esa-sceva/satcom-chunk-collection huggingface dataset:
Exosomes, in particular, are easily transported by biological fluids and can reach different parts of the body thanks to their size. They express various chemokine receptors and adhesion molecules that drive their homing to the site of damage or inflammation [17]. The membranes rich in cholesterol, sphingomyelin, and ceramide allow the uptake of the exosomes' contents by the target cells through the mechanism of endocytosis [15; 16]. Exosomes carry nucleic acids, lipids, and proteins, including cytokines, chemokines, and growth factors. By releasing these molecules, exosomes can influence the immune response and promote tissue angiogenesis, repair, and regeneration [17]. Therefore, the EVs of MSCs represent a powerful tool capable of maintaining or renewing tissue homeostasis and interacting directly with the immune system, regulating its activity [18; 19]. Interestingly, secreted factors prepared from MSCsderived from liver and human liver stem cells (HLSC) have been proposed as an effective stimulus to promote liver regeneration [20; 21; 22] supporting the hypothesis that the organ can contribute to its own homeostasis [22; 23]. These findings suggest that liver-derived biological preparations can play an important role to study liver biology and regeneration in vitro, but also represent a potential tool to control the progression of chronic liver injuries in vivo. The aim of this preliminary work was to assess the in vitro safety of a powder obtained through a controlled freeze-drying process of whole porcine livers [24]. The preparation method of the freeze-dried supplement was aimed at preserving the bioactive principles present in the liver tissue of healthy pigs, including soluble proteins, extracellular vesicles (EVs), extracellular matrix components, vitamins (especially of group B), but also minerals (for example iron), and essential amino acids. Two cell types were used to evaluate the supplement cytotoxicity, the liver cell line HepG2, and primary cultures of canine MSCs derived from the adipose tissue (At-MSCs). HepG2 cells have been derived from a human hepatoma and are commonly used in drug metabolism and hepatotoxicity studies, given their ability to preserve many differentiated hepatic functions [25]. MSCs have been chosen as a primary stromal cell model playing essential roles in various tissues homeostasis and regeneration [26]. Furthermore, MSCs are actively studied for the development of cell therapy and tissue engineering strategies aimed to restore liver function [10].
# Application of Single-Electron Transistor to Biomolecule and Ion Sensors
## 5 Experimental Demonstrations of Biomolecule Sensing Based on a Single-Electron Transistor  
Using the biosensors with an SET that has serially connected multiple Si islands, pH sensor and detections of streptavidin and PSA have been achieved.
###### Abstract  
Layered double hydroxides (LDH) containing various exchangeable anions were studied to show how X-ray Photoelectron Spectroscopy (XPS) can provide information on the local environments of the different elements within the interlayer anionic groups and their possible influence on the LDH interlayer hydroxide surfaces. As such, XPS can potentially provide additional information about these systems that cannot be obtained by other common spectroscopic methods, such as infrared and Raman spectroscopy. A Mg\({}_{6}\)Al\({}_{2}\)X(OH)\({}_{16}\). 4H\({}_{2}\)O with X representing interlayer anions CO\({}_{3}\)\({}^{2-}\), PO\({}_{4}\)\({}^{3-}\), SO\({}_{4}\)\({}^{2-}\), MoO\({}_{4}\)\({}^{2-}\), CrO\({}_{4}\)\({}^{3-}\), Fe(CN)\({}_{6}\)\({}^{4-}\), and Fe(CN)\({}_{6}\)\({}^{3-}\) was studied. The hydroxide layer structure is characterized by the Mg 2p and Al 2p with a binding energy of around 50.1 and 74.5 eV for the normal CO\({}_{3}\)\({}^{2-}\) containing LDH. The O 1s contained three peaks related to the layer OH-groups at 531.6 eV, interlayer CO\({}_{3}\)\({}^{2-}\) at 530.5 eV and interlayer water at 532.4 eV. Similar observations were made for the other interlayer anions showing characteristic P 2p, S 2p, and Mo 3d peaks. Intercalation with CrO\({}_{4}\)\({}^{3-}\) shows that a significant amount of the Cr\({}^{6+}\) has been reduced to Cr\({}^{3+}\). Finally, the intercalation of hexacyanoferrate in hydrotalcite showed the potential of XPS in detecting changes in the oxidation state of Fe upon intercalation in the LDH with a change in the Fe 2p peaks with a shift in binding energy and the possibility of determining the amount of reduction of Fe(III) to Fe(II). In general, the XPS high-resolution scans of P 2p, S 2p, Mo 3d, and Cr 2p show that slightly lower binding energies are observed compared to the binding energy values for the corresponding anionic groups as part of a rigid crystal structure, such as in minerals. Overall, the influence of the nature of the interlayer anion on the binding energy of the elements (Mg, Al, O) in the layered double hydroxide structure is minimal and considered to be within the experimental error of XPS. A detailed analysis of XPS data in combination with infrared and Raman spectroscopy shows how XPS can provide additional information that is not readily available via vibrational spectroscopy. XPS can simultaneously account for both surface and bulk properties of LDH that are not available through common vibrational spectroscopic methods.  
