esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Digestate as Fertilizer  
### Use of Digestate as a Fertilizer  
Soil fertilization remains the most widely used method for raw digestate management, requiring minimal processing [6]. While this practice has been in place for years, recent studies have focused on the role of digestate-derived fertilizers in soil amendment. However, their effectiveness varies significantly depending on feedstock composition, which influences chemical properties and fertilization efficiency [18; 50]. Although research has primarily examined agricultural feedstocks due to their relevance in sustainable farming, further studies are needed to assess the specific effects of individual feedstocks on digestion and fertilization.  
Nutrient availability plays a key role in digestate fertilization potential. Agricultural manure and slurry digestates typically contain higher nitrogen, phosphorus, and potassium levels than crop-based digestates. In contrast, crop digestates, though lower in nutrient content, are richer in organic carbon, with higher carbon-to-nitrogen ratios, promoting soil organic matter enrichment [12; 51; 52]. Organic fractions of solid waste digestates have intermediate nutrient levels--higher than crop digestates but lower than manure digestates--reducing the risk of nutrient overload and ammonia volatilization [18; 53].  
Soil pH and salinity regulation are particularly relevant for manure and slurry digestates, which help neutralize acidic soils [54; 55; 56]. In contrast, food waste and organic fraction of municipal waste digestates are generally neutral or slightly alkaline, making them suitable for agricultural use by preventing soil pH fluctuations and heavy metal mobilization [18].  
Microbial activity and stability further influence fertilizer quality. Digestates with high microbial activity, such as those derived from manure and slurry, accelerate organic matter decomposition, enhance nutrient release, and improve stability--reducing volatilization, leaching, and pathogen release while minimizing overall environmental impact [12]. Chemical composition and fertilizing properties vary between digestate types and within digestates from the same category. The results shown in [57] demonstrated that digestates from cattle manure and slurry exhibit significant differences in composition and stability depending on co-digestion materials and process conditions. More biodegradable feedstocks, such as slurry, tend to result in nitrogen loss due to immobilization, reducing fertilization potential. In contrast, manure-derived digestates retain ammonium, leading to better short-term nutrient availability.  
To complement the qualitative description above, Figure 1 summarizes the relative nutrient content of digestate derived from different feedstocks. These visual and tabular comparisons provide a clearer overview of how nitrogen, phosphorus, potassium, the C:N ratio, and organic matter content vary depending on the source material and underline the importance of substrate-specific digestate management.
# Evaluation of Sub-Lethal Toxicity of Benzethonium Chloride in _Cyprimus carpio_ [PERSON]
###### Abstract  
Benzenthonium chloride (BEC, Hyamine 1622) is a quaternary ammonium surfactant with cationic properties widely used in cleaning, sanitation, and medical products that can become harmful to humans and also to the environment. This study aimed to evaluate its acute effects on _Cyprinus carpio_ fish in terms of oxidative stress and morphological changes on hepatic tissue in order to show the sub-lethal toxicity of BEC. Fish were exposed to 1 mg/L BEC for 24, 48, and 96 h, and the liver samples were collected. The most significant changes were noticed after 96 h of exposure when the entire antioxidant enzyme system was affected. The activities of catalase, glutathione peroxidase, glutathione reductase, and glutathione S-transferase decreased by 44%, 31%, 30%, and 45%, respectively, compared to control. Glucose-6-phosphate dehydrogenase activity decreased by 29% after 96 h of control, inducing a reduction of NADPH formation which decreased by half the level of reduced glutathione, the main non-enzymatic antioxidant. These effects correlated with the raised value of lipid peroxidation after 96 h and the morphology changes on hepatic tissue, such as cytoplasmic vacuolization and nuclear hypertrophy that could affect the normal function of the liver. All of these results showed acute toxicity of BEC on _C. carpio_ after 96 h of exposure, causing oxidative stress response at the hepatic level.  
