esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Literature Review  
Although the first laser-induced periodic surface structures (LIPSSs) were discovered in 1965, the mechanisms for obtaining various types of LIPS nanostructures remain not fully studied [1; 2]. The common mechanism of LIPSS formation is based on the theory of interference between a linearly polarized incident laser pulse and a scattered one. Among numerous applications, LIPSSs have proved huge potential in sensors [3], photovoltaics [4], mechanical [5], magnetics [6] and medical [7] areas. Laser processing makes it possible to change the reflective properties of the material's surface [8; 9]. In this case, both profiles of the resulting microstructure elements [10] and the features of their production are studied. A laser-induced solid-liquid transition strategy for fabricating unique structures is known. By modulating the solid-to-liquid transition state of a metal using an initial pulse excitation, the subsequent recoil pressure caused by the ultrafast pulse can suppress plasma emission and metal removal in the liquid phase, leading to the controlled fabrication of ring structures [11]. At the same time, additional parameters of laser processing are also being studied, such as changing the angle of incidence of the beam [12], altering polarization to control the direction of the LIPSSs [13] and the use of inert gases during the process run [14; 15]. Columnar morphology imparts anti-reflective properties to clear glass [16]. The fabrication of laser-patterned structures using ultrashort polarized laser pulses is described [17; 18]. The single-pulse formation of structures [19] and the two-pulse subpicosecond laser ablation of metals allow you to control the depth of the ablation crater due to a delay between pulses [20]. Surface modification of single-crystalline silicon using radially polarized ultrashort donut-shaped laser pulses with zero orbital angular momentum generated by an S-wave plate has been reported. The evolution of laser-generated structures has been studied depending on the laser pulse energy and the number of applied pulses. By varying these parameters, tubular and needle-shaped structures were formed [21]. This is a known mechanism for the formation of porous metal with small voids [22]. Several research groups have reported the use of a femtosecond laser in the fabrication of concentric ring structures [23] with periods ranging from a few micrometers to tens of micrometers on various materials such as metallic glasses [24], fused silica [25], with purposes such as microhole array fabrication [26] and even for obtaining superhydrophobic surfaces [27]. Micro- or nanostructures are flexibly controlled in terms of their geometric morphology during their fabrication process [28]. At the same time, the mechanisms of formation of ring and periodic structures inside the crater remain unexplored.
## 3 Finite Element Model of Anti-Overturning Hybrid Isolation Structure
### Hybrid Seismic Isolation Scheme  
To mitigate the overturning effect in the seismic isolation structure, a hybrid isolation system incorporating viscous dampers is proposed. In this scheme, 16 horizontal viscous dampers are added to the isolation layer of the experimental model to control and reduce the rocking motion. The viscous dampers have a damping coefficient of 19 kN\(\cdot\)s/m and a damping index of 1. The region exhibiting the maximum relative velocity is situated at the edges and corners of the isolation layer. The viscous dampers were positioned at the perimeter of the isolation layer to maximize their lever arm against overturning moments. The plan layout of the hybrid isolation system is illustrated in Figure 8a.  
The equation of motion for the discretized system is expressed as  
\[M\ddot{u}+Ci\dot{u}+Ku+F_{nl}(\dot{u},u)=-M\Gamma\ddot{u}_{g} \tag{1}\]  
where \(F_{nl}\) encapsulates the nonlinear forces from isolators and dampers. \(\Gamma\) represent the influence vector. For clarity, the partitioned form isolating the superstructure and base is  
Figure 8: Schematic diagram of hybrid seismic isolation structure: (**a**) Layout plan of hybrid seismic isolation scheme. (**b**) Finite element model of hybrid seismic isolation structure.  
Figure 7: Time-history curve of floor acceleration under isolation test condition 31.  
Based on the four evaluation metrics--the tensile stress of the bearings, the maximum base shear, the anti-overturning moment ratio, and the floor acceleration amplification factor--it is evident that the hybrid isolation scheme with viscous dampers (damping coefficient of 19 kN\(\cdot\)s/m and damping exponent of 1) effectively addresses the overturning issues observed in the experiments. This scheme can be adopted to optimize the structure's resistance to overturning.
