esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
#### 3.3.1 Surface and Cross-Section Microstructure  
Scanning electron micrographs of film surfaces and cross-sections are shown in Figure 4. The results suggest that the GPP film had the smoothest and most homogeneous surface and cross-section microstructure. The smooth and homogeneous surface and cross-section microstructure can be explained by a well-ordered matrix between alginate, carrageenanan and gac pulp pectin [39]. Overall, micrographs of GP films and other incorporated films also suggest a heterogeneous microstructure that correlates with the lower transparency of these films. The results also indicate that there were more convex irregularities on the surface of the oil-added films than the GP film. A previous study reported by [61] observed that incorporation of the essential oils and plant extracts could result in variation of structures due to the arrangement of film-forming polysaccharides and aggregation of oils and extracts during film production. It should be noted that the films incorporated with essential oils had more homogenous surfaces than that of the films incorporated with the plant extracts (Figure 4). In addition, the results also revealed that all the films had a fibrous-like structure, which concurs with previous studies on semi-refined kappa-carrageenanan edible films [62] and alginate/ginseng films [59].  
Figure 4: _Cont_.
## 2 Theoretical Foundation
### Fluid-Structure Interaction Governing Equation  
Similarly, fluid-structure interactions should also follow the basic physical conservation laws, and the variables such as stress (\(\tau\)), temperature (\(T\)), displacement (\(d\)) and heat flow (\(q\)) between the two phases of the fluid domain and the solid domain should be conserved or equal at the fluid-structure interaction interface, so that the following equations are satisfied:  
\[\left\{\begin{array}{l}\tau_{f}\cdot n_{f}=\tau_{s}\cdot n_{s}\\ T_{f}=T_{s}\\ d_{f}=d_{s}\\ q_{f}=q_{s}\end{array}\right. \tag{7}\]  
where, the subscript \(f\) represents the fluid and the subscript \(S\) represents the solid.
# Ice Production in Ross Ice Shelf Polynyas during 2017-2018 from Sentinel-1 SAR Images
## 3 Method  
The polynya ice productions in 2017 and 2018 are derived from Sentinel-1 SAR images and AMSR2 brightness temperatures. The former is used to identify the polynya area/extent and the latter is used to estimate sea ice thickness in the polynyas.
## 4 Discussion
These results show that charged particles that can be removed only by the EG mesh (not chemically active species such as OH\({}^{-}\) radicals that can pass through both meshes) play an important role in enhancing the dental F\({}^{-}\) coating effect of NCP. Furthermore, the alleviation of dentin hypersensitivity by APF and HA after plasma pre-treatment was observed. Argon generally lost electrons during the early stages of the argon plasma formation process, thereby producing argon ions and electrons. The dentin hypersensitivity impact of NCP in this investigation appears to be caused by charged particles of NCP, because this effect was lessened by the electrically grounded mesh. The dentimal tubules of teeth showing dentin hypersensitivity are open, and the resulting pain is determined by the opening and closing of the dentin tubules [36; 37]. SEM imaging, which was performed to observe the occlusion of the dentimal tubules, followed by comparative analysis and graph plotting, revealed no statistically significant difference between the control, HA, APF, and HA/APF groups. On the other hand, pre-treatment with plasma and HA/APF yielded statistically significant results. After plasma pre-treatment, the occlusion efficacy was confirmed to be about 22.5 times higher in the experimental group treated with HA/APF than that in the other groups. Thus, we can infer that plasma pre-treatment of the tooth surface effectively enhances the adhesion of the HA/APF mixture. There was no statistically significant difference in the Ca and P content of the untreated, HA, APF, and HA/APF groups. On the other hand, the group treated with plasma and HA/APF showed statistically significant results. This shows that HA and APF do not significantly increase the Ca and P content of the coated dentin, contrary to the results of previous studies [38]. Previous studies interpreted an increase in Ca and P levels because the teeth were continuously exposed to the minerals in saliva. Our results showed that pre-treating dentin with plasma significantly increased the ability of APF to close the dentin tubules compared to treatment with only HA, APF, and HA/APF. Pre-treatment with plasma facilitates penetration of the charged particles into the dentin, so F\({}^{-}\) and HA can easily penetrate the dentimal tubules, and the surface area is increased to improve the adhesion with dentin. However, although the effect and mechanism underlying the amelioration of hypersensitivity after plasma pre-treatment were verified in vitro in this study, a limitation is that the efficacy was not reported to be increased in vivo. Future in vivo research is warranted to verify the efficacy of plasma treatment against hypersensitivity. A more complete verification of the efficacy of NCPfor resolving hypersensitivity should be conducted through in vivo effect research. Future studies will examine whether applying fluoride to animal teeth via NCP is more efficient than the current techniques.
# Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks
###### Abstract  
Underwater acoustic sensor networks have recently attracted considerable attention as demands on the Internet of Underwater Things (IoUT) increase. In terms of efficiency, it is important to achieve the maximum communication coverage using a limited number of sensor nodes while maintaining communication connectivity. In 2017, [PERSON] and [PERSON] proposed a new deployment algorithm using the communication performance surface, which is a geospatial information map representing the underwater acoustic communication performance of a targeted underwater area. In that work, each sensor node was a vertically separated hydrophone array, which measures acoustic pressure (a scalar quantity). Although an array receiver is an effective system to eliminate inter-symbol interference caused by multipath channel impulse responses in underwater communication environments, a large-scale receiver system degrades the spatial efficiency. In this paper, single-vector sensors measuring the particle velocity are used as underwater sensor nodes. A single-vector sensor can be considered to be a single-input multiple-output communication system because it measures the three directional components of particle velocity. Our simulation results show that the optimal deployment obtained using single-vector sensor nodes is more effective than that obtained using a hydrophone (three-channel vertical-pressure sensor) array.  
underwater acoustic sensor network; optimal deployment; vector sensor node; particle velocity; communication performance surface +
Footnote †: journal: Sensors
## 2 Results and Discussion
### GNAT-HTH (GaCTA)
#### 2.1.3. _Ga_TA of \(G\). _thermodenitrificans_ NG80-2
It should be noted that in contrast to most TA systems, the order of the genes coding for the putative GNAT-wHTH TA pair in the four _Geobacillus_ strains shows that the toxin-coding gene is upstream of the antitoxin-coding one. This atypical gene order has been reported only in few TA families; HigBA [52], MqsRA [53], and HicAB [54]. Regardless of which of the two mentioned alternatives is correct, the gene order of this GNAT-wHTH TA family highlights the significance of researching it in _Geobacillus_, as it represents one of the potentially unique TA families. Experimental analysis of the RNA expression and the possible post-transcriptional regulations will demonstrate the special protein expression mechanisms that these _Geobacillus_ strains employ to secure the production of wHTH antitoxin to neutralize the GNAT toxin, as has already been done for _E. coli_ strains that harbor HigBA, MqsRA, and HicAB (for details, the reader is referred to [54; 55; 56; 57; 58; 59]. Worth mentioning is that the HITH (RHH)-GNAT TA family, which has been experimentally studied so far, was of the bacterial strains _K. pneumoniae_ HS11286 [43] and _Salmonella enterica_ subsp. _ enterica_ serovar Typhimurium LT2 [60], where the TA-coding genes have the typical gene order. Therefore, the _Geobacillus_ strains are showing a previously unreported gene order of the putative GNAT-HTH TA family. In summary, our analysis indicated that all the four _Geobacillus_ strains have a putative GNAT-wHTH TA family, or GacTA, whose aa sequences are either identical or highly similar (global alignment in Figure S1). The putative wHTH-GNAT TA family represents a potentially unique TA family with atypical TA gene order. Therefore, experimental studies of the _Geobacillus_ putative GNAT-wHTH TA family will be of significance.
# Spot Weld Inspections Using Active Thermography
## 2 Materials and Methods  
Nine different samples are inspected using different active thermography techniques in order to find the best inspection method. The samples are divided into two groups: A and B. The A-series comprises four samples with the same thickness (2.5 mm) and one sample that is 3.15 mm thick. All samples of series B have a thickness of 2.5 mm. An RGB image of the samples can be seen in Figure 1. The A-series samples are used to find the best measurement setup for the inspection of spot welds using active thermography. The B-series will function as a validation set to test the best suitable measurement method.  
The parameters used to weld the samples can be found in Table 1.  
The camera used for these experiments is a FLIR X6540 sc with a 25 mm lens. This cooled camera has a spectral range between 1.5 and 5.5 um and a thermal sensitivity smaller than 25 mK. The thermal camera is mounted on a tripod and placed in front of the sample.
