esa-sceva/satcom-chunk-collection huggingface dataset:
# Biphasic Injection for Masseter Muscle Reduction with Botulinum Toxin
## 3 Results
When masseter contracts, this could eventually result in a bulging of a part of superficial muscle belly that is unaffected by BoNTA due to the presence of the DIT. Subsequent studies confirm that the DIT has been identified as contributing to paradoxical masseteric bulging [69]. Our experience focuses on the findings of these evidence and highlights the importance of having accurate anatomical knowledge to ensure procedural safety. The specific mechanism by which toxin relieves tendon structure has not yet been clearly identified, although previous studies based on pharmacological evidence have shown that muscle and tendon structures should be considered with the aim to prevent complications [70; 71]. Paradoxical bulging may disappear within a week without any medical treatment; thus, it is suggested to wait for toxin diffusion before a touch-up treatment. When paradoxical bulging persists or even worsens after 1-2 weeks, we recommend an additional BoNTA injection over the superficial layer. The deep layer of the masseter is almost vertical in direction and contraction, while the superficial layer originates more medially on the zygomatic bone, creating an oblique direction of contraction; paradoxical bulging usually takes this form. This clinical evidence supports the blocking effect of the tendons structure between deep and superficial masseter layers [55; 68]. The biphasic injection has been developed following this anatomical concept. Ultimately, the superficial part of the masseter consists of not only the muscle belly but also the deep tendon structure: surgeons should be aware of this tendon prior to treating masseter hypertrophy and improving lower face contouring using BoNTA injections. Knowledge of this critical anatomical feature will help to prevent paradoxical masseteric bulging. According to our experience, a biphasic technique of superficial and deep injections is recommended. Considering the biphasic injective procedure applied for masseteric hypertrophy BoNTA treatment, we could predict and avoid the possibility of compensatory hypertrophy of superficial masseter layer.
# Evaluation of a New-Concept Secure File Server Solution
## 3 Research Methodology
### Methodology of the Performance Tests
#### 3.2.3 Reducing the Uncertainty of the Measurements and Filtering Out Measurement Errors  
Reducing measurement uncertainty was essential during the tests, as measurements can be affected by both random and systematic errors. Random errors are difficult to identify and may, for example, result from an anomaly in the functioning of the electronic equipment used for the measurement or the devices providing the physical link between them. Systematic errors may result from shortcomings in the measurement method or from the normal operation of the system under test.  
Our aim was to detect these errors and eliminate their distorting effects on the measurement results. To measure the performance of the server environments under test, we needed to reduce measurement uncertainty as much as possible by reducing the number of external factors that cause uncertainty. To reach this goal, we used a direct cable connection (crossover CAT6 UTP, SFP + DAC) instead of the traditional switched and possibly routed network infrastructure, and we also disabled the possible native real-time virus protection on both sides during the measurements.  
Despite all our efforts, some anomalies might still have occurred in the study, which could be attributed to the following factors, among others:  
* Read/write buffer management (filling up, emptying);
* Initial indexing of files;
* The network throughput sometimes exceeded the theoretical maximal bandwidth of the SATA3 interface (10 Gbit/s vs. 6 Gbit/s), which could lead to uncertainty due to different caching mechanisms;
* Minor fluctuations in read/write speed of SSD drives;
* The performance impact of other running processes.  
In order to reduce measurement uncertainty and the impact of measurement errors, all read and write tests were conducted ten times consecutively in each test environment. The average transfer speeds were calculated based on the time needed for the transmission. We determined the lowest and maximum transfer time values, the average transfer time, and the standard deviation values for both transfer times and speeds. The network load was continuously checked to prevent transmission errors, and the hash calculation check of the data was conducted after each transmission.
