esa-sceva/satcom-chunk-collection huggingface dataset:
# Quantum Computing for Healthcare: A Review
## 4 Requirements of Quantum Computing for Healthcare
### Quantum Communications Networks  
Quantum communication (QC) is a quantum technologies subbranch that concerns the distribution of quantum states of light for accomplishing a particular communication task [73; 74]. The potential use of QC in commercial applications has been gaining popularity recently. Two leading technologies of QC include quantum key distribution (QKD) and quantum random-number generation (QRNG). QKD enables private communication by allowing remote entities to share a secret key, and together, these promise to enable the perfect secrecy protocol to provide resistance to external attacks. The goal of the quantum Internet [75; 76] is to develop a quantum communication network that connects quantum computers together to achieve quantum-enhanced network security, synchronization, and computing. Qirg is an IETF quantum Internet research group that is responsible for the standardization process of the quantum Internet.
## 3 Materials and Methods
### Evaluation Methodology
#### 3.6.2 Visualization and Analysis Tools  
We developed several visualization tools to analyze attack impacts:  
* **Combined Video Generation**: Synchronized display of multiple sensor feeds (RGB, DVS, depth, and LiDAR) with attack state indicators* **Trajectory Plots**: Visualization of actual vs. perceived trajectories during GPS spoofing
* **Statistical Analysis**: Histograms of steering distributions and sensor metrics under different attack conditions
# Comparison of Diagnostic Accuracy of Physical Examination and MRI in the Most Common Knee Injuries
###### Abstract  
Purpose: This study evaluated the diagnostic accuracy of physical examination and magnetic resonance imaging (MRI) in knee injuries. Methods: Ninety-six patients at a regional hospital were included in the study. Each participant underwent a physical examination in which menisci and ACL were evaluated. Knee joint MRI was collected from each patient. Physical examination and MRI scans were then compared with knee arthroscopy findings as a golden standard for meniscal and ligamentous lesions. The data were analyzed and specificity and sensitivity were calculated and correlated on receiver operating characteristics (ROC) curves. Results: Knee arthroscopy diagnosed 32 total ACL ruptures, 45 medial meniscus and 17 lateral meniscus lesions. Three patients were diagnosed with bilateral meniscal lesions. The highest sensitivities were the McMurray test (87.5%) for medial meniscus (MM) and the Thessaly test (70%) for lateral meniscus (LM). The most sensitive ACL test was Lachman (84.5%), whereas, the pivot shift and Lelli tests were the most specific (98.5%). MRI was highly sensitive for MM (96%) with specificity of 52%. MRI showed lower sensitivity (70%) and higher specificity (85.5%) for LM. The specificity of MRI for ACL rupture was 92%, with sensitivity only 75%. Conclusion: McMurray and Apley tests for meniscal lesions seem the most appropriate in daily practice. A combination of lever signs, pivot shifts (PSs) and Lachman tests showed the best sensitivity and specificity in detecting ACL deficiency, and was superior to MRI.  
physical examination; MRI; knee; meniscus; ACL; knee injury +
Footnote †: journal: Medical Imaging
## 3 Challenges and Issues in Hybrid AC/DC Microgrid
### Operational Challenges  
The AC and DC subgrids are tied through interlinking converters and bidirectional power-sharing, which ensures the stability of the network. A hybrid microgrid works in two modes of operation: grid-connected and islanded. In islanded mode, the lack of frequency support to the AC sub-system and the absence of voltage support to the DC sub-system makes the stability of a hybrid microgrid the most important issue to be addressed. The major operational challenges for hybrid AC-DC microgrids have been listed below.  
Power-sharing under different operational conditions is a major issue regarding the stability of hybrid microgrids. It is dependent not only on the AC sub-system but also on the DC sub-system due to the power exchange across the interfacing converter. Many research articles have investigated the power-sharing in hybrid microgrids based on the droop control for all distributed generators. In [10], the authors present the operation of a hybrid AC/DC microgrid where the droop scheme is designed to control the converter operation and losses during unloaded and heavily loaded scenarios. It was found that the power shared affects the dynamics of AC and DC subgrids, creating a stability issue for the whole system. Moreover, the use of a single converter decreases the reliability of the system. In [11], the authors demonstrate the idea of multiple converters to increase system reliability. Still, the drawback is that it makes the AC sub-grid more susceptible to power changes, decreasing the overall performance. In [12], the authors propose the usage of an energy storage system to improve power transfer between sub-grids.  