## 2 Experimental  
The photographs of concrete specimen surfaces were taken using a professional system consisting of a stereoscopic microscope, a CCD camera, a cross table, and a PC with customized software to perform the specimen scanning and setup, image acquisition and numerical analysis (NIS-Elements). A special attachment mounted on the objective lens of the microscope (Figure 1) was an additional accessory. The attachment was fitted with a focused light source placed in the vicinity of the optical axis of the lens (part of the vision field in the left eyepiece was obscured). The light rays were reflected off the specimen's surface and were visible in the right-hand part of the visual field in the objective lens. The image from this part was sent through the camera to the computer.  
The sand and coarse aggregate particles on the image were much brighter than the cement paste that surrounded them. The particles, particularly those of sand, had a dense structure and low porosity, and reflected light rays better than the porous cement pastes producing scattered light. Making the paste darker with the use of phenolphthalein increased the contrast between the aggregate and the cement paste.  
Coarse aggregate particles (even those of basalt, typically regarded as homogeneous) have poorer reflectivity, appear less bright, have irregular edge shapes and require additional time for shape correction and particle filling.  
Figure 2a shows an example of a specimen illuminated with ordinary light, and Figure 2b shows a sample illuminated with the light enhanced by the proposed attachment. Figure 2c presents a binary image after correction in NIS-Elements, with visible particles of sand and aggregate. The correction procedure involved filling in the voids and cracks; in the case of porous aggregate particles, their contour had to be corrected manually.  
A series of colour photographs were combined into a large, single image covering a considerable area of the sample (up to 50 cm\({}^{2}\)).  
Photographs with the sizes of 1280 \(\times\) 980 and 640 \(\times\) 490 pixels were taken using the calibration of 3.37 \(\upmu\)m/px or 6.74 \(\upmu\)m/px. The file size of the combined image was about 135 MB with 6.74 \(\upmu\)m/px calibration. Analysis of larger images was difficult, as with a calibration of 3.37 \(\upmu\)m/px, the size of a file is about 260 MB.  
Figure 1: View of the microscope with the attachment mounted on the objective lens for additional illumination of concrete specimens.  
Figure 2: Image of the sample: (**a**) ordinary light illumination, (**b**) illumination enhanced with the attachment and (**c**) binary image of the aggregate after correction.
# IEEE 802.11 ah: A Technology to Face the IoT Challenge
## 3 Comparative Analysis of IEEE 802.11 ah with Previous IEEE 802.11 Amendments
### Comparison of IEEE 802.11 Amendments Based on MAC Features
#### 3.1.3. Point Coordinated Function (PCF)  
It is an optional MAC protocol that uses polling scheme to determine which station can initiate data transmission. This technique is designed for infrastructure based network only, where different stations can optionally participate in PCF and respond to poll received.  
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Notable Features** & **802.11-2007** & **802.11n** & **802.11 ac** & **802.11 ah** \\ \hline Backwards compatibility & X & X & X & \\ DCF & X & & & \\ PCF & X & & & \\ \hline HCF & HCCA & X & X & & X \\ EDCA & X & X & X & X \\ \hline \multirow{3}{*}{TXOP} & Forward & X & X & X & X \\  & RD protocol & & X & X & X \\  & BDT & & & & X \\ \hline RID & & & & & X \\ Frame Aggregation & & X & X & X & X \\ Block ACK & X & X & X & X & X \\ Multi User (MU) Aggregation & & & & X & X \\ Null Data Packet (NDP) & & & X & X & X \\ Group-ID & & & & X & X \\ BSS color & & & & & X \\ Dynamic Bandwidth Management & & & & X & \\ Subchannel Selective Transmission & & & & & X \\ Traffic Indication Map (TIM) & X & X & X & X & X \\ Delivery Traffic Indication Map (DTIM) & & X & X & X & X \\ Target Wakeup Time & & & & & X \\ Grouping of Stations & & & & & X \\ Hierarchical AID & & & & & X \\ Dynamic AID reassignment & & & & X \\ Restricted Access Window (RAW) & & & & X \\ Group sectorization & & & & X \\ Relay operations & & & & X \\ Power saving at AP & & & & X \\ Low power mode of operations & & & & X \\ \hline \hline \end{tabular}
\end{table}
Table 2: Key MAC features within each amendment.