###### Abstract  
After a vacuum failure in a tokamak, plasma runaway or plasma disruptions frequently occur during plasma recovery, causing difficulties in rebuilding a well-confined collisional plasma. In this work, the impurity behavior during plasma recovery after a vacuum failure in the 2019 spring campaign of the Experimental Advanced Superconducting Tokamak (EAST) was studied by analyzing the spectra recorded by fast-time-response extreme ultraviolet (EUV) spectrometers with 5 ms/frame. During the plasma current ramp-up in recovery discharges, a high content of the low-Z impurities of oxygen and carbon was found, i.e., dozens of times higher than that of normal discharges, which may have caused the subsequent runaway discharges. The electron temperature in the recovery discharge may have dropped to less than 75 eV when the collisional plasma quenched to the runaway status, based on the observable impurity ions in the two cases. Therefore, the lifetime of collisional plasma in the recovery discharge, \(\tau_{\mathrm{c}}\), was deduced from the lifetime of H- and He-like oxygen and carbon ions identified from EUV spectra. It was found that, after several discharges with real-time lithium granule injection, the runaway electron flux and O\({}^{+}\) influx reduced to 45% and 20%, respectively. Meanwhile, the lifetime of confined plasma was extended from 113 ms to 588 ms, indicating the effective suppression of impurities and runaway electrons and improvement in plasma performance by real-time lithium granule injection. The results in this work provide valuable references for the achievement of first plasma in future superconducting fusion devices such as ITER and CFETR.  
tokamak; recovery phase; impurity; EUV spectra +
Footnote †: journal: Physics Letters B
# Digital Denture Fabrication: A Technical Note
## 2 Advantages of Digital Denture  
* **More Accurate** The CAD/CAM fabrication process is a more accurate and reproducible denture fabrication technique in comparison to the conventional method;
* **More Efficient** The CAD/CAM fabrication process needs a reduced total number of appointments (two or three visits) in comparison to the conventional protocol (more than five visits) and a significantly reduced clinical treatment time for the digital fabrication process (approximately 3.5 h less compared to the conventional protocol);
* **Improved Retention** Digital dentures are better in retention, fit, and stability compared to conventional dentures [10, 15]. The improved retention of digital dentures could be explained by their superior fit and absence of polymerization shrinkage;
* **Teeth Arrangement** In the digital denture workflow, the teeth are arranged on the digital denture design software, and the digital preview of the teeth setup of complete dentures is reviewed and easily modified;
* **Remake Dentures** The most beneficial feature of CAD/CAM dentures in comparison to conventional dentures is the stored digital files that allow the fabrication of newprostheses when dentures are lost or damaged. Therefore, the electronic achieving of all clinical data from the patient along with the design of the manufactured prostheses enables making spare or new dentures, in case of breakage or loss, without clinical appointments [16];
* **Better Fracture Resistance** The material used for digital denture fabrication was significantly improved in its properties [17,18]. Increased toughness, ultimate strength, and higher elastic modulus provide clinical benefits regarding the denture base design with minimal thickness, without the common occurrence of denture fractures.  
The process of digital denture fabrication may have some disadvantages related to additive cost. Nevertheless, the above-mentioned benefits and especially increased level of patient satisfaction can help to overcome the other disadvantages.
# Analysis of Hydrological Characteristics of Blue Nile Basin, Nishe Watershed
###### Abstract  
Hydrological modeling is a technique for understanding hydrologic characteristics and estimation of the water balance of watersheds for integrated water resources development and management. The Soil and Water Assessment Tool (SWAT) model was used for modeling the hydrological behavior of the Nishe watershed in the north-western part of Ethiopia. The spatial data, daily climate, and stream flow were the required input data for the model. The observed monthly stream flow data at the outlet and selected sub-watersheds in the catchment were used to calibrate and validate the model. The model performance was assessed between the simulated and observed streamflow by using sequential uncertainty fitting-2 (SUFI-2), generalized likelihood uncertainty estimation, parameter solution (Parasol) and particle swarm optimization. The sensitivity of 18 parameters was tested, and the most sensitive parameters were identified. The model performance was evaluated using p and r- factor, coefficient of determination, Nash Sutcliffe coefficient efficiency, percent bias during uncertainty analysis, calibration and validation. Therefore, based on the set of proposed evaluation criteria, the SUFI-2 algorithm has been able to provide slightly more reasonable outcomes and Parasol is the worst compared to the other algorithms. An analysis of monthly and seasonal water balance has been also accomplished for the Nishe catchment. The water balance parameters were distinct for the three seasonal periods in the catchment. The seasonal water budget analysis reveals that the watershed receives around 19%, 69%, and 12% of rainfall through the short rain, long rain and dry seasons, respectively. The received precipitation was lost due to evapotranspiration by 29%, 34% and 37% for each season respectively. The surface runoff contributes to the catchment by 5%, 86% and 9% of the water yield.  