## 5 Experimental Verification  
The testbed consisted of a driving device, force sensor, data acquisition card, pressure gauge, displacement sensor, solenoid valve, accumulator, relief valve, hydraulic pump and throttle valve. The hydraulic circuit is shown in Figure 24 and the testbed is shown in Figure 25. The improved spool and unimproved spool are shown in the Figure 26.  
Figures 27-29 show the change of flow force with the spool opening under different inlet and outlet pressure differences. The flow force increased greatly with increasing opening. Compared with the unimproved spool, the flow force of the improved spool is significantly reduced. With the increase of the opening, the decrease in flow force of the improved spool is more obvious.  
Figure 24: Hydraulic circuit. **(1)** Driving device, **(2)** force sensor, **(3)** data acquisition card, **(4)** pressure gauge, **(5)** displacement sensor, **(6)** solenoid valve, **(7)** accumulator, **(8)** relief valve, **(9)** hydraulic pump, **(10)** throttle valve.  
Figure 25: Test bed.  
Figure 26: Improved spool and unimproved spool.  
In order to quantitatively study the flow-force compensation of the improved spool, the compensation coefficient \(\gamma\) is defined as the flow-force increment per spool opening, and \(\gamma\) can be expressed as follows:  
\[\gamma=\frac{\Delta F_{flow}}{\Delta x_{v}} \tag{15}\]  
Obviously, when \(\gamma>0\), it indicates that the flow force is completely offset and produces a flow force in the opposite direction, that is, it produces over-compensation. When \(\gamma=0\), it indicates that the flow force is completely offset. When \(\gamma<0\), it means that part of the flow force is compensated for; and, the smaller the absolute value of \(\gamma\), the more the flow force is compensated for, and the more stable is the compensation characteristic.  
Figure 28: Flow force at 2.5 MPa.  
Figure 27: Flow force at 1.5 MPa.  
Figure 29: Flow force at 3.5 MPa.  
The flow forces under different pressure difference were fitted to the spool opening to obtain various compensation coefficients, as shown in Table 2. With the increase of pressure difference, the absolute values of \(\gamma\) for the two spools became larger, the compensation effect decreased, and the compensation characteristic became unstable. However, at the same pressure difference, the absolute value of the compensation coefficient of the improved spool was less than that of the unimproved spool. When the pressure difference was 1.5 MPa, the absolute value of the compensation coefficient of the improved spool was 53.3% lower than that of the unimproved spool. When the pressure difference was 3.5 MPa, the absolute value of the compensation coefficient of the improved spool was 36.5% lower than that of the unimproved spool; the compensation effect is more obvious in the case of small pressure differences.
# Energy-Efficient IoT-Based Light Control System in Smart Indoor Agriculture
## 3 Plants Light Requirements  
Light is the source of energy that plants use for their growth and development processes. It is therefore considered a very critical factor when growing plants in indoor environments. Thus, understanding plants' light requirements is necessary for successful cultivation. Plants need very specific light conditions for optimal growth; these conditions include light intensity, light quality, light duration, and light source. Understanding and optimizing these factors can help to ensure a healthy and high-yielding plant growth, which results in a good final product. The light intensity received by plants is measured in photon flux density (PFD) (\(\upmu\)mol/m\({}^{2}\)s) in the photosynthetically active radiation (PAR) region, which represents the spectrum region used for photosynthesis. The light intensity required by plants changes depending on the plant species, their growth stage, and some environmental factors like temperature and humidity. In general, the PAR light intensity required for growth is at least 100-200 \(\upmu\)mol/m\({}^{2}\)s [62]. Light quality refers to the wavelengths of light spectrum that plants receive. It is known that red and blue wavelengths are used for photosynthesis with different amounts depending on the species and the growth stage. More specifically, blue light is needed more in the vegetative growth stage, while red light is needed more for flowering and fruiting. Light duration, also known by photoperiod, refers to the duration of plants' light exposure per day. In general, the photoperiod is about 12-16 h per day, and it also varies depending on the species and the growth stage. By adjusting the photoperiod, developmental processes like germination or flowering can be triggered. Natural sunlight contains all the mentioned requirements, and it is therefore the ideal light source for plants. However, in the case of indoor farming, LED lights are gaining in popularity thanks to their energy-efficiency, durability, and ability to provide the necessary wavelengths of light.