## 4 Backgrounds and Methods
### Backgrounds  
#### 4.1.1 LTE Handover and Parameters  
The HO is a major task that supports continuous transmission for a UE moving across different radio coverage areas. In the standard LTE system, HO is based on the network-controlled hard HO (NCHH) [4]. NCHH is a \"break before make\" method; that is, the radio link between the UE and serving cell is disconnected before a new radio link is established between the UE and the target cell. A mobile relay HO procedure, such as the typical HO procedure, includes three phases: preparation, execution and completion [5].  
Figure 6 depicts the existing HO procedures of the LTE. In this procedure, the serving eNB sends a measurement control command (M request) to a UE. On receiving the measurement control command, the UE starts the measurement procedure and consequently sends a measurement report (M report) to the serving eNB. The serving eNB then makes the HO decision and selects the target eNB based on the measurement report from the UE. The preparation phase is thus completed. If the HO is necessary, the serving eNB sends the HO request (HO req) to the target eNB. The target eNB accepts and preparesthe HO of the UE and replies with the HO request ACK (HO req ACK) to the serving eNB. Then, the serving eNB sends a HO command (HO command) to the UE. Upon receiving the HO complete message (HO confirm), the UE disconnects from the serving eNB and requests a connection with the target eNB. If the HO is successful, the UE replaces the status of the serving eNB from the target eNB.  
Let us now look at the important HO parameters for our focus \"Event A3\" based on NCHH. In the HO procedure [17], the presented HO parameters are HH, TTT, offset and CIO. The CIO is the departing range of the serving cell or the entering range of the target cell if a CIO is stored in that cell. Otherwise, if it is equal to zero, the departing or entering range of the cell is set as the measurement result. Equation (1) defines the condition for Event A3:  
\[M_{n}+Oc_{n}-Hys_{A3}>M_{s}+Oc_{s}+off_{A3} \tag{1}\]  
where \(M_{n}\) and \(M_{s}\) denote the measured RSS of the target eNB and serving eNB, respectively. \(Oc_{n}\) and \(Oc_{s}\) are the CIOs of the target eNB and serving eNB, respectively. \(Hys_{A3}\) denotes hysteresis, and \(off_{A3}\) is the offset.  
Figure 7 illustrates the entering condition for the target cell based on Event A3 in the LTE network. Hys1 denotes \(Hys_{A3}\) + \(Oc_{n}-Oc_{s}\). Once the condition for Event A3 is satisfied, the serving cell can begin the TTT. After TTT is finished, if the condition is satisfied, the serving cell initiates the HO procedure using the HO request command (HO preparation phase). The serving cell sends the HO command on receiving \"HO req ACK\" from the target cell.  
Figure 6: Existing hard HO procedure for user equipment (UE) in LTE.
## 4 Results and Discussion
### Container Volume Calculation
#### 4.4.2 Force on the Container  
When waste is placed in a garbage bag that can pass through the dimensions of the refuse chute intake door, the total weight of the waste is recorded as a maximum of 10 kg (\(m_{w}\)) and the single waste volume (\(V_{u}\)) is 0.001 m\({}^{3}\). In previous calculations, the volume of the container with dimensions \(l\) = 0.7 m, \(w\) = 1 m, \(h\) = 1 m, \(V_{c}\), was found to be 0.7 m\({}^{3}\) in Equation (14). The number of waste bags that the container can carry in terms of volume, (\(n_{c}\)), can be found by dividing the container volume (\(V_{c}\)) by the waste volume (\(V_{u}\)), as in Equation (16).  
\[n_{c}=v_{w}/v_{u} \tag{16}\]  
Figure 14: Waste container.  
Here, \(V_{c}\) = 0.7 m\({}^{3}\), \(V_{u}\) = 0.001 m\({}^{3}\), therefore an \(n_{c}\) = 700 pc was found. Accordingly, we can place a total of 700 waste bags (\(n_{c}\)) in the determined container.  
The load on the container (\(f_{c}\)) can be found by multiplying the maximum weight of a waste ag (\(m_{w}\)), the acceleration of gravity (\(g\)), and the number of waste bags placed in the container (\(n_{c}\)). The impact force of the first impacts of the elbow is absorbed by the receiver mouth, so the impact force of the elbow on the container can be neglected. The force on the container is shown in Equation (17).  
\[f_{c}=m_{w}g\ n \tag{17}\]  
Here, with \(n\) = 700 pc and \(m_{w}\) = 10 kg, an \(f_{c}\) = 7.000 N was found. The selection was made according to this criterion when ordering the container.
