esa-sceva/satcom-chunk-collection huggingface dataset:
# Satellite Quantum Communications When Man-in-the-Middle Attacks Are Excluded
## 5 Conclusions  
The approach presented in this paper can be applied to key distribution, not only when using satellites, but also in other types of FSO-based systems. For example, in ad-hoc networks where the transmitter and receiver can visually identify each other, it may be straightforward to assess the absence of a man-in-the-middle and use PKD type protocols to establish a secret key. If the possibility of man-in-the-middle attacks can be excluded or monitored by conventional means, then PKD protocols can allow for secure key distribution using quantum communication methods at increased losses using similar or simplified hardware. In a practical key distribution scenario, it is worthwhile to have a better specification of the threat model and to devote efforts in closing physical side-channels, rather than attempting to defeat a hypothetical quantum adversary. Finally, we remark that using QKD hardware it may be possible to switch to a PKD protocol when the channel is assessed to be free of active attacks, and thus increase key distribution rates.
# New Methods of Series Expansions between Three Anomalies
## 2 Materials and Methods
### The Derivation of the Expansion Formula for the Relationship between True Anomaly and Mean Anomaly  
By substituting Formula (14) into Formula (8), we can obtain the trigonometric series expression between the mean anomaly \(M\) and the true anomaly \(f\). Then, around \(m=0\), we expand the obtained formula into a power series of \(m\). We expand the formula to \(m^{8}\).  
\[M=f+\sum_{n=1}^{8}d_{n}\sin nf \tag{27}\]  
\[\left\{\begin{array}{l}d_{1}=-4m+4m^{3}-4m^{5}+4m^{7}\\ d_{2}=3m^{2}-4m^{4}+4m^{6}-\frac{2m^{6}}{5}\\ d_{3}=-\frac{8m^{3}}{5}+4m^{5}-\frac{18m^{6}}{5}\\ d_{4}=\frac{5m^{2}}{5}-\frac{2m^{6}}{5}+\frac{14m^{6}}{5}\\ d_{5}=-2m^{5}+\frac{14m^{7}}{5}\\ d_{7}=-\frac{8m^{6}}{5}\\ d_{8}=\frac{8m^{6}}{5}\\ \end{array}\right. \tag{28}\]  
If the eccentricity \(e\) is taken as the parameter, the coefficient of the formula is as follows:  
\[\left\{\begin{array}{l}d_{1}=-2e\\ d_{2}=\frac{3e^{2}}{4}+\frac{e^{4}}{8}+\frac{3e^{6}}{64}+\frac{3e^{8}}{128}\\ d_{3}=-\frac{e^{3}}{5}-\frac{18m^{6}}{5}-\frac{18m^{6}}{16}\\ d_{4}=\frac{8e^{4}}{3}+\frac{3e^{2}}{3}+\frac{15e^{8}}{256}\\ d_{5}=-\frac{3e^{5}}{40}-\frac{e^{7}}{16}\\ d_{6}=\frac{7e^{6}}{192}+\frac{5e^{8}}{128}\\ d_{7}=-\frac{e^{7}}{56}\\ d_{8}=\frac{e^{8}}{128}\\ \end{array}\right. \tag{29}\]  
By substituting Formula (15) into Formula (24), we can obtain the trigonometric series expression between the true anomaly \(f\) and the mean anomaly \(M\). Then, around \(m=0\), we expand the obtained formula into a power series of \(m\). We expand the formula to \(m^{8}\).  