benzethonium chloride; cationic surfactants; _Cyprinus carpio_; oxidative stress; antioxidant enzymes
###### Abstract  
Global remote sensing of solar-induced fluorescence (SIF), a proxy for plant photosynthetic activity, represents a breakthrough in the systematic observation of global-scale gross primary production and other ecosystem functions. Here, we hypothesize that all earth ecosystem variabilities, including SIF, are affected by climate variations. The main contribution of this study is to apply a global empirical orthogonal function (EOF) analysis of SIF to quantify the relations between the large-scale GPP variability and climate variations. We used 2007-2019 SIF data derived from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensor observations and a rotated empirical orthogonal function (EOF) analysis to explore global SIF variability over years and decades. The first leading EOF mode captures the well-known ENSO pattern, with most of the variance over continents in the tropical Pacific and Indian Oceans. The second and third leading EOF modes in SIF variability are significantly related to the NAO and PDO climate indices, respectively. Our analysis also shows that the 2011 La Nina (2015 El Nino) elevated (decreased) global SIF.  
solar-induced chlorophyll fluorescence; remote sensing; variability; climate indices 2022
# Review of CMOS Integrated Circuit Technologies for High-Speed Photo-Detection
## 6 Clock and Data Recovery (CDR) Circuits  
### CDR Basic  
Because the transmission of binary data in optical communications is based on a time-division multiplexing [116], just amplifying the incoming signal is not sufficient to recover the data [93]. The other requirement for the complete recovery of the data is to retime the incoming data with a clock whose frequency is well-aligned with the bit-rate of the data. In general, the retiming operation is based on sample-and-regeneration using a clocked sense amplifier [117; 118]. That is, the timing information of the data is recovered by sampling, while the value of binary data is gathered by sampling and recovered to digital rail-to-rail amplitude by regenerating. Notably, the SNR at the sense amplifier input is restored after being regenerated at the sense amplifier output, unlike linear amplifiers where the input SNR propagates to the output, because the regeneration is based on the positive feedback. Rather, the input SNR leads to a probability of wrong decisions while the output has little noise component. Therefore, during the retiming operation, it is very important to sample the data at a proper time at which the SNR is maximized. Unlike the retiming of the digital signal domain, where only the requirements of the setup and hold time are considered, the error rate from the retiming of analog domain varies with the timing, even though the timing satisfies the setup and hold time requirements. Figure 41a illustrates this aspect. In [119], the theoretical dependency of BER on the sampling timing is analyzed. The calculated BER as a function of the sampling timing using  
Figure 40: Resistor-based TIA with IIR-DFE proposed in [55].  
Figure 39: Simplified block diagram of DFE.  
the formula provided in [119] is shown in Figure 41b, where a maximum SNR of 10 is used for the calculation. For the sake of simplicity, it is assumed that there is no random timing error, which is referred to as a jitter. As observed in Figure 41b, the BER is exponentially degraded as the sampling timing alters from the ideal position. A CDR circuit is used as the building block of an optical receiver, and it generates the sampling clock with a precise frequency and drives the sampling timing to the ideal position. In conventional optical receivers, the importance of CDR has been underestimated or even ignored for a long time [93]. However, recently, there have been some engineering examples that include the CDR circuits for better performance and robustness. This section provides the CDR circuit examples used in a high-speed photodetection receiver.
# Multivalent Aptamer Approach: Designs, Strategies, and Applications
## 4 Biosensing and Biomedical Applications
### Biosensors
In this work, the PDMS microfluidic channel was modified with PAMAM dendrimers that were subsequently conjugated with capturing long ssDNA chains containing hundreds of repeating aptamer units. The resultant channel modified by multivalent aptamer chains captured approximately 5-fold more target cells compared to a channel modified by aptamer monomers. More importantly, this multivalency-driven improvement was observed to be more significant under higher flow rates, suggesting that this multivalent strategy can be a potential solution for achieving higher throughput in microfluidic devices while maintaining sufficient capturing efficiencies.
