esa-sceva/satcom-chunk-collection huggingface dataset:
# Optical Realization of Wave-Based Analog Computing with Metamaterials
## 3 Other Emerging Approaches
### Random Medium  
Another counterintuitive approach is by employing random medium rather than deliberately designed structures with certain scattering properties to perform wave-based analog computing. In the study of [PERSON] et al. [146], it consists of two subsystems: a chaotic cavity as the random medium and a reflect-array metasurface playing the role of wavefront shaping device. As shown in Figure 8a, a plane impinging wave with input vector \(X\) is modulated by a wave front shaping device and subsequently propagating through a random medium to obtain the desired output wave front. For controlling spatial degree of freedom, the incident wave front is divided into four segments, marked by A to D (see Figure 8b). Here, an indoor cavity of irregular geometry is used as the random environment characterized with the Green's function, which plays the key role of analog computing by enabling each segment of wave front to contribute to each output point. The reconfigurable metasurface contains 88 units whose reflection coefficient can be tuned from \(-1\) to \(1\). Figure 8c shows the experimental configuration in which microwave absorbers are installed to limit the reverberation of the cavity.  
Figure 8: (**a**) Schematic the random medium scheme for wave-based analog computation; (**b**) tamed contribution of segment \(D\) to observation points; (**c**) experimental setup in a metallic cavity of irregular geometry. Adapted with permission from [146], APS, 2018.  
Figure 7: (**a**) Schematic of sinusoidally modulated of split-ring resonators; (**b**) transmission spectrum with different incident angle; (**c**) schematic of asymmetric metasurface with a horizontally misplaced array of metallic wires for the first-derivative operation; (**d**) rotated metasurface for 2D second-derivative operation. (**e**) Input image and (**f**) output image of 2D edge detection for linear polarized wave. Adapted with permission from [144], APS, 2018.
# Performance of Graph and Relational Databases in Complex Queries
## 3 Test Database  
Our test database is a general example from enterprise information systems, where different types of information are associated with customers. In the example, a customer may have several targets for which different types of works and items are associated. When sending an invoice to a customer, the stored works and items must be found and calculated which may require complex navigation among stored data. As it is an invoicing database, one of the most important use cases is the calculation of the price for a customer invoice. This is achieved by calculating the used time for work of different work types and the price of the items used when working. Invoices might also have relations to other invoices if several invoices are sent to the customer.  
The relational database has 10 tables. The basic tables customer, invoice, target, work, worktype and item represent entities of the application domain. These tables contain the customer information, customer's invoices, the target (or project) where the work is performed, a listing of each work, and a listing of different worktypes with different prices and information about the items used for each work. Relationships between the entities are stored in relationship tables of worktarget, workinvoice, useditem and workhours. These represent many-to-many relationships between entities. Figure 1 shows the database structure as a relational database schema. Arrows illustrate how the tables are associated with each other. For example, the arrow from the invoice to the customer means that customer_id in the invoice table refers to an id in the customer table.  
In our graph database schema, entities are represented as nodes, and relationships as directed edges. Two edges are used to represent many-to-many relationships. Customer, invoice, target, work, and worktype entities are represented as nodes. Relationships PAYS from the customer to invoice, and CUSTOMER_TARGET from the customer to the target, and PREVIOUS_INVOICE from an invoice to another are represented by directed edges,  
Figure 1: Database structure in relational format.  
the last being a recursive relationship. WORK_TARGET, WORK_INVOICE, WORKHOURS and USED_ITEM are each represented by two edges. Figure 2 represents the database structure in a graph format. The attributes of nodes and edges are not illustrated.