\[f=M+\sum_{n=1}^{8}g_{n}\sin nM \tag{30}\]  
\[\left\{\begin{array}{l}g_{1}=4m-6m^{3}+\frac{3e^{3}}{5}m^{5}-\frac{720}{50} m^{7}\\ g_{2}=5m^{2}-\frac{5m^{4}}{5}m^{4}+50m^{6}-\frac{5544}{50}m^{8}\\ g_{3}=\frac{3e^{3}}{5}m^{3}-\frac{95}{5}m^{5}+\frac{720}{50}m^{7}\\ g_{4}=\frac{103}{5}m^{4}+\frac{644}{50}m^{6}+\frac{20804}{45}m^{8}\\ g_{5}=\frac{1092}{5}m^{5}-\frac{12503}{50}m^{7}\\ g_{6}=\frac{1723}{5}m^{6}-\frac{32488}{50}m^{8}\\ g_{7}=\frac{4723}{50}m^{7}\\ g_{8}=\frac{5564403}{12850}m^{8}\\ \end{array}\right. \tag{31}\]  
If the eccentricity \(e\) is taken as the parameter, the coefficient of the formula is as follows:  
\[\left\{\begin{array}{l}g_{1}=2e-\frac{e^{3}}{5}+\frac{5e^{3}}{50}+\frac{102 ^{7}}{50}\\ g_{2}=\frac{5e^{2}}{5}-\frac{114}{124}+\frac{1124}{124}+\frac{88m^{6}}{50}\\ g_{3}=\frac{15^{3}}{5}-\frac{145}{124}+\frac{957}{52}\\ g_{4}=\frac{1044}{50}-\frac{8514}{50}+\frac{11213}{113}^{3}\\ g_{5}=\frac{1092}{500}-\frac{8907}{5000}\\ g_{6}=\frac{122240}{50}-\frac{7230}{4280}\\ g_{7}=\frac{472725}{50}\\ g_{8}=\frac{564403}{2850}\\ \end{array}\right. \tag{32}\]
# Design Optimization of Truss Structures Using a Graph Neural Network-Based Surrogate Model
## 4 Results and Discussion
### Seventy-Two-Bar Space Truss  
Figure 9 shows a 72-bar multi-story space truss consisting of 20 joints connected by 72 elements. To simplify the design process and make use of the structural symmetry, the 72 elements were classified into 16 groups. Thus, the number of design variables was reduced to 16, which represent the cross-sections of truss elements in each group. These cross-sections were chosen within the range of 0.1 in\({}^{2}\) to 3 in\({}^{2}\). The design parameters used to solve the size optimization problem are summarized in Table 4. The applied loading case is also presented in Table 5.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Modulus of elasticity & 10,000 ksi \\ Material density & 0.1 lb/in\({}^{3}\) \\ Allowable stresses & \(\pm\)25 ksi \\ Allowable nodal displacement & 0.25 in \\ \hline \hline \end{tabular}
\end{table}
Table 4: Design parameters of the 72-bar space truss.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{2}{c}{**Variables**} & \multicolumn{2}{c}{**Cross-Sectional Areas (in\({}^{2}\))**} \\ \hline \multirow{2}{*}{**Element Group**} & \multirow{2}{*}{**Members**} & **FEM-Based Optimization** & **GNN-Based Optimization** \\  & & **(Benchmark)** & **(**)** & **Optimization** \\ \hline
1 & 1 & 15.000 & 15.000 \\
2 & 2 & 1.000 & 1.000 \\
3 & 3 & 12.268 & 12.012 \\
4 & 4 & 7.644 & 7.660 \\
5 & 5 & 1.000 & 1.000 \\
6 & 6 & 1.000 & 1.000 \\
7 & 7 & 4.684 & 4.943 \\
8 & 8 & 11.202 & 11.088 \\
9 & 9 & 10.913 & 10.966 \\
10
## 4 Paleolakes and Groundwater
### Introduction, Method and Its Limitations
#### 4.1.2 Our Method to Detect Paleolakes  
A new method, independent of all others used till now, to detect paleolakes via their gravity signal (using the gravity aspects) has been proposed and tested in [3] for the Sahara and in [1; 4] with implications for geoscience and archaeology in the Sahara, specifically in North-Western Egypt (GSS). The method was mentioned in Section 2; here, we provide further details.  
