esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion  
### Heavy Metal Concentrations in Soil and Water  
Figure 1 presents the concentrations of Cd and Cu in the soil for the experimental and control groups before and after planting the various vegetables. Pre-planting, Cd concentrations in group 1, group 2, and control were 8.24, 20.6, and 0.11 mg/kg d.w. (dry weight), respectively. At the end of the growing period, Cd concentration in the soil decreased by 58%, 18%, and 4% in group 1 and decreased by 44%, 19%, and 16% in group 2 after planting spinach/sweet potato leaves, potato/sweet potato, and tomato, respectively. In pre-planting soils, the Cu concentrations were 423 \(\pm\) 3.74, 1492 \(\pm\) 175, and 27.1 \(\pm\) 1.47 mg/kg in group 1, group 2, and control, respectively. Overall, at the end of the growing period, the Cu concentration in the soils of group 1 decreased by 15%, 15%, and 10% in water spinach/sweet potato leaf, potato/sweet potato, and tomato, respectively, and then decreased by 46%, 23%, and 31%, respectively, in the soils of group 2 for the same vegetable categories. To account for any interference from additional metals in the irrigation water during the pot experiment, Cd and Cu concentrations were also monitored in the first, second, and third phases of the pot experiments. The Cd and Cu concentrations were non-detectable in all of the samples, which indicated that the results should not be affected by water pollution during the experiment.  
The Cd and Cu contamination ranges in the soils in the current study were comparable with those in other studies. [PERSON] et al. [32] analyzed heavy metal concentrations in selected agricultural land that was adjacent to industrial areas in the eastern, western, and central regions of China. Cd was considered to be the most toxic (0.00-16.8 mg/kg), and Cu was found to contaminate the central area (4.43-217 mg/kg). In Taiwan, [PERSON] et al. [33] also reported soil contamination by Cd in Taoyuan (1.90-19.4 mg/kg) and Taichung (0.48-3.89 mg/kg). These results suggest that health risks should be taken into consideration for the food safety of local crops. Overall, the investigation of industrial waste treatment and pollution distribution of these heavy metals is necessary and it should be carried out by the government.
# Removal of Contaminants in Water with Scallop Shell Waste
###### Abstract
Therefore, scallop shells have become a problem for artisanal fishermen and the region's companies, who must pay thousands of dollars (USD) annually to transport and dispose of the residue in authorized landfills. In addition, a single company generates approximately 1000 tons of shells per year as waste, ending in landfills and creating severe environmental problems. Over time, they decompose, producing foil odors, contaminating the soil and the environment, and releasing toxic gases such as NH\({}_{3}\) and H\({}_{2}\)S [13]. These are just some of the reasons fisheries and aquaculture are among the UN Sustainable Development Goals (SDGs), making it necessary to have policies and actions promoting a circular economy and sustainable development [14]. Seashells are a composite biomaterial made up of 95-99% calcium carbonate (CaCO\({}_{3}\)), with different superimposed CaCO\({}_{3}\) layers, which are microstructures of calcite or aragonite, and an external organic layer [15]. Since prehistoric times, seashells have been used by many cultures as tools, ornaments, and artifacts [16]. Also, some of those developed a currency based on seashells that facilitated trade, the purchase of food, and payment for services [17]. Currently, they have different applications, such as being used in additives for construction materials [18; 19], construction of rural roads [20], animal feed supplements [6], lime for industrial sectors [21], and additives for agricultural soils [22]. Other studies have found that the shell waste possesses antifungal properties [23]; in agriculture, they can prevent the loss of soil nutrients by leaching [24] and reduce the accumulation of Cd in plantations of brown rice, oilseeds, and radishes [25; 26]; in contaminated mining soils, calcined shell waste can decrease the concentrations of Cd and Pb [27; 28]. Also, shell waste subjected to pyrolysis can eliminate 98% of phosphates in wastewater [29], and adhering them to filtering processes can increase the removal efficiency of COD, NH\({}_{3}\)-N, and phosphorus [30], remove methylene blue [31] and stabilize or precipitate heavy metals in water, such as arsenic, nickel, and copper [32; 33]. These are some of the uses that are given to mollusk shell waste as a resource in another process or product, promoting the circular economy. This work describes the physical and chemical properties of the northern Chile scallop shell, specifically those produced in the Coquimbo region, which had not been previously reported in the literature. Such properties provide key information when defining possible applications for this waste in different fields. Out of these possibilities, this study proposes the application of scallop shell waste in water treatment processes, specifically the removal of caffeic acid from wine distillery wastewater as well as the removal of arsenic III ions from certain potable waters. Additionally, the correlation between pore size distribution and water pH was evaluated in order to determine removal percentages of the selected contaminants, which has yet to be reported in the literature.