The parallel operation of multiple interlinking converters is another important challenge. The operation of converters has many advantages such as improved reliability of the system, low rating converter for high power applications, etc. However, parallel ICs operation generates serious issues such as non-linear load behavior of converters, re-synchronization required after different grid operational modes, and the circulating current issue between parallel operation [13].  
Figure 2: Challenges of hybrid AC/DC microgrid.  
A large gap between generation and load can lead to voltage and frequency problems because microgrids have the tendency to transition between grid-connected mode and islanded mode. Due to the interconnection of a large number of distributed generators, \"plug and play\" can be a serious problem. The generation and load uncertainties are a big challenge to the optimal dispatch and operation of a microgrid. Much research is needed for the usage of stochastic optimization to resolve these uncertainties, and these techniques must also include the impact of interlinking converters on overall optimization. A robust optimization model also needs to be developed for the operation of microgrids [14].  
Another critical aspect of the operation of hybrid microgrids is the control and load management strategy during islanded and grid-tied connections, discussed in detail in the last section of this paper.
# Anomaly Detection in High-Dimensional Time Series Data with Scaled Bregman Divergence
## 2 Materials and Methods  
An anomaly, or outlier, is an observation that significantly deviates from the majority of the data, often indicating that the distribution of data containing the anomaly differs from that of normal data. So, the anomaly detection aims to identify such patterns, which may signify critical information, by modeling the underlying probability distributions of the data and distinguishing anomalies from normal observations.  
We use two datasets, a training set \(\{x_{j}^{tr}\}_{j=1}^{\eta_{tr}}\sim p_{tr}(x)\), which consists entirely of normal samples, and a test set \(\{x_{i}^{te}\}_{i=1}^{\eta_{te}}\sim p_{te}(x)\), which may include both normal and anomalous samples, where \(p_{tr}(x)\) and \(p_{te}(x)\) are the respective probability density functions. The training set is used to learn model parameters that capture the distribution of normal data, under the assumption that they do not contain any anomalies. By comparing the test data distribution against the learned normal data distribution, anomalies can be identified as data points that significantly deviate from the expected normal distribution. Individual density estimation is often impractical in high-dimensional data. In this work, we focus on the density ratio between the training and test data, \(w(x)=\frac{p_{tr}(x)}{p_{te}(x)}\), which eliminates the need for the estimation of individual density functions. Next, we will discuss how to integrate the density ratio with divergence functions to develop a more effective framework for anomaly detection.
## 2 Materials and Methods
### The Study Area  
The mine, a large metamorphic iron ore deposit in Anhui, China, stretches over 4 km with a maximum depth of \(-\)862 m, the geography of which is shown in Figure 2. The majority of the ore deposit area is covered by Quaternary deposits. The main rock types include granite, gneiss, iron ore, and diabase. Among them, the gneiss rock mass has a good quality, while the ore body, granite, and diabase rock masses range from moderate to good quality. The rocks in the mining area are mainly characterized by stratified and disseminated structures, with blocky structures being secondary. The overall stability of the ore rocks is good. The mine uses a mining method of subsequent backfilling of the stage empty field and fan-shaped medium-deep hole drilling and blasting. A large number of residential areas and offices are distributed around the mining area, and blasting vibrations can affect the safety of buildings.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Category**} & \multirow{2}{*}{**Max Charge of Per Delay (kg)**} & **Vertical** & **Horizontal** & **X-PPV** & **Y-PPV** & **Z-PPV** \\  & & **Distance (m)** & **Distance (m)** & **(cm/s)** & **(cm/s)** & **(cm/s)** \\ \hline \multicolumn{6}{c}{Training dataset (80\%)} \\ \hline Min & 180.000 & 250.000 & 143.000 & 0.035 & 0.031 & 0.071 \\ First quartile & 240.000 & 300.000 & 260.000 & 0.073 & 0.061 & 0.132 \\ Median & 265.000 & 375.000 & 455.000 & 0.105 & 0.093 & 0.169 \\ Mean & 269.211 & 348.684 & 408.649 & 0.107 & 0.099 & 0.191 \\ Third quartile & 285.000 & 400.000 & 530.000 & 0.134 & 0.125 & 0.240 \\ Max & 412.500 & 400.000 & 673.000 & 0.291 & 0.274 & 0.471 \\ \hline \multicolumn{6}{c}{Testing dataset (20\%)} \\ \hline Min & 180.000 & 250.000 & 159.000 & 0.039 & 0.032 & 0.066 \\ First quartile & 230.000 & 337.500 & 192.000 & 0.063 & 0.056 & 0.133 \\ Median & 265.000 & 375.000 & 456.000 & 0.074 & 0.075 & 0.163 \\ Mean & 264.333 & 355.000 & 392.133 & 0.100 & 0.113 & 0.173 \\ Third quartile & 290.000 & 400.000 & 518.000 & 0.124 & 0.110 & 0.179 \\ Max & 397.500 & 400.000 & 667.000 & 0.234 & 0.320 & 0.349 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The datasets of blasting vibration for the prediction of X-PPV, Y-PPV, and Z-PPV.  