The first step is to transform differences in the gravity anomalies to height differences to estimate roughly where the paleolake might be located and how large/deep it might be. We make use of EIGEN 6C4 and _ETOPO 1_ for this purpose.  
Then, taking the available archaeological literature, the positions of archaeological sites are utilized for a fine-tuning of the lake level, extent and shape such that the known archaeological sites would be at its shore for the given epoch. In our recent study [4], the positions of archaeological sites with remains of Holocene occupations between \(\sim\)10,500 and \(\sim\)7300 BP in the Western Desert of Egypt were utilized (following [24]). For the current study (see Section 4.3), the input data gathered in Table 1 include more detailed and more recent data for the southern part of the Egyptian Western Desert as compared with [24].  
The use of combed \(\theta\) to co-predict groundwater or paleolakes and paleorivers will now be extended outside North-Western Egypt. Here, we show, first of all, the strike angles over the entire country of Egypt (Figure 16a). Many areas contain combed \(\theta\), as expected, including the hypothetical paleolakes in the north-western part of the Egyptian Western Desert (Figure 16b,c). Moreover, other areas have often combed \(\theta\); see below. We cannot exclude the presence of groundwater, oil and gas or a combination of them (because they often appear together) in such locations. This alone would be a very interesting result for Egypt.  
Figure 16: Cont.  
How can we proceed to estimate the position, depth, shape and extent of a hypothetical paleolake?  
1. We transform the maximum existing gravity anomaly difference in the investigated area (read from the map of \(\Delta g\); here, from EIGEN 6C4) to the height difference. This provides a maximum estimate of the depth when the lake is fully filled with water.
2. We plot surface topography (here, _ETOPO I_) and select a few appropriate contour lines for a realistic range of the paleolake level estimate.
3. We plot the known locations of archaeological sites (Table 1 in this study, and [24] in [4]) into the maps of topography and check whether and how the sites correlate with the water. This is the final fine-tuning of the lake level. For complete figures, see [1,4]; one is reproduced here as Figure 16b, and one new figure is added as Figure 16c.
# Integrating AIoT Technologies in Aquaculture: A Systematic Review
## 3 Components of AIoT in Aquaculture
### AI Algorithms in Aquaculture
#### 3.2.3 Advanced Techniques in Visual Data Processing  
Artificial intelligence (AI) is effectively integrated into aquaculture through computer vision and image processing, which facilitate interpreting and analysing visual data collected from video feeds. These technologies facilitate the assessment of fish behaviour, the detection of abnormal patterns, and the identification of signs of stress or disease. Advanced techniques such as edge detection [98], image segmentation [99], and object tracking allow researchers and farmers to extract meaningful insights from video footage, including estimation of fish biomass and monitoring the movements of each fish. Studies such as those conducted by [PERSON] et al. [2] have demonstrated how computer vision enhances understanding fish health and behaviour, providing a foundation for developing responsive and data-driven aquaculture management strategies.
## 1 Introduction  
Head and neck cancer (HNC) is one of the most common malignancies worldwide. Approximately 650,000 patients are diagnosed annually with HNC worldwide [1]. Most HNCs arise in the epithelial lining of the oral cavity, orophnx, larynx, and hypopharynx. They share similar risk factors, including cigarette smoking and alcohol drinking [2].  