# Compressive Sampling with Multiple Bit Spread Spectrum-Based Data Hiding
## 3 Data Hiding Model
### Signal Reconstruction  
Once \(\widehat{\mathbf{A}}\) is obtained, \(\widehat{\mathbf{S}}_{\mathbf{r}}\) reconstruction is simply solved by Orthogonal Matching Pursuit (OMP) [22; 23]. The reconstruction process is carried out on each column of \(\mathbf{Y}\) in sequence with \(\widehat{\mathbf{A}}\) as a dictionary. Let \(\mathbf{y}_{m}\) as a vector taken from the \(m^{\text{th}}\) column of \(\mathbf{Y}\), then for a general case, we can find the row position of the strongest atom as:  
\[q_{m}=\underset{i\in\{1,2,\dots,p\}}{\text{argmax}}\ \widehat{\mathbf{A}}^{T} \mathbf{y}_{m}. \tag{37}\]  
For a specific case, i.e., a singular matrix solution as the reconstructed one, the position of the highest atoms are indeed known, then (37) can be simplified as:  
\[q_{m}=m. \tag{38}\]  
Denote \(\mathbf{a}_{r}\) as a vector taken from the \(r^{\text{th}}\) column of \(\widehat{\mathbf{A}}\), then we take a column of \(\widehat{\mathbf{A}}\), which makes the strongest atom as:  
\[\
abla=\mathbf{a}_{q_{m}}. \tag{39}\]  
We reconstruct a non-zero element of \(\widehat{\mathbf{S}}_{\mathbf{r}}\) in column \(m\) by:  
\[s_{q_{m}}=\left(\
abla^{T}\
abla\right)^{-1}\
abla^{T}\mathbf{y}_{m}. \tag{40}\]  
This reconstruction procedure including (37), (39), and (40) is repeated \(r\) times with the increment of \(m\), thus obtaining:  
\[\widehat{\mathbf{S}}_{\mathbf{r}}=\begin{bmatrix}s_{q_{1}}&0&\cdots&0\\ 0&s_{q_{2}}&\cdots&0\\ \vdots&\vdots&\ddots&\vdots\\ 0&0&\cdots&s_{q_{r}}\end{bmatrix}. \tag{41}\]  
Then, the next step is to form the signal by SVD reconstruction, as described in (7). Thus, finally, we can compute the signal quality.
