esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Berry Analysis  
Non-invasive measurements of 19 berries per 30 berries were conducted in the lab directly after berry sampling by using a hand-held optical sensor based on chlorophyll fluorescence (Multiplex Research(r), Force-A, Orsay, France) as described previously [30; 31]. The spectroscopic index SFR_R (simple fluorescence ratio after red excitation) as a chlorophyll index was calculated according to [PERSON] et al. [30]. The SFR_R index was related to total soluble solids (TSS).  
Juice of berry samples was obtained using a pressure-controlled sampling press at 1 bar (Longarone 85, QS System GmbH, Norderstedt, Germany). Must was collected in 50 mL tubes and centrifuged (5430R, Eppendorf AG, Hamburg, Germany) at 7830 rpm for 5 min at 20 \({}^{\circ}\)C. Must was analyzed for TSS (\({}^{\circ}\) Brix) using a handheld refractometer (HRKL32, Kruss, Hamburg, Germany). Total acidity (TA) and pH were measured with a 719 S Titrino and an additional 778 Sample Processor (Metrohm, Hamburg, Germany). The concentration of amino acids of the juice was determined according to the N-OPA procedure of [PERSON] [32]. Briefly, this method involves derivation of \(\alpha\)-amino acid groups with \(o\)-phthaldialdehydedehyde/N-acetyl-l-cysteine (OPA/NAC) reagent. Absorbance was measured at 335 nm with an UV/VIS spectrometer (Specord 500, Analytik Jena AG, Jena, Germany). Results were calculated as mg of isoleucine equivalent/L from a standard curve.  
Analyses of organic acids (tartaric acid, malic acid, citric acid, and shikimic acid) were performed using high performance liquid chromatography (HPLC) according to [PERSON] et al. [33] and modified by [PERSON] et al. [34] with the following changes: Firstly, 5 mL of sample was injected into the Agilent Technologies 1100 series liquid chromatograph equipped with a multiwave-length detector (MWD) and analyzed using an Allure(r) Organic Acid column (250 mm \(\times\) 4.6 mm inside diameter) (Restek GmbH, Bad Homburg, Germany) with a Security Guard(tm) Cartridge C18 \(\times\) 3 mm (Phenomenex,  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Vegetation Period** & \begin{tabular}{c} **Mean Daily Max.** \\ **Temperature (\({}^{\circ}\)C)** \\ \end{tabular} & \begin{tabular}{c} **Mean Daily Min.** \\ **Temperature (\({}^{\circ}\)C)** \\ \end{tabular} & \
\begin{tabular}{c} **No. of Heat** \\ **Days (\textgreater{}30 \({}^{\circ}\)C)** \\ \end{tabular} &
\begin{tabular}{c} **Precipitation** \\ **(mm)** \\ \end{tabular} \\ \hline
2014 & 21.6 & 11.3 & 10 & 441 \\
2015 & 21.5 & 10.5 & 26 & 227 \\
2016 & 21.5 & 10.5 & 17 & 371 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Climatic data for Geisenheim, Rheingau, Germany for growing seasons 2014 to 2016, 1 April-31 October.  
Aschaffenburg, Germany). As an eluent, distilled water was used with 0.0139% sulfuric acid and 0.5% (_v/v_) ethanol. The column was operated at 46 \({}^{\circ}\)C with an eluent flow rate at 0.6 mL/min. Eluting compounds were detected by UV absorbance at 210 nm. Organic acids are reported as single values because samples were taken as triplicates per single FACE ring.
## 5 Therapeutic Implications of WA in AD
### Role of WA and Its Derivatives
#### 5.1.2 WA Acts as Antioxidant in AD  
AD etiology often starts with the accumulation of \(\beta\)-amyloid fibrils, accompanied by tau pathology and then neuronal cell death. In this respect, the free radical-triggered harm of the brain tissues is also one of the vital factors considered in this disease. Furthermore, increased levels of Al, Fe, Hg, and Ca decreased polyunsaturated fatty acids, increased oxidation of protein and DNA and lipid peroxidation, and the presence of oxidation products such as carbonyls, malondialdehydedehyde, heme oxygenase-1, and peroxynitrite, which are initiators of free radicals, could trigger AD [146].  