For patients with HNC, many strategies are utilized, such as surgery, definitive radiotherapy (RT), and chemoradiation (CCRT) [3]. HNC is relatively sensitive to radiation and anti-cancer drugs, such as cisplatin. Therefore, CCRT is increasingly used, not only in definitive settings but also as sequential treatment after induction chemotherapy of hypopharyngeal cancer, especially in locally advanced disease, where organ preservation, and lower rates of complications and mortality compared to surgery, can be achieved [4]. However, treatment-related toxicities, including oral mucositis, dysphagia, xerostomia, and weight loss occur, and may interfere and prolong the RT process with discomfort. Oral fixation has been considered important for RT dose reduction in adjacent normal tissues and toxicity prevention. Multiple conventional universal oral corks are manufactured for the benefit of oral fixation, and widely used in head and neck RT with low cost and easy production. Nowadays, a variety of bite blocks are commercialized, and their usefulness has been well-reported [5]. In external beam RT for cancer of the tongue, floor of the mouth, and lower gingiva, bite blocks can reduce the radiation dose to the upper gingiva or hard palate by supporting opening of the mouth. Bite blocks also immobilize oral tongue, which is important when treating HNC patients. Bite blocks can also reduce the radiation dose to adjacent normal tissue, such as salivary gland and mandible [6; 7].  
The usefulness of commercialized bite blocks in RT is well known, but studies on customized devices to fix the mouth and tongue are few. There is a growing interest in the application of three-dimensional (3D) printing to the RT process. The majority of studies focus on the creation of boluses [8; 9], masks [10; 11], and phantoms for quality assurance [12; 13]. Their clinical use in HNC RT is still under investigation. We aim to customize the bite blocks by establishing a 3D printing technology and examining its clinical feasibility and practicality.
## 1 Introduction
[PERSON] and [PERSON] presented an image alignment system with visual servo control by using a special design coplanar XXY stage, and each alignment motion was less than 1 s with accuracy of \(\pm 1\)\(\upmu\)m and \(\pm 5\)_arc_ sec [11]. [PERSON] _et al._ proposed an automatic locating and image-servo alignment design with four CCDs integrated with the coplanar XXY stage for an automatic laminating machine for the touch panel [4]. [PERSON] _et al._ designed an optical alignment system using the coplanar XXY stage integrated with dual CCDs. Although, [PERSON] _et al._ used a neural network method to increase the accuracy of their image-servo system [5]. However, the time taken for image pattern matching and image processing should be improved for real-world implementation. This study focuses on two key issues of the image-servo mask alignment system using the XXY stage. The first one is to deal with the nonlinear motion planning of the XXY stage due to coupling effects. Although the coplanar XXXY stage has some advantages such as smaller cumulative errors and quicker response than the stacked \(XY\theta z\) stage, motion planning of the XXY stage is difficult to compute as the X1-, X2- and Y-axes' movements are coupling and its kinematic relationship is nonlinear. Therefore, an ANN-based motion planning is proposed in this paper to solve this problem. The second one is to solve pattern recognition of the alignment marks as the positioning marks overlap. Because overlapped marks make it difficult to recognize each mark using the center of gravity method, another image processing and pattern recognition method robust to overlapping is needed to improve the accuracy of mask alignment. The generalized Hough Transform (GHT) is studied to find the dual positioning marks in this paper. The rest of this paper is organized as follows: in Section 2, the nonlinear kinematic relationship of the XXXY stage is discussed at first and then the supervised learning ANN and the back-propagation neural network (BPNN) is investigated to establish the relationship between the motor command'sand the actual position in the global frame. In Section 3, the positioning fiducial mark as well as the image-servo alignment, the image processing and pattern matching methods to extract the positions of the fiducial mark. Some alignment problems are discussed and a solution is proposed. In Section 4, after obtaining the positon of the two sets of the fiducial mark images, the position compensation and the angular orientation of the alignment part on the XXY stage can be calculated. Then, the compensation command for the XXY stage can be obtained according to the D-H transformation and they can then be fed back to the image-servo loop to achieve precision alignment tasks. In Section 5 we conclude with a summary of our contributions.
# Development of Alfa Fiber-Based Mortar with Improved Thermo-Mechanical Properties
## 4 Conclusions  
In this paper, mortar reinforced with alfa fiber for thermal insulating building construction was developed. The physical and thermal-mechanical properties of this new composite were investigated for AF mass ratio ranging from 0% to 5%. The analysis of the SEM pictures demonstrates that alfa fibers are randomly dispersed, separated, and well embedded in the mortar matrix which could indicate good bonds between AF and the surrounding solid matrix.  