X-ray Photoelectron Spectroscopy; layered double hydroxide; LDH; interlayer anion +
Footnote †: journal: Applied Sciences  
1
Footnote 1: email: _Article_  
Footnote †: journal: Applied Sciences
# MALDI-TOF Mass Spectrometry Applications for Food Fraud Detection
## 3 Conclusions  
The range of analytes typically targeted in MALDI-TOF MS analyses has expanded over the years from macromolecules, such as peptides and proteins, to smaller molecules, such as lipids, hydrocarbons, sugars, phenols, and many others, widening the possible applications of the technique, which has been projected towards fields not initially contemplated, including food quality evaluation and adulteration detection. Consequently, several MALDI-based applications for the fight against food frauds have been reported in the literature over the years. The higher number of papers have been focused on milk, oils, fish and seafood, meat, fruits, and vegetables. In the case of milk, the target analytes have been mainly proteins and peptides and, to a minor extent, lipids and phospholipids. Oils were mostly characterized by means of triacylglycerlogycerols profiles, even if some studies focused on proteins/peptides and phospholipids were also reported. Again, proteomic studies were the most performed in matrices such as fish and meat as well as in fruit and vegetables samples, where smaller polyphenolic and carotenoid compounds were also determined. The MALDI approach has proved to be an excellent system for the determination of food fraud, allowing in many cases the development of reliable, fast, and cost-effective analytical methods, often requiring very simple sample pre-treatment protocols, and sometimes assisted by chemometrics. On these bases, also considering the noticeable number of recent papers available in the literature, a further increase of these applications is likely to be observed in the next future.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
# A Dual-Branch Speech Enhancement Model with Harmonic Repair
## 2 Proposed Methods
### Time Series Modeling  
To avoid the issues caused by the 3S paradigm adopted in the recent Continuous Speech Separation (CSS) systems [22; 23; 24], such as the increased computational burden due to multiple overlaps between windows, and the dilemma of choosing window length for the performance and stitching stability, for time series modeling, the enhancement network employs Long Short-Term Memory (LSTM) layers with memory skipping to capture the contextual information of speech [25]. This layer is an improvement on LSTM [26], and the traditional LSTM mapping function can be represented as  
\[\hat{W},\hat{c},\hat{h}=LSTM(W,c,h), \tag{1}\]  
where \(W\in\mathbb{R}^{T\times N}\) is the input sequence, and \(c\) and \(h\) are the initialized cell state and hidden state, respectively. On the left side of the equation, \(\hat{W}\) represents the output sequence, while \(\hat{c}\) and \(\hat{h}\) are the updated cell state and updated hidden state, respectively. Generally, it is believed that \(\hat{c}\) encodes the entire long-term memory sequence to form long-term memory, while \(\hat{h}\) is used for short-term memory of the processed sequence.  
In the time domain task of speech, T in the input sequence \(W\in\mathbb{R}^{T\times N}\) can usually take a very large value. \(W\) can be divided into several smaller segments \(\left[w_{l}^{1},w_{l}^{2},\cdots,w_{l}^{5}\right]\), where \(S\) is the total number of segments, and the length of each segment is determined using the parameter \(K\), with \(W_{l}^{s}=W[sK-K:sk,:]\in\mathbb{R}^{K\times N}\).  
