esa-sceva/satcom-chunk-collection huggingface dataset:
# Laser Technology in Photonic Applications for Space
## 3 Lasers in Space
### Science
#### 3.1.3 Quantum Scientific Technologies
The laser source is a commercial JDS 5421 master diode laser, based on the extended cavity laser diode (ECLD) concept and emitting 30 mW at 852 nm with a linewidth of 100 kHz and a single mode tunability of 1 GHz, that seeds two slave laser diodes for output powers of 100 mW ([PERSON], 2018). The ESA's Space Optical Clock on ISS (ISOC) mission, planned to be launched in 2022, will also include an atomic clock mainly for fundamental science measurements, such as the Earth, Sun, and Moon's gravitational time dilation, clocks comparison in the line of the ACES mission, and search of Dark matter topological defect. The device will use several lasers at 461 nm, 689 nm, and 698 nm, but also commercial Toptica lasers at 679 nm and 707 nm for re-pumping and a lattice based on the ECLD/TA concept [83]. Finally, ESA is working on the LISA mission, planned to be launched in 2034, to detect and accurately measure gravitational waves using the so-called Laser Interferometer Space Antenna (LISA). In order to test the technology, the LISA Pathfinder mission was launched at the end of 2015. The reference laser unit used in the laser interferometer technology was based on a 35 mW Nd:YAG non-planar ring oscillator emitting at 1064 nm [84].
## 3 SEIRS-F Agent-Based Model
### Agents and Environmental Characteristics  
Sensors and some other environmental factors compose the SEIRS-F agent-based model--sensor nodes, malware, network topology, environment, and maintenance resource. These factors have been selected after analyzing the different characteristics and environments that may affect the operation of the wireless sensor network. The main characteristics considered for each factor are as follows: (1) importance to the component failure process and maintenance process and (2) contribution to the malware propagation process. The factors with their specific characteristics and corresponding values are described in Table 1.  
Sensors can collect data from the environment, which is the main element in WSN. Based on the consideration of reliability and security, we will consider the following characteristics of sensors:  
* Reliability state of sensor: the sensor has two states, i.e., the normal state and the failure state. The sensor can achieve the expected function such as collection, processing, and transmission in the normal state. While in the failure state, one or all of these functions cannot be accomplished. * Reliability level: has been divided into a high level, medium level, and low level, corresponding to the sensor nodes whose reliability level is from high to low. * Security level: has been classified into high level when the trusted security methods are used, medium-level if it uses basic means, and low level if it does not have any security designs. * Transmission capability: Some nodes are limited by software and hardware function and cannot spread malware to their neighbors. * Battery power: essentially determines the lifetime and thus the reliability of the sensor node [25; 43]. The initial battery power is divided into three levels, from low to high. Malware is any software intentionally designed to cause damage to a computer, server, client, or computer network. The following two characteristics of malware are considered in our model:  
* Infection intensity is the attack strength of malware; higher infection intensity has a greater possibility of infecting the node's neighbors. Infection intensity may vary between very high and very low. * Target: malware is designed for different targets, some of which hinder the function of the software; some could increase energy consumption and accelerate the consumption of battery lifetime; others can even damage the hardware. The target can be software function, subsystem hardware, or battery power.
# AMR-Assisted Order Picking: Models for Picker-to-Parts Systems in a Two-Blocks Warehouse
## 5 Numerical Experiments
### Comparison of the Implementations
#### 5.3.1 Tardiness Values for Different Instance Sizes  
The values of tardiness as a function of instance size are given for each warehouse layout; the graphical representation is shown in Figure 6. These values are derived for a fleet size of 2 and an AMR speed of 2.4 km/h.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Small** & \multicolumn{2}{c}{**Medium**} & \multicolumn{2}{c}{**Large**} \\ \hline
**AMR Speed** & **Number of** & **Number of** & **Number of** & **Number of** & **Number of** \\
**(km/h)** & **AMR = 2** & **AMR = 2** & **AMR = 2** & **AMR = 2** & **AMR = 3** \\ \hline
2.4 & 1269 & 7341 & 2945 & 10,207 & 95 \\
3.6 & 0 & 2981 & 2085 & 9885 & 0 \\
4.8 & 0 & 2946 & 1656 & 9912 & 0 \\
6.0 & 0 & 2857 & 1245 & 8603 & 0 \\
7.2 & 0 & 1250 & 904 & 3199 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Values of tardiness as a function of the AMR speed—shared handover locations.  