## 2 Patients and Methods
### Patients
Therefore, this study only recorded the signals from patients' movements, and all other signals were regarded as noise. This was accomplished by using the Kalman filter, which filtered out noise and retained signals that indicated actual movement. The system was also capable of detecting different movements. Figure 2 shows the waveforms of sitting still, standing up, sitting down, swaying back and forth, and swiveling, demonstrating that the system could clearly represent the behavior of the patients on the medical chair. Patients with ADHD tend to fidget while sitting down, and this characteristic can be quantified through the variance, zero-crossing rate, and high energy rate. These factors were used to analyze the signal in this study. A greater variance indicated greater fidgeting by the patient and was defined as follows:  
\[VAR=\frac{1}{N}\sum_{n=1}^{N}(x(n)-\overline{x})^{2} \tag{1}\]  
where \(\overline{x}\) represents the mean of a given signal with \(N\) samples and \(x(n)\) is the \(n\)th sample. The zero-crossing rate refers to the proportion of the signals that cross zero within a period. The zero-crossing rate was defined as follows:  
\[ZCR=\frac{1}{2N}\sum_{n=1}^{N-1}\lvert\text{sgn}[x(n)]-\text{sgn}[x(n-1)]\rvert \tag{2}\]  
\[\text{where sgn}[x(n)]=\left\{ \begin{array}{c}1,x(n)\geq 0\\ -1,x(n)<0\end{array} \right.\]  
A higher zero-crossing rate indicates that the participant moves more frequently. The signal is also generated when the participant sits still. Figure 2: Waveforms of different movements. A high energy rate over a threshold Dv was used to identify when a participant made overly large movements. In this paper, Dv was set as a reasonable value of 0.05 mv. This value can distinguish sitting still from other actions. \[HER=\frac{1}{N}\sum_{n=1}^{N}ture[|x(n)|\geq D_{v}] \tag{3}\]  
\[\text{where}\;ture[|x(n)|\geq D_{v}]=\left\{ \begin{array}{l}1,|x(n)|\geq D_{ v}\\ 0,|x(n)|<D_{v}\end{array} \right.\]  
The high energy rate also indicated the cumulative time in which the patients made overly large movements.
# Distributed MIMO Measurements for Integrated Communication and Sensing in an Industrial Environment
## 4 System Calibration
### Delay Calibration  
Assuming line-of-sight conditions with no contributions from MPCs, the transfer function between antennas \(h\) and \(h^{\prime}\) can be modeled as follows:  
\[\left[\mathbf{r}_{n}^{(hh^{\prime})}\right]_{n_{f}}\approx\alpha_{l,n}^{(hh^{\prime} )}\exp\left\{-\mathrm{j}2\pi f\frac{\|\mathbf{p}_{n}^{(h)}-\mathbf{p}_{n}^{(L^{\prime} )}\|}{\mathrm{c}_{0}}\right\}, \tag{7}\]  
where \(\|\mathbf{p}_{n}^{(h)}-\mathbf{p}_{n}^{(h^{\prime})}\|=d_{n}^{(hh^{\prime})}\) denotes the scalar distance between antennas \(h\) and \(h^{\prime}\). Calibrating the delay \(\tilde{\alpha}_{l,n}^{(hh^{\prime})}\) can be omitted.  
\[\angle\left[\mathbf{r}_{n}^{(hh^{\prime})}\right]_{n_{f}}=2\pi f\cdot\frac{d_{n}^ {(hh^{\prime})}}{\mathrm{c}_{0}}=a\cdot f. \tag{8}\]  
Equation (8) is a straight line with slope \(a=2\pi d_{n}^{(hh^{\prime})}/\mathrm{c}_{0}\). Since both the frequencies and the constant distance during the snapshots selected for calibration are known, the \"true\" slope is known. By estimating the measured slope, \(\hat{a}\), of Equation (8) and with the knowledge of the ground truth positions, a delay calibration can be formulatedas follows:  
\[\hat{e}^{(hh^{\prime})}\triangleq-\hat{a}+2\pi d_{n}^{(hh^{\prime})}/\mathrm{ c}_{0}. \tag{9}\]  
Of course, this will not be true in practice, but this is a first approximation to enable calibration to compensate for delays induced by cables and signal processing on the FPGA. If the channel is a non-line-of-sight condition, this approach will overestimate the delay and move the channel impulse response too far.
# Adaptive Power-Controlled Depth-Based Routing Protocol for Underwater Wireless Sensor Networks
## 4 Theoretical Analysis and Experimental Results
### Results and Analysis
#### 4.4.2 Influence of the Node Number on the Average End-to-End Delay  
The variation in end-to-end delay with different node numbers is depicted in Figure 12. From the graph, it can be observed that the end-to-end delay of all protocols is highest when the node number is 100. This is because the network density is low at this point, resulting in fewer available next-hop nodes and possibly unfavorable positions, leading to increased delay. Due to the energy-saving nature of the proposed APCDBRP, it introduces an increase in packet hops to some extent, resulting in a slight increase in end-to-end delay.  
Figure 11: The influence of \(\alpha\) on the network lifetime.  
Figure 10: The influence of \(\alpha\) on the total energy consumption.