GLUE; parasol; PSO; SUFI-2; SWAT-CUP; uncertainty analysis; water balance +
Footnote †: journal: Applied Sciences  
1
Footnote 1: [[https://doi.org/10.3390/appl12411791](https://doi.org/10.3390/appl12411791)]([https://doi.org/10.3390/appl12411791](https://doi.org/10.3390/appl12411791))
## 4 Emerging Lightweight Security Approaches
### Asymmetric Encryption--Lightweight ECC Approaches
#### 4.2.1 Elliptic Curve Diffie-Hellman  
An application of ECC is the elliptic curve Diffie-Hellman key exchange protocol. ECDH allows the sender and receiver to generate a secret elliptic curve point that is used to create a session key for symmetric encryption [93]. ECDH is similar to the original  
Figure 9: Elliptic curve of \(y^{2}=x^{3}+\mathrm{ax}+\mathrm{b}\).  
Diffie-Hellman key exchange protocol. It relies on the difficulty of solving the discrete logarithm problem. This problem requires exponential computational complexity and relies on the principle of one-way functions, which are easy to compute in one direction but difficult to reverse [11]. ECDH, however, utilizes the inherent difficulty of finding the discrete logarithm of elliptic curve elements from a publicly shared base point rather than large integers [94]. This means a higher level of complexity. This variant of the discrete logarithm problem is called the Elliptic Curve Discrete Logarithm Problem (ECDLP) [92].  
Figure 10 illustrates how ECDH works, assuming that it is implemented for a LoRA-based IoT system. First, the sender (i.e., the gateway) and receiver (i.e., the application server) agree on an elliptic curve over a finite field \(\mathrm{E}(\mathrm{F}_{\mathrm{q}})\). The field size \(q\) is derived from a prime number \(p\). They must also agree on a co-factor \(h\) and a base point \(G\). The sender then selects a private key \(a\) that is a random integer within the range \([1,\,\ldots,\,n-1]\), where \(n\) is the order of the subgroup consisting of the real points of the curve \(\mathrm{E}(\mathrm{F}_{\mathrm{q}})\).  
As in the first row of Figure 10, the scalar multiplication of the private key \(a\) with the base point \(G\) generates the sender's public key \(\mathrm{H}_{\mathrm{a}}\), thus completing the sender's key pair (\(\mathrm{H}_{\mathrm{a}}\), \(a\)). The receiver generates a key pair (\(\mathrm{H}_{\mathrm{b}}\), \(b\)) using the same procedure.  
Then, the gateway and server exchange their public keys \(\mathrm{H}_{\mathrm{a}}\) and \(\mathrm{H}_{\mathrm{b}}\) over the network. After the gateway receives the server's public key, it generates the session key \(K\) by multiplying the server's public key \(\mathrm{H}_{\mathrm{b}}\) with its private key \(a\) (this multiplication is shown in the third column, the first row of Figure 10). The server also generates the same session key \(K\) using the gateway's public key \(\mathrm{H}_{\mathrm{a}}\) and its private key \(b\). At this point, both parties have remotely agreed on a shared session key \(K=abG\)[95]. Key \(K\) will be used to encrypt the subsequent messages using a symmetric encryption algorithm such as AES or PRESENT.
## 4 Results and Discussion
### Synthetic ECG Results  
First, the models are tested on synthetic ECG data to check the effectiveness of the approach [29]. Once the models are trained and optimized, as shown, they can be used with real-patient ECG data, showing temporal dynamics captured and reconstruction with adaptive sampling. Figure 7 presents the performance of the TCN model on synthetic data. The original data are 30 sample points roughly defining the ECG signal. The modified signal is the interpolated one. Optimally chosen time points give a close interpolation of the original signal, proving the efficiency of our model to a great extent, as depicted in the graph. Figure 8 displays the performance of the transformer model on synthetic data. Similar to the TCN model, the transformer model also performs quite well in reconstructing the original ECG signal with given sample points. A non-uniform sample series approximates an irregular synthetic ECG signal, which in turn represents the modified signal.  