Figure 2: Geographical location of the study area.
# Feed Rate Variation Strategy for Semi-Conical Shell Workpiece in Ball Head End Milling Process
## 3 Design of Feed Rate Variation Strategy
### Design of Discrete Feed Rate Variation  
Based on the results and discussions mentioned above, each contour tool path can be divided into five segments, no matter the height of the contour located. The segments located at the beginning and the end of each contour are the low feed rate segments due to the vibration response. The segment located at the middle of each contour is another low feed rate segment due to the cutting force. Two rest segments located between adjacent low feed rate segments are two high feed rate segments. Consequently, a discrete feed rate variation (DFV) is proposed based on the design and result of CFV.  
As shown in Figure 13 with orange lines, the piecewise DFV is proposed based on the five segments. The length of the first and last segments are set as 20% of the total length of each contour. The length of the middle segment is set as 5% of the total length of each contour, and the rest parts are set as high feed rate segments. Comparing with the use of CFV, the time loss with the use of DFV is less than 15% and the lower the contour located; the less time is lost. The maximum cutting force occurs from the contour at LP; near 5% over the threshold is acceptable. The maximum vibration response also occurs from the contour at LP with about 30% over the threshold. This can be explained by the additional modal sensitive positions located a little far from the end of the workpiece, as shown in Figure 7. In general, the performance of DFV is acceptable, but the double increase or decrease of the feed rate in the switch position may be hardly achieved by the servo drive motor and control system of the machine tool. Considering the machine capability, an improved discrete feed rate variation (IDFV) is obtained by replacing the sudden step switch in the DFV as the linear switch. The period of each linear switch last 5% of the total length of each contour, as shown in Figure 13 with green lines. It can be observed that the maximum of the cutting force and vibration from IDFV are lower than that from DFV and the consuming time stay the same. Hence, the machining process with IDFV is more stable, and it is chosen to be used in the practical milling experiment.
## 7 Results and Discussion  
An IEEE-33 test bus system is used to validate the performance and scalability of the presented BWO algorithm and the outcomes are then compared to the standard PSO approach. The DLF method is primarily applied to a test bus system to determine unstable buses by evaluating voltage limit breaches in line with the voltage stability indices derived analytically using Equation (7). The P-Index is formulated using Equation (6), considering the VSF index, demonstrating weak buses as given in Table 1. The scalability of DGs is optimised using the objective function by minimising Equation (8) to integrate appropriate-sized DGs at buses determined using Equation (6). When WTGS-DGs are added to the system, the voltage profile improves, as seen graphically in Figure 5. Incorporating appropriately sized WTGS-DGs enhances the P-Index for all buses and stabilises the VSF, as illustrated in Figures 6 and 7, respectively.  
