esa-sceva/satcom-chunk-collection huggingface dataset:
# Femtosecond Laser-Inscripted Direct Ultrafast Fabrication of a DNA Distributor Using Microfluidics
###### Abstract  
A femtosecond laser can be used for single or multiple writing processes to create sub 10-\(\upmu\)m lines or holes directly without the use of masks. In this study, we characterized the depth and width of micro-channels created by femtosecond laser micro-scribing in polydimethylsiloxane (PDMS) under various energy doses (1%, 5%, 10%, 15% and 20%) and laser beam passes (5, 10 and 15). Based on a microfluidic simulation in a bio-application, a DNA distributor was designed and fabricated based on an energy dose of 5% and a laser beam pass of 5. The simulated depth and width of the micro-channels was 3.58 and 5.27 \(\upmu\)m, respectively. The depth and width of the micro-channels were linearly proportional to the energy dose and the number of laser beam passes. In a DNA distribution experiment, a brighter fluorescent intensity for YOYO-1 Iodide with DNA was observed in the middle channels with longer DNA. In addition, the velocity was the lowest as estimated in the computational simulation. The polymer processability of the femtosecond laser and the bio-applicability of the DNA distributor were successfully confirmed. Therefore, a promising technique for the maskless fabrication of sub 10-\(\upmu\)m bio-microfluidic channels was demonstrated.  
femtosecond laser micro-scribing; polydimethylsiloxane; DNA distribution; microfluidic channels +
Footnote †: journal: Applied Sciences
## 4 Proposed Method and Procedures
### Machine Learning and Classification  
In the classification step, we applied three of the well-known classifiers to evaluate the classification performance of epileptic or non-epileptic signals for epileptic seizure detection using EEG signals. SVM, KNN, and ANN classifiers were used in this study. For  
Figure 10: Power Spectral for Epileptic Signal.  
the SVM, we used a one-versus-all multiclass SVM combined with a linear kernel function. For KNN, the Mahalanobis distance metric was applied with 1, 2, 3, 4, and 5 \(k\) neighbors, and we achieved the best results when \(k\) was equal to 5. Finally, the ANN classification using a feed-forward neural network with two layers and one hidden layer that had ten neurons was also applied. In the output layer of ANN, the number of neurons was equal to the number of classes. After the careful random division of data, experiments with different training and testing percentages of 50% and 50%, 60% and 40%, 70% and 30%, and 80% and 20%, respectively, were performed. Each percentage was trained and tested randomly ten times with each classifier, and then the average accuracy was recorded.
# Recent Progress on Graphene-Functionalized Metasurfaces for Tunable Phase and Polarization Control
## 4 Polarization Modulation in Graphene Metasurfaces
### Graphene-Based Quarter-Wave Plate
Furthermore, the efficiency is very high (\(\sim\)70%) by working in reflection mode.
# Optimization of a Permanent Magnet Synchronous Motor for e-Mobility Using Metamodels
## 2 Torque Ripple  
Torque ripple is caused by a change in the magnetic energy between the permanent magnets of the rotor and slots of the stator of a PMSM [19]. When the magnetic energy changes depending on the relative position of the magnetic pole and slot in a rotating motor, a reluctance torque is generated by the slot structure; this results in a torque ripple, which causes noise and vibrations in traction motors. As such, the torque ripples must be minimized. Moreover, traction motors used in electric vehicles should have torque ripple values of < 10% [20].
## 3 Normalization Algorithms
### Pseudo\(-\)Invariant Polygon Features\(-\)Based Normalization  
Due to spatial resolution differences, the true geometrical position of each pixel covers a unique range. This may result in very different data for the same locations from different sensors. To mitigate this effect, we expanded pseudo\(-\)invariant features from polygon points using the mean reflectance of selected areas to replace reflectance from selected pixels. This has the effect of lowering the geometrical error, thus, reducing the uncertainty that may be caused by non\(-\)corresponding points.
# Experimental Study of the Dynamic Characteristics of PVA-Amended Expansive Soils
## 3 Analysis of Test Results  
### Analysis of the Static Triaxial Test Results  
#### 3.1.1 Stress-Strain Curve  
The stress-strain relationship for soil can be described by a mathematical expression reflecting the mechanical properties of the material, which, for triaxial stress, is mainly expressed as the relationship between the bias stress and axial strain applied to the specimen. The curves are divided into two types: (1) The strain shows a decreasing tendency with increasing stress (the curves have a peak), which is referred to as strain softening. (2) The strain exhibits an increasing tendency with increasing stress; this is referred to as strain hardening. Figure 2 shows the curves for bias stress (\(\sigma_{1}\)-\(\sigma_{3}\)) versus axial strain (\(\varepsilon_{1}\)) for the soil under different confining pressures, which reflects the nature of strain hardening.  