# Two Polarization Comb Dynamics in VCSELs Subject to Optical Injection
## 2 Experimental Polarization Dynamics  
### Experimental Setup  
Figure 1a shows the experimental setup for parallel optical injection in a single-mode VCSEL. The tunable laser (TL) output is first amplified by an Erbium-Doped Fiber Amplifier (EDFA). The output of EDFA is then sent to the RF port of the Mach-Zehnder Modulator (MZM), which is driven with an electrical signal modulation generated by an Arbitrary Waveform Generator (AWG) (Tektronix AWG 700002A). Three optical frequency lines are created at the output of the MZM. The polarization controller at the input of the MZM is used to align its polarization with the tunable laser. A fiber circulator is arranged to provide isolation for the comb injection in the VCSEL. The total power of the injected comb is controlled using a Variable Optical Attenuator (VOA). The VCSEL output is amplified before being sent to a 50/50 coupler to analyze the optical spectra and the corresponding time series separately. Optical spectra are analyzed with a high-resolution optical spectrum analyzer, BOSA 400, which allows monitoring optical spectra with a resolution of about a minimum of 0.1 pm (12 MHz) at the operating wavelength of 1550 nm. Figure 1b-d present the optical spectra of the injected comb for a fixed comb spacing of \(\Omega=1\) GHz, \(\Omega=2\) GHz and \(\Omega=4\) GHz, respectively. The ratio between the power of the central comb line and the side comb lines is around 12 dB. The VCSEL (Raycan) used is a single-mode device with a threshold current equal to I = 3 mA. In free-running conditions, the dominant polarization mode (normally depressed polarization mode) emits along the X (Y) axis, as shown in Figure 1e. The ratio between the power of the linear polarization modes (X-PM and Y-PM) is around 43 dB. Figure 1e is obtained for a bias current at I = 6 mA, which corresponds to 2-times the threshold current. At that current, the total output power of the VCSEL has been measured to be \(P_{inj}=330\) uW. The dominant polarization mode (X-PM) emits at 1553.8 nm at I = 6 mA. The difference in frequency between linear polarization modes (VCSEL birefringence) is around 17.71 GHz at 23 \({}^{\circ}\)C. The x-axes of the optical spectra will show the relative frequency with respect to the X-Polarization mode (X-PM), i.e., the zero value will correspond to the frequency position of the dominant X-Polarization mode (X-PM). In the following, the frequency detuning \(\Delta v\) will be defined from the frequency  
of the central injected comb line to the frequency of dominant polarization mode of the VCSEL (X-PM), i.e., \(\Delta\
u=v_{0}-v_{x}\), where \(v_{0}\) and \(v_{x}\) are the frequencies of the central injected comb line and the X-polarization mode of VCSEL (X-PM), respectively.
# Acoustic Pressure Amplification through In-Duct Sonic Black Holes
## 3 Simulation Analysis
### FEM Validation  
Simulations have been performed from the TMM and from the FEM Visco-Thermal Acoustics models to calculate the PGs at the back cavities of O-SBH (resp. MPP-SBH) sensors over the range of maximum amplification, 1500 Hz\(-f_{c}\) (resp. 700-1700 Hz) determined in Section 3.2. Figures 8a and 9a show that the PG variations simulated by the TMM are well predicted by the FEM, with a relative total error lower than 9% (resp. 6%) for the O-SBH (resp. MPP-SBH) evaluated over the sensor efficiency ranges. The error is lower for the MPP-SBH with respect to the O-SBH as there is less inter-resonator coupling between the activated cavities when shielded by a MPP skin, especially at the resonance peaks. A larger deviation is observed away from the resonances due to the evanescent coupling  
Figure 7: (a) Axial spectrogram of the sound pressure level upstream and within an outer MPP-SBH sensor (the red patch shows the axial sensor location); (b) Axial spectrogram of the PG simulated with TMM at the back of the MPP-SBH cavities (the red dots spot the peak levels at the cavities axial locations).  
between adjacent cavity mouths, which are neglected by the TMM. The FEM and TMM also well correlate on the inner C-SBH sensor.  
Figures 8b and 9b provide FEM simulation results of the sound pressure level (SPL) distributions within the O-SBH and MPP-SBH at two frequencies activating the cavities \(n=13\) and \(n=6\) with a PG greater than 8. It is observed that the pressure amplification process does not result from a single cavity activation but involves two or three adjacent cavities given the proximity of their resonance frequencies (especially the deepest cavities) and the amount of losses that contribute to the merging between their bandwidths. This phenomenon is more pronounced for O-SBH and explains the largest bandwidth of the PG peaks observed in Figure 8a compared to Figure 9a. Note that pressure continuity  
Figure 8: **(a)** Pressure gain simulated with TMM (thick plain) and FEM (thin with bullets) at the back cavities (\(n=13\), blue; \(n=15\), green; \(n=20\), orange) of an outer O-SBH-type sensor; (b) Cross-sectional view of the sound pressure levels within the O-SBH-type sensor and its cavities when the 13 th cavity is activated at 1836 Hz.  