## 4 Results and Discussion
### Cone Resistance of Confined Granular Fill  
Figure 6A presents the cone resistance of filled granular soil subjected with and without external dynamic vibrations. Digital SCP tests were performed at locations 'A', 'B', 'C', and 'D' in the test section. [PERSON] et al. [20] performed a digital SCP test to estimate the load displacement of fine-grained soils. Digital SCP results are not identical at all the testing locations. However, they follow a similar pattern for each test section at different excitation frequencies. The cone resistance can be utilized to determine the stress at a penetration depth. The results clearly show that after 10-20 Hz frequency vibration, granular soil has greater resistance against applied load than before vibration. After 30 Hz frequency vibration, the cone resistance decreased up to 22% due to changes in the relative density of the granular fill. The relative density and overburden pressure control the cone resistance of the granular fill [21]. Figure 6B presents the cone resistance of the granular fill after 40-50 Hz excitation frequency.  
\begin{table}
\begin{tabular}{c c c c c c} \hline Excitation Frequency (Hz) & 10 & 20 & 30 & 40 & 50 \\ \hline Natural frequency (Hz) & 31 & 31 & 30 & 32 & 49 \\ Damping loss factor (\(\xi\)) & 0.121 & 0.127 & 0.132 & 0.176 & 0.122 \\ \hline \end{tabular}
\end{table}
Table 4: Damping loss factor and natural frequency of the confined granular fill.  
Figure 5: Influence of depth of granular fill (20–40 cm) on the displacement spectrum at an excitation frequency of (**A**) 10 Hz; (**B**) 20 Hz; (**C**) 30 Hz; (**D**) 40 Hz; (**E**) 50 Hz.  
It is observed that the cone resistance increases after excitation frequency above the natural frequency. The overlapping at shallow depth signifies an unstructured response at low overburden pressure. The relationship between the cone resistance and penetration depth at varying excitation frequencies followed an empirical law as  
\[D_{P}=\alpha q_{c}^{2}+\beta q_{c} \tag{10}\]  
where \(\alpha\) and \(\beta\) are fitting parameters that vary with an excitation frequency of vibration (Table 5) with a satisfactory coefficient of regression (R\({}^{2}\)). The cone resistance \(q_{c}\) and depth of penetration \(D_{p}\) are expressed in kPa and mm, respectively.
## 2 Materials and Methods
### Design of Drive and Control System
Subsequently, incrementally increase the integral coefficient and derivative coefficient from zero until a smooth response curve is observed, indicating that the laser driver has entered the desired operational state. This sophisticated control strategy ensures precise and efficient pulse current delivery, meeting the demanding requirements of laser operation in deep space exploration missions. \[y(t)=K_{p}x(t)+\frac{K_{p}}{T_{r}}\int\limits_{0}^{t}x(t)+K_{p}\tau\frac{dx(t )}{dt} \tag{2}\]  
To achieve fast turn-on and turn-off of the MOSFET, shortening the rising and falling edges of the pulse current, gate current is required for the gate-source and gate-drain capacitance to charge and discharge. However, the operational amplifier's drive capability is limited. Therefore, an Output Capacitor-Less (OCL) circuit is introduced after PID control in the pulse constant current source to enhance the drive capability of the MOSFET. For the temperature control system, high-grade integrated temperature control chips are selected to achieve a balance between temperature control accuracy, low power consumption, and compact design. These chips offer high integration, small size, high precision, and excellent safety. The control diagram is illustrated in Figure 8. Utilizing its internally stabilized zero-crossing wave operational amplifier and integral amplifier, it forms a PID regulation system. One input terminal imports the voltage value for the set temperature from the microcontroller's DAC through a bridge circuit, while the other input terminal is connected to a Negative Temperature Coefficient Thermistor (NTC) to collect the real-time voltage value corresponding to the temperature. After processing by the PID controller, the driving current for controlling the Thermoelectric Cooler (TEC) is provided through a Field Effect Transistor (FET). To ensure the cooling efficiency and longevity of the laser, a high-quality semiconductor cooler was selected. It features 71 pairs of thermoelectric couples and has dimensions of 31.3 \(\times\) 17.6 \(\times\) 3 mm\({}^{3}\), matching the area of the oxygen-free copper baseplate in the laser system, thereby minimizing heat dissipation power consumption.