## 3 Results and Discussion
### Soil Leaching by Low-Molecular-Weight Organic Acids
#### 3.2.1 Effects of Organic Acids on the Lead Removal from Protogenetic Soil  
Five kinds of inorganic acids (CA, OA, TA, AA, and MA) were used for leaching remediation of lead-contaminated soil. The remediation results are shown in Figure 4. It can be seen that under the same leaching conditions, CA showed the highest leaching efficiency of Pb\({}^{2+}\) in contaminated soil, reaching 61.4%, which is slightly higher than that of MA, i.e., 58.5%, followed by AA, while TA and OA had a weak ability to leach Pb\({}^{2+}\) from soil. Compared with inorganic acids such as HCl, the remediation efficiency of organic acids was not much lower. Generally speaking, the remediation ability of organic acids to heavy metals is related to the number of functional groups such as hydroxyl and carboxyl groups. CA is a tribasic acid, which can provide more reaction sites and more H\({}^{+}\) at the same time, so it has a strong acid dissolving effect and can dissolve lead ions adsorbed in the soil; in addition, it is also a natural chelate agent, with a certain complexity ability; that is, it can couple with Pb\({}^{2+}\) in the soil to form soluble complexes, enhancing the activity and mobility of the Pb\({}^{2+}\) so as to be leached out. TA and OA are both dicarboxylic acids and have fewer reaction sites, which could provide limited acidity and acid radical ions. In addition, their acid radical ions, such as oxal acid ions, could further react with Pb\({}^{2+}\), as shown in Equation (12) and form insoluble compounds PbC\({}_{2}\)O\({}_{4}\) (K\({}_{\text{sp}}\) = 4.8 \(\times\) 10\({}^{-10}\)) [39], thereby inhibiting the leaching of Pb\({}^{2+}\), leading to the lower remediation efficiency. Hence, CA presents the best repair effect.  
\(\text{C}_{2}\text{O}_{4}{}^{2-}+\text{Pb}^{2+}=\text{PbC}_{2}\text{O}_{4}\) (12)  
Figure 4: Remediation efficiency of five organic acids.
## 3 Results
### Transcriptional Activity of the Apoptosis-Related Genes
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **C** & **F** & **F + SMF1** & **F + SMF2** & **F + SMF3** & \({}^{*}p\) \\ \hline \multicolumn{8}{c}{**mRNA Copy Numbers/ng RNA**} \\ \hline SOD1 & 1,359,583 \(\pm\) 114,105 & 1,438,688 \(\pm\) 177,946 & 1,343,5500 \(\pm\) 19,0836 & 1,29,125 \(\pm\) 163,142 & 1,764,375 \(\pm\) 183,910 & 0.007 \\ \hline SOD2 & 200,606 \(\pm\) 21,341 & 206,831 \(\pm\) 15,712 & 228,050 \(\pm\) 13,736 & 216,919 \(\pm\) 13,361 & 251,125 \(\pm\) 22,574 & 0.009 \\ \hline _CSR_ & 65,088 \(\pm\) 4503 & 69,269 \(\pm\) 13,353 & 63,300 \(\pm\) 16230 & 80,150 \(\pm\) 4503 & 101,813 \(\pm\) 11,462 & \(<\)0.001 \\ \hline _CAT_ & 47,069 \(\pm\) 15,632 & 51,825 \(\pm\) 9008 & 58,769 \(\pm\) 8490 & 61,044 \(\pm\) 16,132 & 60,588 \(\pm\) 10,691 & NS \\ \hline _GPx1_ & 544,500 \(\pm\) 81,698 & 511,500 \(\pm\) 48,140 & 522,750 \(\pm\) 63,346 & 507,000 \(\pm\) 30,043 & 473,500 \(\pm\) 65,479 & NS \\ (glutathion peroxidase 1) & 283,006 \(\pm\) 56,731 & 339,250 \(\pm\) 80,532 & 208,100 \(\pm\) 117,469 & 420,725 \(\pm\) 264,477 & 294,994 \(\pm\) 293,390 & NS \\ \hline _NFE2L2_ & 238,755 \(\pm\) 89,756 & 28,271 \(\pm\) 28,022 & 143,538 \(\pm\) 78,523 & 129,013 \(\pm\) 51,919 & 127,938 \(\pm\) 25,088 & 0.006 \\
2-related factor 2) & & & & & & \\ \hline \multicolumn{8}{c}{C—control cells; F—sodium fluoride (NaF)-treated cells; F + SMF1—NaF-treated cells and exposed to SMF with 0.45 T flux density; F + SMF2—NaF-treated cells and exposed to SMF with 0.55 T flux density; F + SMF3—NaF-treated cells and exposed to SMF with 0.65 T flux density; the results are expressed as the means \(\pm\) standard deviation (SD); statistical significance: \({}^{*}p<0.05\), the one-way analysis of variance (ANOVA) test, NS—not statistically significant.} \\ \hline \multicolumn{8}{c}{_NFE2L2_} \\ \multicolumn{8}{c}{0.45 T flux density; F + SMF2—NaF-treated cells and exposed to SMF with 0.45 T flux density; F + SMF2—NaF-treated cells and exposed to SMF with 0.45 T flux density; F + SMF3—NaF-treated cells and exposed to SMF with 0.65 T flux density; the results are expressed as the means \(\pm\) standard deviation (SD); statistical significance: \({}^{*}p<0.05\), the one-way analysis of variance (ANOVA) test, NS—not statistically significant.} \\ \hline \end{tabular}
\end{table} 
Table 1: The expression of the cellular antioxidant system-related genes in fluoride-treated fibroblasts and in fibroblasts that had been treated with fluoride, and then subjected to the influence of static magnetic fields (SMFs) of different intensities (0.45, 0.55, and 0.65 T) for 12 h compared to the control culture without fluoride and without the magnet (flux density 0.0 T). The above data indicate that the genes whose expression is associated with the induction of apoptosis are down regulated as a result of the exposure to a SMF; the effect was strongest on the cells that had been subjected to a SMF with a 0.65 T flux density.