Figure 9: **(a)** Pressure gain simulated with TMM (thick plain) and FEM (thin with bullets) at the back cavities (\(n=3\), blue; \(n=6\), green; \(n=8\), orange) of an outer MPP-SBH-type sensor; (b) Cross-sectional view of the sound pressure levels within the MPP-SBH-type sensor and its cavities when the 6 th cavity is activated at 936 Hz.  
(resp. pressure jump) is observed across the cavity mouths of the O-SBH (resp. MPP-SBH), as expected.
# A Simplistic Downlink Channel Estimation Method for NB-IoT
## 1 Introduction
### Organization of the Paper  
The remainder of this paper is organized as follows. Section 2 introduces the proposed channel estimation technique. Section 3 presents evaluation methodology for the assessment of the channel estimation method. Section 4 describes the test setup used to measure the channel quality indicators. Section 5 shows the results of the measurements, including the SNR performance and the computation time. The closing section discusses the outcomes of this study.
# Analytical Pyrolysis and Mass Spectrometry to Characterise Lignin in Archaeological Wood
## 3 Results and Discussion
### Single-Shot Py(HMDS)-GC/ms
\begin{table}
\begin{tabular}{c c c c c} \hline N\({}^{\circ}\) & **Compound** & **L. cat.** & **N\({}^{\circ}\)** & **Compound** & **L. cat.** \\ \hline
1 & 1,2-dihydroxyethane (2 TMS) & 59 & 5-methyl-3-methoxy-1,2-benzenedi (2 TMS) & D \\ \hline
2 & 2-hydroxymethylfuran (TMS) & 60 & 4-ethylsyringol (TMS) & SC \\ \hline
3 & phenol (TMS) & 61 & _E_-isoeugenol (TMS) & LC \\ \hline
4 & 2-hydroxypropanoic acid (2 TMS) & 62 & 1,4-anhydro-D-galactopyranose (2 TMS) & \\ \hline
5 & 2-hydroxyacetic acid (2 TMS) & 63 & 1,6-anhydro-D-galactopyranose (2 TMS) & \\ \hline
6 & 1-hydroxy-1-cyclopenten-3-one (TMS) & 64 &
\begin{tabular}{c} 2-hydroxymethyl-5-hydroxy-2,3- \\ dihydro-(4H)-pyran-4-one \\ (2 TMS) \\ \end{tabular} & \\ \hline
7 & 3-hydroxymethylfuran (TMS) & 65 & 4-vinylsyringol (TMS) & SC \\ \hline
8 & o-cresol (TMS) & 66 & 1,4-anhydro-D-glucopyranose (2 TMS at position 2,4) & \\ \hline
9 & 2-furancarboxylic acid (TMS) & 67 & 1,2,4-trihydroxybenzene (3 TMS) & \\ \hline
10 & unknown holocellulose I & 68 & acetovanillone (TMS) & C \\ \hline
11 & m-cresol (TMS) & 69 & 4-hydroxybenzoic acid (2 TMS) & A \\ \hline
12 & 2-hydroxy-1-cyclopenten-3-one (TMS) & 70 & 4-propenylsyringol (TMS) & LC \\ \hline
13 & p-cresol (TMS) & 71 & 1,6-anhydro-\(\beta\)-D-glucopyranosideose (2 TMS at position 2,4) & \\ \hline
14 & 3-hydroxy-(2H)-pyran-2-one (TMS) & 72 & vanillic acid methyl ester (TMS) & E \\ \hline
15 & unknown holocellulose II & 73 & 5-vinyl-3-methoxy-1,2-benzenedi (2 TMS) & D \\ \hline
16 & unknown holocellulose III & 74 & _Z_-4-isopropenylsyringol & LC \\ \hline
17 & _Z_-2,3-dihydroxycyclopent-2-enone (TMS) & 75 & 1,4-anhydro-D-galactopyranose (3 TMS) & \\ \hline
18 & _E_-2,3-dihydroxycyclopent-2-enone (TMS) & 76 & unknown lignin I & O \\ \hline
19 & 1,2-dihydroxybenzene (TMS) & 77 & syringaldehyde (TMS) & C \\ \hline
20 & 3-hydroxy-(4H)-pyran-4-one (TMS) & 78 & 2,3,5-trihydroxy-4H-pyran-4-one (3 TMS) & \\ \hline
21 & 5-hydroxy-(2H)-pyran-4(3H)-one (TMS) & 79 & 1,6-anhydro-\(\beta\)-D-glucopyranose (3 TMS) & \\ \hline
22 &
\begin{tabular}{c} 2-hydroxymethyl-3-methyl-2- \\ cyclopentenone \\ (TMS) \\ \end{tabular} & 80 & 1,4-anhydro-D-glucopyranose (3 TMS) & \\ \hline
23 & 1-hydroxy-2-methyl-1-cyclopenten-3-one (TMS) & 81 & _E_-4-isopropenylsyringol (TMS) & LC \\ \hline
24 & 1-methyl-2-hydroxy-1-cyclopenten-3-one (TMS) & 82 & 1,6-anhydro-\(\beta\)-D-glucofuranose (3 TMS) & \\ \hline \end{tabular}