As shown in Figure 2, under three different confining pressures, the effect of PVA on the improvement of expansive soil significantly improved, and with the same PVA dosage, the greater the confining pressure, the greater the bias stress that the improved soil can withstand. This is because under the same PVA content and with increasing confining pressure, the consolidation pressure increases, the soil particles are extruded and subsequently increased, and the relative sliding becomes increasingly difficult. Under the same stress conditions, the deformation produced decreases. When the peripheral pressure is the same, the soil specimen can withstand the smallest bias stress. Additionally, with increasing PVA content, the specimen bias stress trend first increases after a slight decrease in the PVA content of 3% for the improved soil to reach the peak value. PVA dissolved in water forms a viscous white gelatinous material, and its combination with soil particles facilitates the formation of a cemented material and a filling of the internal pores in the soil samples to enhance the cohesion of soil particles so that the load-bearing capacity of the soil increases. On the other hand, PVA is hygroscopic; when its dosage reaches 4%, more water in the soil sample is absorbed by PVA, so there is a lack of sufficient water molecules between the expansive soil particles, which is the state of nonoptimal water content. Therefore, the sample has relatively weak strength.
# A Molecularly Imprinted Polymer for Selective Extraction of Phenolic Acids from Human Urine
## 3 Results and Discussion
### Binding Properties and Adsorption Isotherns  
For evaluation of the imprinting ability of phenolic acids, its imprinting factors (IF) were evaluated. IF compares the adsorption ability of MIP to NIP and was obtained from the ratio of the adsorption capacity of MIP (QMIP) to NIP (QNLP). Results indicate that the template presents higher adsorption capacity and stronger interaction than its structural analogues because the MIP specific sites are complementary in shape, size, and spatial distribution to template. Consequently, the highest IF is presented by 4-HPA (the template), followed by its isomer (3-HPA), IF values were 3.5 and 3.2. Other analogues show intermediate IF values. SyA IF value was 2.9, PCA and 4-HBA IF values were 2.6 and 2.4, respectively. On the other hand, the lowest IF is presented by HA, IF was 2.2. It can also be seen that IF values are more than 1.0, and MIPs exhibit an imprinting effect for studied compounds with chemical structures similar to that of the 4-HPA imprinting template [17]. In MIP, adsorption capacities were influenced by the presence, number, and position of hydroxyl and carboxyl groups in the aromatic ring [17; 29]. On the other hand, the position of the hydroxyl group in relation to the carboxyl group also influences selectivity of MIP [16].  
Modeling the adsorption isotherm data is an essential way for predicting and comparing the adsorption performance. In this work, Langmuir and Freundlinch isotherm models were used to analyze the adsorption data of MIP [30]. Table 1 resume Langmuir and Freundlich isotherm parameters for MIP and the different phenolic acids. Standard deviation (SD) and the correlation coefficient (R) were used to determine the best-fitting isotherm to the experimental data. Results suggest that Langmuir model was more applicable to estimate the affinity distributions than the Freundlich model according to the correlation coefficients (R). These clearly show that the MIP values of Qmax, obtained in the Langmuir model, were higher for 4-HPA and 3-HPA.  
Figure 4: ATR-FTIR spectra for MIP, NIP, and 4-HPA.
# On Training Data Selection in Condition Monitoring Applications--Case Azimuth Thrusters
## 2 Materials and Methods
### Description of Data
#### 2.2.3 Generated Feature Values  
Figure 6 shows the feature values and shaft speed values in chronological order. The feature values followed the changes in the rotational speed values in a regular manner during the period which suggests that the monitored operation was relatively unchanged. Most feature values typically increased when the rotational speed increased considerably, but l\({}_{20}\)/l\({}_{2}\) and kurtosis had a weak correlation with the shaft speed.  
Figure 4: Shaft speed values of samples in chronological order and the progression of distribution based on median, interquartile range and 95% coverage.  
Figure 5: Illustration of 1 st to 99 th percentiles of shaft speed values. The deciles from first to ninth are marked by using black lines with squares placed on chosen sample sizes.  
Figure 7 illustrates the correlation between the features and the shaft speed with scatter plots. Certain speed areas clearly resulted in high variation in the feature values. The high variation in kurtosis and \(\mathrm{l}_{20}/\mathrm{l}_{2}\) roughly at 200-rpm speed could be explained by the steering angle changes during maneuvering, whereas the variation in many other features at the speed over 400 rpm is possibly a result of the ship movement during cruise. However, the effects of maneuvering and ship movements are left for future work.  
Figure 6: Feature values and rotational speed in chronological order. The number of a sample is shown on horizontal axis, whereas vertical axis shows the value of each sample.  
Figure 7: Scatter plots between feature values and rotational speed using the largest training set with 3000 samples.