# Detection of Movement and Lead-Popping Artifacts in Polysomnography EEG Data
## 2 Methods
### Algorithm
#### 2.1.5 Expert-Assessed Ground Truth  
We demonstrated our algorithm's performance using a single PSG EEG recording, for which we established a ground truth based on another expert's re-examination of the de-identified EEG data. This recording was obtained in 2021 from a 19-year-old female subject. For the PSG EEG recording used for comparison, the artifacts in the PSG EEG from one of the six channels (C3) were manually annotated by an AASM-certified sleep physician. We considered the expert-annotated signal the ground truth for evaluation of algorithm performance. All subsequent discussions on performances are related this specific subject.  
The expert did not attempt to annotate the entire recording at a 1 s resolution; instead, the expert identified ranges for all movement-related and loose-lead-related artifacts. Since the expert denoted the start and end positions of each artifact region, we labeled all segments from the start to the end of the artifact region as expert-identified artifacts. We counted the number of segments out the total of 46,422 that agreed in annotations between the expert and the algorithm as belonging to artifact regions. In calculating the comparison, we considered two thresholds for the local moving-window cutoff and two thresholds for the global cutoff. The comparison was restricted to NREM and REM epochs; it excluded arousal epochs.
## 4 Experimental Verification of the Digital Twin Model
### Verification of the Tele-Powering Field Conformity
This phenomenon was caused by the inconsistency between the current \(i_{\text{d}}\) of the tele-powering signal used in the calculation and the current on the onboard transmitting antenna during the measurement. Due to the accumulated errors in the measurement process, the current intensity of the tele-powering signal on the onboard transmitting antenna may not reach 1000 mA. We adjusted the current intensity of \(i_{\text{d}}\) in the calculation model to 880 mA, and kept all the other parameters as before. The corrected calculation result could be obtained as shown by the black dotted line in Figure 13. The corrected calculation result curve almost coincided with the measurement result curve, and the difference between the corrected calculation result and the measurement result was only 0.23 nVs at \(\Delta x=0\). This confirmed the previous conjecture that the error was caused by the difference in the current of the tele-powering signal. The Pearson correlation coefficient, Spearman rank correlation coefficient, and maximum mutual information coefficient were 0.9998, 0.9786, and 0.9999, respectively, for the corrected curve and the measured curve. This indicates that the electromagnetic coupling calculation model proposed in this paper can accurately predict the tele-powering field conformity measurement results.
## 3 Results
### Changes in Properties According to Storage Conditions
#### 3.1.3 ACC Changes  
All test NW preparations exhibited a decrease in ACC during the 126-day storage period, and it decreased to 5 mg/L (one-fifth of the initial value) in NW\({}_{25}\) stored under L\({}_{\text{RT}}\). The remaining seven NW preparations exhibited an ACC of 15 mg/L or higher under all storage conditions. NW\({}_{25}\) and NW\({}_{35}\) showed no significant difference between S\({}_{\text{RT}}\) and S\({}_{\text{LW}}\) conditions after 126 days (_p_ > 0.05), and the remaining six NW preparations demonstrated the smallest ACC decrease under S\({}_{\text{LW}}\) conditions (_p_ < 0.05) (Figure 3). Under L\({}_{\text{RT}}\) storage conditions, NW\({}_{25}\) (\(-\)81.3 \(\pm\) 3.0%) and NW\({}_{1000}\) (\(-\)84.2 \(\pm\) 1.1%) exhibited substantially higher reduction rates than the other NW preparations, indicating a weak negative correlation between the initial ACC of NW and the ACC change rate (R: \(-\)0.347). In other storage conditions, NW\({}_{1000}\) showed the largest ACC reduction rate with a strong negative correlation between the initial ACC of NW and the ACC change rate (R: \(-\)0.868 in S\({}_{\text{RT}}\) and \(-\)0.887 in S\({}_{\text{LW}}\), respectively) (Figure 4). There were strong positive correlations between the ACC and ORP values of the NW preparations after 126 days of storage, and a negative correlation between their rates of change. The R values were 0.947 and \(-\)386, respectively (Supplementary Figure S4).