\end{table} 
Table 3: List of wood pyrolysis products identified by Py(HMDS)-GC/MS. In the case of lignin pyrolysis products, lignin categories (L. cat.) are indicated: SC—short chain; LC—long chain; M—monomers; C—carbonyl; A—acids; D—demethylated/demethosylated; E—esters; and O—others. The other pyrolysis products mainly derive from holocellulose.
# Vibration Response Characteristics of Prefabricated Frame Structures Around the Subway
## 2 Modeling Method and Verification of Prefabricated Frame Structures with Semirigid Joints
### Selection of Joint Model for Prefabricated Frame Structures  
Semirigid joints typically employ connection types such as bolt-welded hybrid connections, prestressed prefabricated connections, and bolted connections. Given that upper structures predominantly remain within the elastic range under subway-induced vibrations, linear spring elements were adopted in linear elastic simulations to represent the rotational stiffness effects of semirigid joints on the global stiffness matrix, as schematically shown in Figure 1.  
At the semirigid joint, the relationship among the shear force \(F_{\
u}\), bending moment \(M\), joint shear deformation \(V_{j}\) and joint rotation angle \(\theta_{r}\) is as follows:  
\[F_{\
u}=K_{\
u}V_{j},\ M=K_{r}\theta_{r} \tag{1}\]  
Equation (1) can be employed to simulate the influence of semirigid joints on beam element stiffness matrices. The ABAQUS software offers solutions for modifying 3D beam element stiffness matrices via semirigid connections, with its Interaction module's Connector tool enabling integrated stiffness modeling. Within the Connector tool, the Bushing component enables separate specification of translational stiffness components (\(K_{a}\), \(K_{\
u x}\), \(K_{\
u y}\)) and rotational stiffness parameters (\(K_{\text{rx}}\), \(K_{\text{ry}}\), \(K_{\text{rz}}\)). As the axial stiffness \(K_{a}\) does not contribute to the beam-end stiffness matrix in semirigid connections, it is appropriately designated as rigid in the model configuration.
# High-Power, High-Beam-Quality, Long-Pulse-Width 532 nm Laser Based on a 4f Optical System
## 1 Introduction
This parameter is useful for characterizing the propagation behavior of the beam in free space or optical systems. Maintaining a constant q-parameter for a laser beam is of great significance, as it implies that the beam's focal length, divergence properties, and spatial distribution remain stable [13]. This stability allows for precise control and stable transmission of the beam, ultimately leading to higher beam quality and output power. A 4f optical system, consisting of just two lenses with a distance between them equal to twice the focal length of each lens, can be applied to all-solid-state 532 nm lasers. It enables pulse width broadening while maintaining the q-parameter of the Gaussian beam. This paper first extends the laser resonator on the basis of a Nd:YAG 532 nm laser with double acousto-optic Q-switching and LBO frequency doubling, using a 4f optical system while maintaining the laser's q-parameter. The results show that, at a repetition rate of 10 kHz, the extended cavity achieves a maximum average power of 112 W, with a decrease of less than 10 W compared to the short cavity. The pulse width is extended from 58 ns to 85 ns with an average power of 108 W, the beam quality in the horizontal and vertical directions are M\({}^{2}_{\rm x}\) = 15.76 and M\({}^{2}_{\rm y}\) = 14.25, respectively.