From the results presented in Figure 6, it is remarkable that how for medium size instances the implementation with separated handover locations emerges as the most efficient one; in the other two cases of small and large instance sizes, the one with shared handover locations is optimal instead. This happens because, in the case of a small instance, the complexity of the problem is low and the layout with shared handover locations allows minimizing the waiting time of both picker and AMR, without excessive coordination effort between complementary sub-corridors. The result achieved for the medium-sized instance is more meaningful. In that case, the layout with separated location is optimal since it is more intuitive for a limited number of items in each sub-corridor while the alternative layout probably only adds complexity without providing any improvement to tardiness. Finally, for a large instance, the ability to load items in the complementary aisle leads to a significant improvement in tardiness. Therefore, the layout with shared locations is indeed optimal: in the presence of many items per sub-corridor it significantly decreases the waiting time of both the picker and the AMR, improving coordination between the two.
## 2 Methods
### Data Collection Tool  
The research team formulated a semi-structured survey questionnaire based on [PERSON] et al.'s [42] conceptual model. The questionnaire consisted of four sections, comprising both closed and open-ended questions. In addition, the validity of the questionnaire was assessed in two steps. First, feedback was obtained from two experts in the field of rehabilitation--a professor in rehabilitation medicine and a professional working in the assistive devices domain. Secondly, a pilot test was conducted with three participants to ensure that the questions were clear and could gather information relevant to the research objectives. Finally, based on expert feedback and suggestions from pilot participants, some revisions were made to the original survey questionnaire.  
In the first section of the questionnaire, the research team formulated questions related to demographic information. Participants provided their age, gender, occupation, type of lower-back pain, and history of LSAD usage in interviews.  
In the second section of the questionnaire, participants underwent interviews regarding their LSAD usage. Specifically, researchers asked four questions related to LSAD usage:  
1. What type of LSAD have you used? Could you show or describe it to us?
2. At which stage of lower-back pain do you typically use LSAD? For example: before regular treatment, after regular treatment, relying only on the LSAD for rehabilitation, etc.?
3. In what environment or scenario do you usually wear LSAD?
4. How often did you use LSAD on average during your most recent episode of lower-back pain?  
The third section of the questionnaire incorporated, in interview format, device satisfaction questions related to the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0). Participants responded to eight questions, evaluating their satisfaction with various aspects of the device on a 5-point Likert scale (1 = completely dissatisfied, 5 = very satisfied). According to the QUEST 2.0 reference manual, participants were required to provide detailed explanations when any item scored below 5 [44]. QUEST 2.0 also includes four items related to services but, during the pilot test, three participants found them confusing as they had never received any service related to LSAD. Therefore, in the formal testing, we did not administer the service test section of QUEST 2.0 to the remaining participants.  
At the end of the questionnaire, we presented participants with open-ended questions to further explore detailed information about their experiences wearing LSAD. We specifically inquired of participants (1) if they had any additional perspectives or sentiments regarding the experience of wearing LSAD and (2) if they had any corresponding suggestions or requests.
## 5 Analysis of Sandstone Failure Characteristics Under Different Soaking Times and Temperatures  
In the previous sections, the damage evolution process of sandstone under different soaking times and temperature conditions has been analyzed. To further investigate the failure characteristics and the final failure type of sandstone, based on the acoustic emission (AE) RA evolution characteristics, the failure modes of sandstone specimens under different soaking times and temperature conditions are examined. The ratio of the rise time to amplitude, denoted as RA, can be used to characterize the development of cracks and failure in rocks. High RA values indicate tensile failure in sandstone, while  
Figure 10: Damage evolution law of sandstone under different temperature and soaking time.  
low RA values correspond to shear failure [30]. In this study, a threshold of 5 ms\(\cdot\)V\({}^{-1}\) is defined for high and low RA values [19]. The time-stress-RA values and the failure types of specimens under different temperatures are illustrated in Figure 11.  