# Analysis of the Effect of Temperature on the Sound Transmission Loss of a Curved Plate
## 3 Model Validation
### Effect of the Radius of Curvature and Opening Angle  
The radius of curvature and opening angle, which are important parameters for the design of structures, are geometrical characteristics unique to curved plates rather than flat plates. The variation in STL with temperature for an opening angle of \(\pi\)/3 and radii of curvature of 2, 4, 8, and 10,000 m for a curved plate at the vertical incidence of acoustic waves is shown in Figure 12. The figure shows that the first trough of the STL becomes progressively smaller as the radius increases. Simultaneously, the effect of temperature on the STL is more evident in the low-frequency range. As the temperature decreases, the trough gradually shifts to a high frequency; when the curved plate approaches a flat plate, the effect of temperature on the STL is evident. This is due to the effect of the radius of  
Figure 11: Effect of different azimuth angles on STL.  
Figure 10: Effect of different pitch angles on STL.  
curvature, which produces membrane stress, and the effect of temperature, which produces temperature stress. As the radius increases, the membrane stress gradually decreases, and the lower the temperature, the greater the temperature stress. Thus, if the radius is large and the temperature is low, the effect of temperature is noticeable.  
Figure 13 shows the variation in STL of the curved plate at a radius of curvature of 1 m and opening angles of \(\pi/6\), \(\pi/3\), \(\pi/2\), and \(2\pi/3\). The figure shows that as the opening angle increases, the STL at (1, 1) modal frequencies are all in the trough position. The larger the opening angle, the more evident the aggregation effect at this position and the smaller the effect due to temperature. This is because the larger the opening angle, the farther the curved plate is from a flat state and the more pronounced the effect of curvature, intensifying the centripetal effect toward the center of the surface. As the opening angle increases, the first trough position of the STL becomes inconsistent. This is due to the change in angle, causing the distribution of modal formations to appear out of sequence. When the sound waves are incident vertically, the parity distribution of the mode shape determines the trough position of the STL.  
Figure 12: Influence of the temperature on STL at different radii. (**a**) \(R=2\) m. (**b**) \(R=4\) m. (**c**) \(R=8\) m. (**d**) \(R=10\),000 m.
## 2 Main Arthropod Pests/Vectors in Olive Groves
### Bactrocera (Dacus) oleae  
The family Tephritidae consists of flies commonly known as \"fruit flies\". It is one of the most numerous Diptera families (nearly 5000 species are currently recognised) and is the most economically relevant. The larvae of most species develop in the seed-bearing organs of plants and a large number of them attack commercial fruits [23; 24; 25; 26].  
The species _Bactrocera oleae_ ([PERSON] 1790), also known as the olive fruit fly (_olf_), belongs to this family and is the most important pest of olive trees. There appear to be references to olive infestations in the eastern part of the Mediterranean Basin from as early as the 3 rd century BC [27]. However, the first reliable reference is that of [PERSON] (1 st century AD), who speaks of a \"vermiculatio\" of olives that affected their production for many years [28].  
The only natural hosts of the olive fruit fly are the fruits of plants of the genus _Olea_. In general, females prefer varieties with large olives for oviposition. However, they are capable of infesting all olive varieties, including wild varieties. Most species of invasive Tephritidae are established in only 5 or a few countries, but _Bactrocera oleae_ has been detected in 34 countries [29]. This insect is distributed throughout the Mediterranean region and the Middle East. It is also found in Southern and Eastern Africa, India, and Pakistan, and since the end of the 20 th century, the olive fly has also been reported in California and Mexico [19].  
In the Mediterranean Basin, this species has between two and five generations per year during the summer and early autumn, in parallel with the growth and ripening of the olives [30; 31]. The damage caused by this Diptera is linked to the feeding habits of the larvae, which are strictly monophagous and feed on the olive pulp [27]. The females  
Figure 2: Life cycles of the two main olive pests and of vectors of _Xylella_ in parallel with olive fruit development and olive phenology.  
lay eggs under the epidermis, and when they hatch, the larvae have direct access to the fruit. If the olive tree is grown for the production of table olives, the mere presence of the oviposition mark alone will result in the fruit being discarded. If the production is intended for the production of olive oil, several types of damage can be considered. The most important of these are the premature drop of the infested fruit, the destruction of the pulp caused by the larvae developing inside the olives, and the increased acidity and other side effects associated with the development of the larvae, including infections resulting from the hole in the skin caused by the oviposition and the galleries resulting from the feeding of the larvae. An infestation level of more than 1% prevents the fruits from being used as table olives and an infestation level of more than 10% also prevents them from being used for oil production, causing olive oil yield losses of up to 11.5% and 18% [32].