## 3 Dynamic Seal Package  
As previously stated, the test bench for the DSP components developed by Avio was taken as a reference application. A redesigned and more compact DSP dedicated to a new oxygen turbopump was tested to verify the separation between the hot gases feeding the turbine (\(+600\)\({}^{\circ}\)C) and the LOx on the pump side (\(-180\)\({}^{\circ}\)C). A dedicated test bench was therefore developed to simulate the oxidizer turbopump's secondary flow paths and test the DSP's operation.  
Figure 4 shows a simplified cross-section of the DSP test bench. The assembly was characterized by the oxidizer turbopump's shaft, the bearings, the seal package, and a  
\begin{table}
\begin{tabular}{l l} \hline \hline
**State Variable** & **Governing Equation** \\ \hline Species masses & Mass conservation equations (Equation (1)) \\ Flow rate & Momentum conservation equations (Equation (2)) \\ Fluid enthalpy & Energy conservation equations of fluid (Equation (3)) \\ Species enthalpies & Energy equations of fluid (Equation (17)) \\ Wall temperature & Energy conservation equations of solid (Equation (4)) \\ Pressure & Thermodynamic state (Equation (19)) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Mathematical closure of the model formulation, where each state variable and the designed governing equation to solve that variable are listed.  
series of inlet and drainage ducts used to simulate the inlets and outlets of fluids within the secondary flow paths. The DSP uses He as a buffer fluid and keeps the internal fuel and oxidizer seal leakage flows separated. The gaseous nitrogen (GN2) and LOx inlets are two conduits that simulate the hot gas from the turbine and the oxidizer flow used to cool the bearings, respectively. He is injected between the two fluids through the He inlet at a pressure high enough to guarantee no flow return across the segmented seal, avoiding mixing between the two propellants. Both GN2 and LOx mix with He in two separate drainage ducts and exit the assembly. Finally, the slinger and the labyrinth seal were designed to lower the pressure and density of the oxygen flowing from the bearing's chamber to the drainage, thus limiting the oxygen leakage.  
The validation of the numerical tool was carried out considering the portion of the Dynamic Seal Package dedicated to He/LOx. The DSP test bench is instrumented with several probes to check the operation of the DSP under various conditions. Four temperature probes were selected to carry out the validation of the tool, two of which are located in the drain conduit, while the other two are in the He inlet. Both pairs of probes are placed radially opposite each other in the outer crown, aligned with the drainage conduit.
## 2 Technical Background  
### Basis Pursuit  
In the theory of CS, the number of observations is much smaller than the length of the signal, so the signal reconstruction is faced with the problem of solving underdetermined equations. In order to solve this problem, the BP algorithm is proposed. The BP algorithm is a new method in signal sparse representation and also a principle of global optimization [14]. The observation matrix has restricted isometric properties (RIP). Moreover, RIP also provides a theoretical guarantee for accurately recovering signals from observed values. The classical basis pursuit algorithm is based on the above principles to achieve the purpose of reconstruction and Gaussian white noise denoising. At present, the basis pursuit method has good applications in the field of one-dimensional signal processing [31; 32; 33]. In the case of noisy observations, the model is as follows:  
\[\mathrm{y}=Mx+f+n \tag{1}\]  
where \(x\in R^{n}\) is an unknown vector, \(y\in R^{m}\) is the measuring signal, the baseline wander \(f\), and the Gaussian white noise \(n\). \(M\in R^{m\times n}\) is the perceptual matrix, and the goal is to recover the unknown vector \(x\) from the noisy signal \(y\).