From Figure 11, it can be observed that the RA value distribution characteristics of sandstone under different soaking times and temperatures are similar. During the compaction stage, under external force, a small amount of acoustic emission signals is generated due to the closure of internal pores and friction between particles, resulting in very low RA values, all below 5 ms\(\cdot\)V\({}^{-1}\). As the axial compressive stress increases, during the elastic stage, the number of RA values begins to increase, indicating the initiation of microcracks start to initiate within the rock, which leads to some tensile cracks, though high RA values remain relatively few. During the plastic stage, internal cracks in the sandstone begin to develop and propagate continuously, resulting in an increase in the number of RA values and the emergence of high RA values. This indicates that microcracks within the rock gradually cluster together, leading to an increasing number of tensile cracks, which ultimately results in the formation of a main crack. In the post-peak stage, the number of RA values decreases as the rock fractures. Under different temperatures, the sandstone generates the maximum RA signal near the peak stress, as shown in Table 3. This indicates that, under soaking conditions, a significant number of tensile cracks are generated near the peak stress at all temperatures, accompanied by a certain number of shear cracks. The primary mode of failure in sandstone is tensile failure, with a combination of tensile and shear failure. This conclusion is also supported by the photographic results of the experiments conducted under various soaking times and temperatures.  
Figure 11: _Cont._  
Figure 11: Characteristics of RA distribution in sandstone under different temperatures and immersion times and specimen damage maps.
## 3 Results and Discussion
Again, the results obtained show that the DTC-Hoo-SFC controller allows for significantly better performance of the control system because it exhibits a lower ISE and a lower IAE. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **ISE** & **ISE** \\ \hline  & (NOMINAL) & (DISTURBANCE) \\ \hline DTC+PI & 14,149 & 140 \\ DTC-Hoo-SFC & 13,230 & 45 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparative results of integral squared error (ISE) performance index of the control system with the DTC-Hoo-SFC and DTC+PI designed controllers and external disturbance. Figure 7: Performance comparative results of the control system with DTC-Hoo-SFC vs. DTC+PI controllers against variations in the command signal, and external disturbance. Therefore, the DTC-Hoo-SFC designed controller provides important improvements in the precalciner temperature control of the cement rotary kiln, producing higher rank cement with lower energy consumption, and with lower emission of polluting gases.
# Nanoarchitectures in Management of Fungal Diseases: An Overview
## 4 Nanocarriers in Management of Fungal Infections
### Nanoparticles
#### 4.2.4 Solid Lipid Nanoparticles and Nanostructured Lipid Carriers  
Solid lipid nanoparticles (SLNs) are emerging as alternative nanocarriers to the colloidal systems for targeted and controlled delivery [68]. The SLNs can be prepared by utilizing lipids, which have less-arranged crystal lattice structures like glyceryl-behenate and glyceryl-monostearate. These lipids favor effective drug inclusion compared to those synthesized using extremely ordered crystal lattices structures such as cetyl-palmitate, beeswax, solid paraffin, and tripalmitate. The SLNs have advantages, like good acceptability, less risk of acute and chronic toxicity, improved bioavailability, precise targeting, controlled release, encapsulation, and the prevention of unstable compounds from degradation and easy, large-scale production techniques [69].  
Nanostructured lipid carriers (NLCs) consist of a higher concentration of liquid lipids than any other architecture. The solubility of therapeutic drugs in liquid lipids is more as compared to solid lipids. Consequently, NLCs show a sustained release and increased drug loading, thus evading loss and leading to solid lipid decomposition. The NLCs are established as an advancement over the SLNs. The NLCs are fabricated by monitoring the mixture of SLNs with liquid oil, foremost to singular nanostructures in the matrix form. The possible disadvantage of SLNs is the predetermined drug-loading capacity and drug leaching during storage. In contrast, NLCs represent the improved EE of drugs due to extra space for drug loading by liquid lipids [70].  
[PERSON] et al. researched and fabricated FLZ-loaded SLN-based topical gels with the ultimate goal of improvement in the drug efficiency for _Pitviasis versicolor_ treatment. The drug showed a sustained drug release with a 1.4-fold improved therapeutic response [71]. In another study, [PERSON] et al. investigated the effect of drug EE, drug release, and the biopharmaceutical properties of AmB-based lipid formulations. Their observations concluded that AmB-loaded SLNs showed an enhanced solubility of AmB by combining lecithin and resulted in an extended-release with diminished toxicity and improved antifungal activity [72].  