The addition of AF into mortar makes the new composite lighter by reducing its density by up to 15%, increasing its porosity by around 51% and improving its thermal conductivity by up to 57%. Comparison between the measured thermal conductivity and that predicted by [PERSON]'s model shows a good agreement, within 9.6%. This finding can help in the future to limit the need for thermal conductivity measurements if one has sufficient a priori information. Moreover, good heat damping properties were reached as the thermal diffusivity of the mortar-AF composite is decreased by up to 49% compared to the reference material. The incorporation of 0.5% to 1% of AF mass content leads to a better homogeneity and more consolidated structure within the composite. An enhancement of its mechanical properties by about 10.45% for the flexural strength and 9% for the compressive strength was observed. The composite samples with AF mass content less than 4.8% could be classified as structural and thermal insulating materials. Above 4.8%, it could be used as an insulating material.  
In conclusion, this AF mortar composite, thanks to its simple manufacturing process, can be a very attractive material to be used in building in the Mediterranean region.  
Experiment planning, S.S.; experiment measurements and data analysis, S.S., L.B. and M.B.; theoretical models, L.B., M.B. and S.S.; writing-original draft preparation, S.S. and L.B.; writing-review and editing, L.B. and B.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
## 2 Materials and Methods  
### Description of Trial Site  
A long-term field trial was established in the year of 2001, in the middle of the Loess Plateau, China (35\({}^{\circ}\)39\({}^{\prime}\) N, 107\({}^{\circ}\)51\({}^{\prime}\) E). Here, the altitude is approximately 1297 m, the temperature range is \(-\)22.4-39.6 \({}^{\circ}\)C, the annual rainfall is around 480-660 mm, and the growing season is 255 days per year. The soil is Calcisols layer soil [30]; soil organic C was below 1.70 g kg\({}^{-1}\), and Olsen phosphorus (P) was below 25 mg kg\({}^{-1}\)[22].  
The trial was set up with a rotation system of maize, winter wheat, and soybean in 2001. A conventional tillage (CT) process, whereby the top soil (20 cm) is filled using a Chisel flow in September or October once a year, was carried out in the same way with local farmers. The CT was taken as the control treatment. Three conservational practices were employed in the study, including conventional tillage plus previous crop residue (CTR), no-tillage (NT), and no-tillage plus previous crop residue (NTR) [22]. For each treatment, there were four replicates randomly arranged with a total of 16 plots. The size of the plot was 4 m \(\times\) 14 m (56 m\({}^{2}\)) with 1 m space between plots.  
Local farmers sow maize, winter wheat, and soybean varieties according to traditional practices. The growth stage for maize extends from late April to late September, followed by the sowing of winter wheat, which is harvested in late June or early July of the subsequent year. Soybean is then sown immediately after and harvested in October, followed with a 6-month period of bare fallow. Maize is sown again to initiate a new growth cycle after a fallow period.  
No irrigation is applied, and 300 kg/ha of diammonium phosphate (DAP) is applied to both the winter wheat and maize treatment before sowing. Additionally, 150 kg/ha of CO(NH2)2 is added to winter wheat at the jointing stage, while 300 kg/ha is applied to maize during its late growth stage. For soybean, only 63 kg/ha of phosphorus (P2O5) is applied before sowing.
## 5 Performance Evaluations and Discussion
### M-QAM 4-SSB Uncoded System Using Shadow Equalizer Evaluation and Complexity Analysis
#### 5.1.2 Performance Evaluation  
Figure 6 shows the 4-QAM 4-SSB shadow equalization iteration performance compared to the equivalent scheme in uncoded system.  
Overall, the 4-QAM 4-SSB OFDM performance can reach SNR efficiency close to equivalent amount information as of 16-QAM after the fifth iteration as verified in our prior work in 4-SSB [11]. However, the 4-QAM OFDM performs worse than 4-QAM 4-SSB because OFDM scheme carries less amount of bit compared to 4-SSB.  