In addition, WA was evaluated for antioxidant activity using major free-radical scavenging enzymes such as catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPX), and NADPH dehydrogenase levels in the frontal cortex and striatum of the rat brain [28]. It exhibits anti-oxidative activity by increasing the levels of various antioxidant enzymes, which reduce the free radicals or stress formed in the affected cells and provide a healthy mitochondrial function. This function is demonstrated in several recent studies by simple testing of treated and untreated mouse models and human cell lines. Treated cells with WA have significantly reduced cellular oxidative damage [152; 153]. Accordingly, these findings indicate that _W. sommifera_ extracts, especially WA, reduce oxidative stress and mitochondrial dysfunction, and their beneficial role appears to be primarily based on their antioxidant properties [6]. Withanamides are a subset of these components that have been proven to scavenge free radicals produced at the time of the initiation and progression of AD [7; 151].
## 4 Discussion
### Study Limitations  
A primary limitation of this study is its small sample size of 32 participants, which may affect the robustness of the findings and the effectiveness of the intervention. The participants formed a highly heterogeneous group with varying physical and functional issues, and age differences between groups approached statistical significance (\(p=0.06\)), potentially impacting results--particularly in Group I, where perceived exertion (RPE) could tended to be higher.  
Furthermore, the study included only a single training session and a brief testing period for the video games, leaving it unclear how enjoyment and satisfaction might evolve over a longer intervention period. Previous research has indicated that individuals with no prior experience in video games tend to experience greater enjoyment than those with experience; this is a limitation [44]. Although this is a limitation, this is the first study to compare different exercise doses through an augmented reality exergame.  
Additionally, although participants tolerated the interventions well and no serious adverse effects were observed, further and longer research is needed to better assess potential adverse effects in exergaming interventions.  
Another study limitation is the approach to exercise prescription, which ideally should be tailored to each participant to control intensity. In this case, participants self-selected their exercise intensity, potentially introducing variability in the prescribed intensity across individuals.
## 3 Results and Discussion
### Mediterranean System (Low Temperature)
The results of the TGA performed for the same three PCM candidates for the MED system are shown in Figure 3. The mass loss of the three PCM is less than 0.1% when the temperature is below 48 \({}^{\circ}\)C and only RT3 HC_1 reaches a mass loss of 1.5 wt % at 87 \({}^{\circ}\)C. At 100 \({}^{\circ}\)C. The mass losses for savE OM 03, RT4, and RT3 HC_1 are 0.45 wt %, 0.91 wt %, and 2.15 wt %, respectively. If a lower heating rate of e.g., 1 \({}^{\circ}\)C/min was used instead of 10 \({}^{\circ}\)C/min, the temperature for the stability limit would be lower than the values shown here, but still, the mass loss in the temperature range of the application would be negligible. Therefore, from this point of view, the three PCM candidates are suitable because the ambient temperature is expected to be below 50 \({}^{\circ}\)C in practically all locations in the world. To summarize, the results given by the decision matrix indicate that savE OM 03, RT4, A3, RT3 HC_1, and PureTemp 4 are the most promising options. Nevertheless, because of the very large hysteresis of around 8 \({}^{\circ}\)C, savE OM 03 is not a recommended option for the MED solution.
## 3 Intermittent Periodic Transmit (IPT)  
### Principle and Fundamental Characteristics on String Topology  
Figure 2 depicts the basic concept of IPT forwarding. As shown in Figure 1(a), the source node periodically transmits packets with a constant interval, \(P\), and relay nodes immediately forward their own packets after the reception of downlink packets, i.e., downlink packet flow is regarded as a  
polling signal. It is quite simple since the specific modification is required only in the core node. Interval \(P\) provides frequency reuse space (in this case, 3) and thus co-channel interference on the forwarding path, i.e., intra-path interference, can be avoided. It enables collision-free and highly efficient multi-hop relay while eliminating overheads such as request to send (RTS)/clear to send (CTS) handshakes and random back-off for CSMA/CA functions. Figure 3 plots basic throughput performance provided by IPT on the string topology compared to the RTS/CTS based CSMA/CA. This assumes transmission rate of 54 Mbps per hop and the signal radiation reaches for the adjacent nodes for simplicity. As shown, IPT forwarding can improve end-to-end throughput performance even while eliminating RTS/CTS function. Furthermore, throughput performance becomes independent of the hop count over 3 hops since the frequency reuse space of 3 is constantly kept.