[PERSON] et al. compared the physio-pathological conditions of nails and skin to highlight the unrevealed applications of lipid NPs in onychomycosis. The fabrication techniques and ingredients of NPs influence the EE, in vitro fungal activity, drug release, and stability. Lipid NPs like NLC and SLN showed great potential in skin permeation. The VCZ-loaded NLC significantly influenced the depth penetration of an encapsulated cargo drug and allowed deep penetration in porcine hooves compared to the unloaded drug. The NLC and SLN helped in reaching a high EE and cutaneous delivery [73]. Moreover, [PERSON] and [PERSON] designed NLC and SLN-based semi-solid preparation using Carbopol(r) 934. After a shelf-life of 2 years, the results showed >95% of CLO and <30% of ketoconazole present in the developed formulations [74].
## 3 Considered Two-Way Relaying PNC Systems
### Reference PNC Algorithm
Namely, terminal A finds the bits transmitted by terminal B from the equation:  
\[\hat{b}_{3}=\hat{a}_{1}\oplus b_{1},\quad\hat{b}_{4}=\hat{a}_{2}\oplus b_{2} \tag{6}\]  
whereas terminal B determines the bits transmitted by terminal A from the expression:  
\[\hat{b}_{1}=\hat{a}_{1}\oplus b_{3},\quad\hat{b}_{2}=\hat{a}_{2}\oplus b_{4} \tag{7}\]  
The presented procedure is very simple; however, it does not take into account the fact that channel coding is applied in both terminals; thus, making symbol-by-symbol decisions followed by appropriate mapping for the broadcast symbols is evidently not optimal.
## 2 Materials and Methods
### COD, TOC, OUR and BOD  
The end products were featured by such sum parameters used in water analysis as COD, TOC, biochemical oxygen demand (BOD\({}_{5}\)), and oxygen uptake rate (OUR). In COD measurements, the organic content of the sample is oxidized by potassium dichromate, and the amount of O\({}_{2}\) needed for oxidation (in mg dm\({}^{-3}\) O\({}_{2}\) units) is calculated (ISO Standard 6060:1989, [19]). In the experiments, a Behrotest TRS 200 COD digestion system was used. The rate of mineralization was assessed by TOC content measurements using Shimadzu TOC-LCSH/CSN equipment. This assay is based on catalytic combustion of the organic content of samples and analysis of the formed CO\({}_{2}\) using nondispersive infrared detection. TOC expresses the organic carbon content in mg dm\({}^{-3}\) C units.  
BOD\({}_{5}\) is the amount of O\({}_{2}\) dissolved in water (in mg dm\({}^{-3}\) O\({}_{2}\) units) required for biotransformation of organic compounds by aerobic bacteria during 5 days of incubation. BOD\({}_{5}\) experiments were performed using an Oxi-Top\({}^{\circledR}\) Control BOD Respirometer System according to DIN EN 1899-1 (1998) [20]. During the test, the change in air pressure in 500 cm\({}^{3}\) brown bottles was measured at (20 \(\pm\) 0.5) \({}^{\circ}\)C. In the experiments, 0.1-50 mg dm\({}^{-3}\) decanted and filtered activated sludge taken from the aeration basin of the SPWTP was used. The inoculant was tested separately: 20 cm\({}^{3}\) of inoculant was added to 1 dm\({}^{3}\) standard dilution water. Three measurements were made for each concentration simultaneously, and the measurements were repeated at least four times.  
Pharmaceuticals influence the biological activity of microorganisms in water. This influence was studied in oxygen uptake rate respiratory tests (OUR, mg dm\({}^{-3}\) h\({}^{-1}\) O\({}_{2}\)). In OUR measurements, the dissolved O\({}_{2}\) uptake increases in the presence of biodegradable compounds, and it is reduced when toxic compounds are in the solution. The measurements were made according to the ISO 8192:1986 standard [21]. O\({}_{2}\) consumption was measured in 300 cm\({}^{3}\) Kalsruher flasks with an FDO\({}^{\circledR}\) 925 O\({}_{2}\) sensor at 20 \({}^{\circ}\)C. A 150 cm\({}^{3}\) solution containing the pharmaceutical was poured into the flask, and an amount of sewage sludge corresponding to 25 mg of dry organic matter was added to it. Three parallel measurements were made in each case. OUR measurements for a series were made on the same day using the same activated sludge.  