The Skipping-Memory LSTM, which consists of L basic layers connected in series, is shown in Figure 4. In each layer structure, \(S\) seg-LSTMs are used to process the \(S\) small  
Figure 3: The structure of the harmonic fading-out module.  
segments \(\ [w_{l}^{1},w_{l}^{2},\cdots,w_{l}^{5}]\), where 1 represents the l-th input. At this point, the mapping function of the seg-LSTM can be expressed as  
\[\overline{W}_{l+1}^{S},c_{l+1}^{S},h_{l+1}^{S}=\text{Seg\_LSTM}\left(W_{l}^{s},c _{l}^{s},\hat{h}_{l}^{s}\right) \tag{2}\]  
and  
\[W_{l+1}^{s}=\text{LN}\left(\overline{W}_{l+1}^{s}\right)+W_{l}^{s} \tag{3}\]  
where LN is the layer normalization operation in the residual connection, and \(\hat{c}_{1}^{s}\), \(\hat{h}_{1}^{s}\) are all initialized to 0. All the segments are finally collected in the Mem-layer for global modeling to conduct cross-segment processing. The memory-skipping LSTM constructed in this way can handle relatively long speech sequences. By purposefully discarding the overlapping areas of adjacent segments, it achieves an effective balance between performance and efficiency.
# A Cross-Level Iterative Subtraction Network for Camouflaged Object Detection
## 4 Experiments
### Ablation Studies
#### 4.5.1 Effectiveness of Cross-Level Integration Mechanism and Strip Convolutions in MSCSub
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**cross\_level**} & \multirow{2}{*}{**adjacent\_level**} & \multirow{2}{*}{**strip\_conv**} & \multicolumn{4}{c}{**COD10K-Test**} & \multicolumn{4}{c}{**NC4K**} \\ \cline{5-12}  & & & & \(\mathbf{S_{a}\uparrow}\) & \(\mathbf{E_{\phi}\uparrow}\) & \(\mathbf{F_{\beta}^{\omega}\uparrow}\) & \(\mathbf{M\downarrow}\) & \(\mathbf{S_{a}\uparrow}\) & \(\mathbf{E_{\phi}\uparrow}\) & \(\mathbf{F_{\beta}^{\omega}\uparrow}\) & \(\mathbf{M\downarrow}\) \\ \hline \#1 & ✓ & & & & 0.878 & 0.930 & 0.810 & 0.022 & 0.879 & 0.927 & 0.834 & 0.036 \\ \#2 & ✓ & & & 0.876 & 0.932 & 0.809 & 0.023 & \(\mathbf{0.880}\) & 0.928 & 0.834 & 0.036 \\ \#3 & ✓ & ✓ & & 0.873 & 0.930 & 0.804 & 0.023 & 0.878 & 0.927 & 0.831 & 0.036 \\ \#4 & & ✓ & & ✓ & 0.876 & 0.933 & 0.809 & 0.022 & \(\mathbf{0.880}\) & 0.928 & 0.832 & 0.036 \\ \#5 & ✓ & & & ✓ & 0.878 & 0.931 & 0.811 & 0.022 & \(\mathbf{0.880}\) & 0.930 & 0.836 & \(\mathbf{0.034}\) \\ \#OUR & ✓ & & ✓ & & **0.879** & **0.938** & **0.812** & **0.021** & **0.880** & **0.931** & **0.837** & **0.034** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Ablation study on the effectiveness of cross-level integration mechanism and strip convolutions in MSCSub on COD10K and NC4K.
## 4 Discussion
Furthermore, slab ground motion prediction equations (GMPEs) account for hypocentral distance, indicating that the probability density functions of distances are influenced by the depth of the slab area source. Consequently, this results in lower peak ground acceleration (PGA) and peak ground velocity (PGV) values than those computed using crustal models. Therefore, when considering both crustal and slab area sources, the PGA and PGV values are reduced, providing a more realistic representation of seismic hazard. Future research could involve the disaggregation of PSHA outcomes to identify the parameter pair of magnitude and epicentral distance that contributes most to the seismic hazard. This could facilitate the generation of seismic scenarios and enable the adoption of stochastic modeling of seismic hazard. Modern artificial intelligence (AI) techniques could also offer a promising alternative to earthquake prediction (in terms of future earthquake probabilities) using reliable seismological and geophysical indicators as an input [98; 99]. Additionally, a comprehensive investigation of the Peak Ground Rotational Acceleration (PGRA) and Velocity (PGRV) values could be conducted, given their potential utility for engineering purposes [58]. Finally, the results of the present seismic hazard study could be leveraged in the future to evaluate seismic risk after the integration of vulnerability data. The evaluation of seismic vulnerability is of critical importance for Athens, the most populated city in Greece, as it hosts a plethora of different structural typologies.
