esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experimental Results and Discussion
### Performance Evaluation of the Deep Learning Models  
The trained CNN models were tested with the previously mentioned independent set, which consists of 75 samples from healthy subjects and 73 from glaucoma subjects. The results achieved per network architecture and fold have been included in Table 2, highlighting those corresponding to the best performance per architecture in terms of balanced accuracy, which is the arithmetic mean of sensitivity and specificity [46]. Analogously, Tables 3 and 4 show the performance obtained by evaluating the trained models on the REFUGE and DRISHTI-GS1 datasets. It is important to remark that these additional image sets have only been used for testing. Furthermore, as a representative example, we present in Figure 4 the validation accuracy and loss curves for the ResNet50 model, which achieved the highest test accuracy in one of the folds. These plots offer additional insights into the model's behavior during training, complementing the test performance metrics. While a comprehensive evaluation of the trained CNN models' performance is beyond the scope of this article, it can be seen that the models classify the images across all considered datasets with reasonable accuracy. Figure 4: Validation accuracy and loss per epoch for each of the five cross-validation folds using the ResNet50 model. Each line and color represents a different fold. The plots illustrate the model’s convergence behavior and consistency across folds, providing insight into the training dynamics and generalization performance. \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Network** & **Fold** & **Sensitivity** & **Specificity** & **Accuracy** & **B. Accuracy** & **F1 Score** \\ \hline VGG19 & 1 & 0.8767 & 0.9467 & 0.9122 & 0.9117 & 0.9078 \\ VGG19 & 2 & 0.9726 & 0.9467 & 0.9595 & 0.9596 & 0.9595 \\ VGG19 & 3 & 0.9041 & 0.9733 & 0.9392 & 0.9387 & 0.9362 \\
**VGG19** & **4** & **0.9863** & **0.9467** & **0.9662** & **0.9665** & **0.9664** \\ VGG19 & 5 & 1.0000 & 0.9200 & 0.9595 & 0.9600 & 0.9605 \\ VGG19 & \(\text{M}\pm\text{SD}\) & 0.9479 \(\pm\) 0.0543 & 0.9467 \(\pm\) 0.0189 & 0.9473 \(\pm\) 0.0221 & 0.9473 \(\pm\) 0.0225 & 0.9461 \(\pm\) 0.0243 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results obtained by training and testing with our dataset, according to different metrics. Results corresponding to the maximum balanced accuracy (B. Accuracy) are highlighted in bold. The last row of each architecture shows the mean (M) \(\pm\) the standard deviation (SD) for every metric.
## 2 Materials and Methods
### Measurement of the Generated Reactive Species  
The concentration of the reactive species in the solution after plasma treatment was measured to determine the influence of the plasma gas species on reactive species' generation. In this experiment, OH radicals, singlet oxygen, ozone, and hydrogen peroxide were measured. The concentrations of OH radicals and singlet oxygen were measured using electron spin resonance (ESR; JES-FA100, JEOL Ltd., Tokyo, Japan). The concentrations of ozone and hydrogen peroxide were measured via a colorimetric method using a pocket ozonometer (DR300, Hach Company, Loveland, CO, USA) and double-beam spectrophotometer (U-2900, Hitachi High-Tech Science Corporation, Tokyo, Japan). Anoverview of the plasma treatment is shown in Figure 1. Nitrogen, carbon dioxide, oxygen, and argon plasma at 3 L/min (standard) were used. The gas temperature of each plasma was controlled at 30, 45, 60, 75, and 90 \({}^{\circ}\)C at a distance of 2 mm from the plasma outlet. Thereafter, 200 \(\upmu\)L of the solution was dispensed in a 10.3 mm diameter well, and treated from a height of 16.5 mm above the liquid surface for 15 s.  
The spin-trapping reagents for the OH radical and singlet oxygen were 5,5-dimethyl-1-pyrroline-N-oxide (DMPO) [17] and 2,2,5,5-tetramethyl-3-pyrroline-3-carboxylate (TPC) [18]. These reagents were dissolved in Dulbecco's phosphate-buffered saline (DPBS) solution, and the concentrations of DMPO and TPC were fixed at 200 and 75 mM, respectively. Each 150 \(\upmu\)L of plasma-treated spin-trapping reagent was measured using ESR within 30 s. The ESR measurement was set to a microwave frequency of 9.425 GHz, modulation frequency of 100 kHz, sweep time of 2 min, magnetic field of 335.5 \(\pm\) 5 mT, and modulation width of 0.1 mT.  