In the radiolysis of aerated solutions, hydrogen peroxide forms with a high yield [22; 23]. Since H\({}_{2}\)O\({}_{2}\) may disturb the biochemical tests [24; 25], the residual H\({}_{2}\)O\({}_{2}\) was eliminated using manganese dioxide (MnO\({}_{2}\), 5 g dm\({}^{-3}\), Sigma-Aldrich, St. Louis, MO, USA) before the BOD and OUR experiments, and catalase enzyme (1 mg cm\({}^{-3}\) in 50 mmol dm\({}^{-3}\) phosphate buffer, Sigma Aldrich) before the Microtax(r) toxicity tests.
## 3 Problem Statement and Fitness Function  
The design problem is to discover the optimum location coordinate \(x_{n}\) and frequency offset \(f_{n}\) for each element of the FDVA, to obtain optimum radiation patterns. The terms f\({}_{0}\) and \(d_{0}\) are considered constants during the optimization process. In this scenario, the optimization variables are computed as,  
\[Q=\left[q^{1},q^{2},\ldots,q^{i}\right] \tag{2}\]  
\[q^{i}=\left[x_{n}^{i},f_{n}^{i}\right] \tag{3}\]  
Figure 3: S\({}_{11}\) parameter of the antenna element.  
Figure 2: Antenna element: (**a**) back view; (**b**) front view.  
The \(Q\) term is a matrix of optimization variables, and each element \(\mathrm{q}^{i}\) represents the location \(x_{n}\) and the frequency offset \(f_{n}\). The index term \(i\) is an individual from the swarm. During the optimization method, the spacings \(x_{n}\) are searched by defining a spacing \(s_{n}=x_{n}-x_{n-1}\) among the drones within the range of \(s_{n}\in[1.7\ \lambda,\ 2.7\ \lambda]\), where the wavelength \(\lambda\) is considering the frequency \(f_{0}=3.5\ \mathrm{GHz}\). This constraint is to avoid a possible collision of drones. The frequency offsets, such as \(f_{n}\in[1\ \mathrm{KHz},\ 20\ \mathrm{KHz}]\), are also constrained. The objective function of this optimization is computed with the next expression:  
\[of=\max(SLL) \tag{4}\]  
SLL is the maximum side lobe level for the radiation patterns \(P(\theta\),\(d)\). The algorithm PSO minimizes the objective function _of_, obtaining the optimum radiation patterns defined in Equation (1). The methodology of PSO is taken as in [37]. This methodology is very efficient for the design of antenna arrays, as mentioned in [37]. However, we do not claim that PSO is the best algorithm for an FDVA. The design process used the PSO just as a tool to find the optimization variables. The next section will describe the simulation results.
# Passive Harmonic RFID System for Buried Assets Localization
## 1 Introduction
The conversion loss of the frequency doubler is characterized according to the input power and is taken into account in the analysis. Measurements are performed for different types of soil (dry and wet), showing the possibility of detecting the tag buried at a depth of around 0.6 m, which highlights the potential of the proposed design. In contrast with simple one-bit harmonic tag configurations ([17; 42; 43]), where detection is based on the presence or absence of the tag, this work presents an advanced detection technique allowing the identification of the type of pipeline by specifying a different modulation frequency for each type. The study is completed with a proof-of-concept of a low-cost reader based on a simple Phase-Locked Loop (PLL) synthesizer used as a transmitter and an RTL software defined radio (SDR) used as a receiver. To the best of our knowledge, the frequency-modulated harmonic tag for localization of buried items is studied here for the first time. The paper is structured as follows. Section 2 describes the system architecture and the harmonic tag design. Section 3 analyzes the tag performance based on the criterion of the maximum depth that can be detected depending on the attenuation of the ground. In this section, the theoretical reading range underground is estimated as a function of the soil composition and water content. A low-cost harmonic reader prototype based on an RTL SDR is presented in Section 4. A discussion of the results and a comparison with the state-of-art is given in Section 5. Finally, some conclusions are drawn in Section 6.