## 3 Recursive Matrix Form  
Since the numerical properties of CVM can be derived from the characteristic equation of its amplification matrix, it is needed to rewrite Equation (2) in a recursive matrix form. Thus, the use of CVM to obtain the free vibration in a system with SDOF can be expressed in the following:  
\[\mathbf{X}_{i+1}~{}=~{}\mathbf{A}_{i+1}\mathbf{X}_{i}, \tag{6}\]  
where \(\mathbf{X}_{i+1}~{}=~{}\left[d_{i+1}~{}(\Delta t)v_{i+1}~{}(\Delta t)^{2}a_{i +1}\right]^{T}\), \(\mathbf{X}_{i}~{}=~{}\left[d_{i}~{}(\Delta t)v_{i}~{}(\Delta t)^{2}a_{i}\right]^ {T}\).\(A_{i+1}\) is the amplification matrix. The explicit expression of the amplification matrix of CVM is found to be:  
\[A~{}=~{}\frac{1}{B}\left[\begin{array}{ccc}B\big{(}1-B_{1}\Omega_{0}^{2} \big{)}&B*B_{2}&B*B_{3}\\ -\big{(}1-B_{1}\Omega_{0}^{2}\big{)}\gamma_{2}\Omega_{0}^{2}&(1+\alpha)-B_{2} \gamma_{2}\Omega_{0}^{2}&(1+\alpha)\gamma_{1}+\alpha\gamma_{2}-B_{3}\gamma_{2} \Omega_{0}^{2}\\ -\big{(}1-B_{1}\Omega_{0}^{2}\big{)}\Omega_{0}^{2}&-\big{(}2\xi\Omega_{0}+B_{2 }\Omega_{0}^{2}\big{)}&\alpha-\gamma_{1}2\xi\Omega_{0}-B_{3}\Omega_{0}^{2} \end{array}\right], \tag{7}\]  
where B is further defined as  
\[B~{}=~{}(1+\alpha)+\gamma_{2}2\xi\Omega_{0}. \tag{8}\]  
Thus, the characteristic equation of A can be derived from \(|\mathbf{A}-\lambda I|~{}=~{}0\) and is found to be:  
\[\lambda^{3}-A_{1}\lambda^{2}+A_{2}\lambda-A_{3}~{}=~{}0, \tag{9}\]  
where \(\lambda\) is an eigenvalue of an amplification matrix A, and the coefficients are found to be:  
\[\begin{array}{l}A_{1}~{}=~{}\frac{1}{D}\big{[}2+3\alpha-(\beta_{2}+\beta_{1} \gamma_{2}-\beta_{3})\Omega_{0}^{2}-(\gamma_{1}-\gamma_{2})2\xi\Omega_{0}\big{]} \\ A_{2}~{}=~{}\frac{1}{D}\big{[}1+3\alpha-(\beta_{2}-\beta_{1}\gamma_{1})\Omega_{0 }^{2}-2\gamma_{1}\xi\Omega_{0}\big{]}.\\ A_{3}~{}=~{}\frac{1}{D}[\alpha]\end{array} \tag{10}\]
## 4 Simulation Results
### Energy Consumption of Logic Operations  
We further extended our analysis to the logic-gate level, functionally evaluating SIMPLY schemes as LIM blocks performing NAND, XNOR, and XOR operations [50]. The logic operations can be implemented using the NAND logic function [51], which is generated with a sequence of SIMPLY and sFALSE operations and uses a single storage MTJ device to store the output [20].  
Figure 8 shows the energy consumption per logic operation under cryogenic and room temperatures for both SMTJ- and DMTJ-based schemes. The average energy consumption increases as a function of the number of required steps: 3 steps for NAND, 9 steps for XNOR, and 13 steps for XOR operation. Overall, the SMTJ-based scheme is the most energy-hungry scheme due to the higher switching currents. When compared to the SMTJ-based  
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**SIMPLY**} & \multicolumn{4}{c}{**sFALSE**} \\ \cline{2-9}  & \multicolumn{2}{c}{**SMTJ**} & \multicolumn{2}{c}{**DMTJ**} & \multicolumn{2}{c}{**SMTJ**} & \multicolumn{2}{c}{**DMTJ**} \\ \hline Temperature (K) & 300 & 77 & 300 & 77 & 300 & 77 & 300 & 77 \\ Vbias (V) & 1 & 1 & 1 & 1 & 0.85 & 0.85 & 0.85 & 0.85 \\ \hline RM (mV) & 51 & 127 & 53 & 122 & 86 & 186 & 90 & 182 \\ RM\({}_{3\,\sigma}\) (mV) & 36 & 94.8 & 36.6 & 89.5 & 63.8 & 146.3 & 65.9 & 141.7 \\ E\({}_{\text{read}}\) (f) & 86.4 & 210.1 & 35.3 & 77.2 & 44.1 & 61.9 & 16.7 & 37.1 \\ E\({}_{\text{write}}\) (f) & 301 & 458 & 67 & 106 & 301 & 458 & 67 & 106 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison results.  