The operator argmin refers to the argument (input value) of a function that minimizes the function's value. For a function f(x), argminx f(x) is the value of x that minimizes f(x). For both our models, the argmin time points or the optimal sampling that leads to the lowest error is approximately averaged around 9.67 s in the sequence.  
The evaluation matrices in Table 1 show the performance as well as the comparison between both models for synthetic data. Based on the measurements, it is possible to draw conclusions about the TCN and transformer models' respective performances. The root mean squared error (RMSE) of 0.0573 and the mean squared error (MSE) of 0.0032 were attained by the TCN model. These error metrics show that there is not much of a difference between the real and predicted values, indicating that the TCN model can accurately mimic  
Figure 8: Synthetic signal output for transformer model.  
Figure 7: Synthetic signal output for TCN model.  
the original signal. In addition, the TCN model's high Pearson's correlation coefficient (0.9766) indicates a linear link between the anticipated and actual values.  
It is in the error metrics, however, that the transformer model performs better than the TCN model, with an MSE of 0.0026 and an RMSE of 0.0510. The smaller these numbers are, the closer a model's predictions are to the actual values, thus indicating greater accuracy. The Pearson's correlation coefficient was marginally lower for the transformer model at 0.9612, compared to that of the TCN model. Nevertheless, this denotes a strong linear relationship between the predicted and true values.
## 3 DL Models for Ocean Studies
### Rnn  
Many oceanographic applications involve time-series data and RNNs are specifically designed for temporal dependencies extraction through recurrent connections. Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) are two notable variants that incorporate gating mechanisms to regulate information flows across time steps [85]. These mechanisms allow the model to selectively retain or discard information, making them effective at capturing long-term dependencies in complex time-series data. In the context of ocean climate change, RNNs facilitate the analysis of historical trends, valuable for temperature, wind speed, or wave height prediction [86].
## 4 Review of Literature
### Rescue in Routing Optimisation Problems
#### 4.3.3 Heuristics and Local Search in Rescue VRPs  
Since 2010, there have only been two studies found in the literature that used heuristic and local search in the domain of rescue VRPs. In [148], the operation stage of the five stages of SAR are addressed, where the maritime victim survivors in the ocean are searched for and rescued by nearby ships and helicopters operating simultaneously and dispatched by the Maritime Rescue Coordination Center (MRCC). In this problem, the longer the arrival time of the rescue team, the more risk of the survivors being dispersed and drifted apart although; in this problem, the location of the survivor is known. A Generalised VRP (GVRP) is adopted in order to represent the problem where multiple depots are considered. The objective is to maximise the profits that are associated to the lives saved during the rescue operation. Because the exact solution performs poorly for a larger instance of the problem, two constructive heuristics are presented to solve the problem, with one being greedier than the other. The first heuristic, which is the sequential construction heuristic, adds a possible next destination that is based on the constraints given. However, the second heuristic constructs the route by considering all feasible next destinations and finally choosing one that has the highest return; hence, the term greedy. These heuristics were applied and they resulted in a pilot heuristic, where, instead of adding and constructing the route one-by-one, a partial solution computed by the pilot method was extended through a sequence of possible clusters. A historical incident that is handled by the local navy was taken as the case study to validate the proposed models.  
The dynamic or multi stage static CVRP with deadlines to emphasise the importance of rescuing the victims in floods was considered by [149]. The deadline is presented as a hard constraint, as opposed to a time window that only incurred a penalty in the objective function. A time flow between demand request and treatment time is added to the objective function weighted by priorities. Additionally, four priorities are defined, namely: the victim that can remain on the spot, victim that need to be rescued within 12 h, victims that need to be rescued within 6 h, and victims that need to be rescued immediately. From these priorities, the dateline and weight factors were determined. The objective of the problem is to minimise the total time flow, which is weighted by the priority of respective demands. The problem is formulated in LP and tested with various scenarios. In this dynamic setup, a multi-static problem is solved offline based on the new updated demand at each stage. Because of the complexity of the real scenario reflected, a MILP formulation is presented and solved by the proposed heuristic. The problem is solved by the proposed Best Time Flow Insertion heuristic, where it is adapted from the well known Best Fit algorithm in the bin packing problem.