# Dynamic Cooperative MAC Protocol for Navigation Carrier Ad Hoc Networks: A DiffServ-Based Approach
## 4 DiffServ-Based Dynamic Cooperative MAC Protocol
### MAC Sub-Protocol with Optimal Relay
#### 4.3.1 Optimal Relay Selection Algorithm  
**Definition 3** (Optimal relay).: _Given the pair \((s,r),s,r\in\mathbf{C}_{g}\), its optimal relay \(s_{\text{rly}}\) is the node satisfying the following constraints. (i) Relay \(s_{\text{rly}}\) is within neighbor sets of nodes \(s\) and \(r\), simultaneously. (ii) Relay \(s_{\text{rly}}\) can decode RTS and CTS of the pair \((s,r)\) correctly. (iii) Relay \(s_{\text{rly}}\) holds the maximum SNR (denoted by \(\gamma_{\text{SRD}}\)) among the candidate relay set (CRS)._  
Conditions (i) and (ii) are the prerequisites for a node to be a CRS member, and condition (ii) can be realized by checking the CRC of the received packet. To reduce the decoding overhead, we adopted an SNR-based checking method, in which a packet will be decoded only if the value of its instantly  
Figure 5: Schematic diagram of data transmission phase.  
receiving SNR exceeds the SNR threshold; thus, the packet below the SNR threshold will be discarded. The following algorithms are designed to judge condition (iii).  
**Proposition 1** (Optimal link).: _Given the quasi-stationary fading channel with free space channel amplitude, the link \(i_{\text{max}}\) with the maximum SNR value can be derived as follows:_  
\[i_{\text{max}}=\underset{1\leq i\leq n}{\text{argmax}}\Big{\{}\gamma_{SRD}^{i} \Big{\}},\,i_{\text{max}}\in\{1,\ldots,n\} \tag{3}\]  
_where \(\gamma_{SRD}^{i}\)is the instantly receiving SNR value of the link \(i\)_  
\[\gamma_{SRD}^{i}=\frac{\gamma_{SR}^{i}\gamma_{DR}^{i}}{\gamma_{SR}^{i}+\gamma_ {DR}^{i}+1},\,i\in\{1,\ldots,n\} \tag{4}\]  
\(\gamma_{SR}^{i}\) _and \(\gamma_{DR}^{i}\) are the average receiving SNR from sender \(s\) to candidate relay \(s_{\text{rly}}^{i}\) and from \(s_{\text{rly}}^{i}\) to receiver \(r\), respectively. As inspired by the literature [29; 30], we design a back-off timer, in which the candidate relay starts its back-off timer as follows:_  
**Proposition 2** (Back-off timer).: _Let the back-off time \(T_{\text{back}-off}^{(i)}\) of the candidate relay \(s_{\text{rly}}^{i}\) be inversely proportional with the link quality \(\gamma_{SRD}^{i}\), then \(s_{\text{rly}}^{i}\) sets its timer according to (5)_  
\[T_{\text{back}-off}^{(i)}=\left[\frac{\gamma_{low}}{\gamma_{SRD}^{i}}\frac{T_{ \text{DIFS}}-T_{\text{SIFS}}}{T_{slottime}}\right],i=1,2,\cdots,n \tag{5}\]  
_where \(T_{\text{back}-off}^{(i)}\) is the back-off time of relay \(s_{\text{rly}}^{i}\), \(\gamma_{low}\) is the threshold of \(\gamma_{SRD}^{i}\) for the relay \(s_{\text{rly}}^{i}\) intending to participate in retransmission, and \(n\) is the number of candidate relay within CRS._  
The optimal relay, which has the optimal link quality and satisfies the constraints of Definition 3, will have the shortest back-off time and get access to the channel first.