Figure 7: Average energy consumption for the SMTJ- and DMTJ-based logic schemes at 300 K and 77 K, for the SIMPLY and sFALSE operations.  
scheme operating at 77 K, the DMTJ-based solution consumes about 68.6% (68.4%) less energy when carrying out XNOR (XOR) operations.
## 5 Results and Discussion
### Bit Error Rate  
When the threshold rises over a certain level, \(BER\) dramatically rises. This indicates that a more potent equalization should be employed since the approach can no longer adequately correct the deficiencies. Thus, the threshold is decided to be the mutational origin of \(BER\). It is important to note that the ideal threshold changes as the data rate varies. The \(BER\) rate similarly decreases as the threshold dose. As a result, the distortions may be eliminated effectively. The bit error rates of the existing and suggested approaches are depicted in Figure 5. Table 1 indicates the contrast of the bit error rate (%). It demonstrates that the proposed method has a 55% lower bit error rate. As a result, it removes the distortions in the UVLC system. In VLC, information is transmitted by changing the visible light spectrum utilized for lighting. Through analytical and experimental studies, it has been shown that VLC can offer high-speed data transmission with the additional advantage of increased energy efficiency and communication security. The formula for \(BER\) is denoted as follows:  
\[BER=\frac{1}{2}erfc\left(\sqrt{E_{b}/N_{0}}\right) \tag{13}\]  
The \(BER\) is often referred to as a function of the normalized carrier-to-noise ratio measure represented as \(E_{b}/N_{0}\).
## 3 Results and Discussion
### The Influence of NaSt on the Hydration Process of AASRSS  
#### 3.2.1 Isothermal Calorimetry  
The exothermic rate and cumulative heat release of AASRSS are shown in Figure 4. It was found that the development of the exothermic rate and the cumulative exothermic curve of AASRSS did not change significantly with the addition of NaSt, while the peak value of exothermic activity around 10 h decreased and the cumulative exothermic heat after 72 h decreased, indicating that NaSt inhibited the hydration reaction of AASRSS. The main reasons for the inhibition of AASRSS hydration by NaSt are as follows: (1) NaSt adsorbs on the surface of silica-aluminate precursor particles, which prevents the precursor and alkali activator from reacting in contact with each other [24]. (2) The wrapping effect of NaSt on the solution in the slurry reduces the liquid-phase distribution of the system to some extent, resulting in a reduction in the contact area between the precursor particles and the alkali activator [26].
# Streetlight Control System Based on Wireless Communication over DALI Protocol
## 5 Experimental Results: Test Scenarios
### Onsite Test
In terms of energy consumption and energy cost, the proposed system present clear savings _versus_ others (ATR up to 31% and DBL up to 5%). Regarding price difference: it is constantly decreasing. Last year the difference was about 10%--regarding a luminaire alone (UCODALI or DBL _vs._ ATR). If the replacement regards a pole and luminaire, it drops to about 3%-4% (UCODALI _vs._ DBL). We are aware that the prices vary, depending heavily on particular market properties. That is why we are focusing on energy savings. Calculating Total Cost of Ownership and ROI requires further research and comparative market analysis. From a technical point of view, this system allows users to fully customize the set of dimming setpoints and the switching time, _versus_ the fixed and limited sets provided by the ATR and DLB methods. In addition, the presented system optimizes the lamps' lifespan and provides a very valuable tool to the end user (mainly public administrators, e.g., citizens) for maintaining street-lighting facilities because the bidirectional communication data flow gathers relevant information about the status of the lamps and provides a source of information to detect any failure or malfunction in the luminaries. Compared to other existing methods and technologies, like those based on power line communication (PLC) or LONWorks(tm), the system presents a clear advantage due to its wireless nature. No additional wires or installations are needed other than attaching a UCODALI board to the \begin{table}
\begin{tabular}{c c c} \hline \hline
**UCODALI Savings** & _vs._**ATR** & _vs._**DBL** \\ \hline Energy (kWh) & 1215.611 & 31.34\% & 145.938 & 5.19\% \\ Cost (€) & 256.57 & 37.58\% & 23.35 & 5.19\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Saving rates (energy and cost) for 1-year operation.