The colorimetric method with ozone reagent (AccuVac\({}^{\text{(\textregistered)}}\) Mid-Range 0-0.75 mg/L, Hach Company, Loveland, CO, USA) was used to measure the ozone. Plasma-treated 120 \(\upmu\)L of DPBS was immediately mixed with the ozone reagent, and the ozone concentration was determined using a pocket ozonometer. The hydrogen peroxide was also measured using the colorimetric method based on the reaction of Fe\({}^{3+}\) with xylenol orange [19]. Fe\({}^{3+}\) is a product formed by the reaction between Fe\({}^{2+}\) and hydrogen peroxide. Plasma-treated 120 \(\upmu\)L of DPBS and 120 \(\upmu\)L of colorimetric reagent (200 \(\upmu\)M xylenol orange, 500 \(\upmu\)M ammonium ferrous sulfate, 50 mM sulfuric acid, and 200 mM sorbitol) were mixed. After 40 min of mixing, the hydrogen peroxide was quantified by measuring the absorbance at 586 nm.
# Ce- and B-Doped Silica Fibers for Monitoring Low-Energy Proton Beams on a Medical Cyclotron
## 4 Conclusions  
A technique for monitoring beam delivery on solid, liquid, and gas targets on a low-energy medical cyclotron has been demonstrated using doped silica fibers of different diameters (600 \(\upmu\)m and 200 \(\upmu\)m) and different dopants (cerium and boron). The fibers are easily attached to the outside of the target body and capture the prompt radiation during irradiation of the target. It has been demonstrated that the signal output of the fibers is a direct measure of the beam current on target for the smaller fibers, as the larger fiber seems to saturate in high radiation fields. The smaller diameter fibers are also ideal for future applications as more fibers can be mounted around the target body. The fiber signal also holds information about beam centering, beam steering and beam size. In addition, the fiber signal depends on the irradiated target material, potentially enabling a rapid test to confirm that the correct target material has been loaded into the target holder. As different beam energies and target systems will create different levels of prompt radiation, the sensitivity will need to be explored further. Overall, fibers offer an easy and cost-efficient monitoring solution for isotope production targets.  
Conceptualization, M.D., M.S., and C.H.; methodology, M.D, C.P., and C.H.; software, C.P.; validation, S.Z. and M.H.; formal analysis, M.H. and S.Z.; investigation, M.H. and S.Z.; resources, M.D. and C.H.; data curation, M.H. and C.H.; writing--original draft preparation, M.H. and C.H.; writing--review and editing, all authors; visualization, M.H. and C.H.; supervision, S.Z. and C.H.; project administration, M.D. and C.H.; and funding acquisition, M.D. and C.H. All authors have read and agreed to the published version of the manuscript.  
TRIUMF receives funding via a contribution agreement with the National Research Council of Canada. This research was funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada via the Discovery Grant program, grant number RGPIN 2016-03972. D-Pace provided partial salary support for [PERSON].  
We would like to acknowledge the TRIUMF TR13 cyclotron operators, [PERSON], [PERSON], and [PERSON] for controlling the cyclotron during each of these experiments and assisting with the installation and adjustment of the fiber optical system.  
The authors declare no conflict of interest.
## 1 Introduction  
The existence of sufficient bone volume is a factor for successful treatment with dental implants [1]. In cases with insufficient bone volume at the implant placement site due to bone absorption or trauma, implant threads can be partially exposed when the implant is placed into the bone tissue, and in these cases, guided bone regeneration (GBR) is applied to augment the bone tissue [2, 3]. Barrier membranes play a crucial role in GBR, because epithelial tissues recover more quickly than bone, and can invade into the space required for new bone formation and inhibit the process. Therefore, positioning the barrier membrane at the interface between the epithelium and periosteum retains the space required for bone healing.  
Absorbent membranes such an atelocollagen or polyglycolic acid display excellent operability and do not require removal, and are used as barrier membranes in periodontal therapy. These absorbent membranes are suitable for small bone defects; however, their application to the grafting of large bone defects is problematic because of their insufficient mechanical strength [4, 5]. Non-absorbent membranes like those made from titanium are superior in mechanical strength to absorbent membranes.  