The BWO approach is then used to optimise the number of EV load capacities such that the enhanced voltage at buses stays within the permissible range by incorporating additional EV loads with minimal impact on active power losses. The preferred position and appropriate size of EV loads are optimised using quadrant operation of EV charging, and the implications are graphically displayed in Figures 5-7 for voltage profile, P-Index, and VSF, respectively. The voltage profile is further improved despite the addition of EV loads, as shown in Figure 5, because EV loads not only add demand to the network but also provide reactive power to maintain network voltage stability. In summary, the network voltage profile is the highest possible in this scenario and the system loss rate is the lowest possible. Table 1 outlines all the voltage level profiles in p.u. and VSF values for all of the buses for three distinct scenarios following WTGS-DG as well as the EV load.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & \multicolumn{3}{c}{**Voltage (p.u.)**} & \multicolumn{3}{c}{**VSF (Index Value)**} \\ \hline \hline
**Bus** & & & **With DG** & & & **With DG** \\
**Number** & **Base Case** & **With DG** & & **and EV** & **Base Case** & **With DG** & **and EV** \\  & & & **Loads**  
+++ ==WARNING: Truncated because of repetitions==
& & & **Loads** \\ \hline  
++
## 5 Conclusions  
We analyzed the effects of aberrations on the CE of spatial light coupled into SMF based on single-aberration spatial characteristics in this study. We found that the effects of the same type of aberrations on the CE are similar, but the CE values are different as the spatial frequency changes. We also assessed the influence of the AO system residual on CE and determined the corrected residual margins of FSM and DM for a FSOC system under different coupling threshold conditions. Finally, we validated our analysis results with a series of experiments.  
Based on the analysis results of the influence of different aberrations on CE in this paper, researchers can focus on controlling the aberrations which have great influence on CE in the design and alignment of optical systems, so as to minimize the impact of the optical system on CE. For ALTD applications such as FSOC and GSL, researchers can make better residual margin allocation for AO systems in these applications based on the results of this study. Through selectivity, devices such as FSM, DM and WFS can better meet the system requirements, so as to improve the correction effect of AO system, and ultimately achieve the improvement of CE. In addition, the results presented in this paper also have reference significance for the application of wavefront sensing technology based on single aberration mode detection, such as holographic wavefront sensor designs.  
We plan to conduct further research, using WFS to directly detect the aberration generation of the 1550 nm coupled beam and make the DM operate in closed loop mode, so as to strengthen the validation of the research results of this study. What's more, we are interested in studying how to apply Extended Nijboer-Zernike polynomials to our model in the follow-up work, so as to establish a new method which can simultaneously analyze the impact of beam intensity and phase changes on coupling efficiency. In addition, considering that we use the Gaussian function approximation to represent the fundamental mode field in this paper, which may cause some errors in the calculation results, it is also worth studying how to use Bessel function to discuss the content of this paper.  
Conceptualization, Y.L.; methodology, J.W., S.G.; software, L.S.; experiments design and performing, Y.L., L.M., K.Y.; writing, Y.L. and C.G.  
This work was supported by the National Natural Science Foundation of China (No. 61605199).  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Materials Properties and Selection
#### 2.1.2 SS 316L  
SAE 316L grade stainless steel (SS 316L) is the second most common austenitic stainless steel after 304/A2 stainless steel. Its primary alloying constituents, after iron, are chromium (between 16-18%), nickel (10-12%), and molybdenum (2-3%), with small (<1%) quantities of carbon, silicon, phosphorus, and sulfur also present. Molybdenum adds corrosion resistance to the alloy, and the cold-worked Mb exhibits a high yield and tensile strength.
# Design and Implementation of Inverse Kinematics and Motion Monitoring System for 6 DoF Platform
## 7 Conclusions  
This study discussed the inverse kinematics of a six-axis motion platform, and the development of a monitoring system. The main contribution of this study is the design of a 6 DoF crank arm mechanism to replace the expensive 6 DoF linear actuator Stewart platform, 3 DoF crank arm platform, and 4 DoF crank arm platform, and the result of obtaining a comparable movement experience to the Stewart system. The algorithm was applied to the motion control of a 6 DoF platform to control the elongation of the virtual cylinder and to determine the platform attitude required by the 6 DoF platform. Unlike the conventional method, which relies on approximation to obtain the required angle, this study proposed a more accurate, real-time, and highly dependent processing method. In addition, this study used LabVIEW to create a set of testing equipment that integrates different sensors and jigs to read the angle, angular velocity, displacement, and linear acceleration of the platform in motion. Subsequently, the differential equation and sampling rate were used to calculate the angular acceleration and linear velocity. The testing equipment data were transmitted to the platform computer via RS-485 or RS-232 digital communication, allowing the platform to control the state of motion at all times. Finally, the experimental results prove the proposed algorithm capable of improving the operation of the platform stroke and thus applicable to simulators with higher specification requirements. Moreover, the implementation of the platform was based on the PID controller. Because of its simple structure, strong robustness, and good stability, the PID controller is still widely used in various fields of industrial control. However, the modern control theory of the platform is not the main topic of this study that will be considered to evaluate the design in future work.  
