is particularly evident when conceiving 3D-printed prosthetics because the data that are derived from scanning are integrated into the CAD/CAM design and manufacturing workflow.  
Of all the materials in contact with the residual limb, 50% were reported to be rigid polymers. This is a very high rate given all the dermatologic problems caused by sockets [(46; 44; 45; 6)]. Apart from this, it is worth noting the low score obtained when assessing aspect M4 (almost no fit adjustments required after the final shape; Figure 5) and the considerable importance that the participants attached to it (Figures 12 and 13). These results are consistent with other works in the literature, in which users reported multiple adjustments regarding their sockets' fit [(13)].  
All of these results reinforce the novelty that introducing new manufacturing methods based on 3D scanning and 3D printing would imply by not only allowing for a fast, precise and non-invasive anthropometric measurement system, but also a low-cost manufacturing method for individuals who cannot afford conventional prosthetics and their derived costs by offering them an alternative tool to improve their personal independence. Moreover, given the problems that rigid materials which come into contact with residual limbs can generate, it should be noted that one of the advantages of the latest advances in 3D printingis the possibility of employing flexible and rigid materials. The popularity of soft materials is growing in 3D-printed prosthetics thanks to their flexibility and shock absorption. They better adapt to the body's contours, which lowers the risk of irritation and pressure sores. However, rigid materials play a crucial role in prosthetic design by serving as mechanical supports and providing structural integrity. Therefore, a suitable solution for a 3D-printed socket design may consist of a rigid shell with an inner layer of soft material.
## 5 Test Experiments
### Calibration Uncertainty
#### 5.4.2 Transit Tilt Error Calibration Uncertainty  
The standard uncertainty evaluated as type A was obtained from a series of measurements of the offset (_MN_) on the measurement repeatability. Based on a set of measurements with \(n=3\), the type A uncertainty \(u_{1}\) was calculated as \(u_{1}=0.001/\sqrt{3}=0.0006\) mm. The type A uncertainty \(u_{2}\) was obtained from a series of measurements of the installation eccentricity error of test rod A. Based on a set of measurements with \(n=3\), the type A uncertainty \(u_{3}\) was obtained from a series of measurements of the installation eccentricity error of test rod B. Based on a set of measurements with \(n=3\), the type A uncertainty \(u_{3}\) was calculated as \(u_{3}=0.001/\sqrt{3}=0.0005\) mm. The type B uncertainty \(u_{4}\) is the error of telecentric measurement system; the corresponding standard uncertainty was determined as \(u_{4}=0.001/\sqrt{3}=0.0006\) mm. The type B uncertainty \(u_{5}\) reflects the changes in the environmental temperature; the error caused by environmental temperature was \(\pm 1\%\), which is considered as uniformly distributed. The corresponding standard uncertainty was determined as \(u_{5}=0.01/\sqrt{3}=0.006\) mm. Therefore, the combined standard uncertainty was \(u_{c}=arctan(\sqrt{u_{1}^{2}+u_{2}^{2}+u_{3}^{2}+u_{4}^{2}+u_{5}^{2}}/502)= arctan(\sqrt{0.0006^{2}+0.0005^{2}+0.0005^{2}+0.0006^{2}+0.0006^{2}}/502)=0.044\) arcseconds. So, the uncertainty evaluation of the transit offset calibration method was 0.044 arcseconds.
# Characteristics of 2.45 GHz Surface-Wave-Sustained Argon Discharge for Bio-Medical Applications
## 3 Results
### Effects of the Dielectric Tube Inner Diameter on the Plasma Column Size
The highest concentration of Ar\({}_{2}\)\({}^{+}\) ion is in the tube with the smaller inner diameter (8 mm/2 mm). This can be the reason for the fast formation of the second filament at a lower wave power in this tube, but further investigations would be needed to explain it. Figure 6: (**a**) Fast camera images of the plasma torch in the three tubes. (**b**) Experimental results for the plasma torch length in the three tubes. (**c**) Appearance of a second filament at higher wave power for 8 mm/3 mm tube. These experimental results show also that even at a low wave power, the length of the plasma torches in all tubes is enough for the direct treatment of the samples. The important question for bio-medical applications is what the temperature at the position of the samples is so that thermal damage is avoided.
## 2 Results
### OrtT Lyses Cells through Membrane Damage and Reduces ATP  
Like GhoT, OrtT is predicted to be a hydrophobic inner-membrane protein with two transmembrane domains (residue 6 to 26 and 34 to 54) [40]. To investigate the structural resemblance of OrtT with GhoT, we modelled both proteins using PHYRE2 [41]. The modelled monomeric proteins have high structural identity as can be seen from the superimposed protein structures in Figure 2A. Previously, introduction of the F38R substitution abolished GhoT toxicity [42]; hence, since the Phe38 residue is conserved in both proteins (boxed nt, Figure 1A), we tested whether Phe38 bears the same functional-significance for OrtT toxin by constructing pCA24N-_ortT_F38R. As shown in Figure 2B, OrtT-mediated toxicity was reduced for OrtTF38R. These results suggest that OrtT is likely a membrane protein that functions in a manner similar to GhoT. Note that, we tried to visualize OrtTF38R via Western blot analysis but like GhoT [42], this toxic protein could not be detected (Figure S1).  
Production of GhoT leads to cell lysis [18]. Hence, to characterize toxin OrtT, we tested if ectopic expression of _ortT_ lyses cells and found that production of OrtT in wild-type cells caused 99.99% of the bacterial population to undergo cellular lysis within two hours after induction (Figure 2C). This suggests OrtT damages the cell membrane.  
To confirm that OrtT causes membrane damage, we performed transmission electron microscopy (TEM) with wild-type cells producing toxin OrtT and compared them to wild-type cells with an empty vector. We found there was a dramatic change in cell morphology due to OrtT production; the two most common phenomena were (i) nucleoid condensation and enlargement of the periplasmic space; and (ii) cellular component leakage leading to almost a hollow cytoplasmic space (top two panels, Figure 2D). In contrast, cells with the empty vector looked healthy with an intact periplasm and cytoplasm.  
Next, we tested whether OrtT-mediated membrane damage leads to loss of cellular ATP level by measuring intracellular ATP concentration. Production of OrtT caused a 27-fold loss in ATP level when compared with the empty vector strain (Figure 2E). This suggests that proton-motive force (PMF) is disrupted in OrtT producing cells. Collectively, these results corroborate that OrtT is most likely a membrane protein that leads to cell lysis via membrane damage and depletion of intracellular ATP pool.