## 4 Results and Discussion
### Evaluation of Experimental Results
#### 4.4.2 Evaluation of Fault Diagnosis Method
Specifically, the proposed method achieves the highest _ave-accuracy_ of 97%. In addition, compared with the SN method and the S-ECNN-rand model, the _ave-recall_ of the proposed method increased by 8.1% and 14.3% respectively, indicating that this method could effectively identify a specific fault type. Meanwhile, the proposed method significantly improves the _ave-precision_ and _ave-F1-score_ compared with the S-ECNN-rand model. Finally, although the _ave-specificity_ of the other methods can achieve some success, the value of the proposed method is still the highest.
## 4 DMRF Protocol
### Faulty Node Detection Method  
In this paper, the faulty node is defined as the node that cannot collect data or transmit data. **Algorithm 1** is the faulty node detection and node state adjustment algorithm. It checks the state of  
Figure 3: Jumping transmission.  
**FCS** to determine whether the node is faulty. A message is sent to the **FCS** nodes. According to the reply, it determines the node state and then updates the content of **FCS** nodes (state, transmission rate and delay). We utilize a variable \(c\) to represent the confidence of a node in **FCS**. Originally the value of each confidence variable is set as 100. Once transmission fails, the value of \(c\) will accordingly decrease. If \(c\) is less than a threshold \(f\), which is used to check the correctness of a node, then that node is considered as FAULTY.The detailed detection process is described in **Algorithm 1.**  
```
Data: FCS, confidence variable \(c\). Result: Node State.
1 Initialize the FCS and \(c\).
2 IF the state of FCS is FAULTY or JFAULTY THEN
3 Set the state of the Node \(i\) as JFAULTY
4 ELSE
5 For each Node \(j\) in FCS of Node \(i\) Node \(i\) Node \(i\) sends a message to Node \(j\)
7 IF Node \(i\) receives no reply from Node \(j\) THEN
8 Decrease the confidence variable\(c\) of Node \(j\)
9 IF the confidence variable \(c\) of Node \(j\) less than the confidence threshold \(f\)THEN
10 Set the state of the Node \(j\) as FAULTY
11 ELSE update the delay and transmission rate of Node \(j\)
```  
**Algorithm 2** Congestion detection algorithm
## 3 Results and Discussion
To achieve higher shift selectivity, the low spatial frequency components of recording phase data page must be removed. It is possible to decrease the value to remove the low spatial frequency components of signal beam pattern by using other coding methods of the phase data pages. In this study, a PQ-PMMA plate with a thickness of 1 mm, which is easy to prepare, was used as a recording medium to experimentally verify the principle of volume retardagraphy. By improving the polarization-sensitivity of recording medium as well as shift selectivity, it is expected to increase data capacity and data transfer rate.
## 6 Non-Linear Methods
### Production Planning and Scheduling  
Production planning in the food industry often involves non-linear relationships between production variables, such as equipment capacity, processing time, and product quality. Non-linear methods provide a sophisticated approach to optimizing these variables, ensuring efficient and cost-effective operations.  
For example, in beverage manufacturing, NLP models have been used to optimize production schedules, balancing demand fluctuations and resource constraints. A case study in a brewery reported a 15% reduction in production costs and a 10% increase in on-time delivery rates through non-linear optimization. Similarly, in meat processing, non-linear methods have been applied to optimize cutting and packaging operations, achieving a 20% reduction in waste and a 12% increase in yield [38].
## 1 Introduction
The object of this analysis is to obtain the highest communication baud rate of a 2.5 Gbps airborne laser communication transmission link based on OOK (on-and-off keying) modulation, which is applied to an airborne air-to-air channel with an altitude of 10 km and a communication distance of 200 km (the meteorological conditions include the presence of high-altitude clouds and weak-to-moderate atmospheric turbulence intensity).