Specifically, the iteration process in 4-QAM 4-SSB shadow initially estimated by \(\tilde{\mathbf{d}}_{n}\) since no previous symbol is available with the steady tendency of SNR. In the second iteration, the first estimation is fed as the previous symbol and the \((n-1)\)th iteration is slightly improved compared to the first iteration. In the third iteration, the symbol has good SNR for estimation which is equivalent to 16 QAM-OFDM performance by 20 dB SNR. Similarly, the fourth iteration is equivalent to bit error rate of 16-QAM till 25 dB SNR. In the last iteration, the 4-QAM 4-SSB has the peak efficiency of bit error rate as it can achieve bit error to \(10^{-3}\) at 25 dB SNR but the equivalent scheme of 16-QAM OFDM still performs better with the same SNR. The red line demonstrates the performance of constellation of 4-QAM modulation over OFDM.  
Besides, to verify the efficiency of the proposal for practical deployment, we take turbo code as a classical coding approach for the transport channel, and we fix the Mean Square Error (MSE) value as 10% for the equalizer's channel estimation used by equalizer to model imperfect equalizer [11]. Specifically, in Figure 7, we compare the BER performance of different modulation schemes in the coded case using turbo code with comparable information data-rates.  
Figure 6: 4-QAM 4-SSB Shadow equalization iteration evaluation compared to the relevant modulation schemes.  
We show that the coded 16-QAM with code rate \(R=1/2\) outperforms the other modulation schemes; however, it also represents the lowest spectrum efficiency with only two information bits per channel use. In contrast, the 4-SSB 16-QAM (\(R=1/2\)) and 64-QAM (\(R=2/3\)) modulation schemes represent the same bit rate with four information bits per channel use, and the evaluation result demonstrates that after SNR = 25 dB, the 4-SSB 16-QAM outperforms the 64-QAM by achieving a gain of 3 dB at BER = \(10^{-3}\).
# Satellite Quantum Communications When Man-in-the-Middle Attacks Are Excluded
## 3 Discussion
### Spontaneous Parametric Down Conversion (SPDC) Photon Pair Source  
For the QKD protocols considered here the SPDC photon pair source was assumed to be an entangled photon pair source performing the BBM92 protocol [15; 16]. The Micius satellite demonstrated an entangled photon pair source in orbit [17; 18] and the SpooQy-1 nanosatellite will demonstrate a miniaturized device in orbit in 2019 [19]. The PKD protocols with this setup can use the same hardware or a simpler correlated (heralded) photon pair source, with unit visibility, such as the miniaturized device flown on the Galassia nanosatellite [20]. To avoid synchronising reference frames the two-state encoding could be in left and right hand circular polarization.  
Protocols using pair sources require two detections i.e., one of the pair must be detected at the source and the other of the pair detected at the receiver. The total detection efficiency at the source was assumed to be 25% (i.e., there was a system loss of \(-6\) dB). The main effect of this approach is that the quantum bit error rate (QBER) partly becomes a function of the accidental rate of coincident detection between the two detectors. This accidentals rate is given by \(S_{1}\times S_{2}\times\tau\)[21; 22], where \(S_{1}\) and \(S_{2}\) are the singles rates observed at the detectors, and \(\tau\) the timing coincidence window.  
In this study, we assume that the source was capable of producing photon pairs at a raw rate of \(1\times 10^{8}\) per second into a single spatial mode, and that the timing resolution was 1 ns, which are readily accessible [23]. This leads to a QBER that is between 3% and 4%; this QBER has a linear relationship with the timing window--faster electronics will lead to smaller QBER. An advantage of using photon pairs is that the probability of multi-photon emission is insignificant (similar to single photon sources), leading to a smaller percentage of the raw key being discarded in privacy amplification.