# Overcoming Limitations of LoRa Physical Layer in Image Transmission
## 3 Background  
### LoRa Network  
LoRa, which stands for the initial letters of the words 'Long Range', is a combination of communication technologies and protocols, developed by Semtech (Camarillo, CA, USA), that provides significantly longer range than other LPWAN technologies. Modulation with LoRa is based on spread-spectrum techniques, and a variation of a chirp spread spectrum (CSS) modulation integrated with forward error correction (FEC) [10]. LoRa's CSS is the key factor for long distance signal transfer with a high-quality link, even when the signal power is up to 20 dB lower than the noise floor [11; 12]. LoRa uses unique frequency shift keying (FSK) for demodulating signals 19.5 dB below the noise floor. In contrast, other network technologies are typically only capable of demodulating signals with powers of 8-10 dB above the noise floor [10].  
The novelty of LoRa is in offering a continuous phase between different chirp symbols in the preamble part of the physical layer packet, which enables simpler and more accurate timing and  
Figure 2: LPWAN is currently the state-of-the-art technology in transmitting images given global concern for low power consumption and limited bandwidth [9]. (**a**) LPWANs are the highest in energy efficiency and lowest in costs. (**b**) LPWANs are the longest in coverage range and the lowest in data rate.  
frequency synchronization, without requiring costly components for generating a settled local clock in the LoRa node [13]. A single LoRa gateway can cover hundreds of square kilometers [14].  
The LoRa MAC layer or LoRaWAN is the communication protocol and system architecture layer of a LoRa network. It has the greatest influence on network capacity, quality of service, battery lifetime of individual nodes, and security. To isolate the testing of the LoRa physical layer and its ability to transfer images at a limited bandwidth, LoRaWAN was not used in this paper.
# Motion, Static Force, and Efficiency Analysis of Planetary Gear Transmission Based on Graph Theory
## 3 Performance Analysis Example of Automatic Transmission
### Discussion  
In the motion analysis of a 6 HP26 automatic transmission, we can observe from Table 4 that the first, second, third, and fourth gears of a 6 HP26 automatic transmission are deceleration gears, and the transmission ratio decreases sequentially; the fifth and sixth gears are growth gears; and the reverse gear ratio is negative. From Table 5, we can observe that the rotational speeds of 6 HP26 automatic transmission components S1, R1, and C1 remain unchanged in each gear, while the rotational speeds of other components vary in each gear.  
In the moment analysis of a 6 HP26 automatic transmission, we can observe from Table 6 that the component torque of a 6 HP26 automatic transmission varies in various gears, which can be positive, negative, or 0.  
In the power flow and efficiency analysis of a 6 HP26 automatic transmission, we can observe from Table 7 that the efficiency is low in first gear, second gear, and reverse gear, because it is series connection in these gears. The other gears are connected in parallel, so the transmission efficiency is higher.  
In addition, the author also compared the motion, torque, and efficiency analysis ofa 6 HP26 automatic transmission with the analysis results in the existing literature [3; 5; 23; 30]. The results showed that the speed, torque, power flow, and efficiency values of each gear foran automatic transmission calculated using this method were accurate, and the method used in this article was easier to achieve through computer programming, making it possible to automate the design and analysis of planetary gear transmissions.
## 2 Materials and Methods
### Adsorption and Catalytic Oxidation Decoloration  
The adsorption of reactive red X-3B was carried out in a glass flask sealed in a water bath at 50 \({}^{\circ}\)C. One milligram of CoPc@s-BC was added to 5 mL of reactive red X-3B dye wastewater (100 umol/L, pH = 2). The catalytic oxidation was initiated by adding 8 mM H\({}_{2}\)O\({}_{2}\) to the CoPc@s-BC containing the reactive red X-3B solution. At given time intervals, the samples were analyzed immediately on a UV-vis absorption spectrometer (UV-2450) at the wavelength of maximum absorbance: 539 nm. The decoloration of reactive red X-3B was expressed as the change in the (C\({}_{0}-\)C)/C\({}_{0}\) value, where C\({}_{0}\) is the initial concentration of the dye, and C is the residual concentration of the dye. The amount of adsorbed dye was calculated as follows:  
\[\text{Adsorbed dye}\left(\upmu\text{mol}\right)=100\upmu\text{mol}/\text{L} \times 5\times 10^{-3}\text{L}\times\frac{\text{C}_{0}-\text{C}}{\text{C}_{0}}. \tag{1}\]  
The adsorption rate of CoPc@s-BC was derived from the slope of the adsorbed dye-adsorption time curves (within 90 min). The decoloration rate of CoPc@s-BC was calculated using Formula (2):  
\[\text{Decoloration rate}\left(\upmu\text{mol}\times\text{min}^{-1}\times\text{ g}^{-1}\right)=\frac{100\upmu\text{mol}/\text{L}\times 5\times 10^{-3}\text{L} \times 90\%}{t\ \ \text{min}\times 1\times 10^{-3}\text{g}\times\text{C}_{ CoPc}\times 630\text{g}/\text{mol}}, \tag{2}\]  
where \(t\) is the time taken for decoloration of 90% of reactive red X-3B, and C\({}_{ CoPc}\) is the immobilized CoPc content of CoPc@s-BC. The EPR signal of radical spin-trapped by DMPO was detected with a Bruker-A300 X-band EPR spectrometer (Bruker, Karlsruhe, Germany).