## 7 Conclusions  
A new CDNG-MTM structure has been designed and characterised in order to develop an MTM inspired circular patch antenna. The proposed antenna has been derived from a circular patch antenna having operating frequency 6.2 GHz. The CDNG-MTM structure is loaded on the circular patch antenna and it functions as a controlling structure that can successfully manipulate the resonance behaviour of the patch. The CDNG-MTM loading has enabled the antenna to operate in two lower bands at 2.4 GHz and 5.2 GHz with percentage bandwidth of 1.63% and 13.15% respectively. The proposed CDNG-MTM structure loaded electrically small circular patch antenna enables dual-band operation with a compact size of 20 \(\times\) 20 mm\({}^{2}\) and is fabricated on low cost FR4 substrate. The loading of CDNG-MTM structure results in percentage miniaturisation of 60.7% with reasonable gain. The parametric analysis of the various design parameters has been done in order to understand the antenna's performance in terms of resonance frequency. From this analysis, it has been observed that the first resonance is caused solely by the CDNG-MTM and the second resonance has been obtained by the combined effect of patch and CDNG-MTM. Performance comparison of the proposed antenna with the other metamaterial loaded microstrip patch antennas shows that the proposed antenna is capable of giving better performance in terms of size, percentage bandwidth, and dual-band characteristics. It is also confirmed that complementary MTM structures are a better solution for patch antenna miniaturisation. The antenna can be easily tuned to various wireless application bands by changing the size and position of CDNG-MTM. This type of antenna is suited to application in wireless devices.
# Integrated GNSS/IMU-Gyrocompass with Rotating IMU. Development and Test Results
## 5 Results
### Results with Phase Measurment Signals from Multiple Satellites  
Consider the results under good visibility of GNSS signals from multiple satellites obtained using differential measurements of pseudorange, radial velocity, and phase single difference (10)-(12) to estimate the state vector (8). Here and below phase measurements (12) from minimum five satellites with elevations from 30\({}^{\circ}\) to 75\({}^{\circ}\) are used. By the satellite elevation we mean the angle counted from the horizon plane to satellite direction. Priority was given to the lowest satellites from this range because their phase measurements are more effective for heading updates: factor of angle \(\alpha\) in (15) grows drastically. The lower bound of elevation range was selected depending on the prevailing height of city buildings to reduce the multipath effects.  
Numbers of GPS satellites used for attitude determination in five channels of satellite receivers are presented in Figure 8. It can be seen that they often change in the receiver channels. Figure 9 presents the elevations and azimuths of satellites with these numbers. Asterisk shows the moment when the i-th satellite appears in visibility zone during path following. The data of i-th satellite started to be used as soon as it entered the allowed elevation zone (red solid lines in Figure 9).  
Figure 7: Heading and heading rate during the route.  
Figure 10a,b present heading errors during the stop and during motion using phase measurements from five GPS satellites. Here and below, heading error was determined compared to reference INS. As seen from the figures, the heading error after the completion of transients in the system including the heating reaches \(1.2^{\circ}\) and \(1^{\circ}\) for the stop (Figure 10a) and in motion (Figure 10b), respectively. Figure 10c present the heading error histogram during motion in a steady-state time interval between two vehicle manoeuvres.  
Figure 8: Numbers of GPS satellites in five channels of satellite receivers.  
Figure 10: Heading errors using data from five GPS satellites: (**a**) During the stop; (**b**) During motion (In lower plots, the ordinate axis is zoomed in); (**c**) The heading error histogram.  
Figure 9: Azimuth and elevation of GPS satellites. Red solid lines show the acceptable elevation zones.  
The estimated components of FOG error model (3): rhumb drifts and biases using differential measurements (10)-(12) are shown in Figures 11 and 12, respectively.