## 2 Materials and Methods
### Experimental Setup  
The design of the experimental set up is shown in Figure 1 and the caption contains all essential information for its operation.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Average Value** \\ \hline pH & 7.3 \\ Conductivity (\(\upmu\)s/cm) & 560 \\ Total Hardness (mg CaCO\({}_{3}\)/L) & 290 \\ Iron (\(\upmu\)g/L) & \textless{}20 \\ Manganese (\(\upmu\)g/L) & \textless{}5 \\ Sulfate (mg/L) & 12 \\ Total Organic Carbon (TOC) (mg/L) & 0.25 \\ Nitrate (mg/L) & 2 \\ Chloride (mg/L) & 15 \\ Total Chromium (\(\upmu\)g/L) & \textless{}1 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Physicochemical parameters of the drinking water from the city of Thessaloniki [19].  
This comprised two treatment parts in row. In the first part, chromium reduction took place in a reactor consisting of pipes via the addition of ferrous sulfate, and in the second part, the produced precipitates were removed by sand filtration. The characteristics of the treatment plant are given in the figure caption.  
The chromium-polluted water was prepared in the 200-L tank. A peristaltic pump drove the polluted water into the pipe reactor system and the flow rate was adjusted accordingly at 15, 30, 44 and 54 L/h. A peristaltic pump pushed the reductant (ferrous sulphate) into the pipe reactor system. The flow rate of peristaltic pump was set at 2 L/h. In the pipe reactor system, the polluted water was mixed with the reductant and the red-ox reaction took place. Fe(II) was oxidized to Fe(III) and Cr(VI) was reduced to Cr(III). The experimental runs took place at the pH value of the tap water of Thessaloniki which is \(7.3\pm 0.1\). The water flowed afterwards through the sand filter, and the formed particles which contain iron and the reduced hexavalent chromium were removed from the water stream by filtration.  
Sampling locations included: (a) the inlet water tank, representing the feedwater influent, corresponding to water spiked with Cr(VI) and (b) the filtered effluent. Total chromium, Cr(VI), Total Iron and Fe(II), pH of treated water and conductivity were measured in each sample on an hourly basis. Regularly, dissolved oxygen and redox potential were measured in these samples.  
The experiments were conducted in a continuous operation mode, applying a once through pass of the Cr(VI) contaminated water through the experimental unit under room temperature (20-22 \({}^{\circ}\)C). The studied treatment unit has the capacity of treating 500 to 1200 L of contaminated groundwater per day, therefore it is simulating treatment needs at the household level, given that the daily water needs per person in Europe is about 130 to 150 L/day.
## 4 Distribution of the Subspace-Based Damage Detection Techniques
### Distribution of the Papers on SSI-COV Approach
A simulated bridge deck with controlled temperature variations was used for verification of the proposed method. Efficiency of the method on simulation model for various temperature cases was confirmed. [PERSON] et al. [168] used a residual of the subspace system identification and global \(\chi\)2-tests for damage detection. A full-scale bridge benchmark was validated by numerical simulation. It is reported that the damage in tower was detected in the same time. In order to consider nonlinearity of structures for identification of modal characteristics [PERSON] et al. [71] defined a nonlinear subspace distance as damage feature. The proposed index was validated by the data obtained from a viscoelastic sandwich structure (VSS) subjected to an accelerated ageing. It is shown that the designed index is very effective to evaluate the health state in the structure. [PERSON] et al. [169] adopted Mahalanobis and Euclidean distance decision functions for the pattern recognition of a proposed damage index. One numerical signal and two simulated FE dynamic beam models were used for the verification of the proposed procedure. The method was capable of locating damage in FE beam structures. Details of selected papers which adopted the SSI-COV approach in their identification process are presented in Table 14.