## 4 Coherent Manipulation on Light Fields via Atomic Coherence Gratings
### Direct Optical Convolution Operation
For simplicity but without a loss of generality, we put two double-slit masks on the front focal plane of lens L1 to modulate the input signal and readout pulses, in which both M1 and M2 were of the same slit width, \(a=200\)\(\upmu\)m, and the same slit separation distance, \(d=1000\)\(\upmu\)m, but one slit of mask M2 was encoded with a variable phase-shift, \(\phi\), with respect to the other slit so that when the readout beam transmitted through the mask, M2, there was a phase difference, \(\phi\), between the transmitting beams through the two slits of M2, as shown in Figure 10. In general, the output convolution of these two input double-slit images was a fringe pattern with three intensity peaks, and it was possible to adjust the relative intensity ratio among the three peaks by varying the phase-shift, \(\phi\), as shown in Figure 10. In particular, when the phase-shift, \(\phi\), was set to be \(\pi\), the central peak disappeared and the fringe pattern had two intensity peaks with a separation distance of \(2d\). Such a dynamically controllable optical convolution operation has potential applications in coherent optical information processing and optical imaging processing. Figure 10: A schematic diagram of the direct optical convolution results of two input double-slit images with a variable phase-shift, \(\phi\), between the transmitting beams through the two slits of M2. Figure 9: The 4\(f\)-imaging system for direct optical convolution operation of two input signals through the light pulse storage and retrieval technique based on the EIT effect in Pr:YSO crystal. M1 and M2 are two masks placed on the front focal plane of lens L1 to modulate the input signal and readout fields. The Pr:YSO crystal is placed on the confocal Fourier plane of the 4\(f\)-imaging system. The iCCD is placed on the rear focal imaging plane of lens L2 to record the convolution results. The focal length of both L1 and L2 is 30 cm.
## 3 Results
### Additional Remarks  
As previously mentioned, participants were not subjected to any time restrictions during the experiment. However, the average durations for each component of the experience are provided below: participants spent approximately 30 min exploring the metaverse, while allocating 10 min for avatar preparation and training beforehand. An additional 15 min were dedicated to completing the tests.  
Furthermore, all participants were interviewed after the experience to gather additional information. Among PC-based participants, 80.00% expressed satisfaction with the experience, while among VR-based interface participants, the satisfaction rate was 90.00%. Regardless of the interface used, 95.00% of participants indicated that they enjoyed the guided tour and the interaction with each other. Additionally, most participants, regardless of the interface, emphasized the need to enhance the quality of the 3D environment and models in order to better appreciate certain interesting aspects of the exhibits. They also expressed a desire for additional capabilities, such as the ability to modify the position and size of the paintings.  
During the experiences, a significant level of interaction was observed not only between participants and the tour guide but also among the participants themselves, despite being unfamiliar with one another. This finding suggests that the use of this type of metaverse can enhance socialization and learning.  
In addition to the aforementioned results, the preliminary version of the developed tourist office metaverse was showcased in collaboration with the Visit Valencia Foundation. The metaverse was presented during a dedicated event focused on tourism and cultural promotion, held at the Valencia Conference Centre in Spain on 27 April 2023 (see Figure 8) [37]. The event provided an opportunity to gather valuable feedback from conference attendees, and their responses were overwhelmingly positive and inspiring. This feedback will be instrumental in further enhancing and refining the beta application.  
Figure 7: SUS results (mean and standard deviation) for case study 3. (a) PC-based interface. (b) VR interface.