**Funding:** This research received no external funding.  
**Conflicts of Interest:** The author has no conflict of interest to declare.  
Figure 19: Measured acceleration responses: (**a**) x axis, (**b**) y axis, and (**c**) z axis.
# Microstructure of Mortar with Ballast Waste as a Cement Replacement
## 3 Results and Discussion  
### Initial Samples  
#### 3.1.1 Mineralogical Composition  
Sample B-1. The mineralogical analysis is presented in Table 1. The composition is dominated by silicates, which are the most abundant minerals. Notable phases include biotite, quartz, kaolinite, and hematite. In terms of feldspars, the sample contains orthoclase (potassium aluminosilicate) and albite (sodium aluminosilicate), along with a fraction of amorphous material.  
Sample B-2: Its mineralogical composition is similar to that of Sample B-1, but with lower quartz content. Additionally, albite is absent, being replaced by labradorite (calcium aluminosilicate) (Table 1).  
The ballast residues, rich in silicates (quartz, feldspars, phyllosilicates), contribute to ordinary Portland cement (OPC) (which is rich in alkalis) by introducing a silicon- and aluminum-dominated composition. This enhances cement properties, particularly workability, leading to the production of ecological pozzolanic cement. This process  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline
**Ballast Waste** & **R\({}_{\text{B}}\)** & **\(\chi^{2}\)** & **Biotite (\%)** & **Kaolinite (\%)** & **Quartz (\%)** & **Orthoclase (\%)** & **Albite (\%)** & **Amorphous Material (\%)** & **Hematite (\%)** & **Lbradorite (\%)** \\ \hline B-1 & 16.5 & 3.3 & 30 & 7 & 29 & 6 & 14 & 10 & 4 & n.d. \\ B-2 & 12.3 & 3.5 & 35 & 6 & 21 & 5 & n.d. & 6 & 4 & 23 \\ \hline \end{tabular}
\end{table}
Table 1: Rietveld quantification of the studied samples (RB and X\({}^{2}\) = agreement factors; n.d. = not detected).  
promotes sustainability by incorporating waste and recycled materials into the cement manufacturing cycle, replacing naturally extracted resources, some of which are becoming scarce. The grinding and fineness of the material disrupt crystalline structures, increasing specific surface area and thereby facilitating the pozzolanic reaction [49].
###### Abstract  
In this study, imidazole derivative-based new ionic liquids were investigated as corrosion inhibitors. These new ionic liquids (ILs) are 1,3-dipropyl-2-(2-propoxyphenyl)-4,5-diphenylimidazole iodide (IL1) and 1,3-dibutyl-2-(2-butoxyphenyl)-4,5-diphenylimidazole iodide (IL2). The corrosion inhibition effects of two new ILs were observed on carbon steel in brackish water media (1% NaCl solution). Carbon steel coupons were exposed to 1% NaCl solution with various concentrations of ILs. Corrosion inhibition effects were tested by the electrochemical impedance spectroscopy (EIS) method and the Tafel method at various temperatures ranging from 25 \({}^{\circ}\)C to 55 \({}^{\circ}\)C. The results showed that ILs have potential as corrosion inhibitors and the adsorption mechanisms of IL1 and IL2 on carbon steel surfaces were also determined, which followed the Langmuir adsorption isotherm model. Acquisition of \(\Delta\)G\({}_{\text{ads}}\) values of IL1 and IL2 were \(-\)35.04 and \(-\)34.04 kJ/mol, respectively. The thermodynamic data of the ILs show that semi-chemical and or physical adsorptions occurred on carbon steel surfaces.  
new ionic liquids; imidazole derivatives; inhibitor corrosion; brackish water +
Footnote †: journal: Applied Sciences