Titanium membranes are used as barrier membrane for GBR because of their superior biocompatibility, mechanical strength, and operability. Therefore, various studies have demonstrated that they make and retain space well in grafts of large bone defects [6, 7, 8]. However, titanium does not have the ability to accelerate bone formation because it is bioinert [9, 10]. It is well known that titanium surface topography can be improved by various modification methods, including gsand or ceramic particles, acid etching, titanium plasma spraying, plasma spray coating, and other methods [11; 12]. Improved titanium surfaces have bioactive ability, and can promote cell adhesion and osteoinduction [13; 14; 15]. In particular, chemical methods such as acid etching or alkali treatment are often used because of their simplicity [16; 17; 18; 19]. A titanium surface modified by a strong acid or alkali solution can form an apatite layer when soaked in body fluid [17; 20; 21]. For this reason, these modified treatments are already being applied as dental implants and titanium plates used in bone reconstruction. Therefore, the creation of bioactive thin titanium membranes would be beneficial for GBR.  
Chemical treatments corrode the titanium surface, making it rough, extremely hydrophilic, and suitable for bone formation [22]. The structural change of chemical treatment is not a serious problem for solid titanium materials such as implant fixtures. However, the effects of these treatments on the surfaces of titanium membranes are not well established, and they may influence the structure and mechanical strength of these membranes. The purpose of this study was to investigate the influence of surface modification treatments on the mechanical strength and structure of titanium membranes.
# A Novel Algorithm to Optimize the Energy Consumption Using IoT and Based on Ant Colony Algorithm
## 6 Conclusions  
In this paper, we tried to improve the performance of energy savings in the Internet of Things based on the evolutionary algorithms. In order to achieve this purpose; the clustering method was applied to increase network life and control sensor nodes' energy consumption in the Internet of Things platform. The ant colony optimization algorithm was used to optimize the routing method, and acceptable results were observed compared to other algorithms. Using the proposed method, the consumed energy for 25 repetitions was about 28% of its original energy, and the mean variance for energy indicated that the energy of the nodes is close to that of others due to the use of all nodes for simulation. These achievements demonstrate that the proposed method can simultaneously decrease the consumption of energy and increase the lifetime of the nodes. Moreover, according to the comparison with other algorithms, the proposed method is about 50% more advanced than the known algorithms and saves more energy and reduces the number of dead nodes by about 81%. One of the shortages of this method is the lack of an optimization approach in the clustering stage. It is suggested to use the ant colony algorithm or other suitable approaches for the clustering stage as one of the possible future research avenues to continue this work.  
Conceptualization, B.S., and Y.Z.; methodology, B.S., and Y.Z.; software, B.S., and Y.Z., validation, B.S., and Y.Z., formal analysis, B.S., and Y.Z.; investigation, B.S., and Y.Z.; resources, B.S., and Y.Z., data curation, B.S., and Y.Z.; writing--original draft preparation, B.S., and Y.Z.; writing--review and editing, B.S., and Y.Z.; visualization, B.S., and Y.Z.; supervision, B.S., and Y.Z.; project administration, B.S., and Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Beijing Information Science & Technology University, grant number 2020 KYNH212.  
Not applicable.  
This study was supported by the Scientific research level improvement project to promote the colleges connotation development of Beijing Information Science & Technology University in 2020 (NO.2020 KYNH212).  
The authors declare that they have no known competing financial interests or personal relationship that could have appeared to influence the work reported in this paper.  
Figure 10: Comparison between the number of dead nodes in different algorithms.
###### Abstract  
Integrity is one of the key indicators used to characterize the performance of the global navigation satellite systems (GNSSs) and is closely related to user safety. In order to realize real-time global integrity monitoring, the BeiDou Global Navigation Satellite System (BDS-3) has realized the \"satellite autonomous integrity monitoring\" (SAIM) function in its satellites for the first time. BDS-3 SAIM has the monitoring functions of signal power, pseudo-range, satellite clock frequency and phase, but not the monitoring function of broadcast ephemeris. In this study, the long-term stability and distribution characteristics of BDS-3 SAIM monitoring data were analyzed by using the actual telemetry data for the first time. The results show that the SAIM monitoring data have good long-term stability and basically follow a normal distribution, which meets the design expectations. Meanwhile, in view of the fact that BDS-3 SAIM does not have the ability to independently monitor broadcast ephemerides, which may lead to the over-tolerance of BDS-3 to the probability risk of risks of integrity in the active space environment, a SAIM enhancement design for ephemeris monitoring is proposed, which integrates three relatively independent methods, with the ephemeris extrapolated from the previous cycle, and the ephemeris generated by autonomous orbit determination, inter-satellite link distance measurement data as reference data, respectively. The three methods are analyzed and verified. The results show that each of the three methods has advantages and disadvantages in terms of monitoring accuracy and resource dependence. The integration of the three methods can combine their complementary advantages and can also provide valuable as an important reference for engineering applications.  