## 7 Discussion
### Seismic Microzoning and Major Site Damage Comparisons According to the 2014 Incident  
In this subsection, the output of the seismic microzoning map is overlaid with the damaged site locations. Figure 11 shows the location of the majorly damaged sites in the 2014 earthquake incident. \"Major damage\" in this study refers to structures that collapsed. However, the infrastructure in the study area was locally constructed without consideration of standards. There are many active faults in the area, but awareness was lower in the past because no significant strong ground motions or intensive seismic damage had previously occurred. The local houses are mainly two stories with a  
Figure 10: (i) Geology map of Thailand ([PERSON], 2011): the geological units are fluvial deposit (flood plain [Qff]), terrace and colluvium [Qt], alluvium (Qa), rhyolite [PTrv], semiconsolidate [Tmm], and granite [Trgr]; (ii) OBC geomorphology map from [PERSON] et al. (2011); and (iii) classified PBC geomorphology map. The geomorphological units for(ii,iii) are based on the descriptions in Figure 4.  
combination of a concrete frame with a fill-in brick wall for the first floor and a wooden structure on the second floor. Typically, a Thai house is raised off the ground (in preparation for flooding or intensive rainfall), and the first floor is usually built later. Therefore, the damage level may be influenced by the construction standard and the vulnerability of the location. From Figure 11, the damage location mostly corresponds to NEHRP class D. When considering the geomorphological units, all damage sites were found to be located in incised terraces and eroded plains of weak rock (classes 11 and 13). However, the damage that was located in NEHRP class C (one location from Figure 11) may have been influenced more by the construction quality. From an elementary visual evaluation, seismic microzoning based on geomorphological units correlates well with the construction damage.
## 1 Introduction
### Basic SEM Operation
#### 1.2.1 Specim Preparation  
For the production of high-quality and accurate SEM images, the sample preparation stage is very important. SEM analysis is susceptible to distortions, artifacts, and other issues in the case of improper specimen preparation. The sample of interest can be a solid material, a biological specimen, or belong to any other area of the object to be analyzed. The specimen material is mounted on a stub or holder using an adhesive conducting double-sided tape or with other mounting techniques. The SEM stubs are electrically conductive pads. No special specimen preparation is needed for conductor or semiconductor materials. For insulator materials, the image is distorted by charging the sample; therefore, a conduction path to the ground is needed for clear image production [11]. If the sample is moist, the sample must be completely dry before the SEM analysis stage. Moisture can introduce charging effects, thereby distorting the quality of the image. For materials of interest without or with lower electrical conductivity, a thin coating of metal such as gold, platinum, palladium, and chromium is applied to prevent charging effects [51; 52; 53]. Samples can be trimmed, fractured, or cut to expose the surface of interest to the electron beam and to make the geometry and size of the sample suitable for SEM analysis.
###### Abstract  
In wireless underwater sensor networks (WUSNs), network protocols for information routing are usually designed when a significant number of nodes are present in the network. Therefore, for sparse conditions, when a noticeable reduction in the number of nodes occurs, the performance of such protocols exhibits a degraded behavior pattern. To cope with routing issues when sparse conditions prevail, two routing algorithms for WUSNs are proposed in this paper. They are energy-aware scalable reliable and void-hole mitigation routing (ESRVR) and cooperative energy-aware scalable reliable and void-hole mitigation routing (Co-ESRVR). The ESRVR uses a number of strategies. Firstly, it uses two hop neighbors' information to develop routing trajectories for information advancement, as one hop information cannot avoid a void-hole, a condition when a node is not able to find neighbors towards the sea surface, and more than two hop information is difficult to obtain when sparse conditions prevail. Secondly, when a void-hole still exists, the protocol uses a backward transmission mechanism to find other routing paths to deliver packets to the end target. Thirdly, the time by which a packet is held by a node prior to transmission is short for the nodes with low energy, depth and high count of neighbors. This reduces packets loss and avoids congestion of the channel. It also helps the nodes with no or few neighbors to hold the packet for a significant chunk of time until they find suitable neighbors, due to sea tides and currents, for further packets' advancement. The Co-ESRVR further adds reliability to information advancement by adding routing in a cooperative fashion to ESRVR, which involves packets advancement to destination along two paths: directly from source and via a relayed path. This provides multiple paths for data advancement to the sea surface, so that if one path is badly affected by the harsh sea characteristics, others may not be. Unlike the counterpart protocol, the proposed algorithms are not dependent on a node's geographical location or the distance from the sea surface, which increases their scalability and reduces the computational complexity. Performance analysis displays superior behavior patterns of the proposed algorithms over the counterpart in terms of the compared characteristics.  
underwater; ESRVR; Co-ESRVR; routing +
Footnote †: journal: Applied Physics Letters  
12 November 2019; Accepted: 20 December 2019; Published: 25 December 2019