## 5 Numerical Results
We assume that these errors follow an independent Gaussian distribution, represented as \(\varepsilon_{\mathrm{CSI}}\sim\mathcal{N}(0,\sigma_{\varepsilon}^{2})\). The variances of these errors are represented by the error parameters \(\delta\) and \(\vartheta\), i.e., \(\sigma_{\varepsilon}=(\delta g)^{\vartheta}\)[32]. We present the simulation results for four different error levels, where \(N=4,K=2\), and \(P_{d}=-13\) dBm. The legend 'perfect CSI' represents the case where the variance is 0. It is observed that both Algorithms 2 and 3 exhibit good robustness. Furthermore, the imperfections in the channel can be mitigated by increasing the transmit power. Figure 5: Sum-rate performance of the proposed MU-PhC-MIMO VLC system with \(N=16\) for different numbers of users. Figure 6: Convergence of Algorithm 1. (**a**) Running Algorithm 1 with five different \(\{\hat{\mathcal{U}}_{t},\hat{\mathcal{V}}_{t}\}\) scenarios determined by Algorithm 3 under \(P_{\text{s}}=-16\) dBm. (**b**) Running Algorithm 3 for different transmit-power scenarios and illustrating the convergence process of Algorithm 1 corresponding to the optimal solution cases.
# Design of a Filtering Power Divider with Simple Symmetric Structure Using Stubs
## 3 Structure of the Proposed WPD
### Odd and Even-Mode Analyses  
The odd- and even-mode equivalent circuits for the initial design of the WPD structure at an operating frequency of 2 GHz are depicted in Figure 5. It should be mentioned that the simulation results for the initial design WPD structure at an operating frequency of 2 GHz are shown in Figure 3b. From the odd-mode equivalent circuit in Figure 5a, Equation (1) can be extracted.  
\[\frac{2}{R(\Omega)}+\frac{-j\cot(\theta_{1})}{2Z_{1}(\Omega)}=\frac{1}{50( \Omega)} \tag{1}\]  
By equating the imaginary and real parts of Equation (1), it can be concluded that \(R=100\)\(\Omega\) and \(\theta_{1}=90^{\circ}\). Furthermore, the even-mode equivalent circuit impedance relations can be written as shown in Equation (2).  
\[\frac{Z_{1}(\Omega)+j\times 100(\Omega)\times tan(\theta_{1})}{100(\Omega) \times+j\times{Z_{1}}^{2}(\Omega)^{2}tan(\theta_{1})}+\frac{1}{Z_{M}(\Omega)+5 0(\Omega)}=\frac{1}{50(\Omega)} \tag{2}\]  
Figure 4: Structure and frequency response of the basic power divider design at the operating frequency of 2 GHz. (**a**) Layout; (**b**) \(\mid\)S\({}_{21}\mid\) and \(\mid\)S\({}_{11}\mid\).  
Figure 5: The (**a**) odd- and (**b**) even-mode equivalent circuit for the initial design WPD at operating frequency of 2 GHz.  
We assume the value of \(\theta_{2}=90^{\circ}\) results in \(Z_{\rm M}=0\). Moreover, by considering the obtained value of \(\theta_{1}=90^{\circ}\) in Equation (2), the values of \(Z_{1}\) will be calculated as \(Z_{1}=70.7~{}\Omega\).  
The odd- and even-mode equivalent circuits for the basic design of the WPD structure at an operating frequency of 2 GHz are depicted in Figure 6. It should be mentioned that the simulation results for the basic design of the WPD structure at an operating frequency of 2 GHz are shown in Figure 4b. It can be seen that the odd mode of the two circuits in Figures 5 and 6 is the same, so it can be concluded that \(R=100~{}\Omega\) and \(\theta_{1}=90^{\circ}\). Furthermore, the impedance relations of the even-mode equivalent circuit can be written in Equation (3).  
\[\frac{-j\cot(\theta_{3})}{2Z_{3}(\Omega)}+\frac{Z_{1}(\Omega)+j\times 50(\Omega) \times tan(\theta_{1})}{50(\Omega)\times Z_{1}(\Omega)+j\times{Z_{1}}^{2}( \Omega)^{2}tan(\theta_{1})}=\frac{1}{100(\Omega)} \tag{3}\]  
Considering the obtained value of \(\theta_{1}=90^{\circ}\) in Equation (3), the values of \(Z_{1}\) and \(\theta_{3}\) will be calculated as \(Z_{1}=70.7~{}\Omega\) and \(\theta_{3}=90^{\circ}\) will be achieved. From both circuit analyses, it can be concluded that the values of \(Z_{2}\) and \(Z_{3}\) can be freely changed while the equations are valid. Therefore, the values \(Z_{2}\) and \(Z_{3}\) can be used to tune the desired bandwidth of the divider.