BDS-3; SAIM; autonomous satellite ephemeris monitoring; GNSS +
Footnote †: journal: remote sensing  
Article  
Research on Autonomous Satellite Ephemeris Monitoring
## 4 Experiments
### Experimental Details
#### 4.1.3 Assessment of Indicators  
The object detection performance is primarily assessed based on both the detection accuracy and speed. In this paper, we conduct a comprehensive evaluation of the model's accuracy, efficiency, and robustness using metrics such as Precision, Recall, mean Average Precision (mAP), and Frames Per Second (FPS).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Experimental Environment** & **Configuration** \\ \hline Operating system & Windows 10 \\ CPU model & Intel i7-12700 KF \\ Memory & 32 GB \\ GPU model & NVIDIA RTX3080 10 G \\ Computing platform & CUDA 11.6 \\ Programming language & Python 3.8 \\ Development IDE & PyCharm 2022.2.2 \\ Deep learning framework & Pytorch 11.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Experimental configuration.  
Figure 14: Actual detection results using YOLOv8.  
Precision and recall are fundamental metrics for assessing the effectiveness of a model's detection capabilities. They measure, respectively, the accuracy of positive case predictions and the recognition rate of positive cases. These metrics are calculated as outlined in Equations (11) and (12).  
\[precision=\frac{TP}{TP+FP} \tag{11}\]  
\[Recall=\frac{TP}{TP+FN} \tag{12}\]  
Average precision (AP) serves as a metric for evaluating the model performance by computing the area under the Precision-Recall (P-R) curve, as illustrated in Equation (13).  
\[AP=\frac{1}{m}{\sum_{i=1}^{m}}\int_{0}^{1}P_{i}(r)dr \tag{13}\]  
The mAP_0.5 metric is derived from the average AP value when the Intersection over Union (IoU) threshold is set at 0.5, as illustrated in Equation (14).  
\[mAP_{0.5}=\frac{1}{n}{\sum_{i=1}^{n}}\,AP(i) \tag{14}\]  
In addition to the detection accuracy, the detection speed serves as a crucial indicator of the performance. The FPS reflect the processing speed of the model; a higher FPS signifies an increased processing speed, making it more suitable for real-time detection tasks.
# AMBIQUAL: Towards a Quality Metric for Headphone Rendered Compressed Ambisonic Spatial Audio
## 3 Subjective Listening Tests Using the MUSHRA Methodology
### Experiment 2-Multiple Point Audio Sources
#### 3.5.3 Conditions  
As in experiment 1, the Ambisonic audio samples were encoded using Opus 1.2 codec, channel mapping family 2 at various bit rates to produce a range of conditions. They were then rendered to a binaural format for presentation. Conditions under the tests included: \"Reference\", 3 rd-order Ambisonics audio: 3 OA512, 3 OA384, 3 OA256 and first-order Ambisonic audio: FOA128, FOA96, FOA64, FOA32. The last condition, encoded at 32 kbps (8 kbps per channel), was used as the hidden anchor.  
Details of encoding schemes and bit rates used in Experiment 2 can be found in Table 5.