## 1 Introduction  
The emergence of Virtual Reality (VR) has posed significant challenges for scientists who started investigating the way VR changes social dynamics [1] as well as social attitudes [2]. Especially during the pandemic, cultural heritage, culture, and tourism had to find new ways to engage the public, since travelling was largely restricted. Thus, the potential of virtual tourism was explored, showing multiple positive effects in promoting sites, allowing the recovery of tourist destinations after the pandemic, and supporting engagement with cultural content for remote audiences. [3]. In addition, virtual applications also allowed interactions with intangible cultural heritage [4]. When VR is combined with storytelling, e.g., 360 video storytelling, cultural content becomes engaging and significant increases in immersion and levels of presence are observed [5]. Finally, research has shown that VR places specific demands on human cognition, and in order to be engaging and provide a smooth experience, its design needs to respect human cognitive requirements [6].  
In recent years, games in cultural heritage have been considered a good way to increase engagement with cultural content; thus, serious games and game-based learning is on the rise. Although challenges remain in their development, there are significant results showing advantages of their use [7, 8]. Moreover, the combination of VR and games in cultural heritage also produced very promising results, especially for specific age groups, regardless of their domain knowledge of cultural heritage [9], making such games important tools for cultural experiences. Therefore, games and gamification processes in cultural heritage can not only increase engagement but also reflection and interpretation, and numerous studies seem to support this finding [10]. Previous reviews on the topic studied both Augmented Reality (AR) and VR games in cultural heritage, as an attempt to map the field and boost future research, focusing on three main aspects: sociability, gamification, and virtualization [11].  
Considering the above, this study explores different ways to effectively incorporate VR games in cultural heritage through a systematic literature review (SLR). The analysis seeks to examine works on VR games, especially with empirical interventions with respect to immersion, motivation, engagement, and culture. Thankfully, there have been many recent studies incorporating VR games within culture settings.  
The remainder of this article is organized as follows. Firstly, the background work presents a basic overview of the field of VR games in cultural heritage. Next, the methodology explains how the data for the current study were gathered. The results and discussion sections include both quantitative and qualitative findings. Finally, the study makes suggestions for future research based on the gaps in the literature.
# An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network +
## 4 Implementation and Experiments
### Discussions  
In this subsection, we discuss some implementation-related issues of the system, including the communication range of Bluetooth beacons, the contention on the BLE advertising channels, the interference from Wi-Fi devices, and how to deal with a large deployment area.
# Building Realistic Mobility Models for Mobile Ad Hoc Networks
## 6 Real Shipping Movement Model
### Real-World Model  
This subsection presents an alternative approach to building a mobility model, using captured trace data as a direct source of movement patterns for simulations. Trace data collected from shipping in the northeastern Irish Sea (via Global Positioning Systems (GPS) receivers and incorporated into satellite navigation systems) is used to construct a simulation that exactly matches the real-world movement of these ships.  
The geographical area covered in this research runs from N52\({}^{\circ}\) (Strumble Head, Wales) to N55\({}^{\circ}\) (the northern end of the Rhins of Galloway, Scotland) and W2\({}^{\circ}\) (Ashton-Under-Lyne, England) and W7\({}^{\circ}\) (Waterford, Ireland), an area of approximately 105,000 km\({}^{2}\). The area is bounded to prevent occasional anomalies within the data from interfering with the model. The particular area is chosen pragmatically, because it depicts a fairly busy sea area with sufficiently diverse nodes, such as fixed coastguard stations, ships at anchor, regular traffic made up mostly of scheduled ferry services, and ad hoc traffic.