# Software Defined Networking Architecture for Energy Transaction in Smart Microgrid Systems
## 5 Simulations and Results
### IPsec Encryption Simulation
Mesh network topology is created by creating data paths between the prosumer SDN node and the smart microgrid SDN node. As a result, the number of network nodes on the data path is further reduced, and the number of data path route options increases. The SDN nodes are configured to use dual internet connections for redundancy. Each node will connect to the Telkom fixed line network and an LTE ISP in the region. Figure 19 shows the layout of the optimized SDN architecture with the decentralized controller located in a hosting facility in Cape Town, Stellenbosch, and the SDN nodes with a directly connected data path (without going through the controller). The final data path availability equates to 99.9999%. The data path availability improves by 0.27%, reducing the data path downtime by 117 min per month. The controller algorithm improves flexibility by monitoring link stats and calculating new data paths in case of a link failure. However, the Floyd\(-\)Warshall algorithm takes longer than a second to switch the data path to the newly calculated route. This process indicates that the network element availability no longer determines data path availability but rather the SDN controller algorithm. A VPN configuration on the data paths between the SDN nodes (controller, prosumer, and smart microgrid) is implemented to encrypt the data on the data path. The decentralized controller placement and redundant link configuration improve the availability of the data path by reducing the number of network elements in the data path and providing alternative routes in the event of a failure. This design implementation improves the reliability of the SDN architecture. The mesh topology configuration with the controller algorithm improves the flexibility of the SDN architecture. The VNP configuration between all the SDN nodes improves the security of the SDN architecture. This applied design scenario proves that the optimized SDN architecture for TESMS improves reliability, flexibility, and security.
# Hybrid Engineered Water-Polymer Flooding in Carbonates: A Review of Mechanisms and Case Studies
## 3 Engineered Water Flooding (EWF)
### Wettability Modification  
In carbonate reservoirs, the main factors in the wettability modification are the potential determining ions (PDIs; Mg\({}^{2+}\), Ca\({}^{2+}\), and SO\({}_{4}\)\({}^{2-}\)), particularly SO\({}_{4}\)\({}^{2-}\), in the injected water, along with the reduction in salinity. The decrease in NaCl results in a reduced ionic density in the electric double layer, which formed on the positively charged carbonate's surface, making surface access of the PDIs easier. SO\({}_{4}\)\({}^{2-}\) adsorption makes the carbonate's surface less positive, and consequently the negatively charged carboxylic group in the oil is detached, making the rock more water-wet [11; 13; 94; 95; 96]. Hence, EWF results in improved microscopic displacement. However, the macroscopic efficiency is generally poor for EWF if the mobility ratio is unfavorable. This can result in early water breakthrough, meaning incremental oil recovery may not be achieved [97; 98; 95]. No EW EOR effect will be observed when the system is strongly water-wet under initial equilibrium conditions.
## 4 Experimental Study  
### Subsection  
In this experiment, an 1860-grade prestressed steel strand (Chongqing Zhiqiao Machinery Manufacturing, Chongqing, China) with a length of 80 cm was used as the test specimen. Tensile loading was applied to the steel strand using a WAW-1000 microcomputer-controlled electrohydraulic servo universal testing machine (Shanghai Hualong Test Instruments, Shanghai, China). To ensure that the gripped length of the specimen met the requirements (no less than three-quarters of the grip length) [29], the grip length was measured to be approximately 23 cm. Consequently, 20 cm of length was reserved at both  
Figure 5: Force–magnetism relationship at different lift-off heights z.  
ends of the steel strand to install aluminum clamps and secure the upper and lower grips. The magnetic signal output by the permanent magnet sensor was collected using a TD-8620 Tesla meter (Tunkia, Changsha, China). Figure 6 shows the experimental platform setup.  
Based on the nominal cross-sectional area of the steel strand specimen (140 mm\({}^{2}\)), the theoretical failure load of the steel strand was estimated to be approximately 260 kN. According to the specifications, the working load range for the steel strand should be set to 0.75 times its ultimate load. Therefore, the load range for the tensile test of the steel strand specimen in this experiment was set to 0-160 kN. With the lift-off height z kept constant, the test design loads were set to 100 kN, 120 kN, 140 kN, and 160 kN, with a loading step of 20 kN, which was also used for unloading. One cycle was defined as a complete loading and unloading process. Each test design load was repeated for four loading/unloading cycles to study the correlation between the magnetic signal parameters and the stress in the anchor cable steel strand at a constant lift-off height z under different test design loads.  
To ensure the effectiveness and reliability of the experiment, the following measures were taken: The loading rate of the universal testing machine was set to 5 mm/min, with an initial preload of 20 kN. When the load reached the predetermined value, it was held for 30 s. During the first 5 s of the holding period, no readings were taken in order to eliminate errors caused by lag in collecting the magnetic signal parameters due to steel strand deformation. Subsequently, five readings were taken each time and averaged to reduce the measurement error.