## 3 Results and Discussion
### The Characteristics of Isolated Rhamolipid-Producing Bacterial Strain
#### 3.1.3 The Characteristics of Rhamolipids Produced by the Isolate  
TLC analysis revealed the presence of mono- and di-rhammolipids based on the spots at _Rf_ values of 0.31 and 0.81 in the biosurfactant mixture produced by the isolated _Shewanella_ strain (Figure 3a). These results are per the findings of [PERSON] and [PERSON] [17], who observed characteristic bands of the di- and mono- rhamnpid-type biosurfactants at _Rf_ values of 0.38 and 0.85, respectively. FTIR analysis also confirmed the presence of a rhamnpid-type biosurfactant based on the peaks located at 2929, 1636, 1405, 1222, and 1061 cm\({}^{-1}\), which corresponded to the presence of CH stretching vibration, C = O stretching vibration, CH/OH deformation, CH deformation, and C-O stretching, respectively (Figure 3b). [PERSON] et al. [51] showed that double bands at 2921 and 2855 cm\({}^{-1}\) corresponded to C-H vibrations, which represent the hydroxydecanoic acid chain tails of rhamnpid, while the C=O stretching band at 1730 cm\({}^{-1}\) is due to the presence of esters and carboxylic acid groups. The area between 1200 and 1460 cm\({}^{-1}\) represents C-H and O-H deformation vibrations, which are characteristic features of carbohydrate molecules. The other peaks might have occurred due to the protein contamination that occurred during the extraction process.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Source** & **Sum of Squares** & **Degrees of Freedom** & **Mean Square** & _f Value_ & _p-Value_ \\ \hline Model & 9.73 & 14 & 0.69 & 30.73 & \textless{}0.0001 \\ A-Crude oil & 6.51 & 1 & 6.51 & 287.93 & \textless{}0.0001 \\ B-Inoculation load & 1.35 & 1 & 1.35 & 59.87 & \textless{}0.0001 \\ C-Temperature & 0.07 & 1 & 0.07 & 3.11 & 0.0980 \\ D-pH & 0.01 & 1 & 0.01 & 0.46 & 0.5076 \\ AB & 0.46 & 1 & 0.46 & 20.15 & 0.0004 \\ AC & 5.62 & 1 & 5.62 & 0.25 & 0.6252 \\ AD & 5.62 & 1 & 5.62 & 0.25 & 0.6252 \\ BC & 0.01 & 1 & 0.01 & 0.69 & 0.4189 \\ BD & 6.25 & 1 & 6.25 & 0.02 & 0.8702 \\ CD & 0.01 & 1 & 0.01 & 0.69 & 0.4189 \\ A’2 & 0.87 & 1 & 0.87 & 38.49 & \textless{}0.0001 \\ B’2 & 0.02 & 1 & 0.02 & 0.96 & 0.3428 \\ C’2 & 0.37 & 1 & 0.37 & 16.22 & 0.0011 \\ D’2 & 0.37 & 1 & 0.37 & 16.22 & 0.0011 \\ Residual & 0.34 & 15 & 0.02 & & \\ Lack of Fit & 0.29 & 10 & 0.02 & 3.01 & 0.1179 \\ Pure Error & 0.04 & 5 & 9.66 & & \\ Cor Total & 10.07 & 29 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Results of ANOVA for the response surface quadratic model.
## 6 Experimental Evaluation
### Evaluation with Aggregate Privacy Attack
The **Reidentified (%)** rates in these trials range from 0% in multiple trials (e.g., Trials 2, 3, and 6) to a maximum of 0.37% in several trials, depending on the \(\varepsilon\) value used. The parameter \(\varepsilon\) is called a privacy budget; it controls the trade-off between privacy and data utility. A smaller \(\varepsilon\) means stronger privacy protection. However, a lower \(\varepsilon\) might also result in a higher utility metric, i.e., Topsoe Divergence. This is because a lower \(\varepsilon\) introduces more random noise to the data, making individual traces harder to distinguish but also increasing the overall distortion of mobility patterns [4]. Conversely, larger \(\varepsilon\) values allow for better data utility but may increase the risk of reidentification. In this case, the combined approach results in higher Topsoe Divergence values, particularly for \(\varepsilon=1\), where the average distance reaches 0.16 with a standard deviation of 0.016. This demonstrates a strong level of data protection, significantly enhancing privacy. In comparison, higher values of \(\varepsilon\) reduce the Topsoe Divergence. In comparison, the reidentification rate and average distance of mobility traces obfuscated only with LDPTrace (Table 4) are 0.31% and 0.16 for \(\varepsilon=1\), respectively. This is significantly lower than the reidentification rate of 19.20% and average distance of 0.034 observed in the non-obfuscated dataset (Table 1). However, when both HMC and LDPTrace are applied (Table 3), for \(\varepsilon=1\), the reidentification rate drops further to 0.19%, and the average distance increases to 0.162, highlighting the enhanced privacy protection achieved by combining both anonymization techniques.
## 5 Limitations  
This study has limitations inherent to cross-sectional studies like not being able to address temporality. We measure for two exposure variables: RAVLT and marital status, but in cross-sectional studies exposures, variables do not precede certain outcomes. Our use of RAVLT test does not avoid the complexity of having false positive subjects, who have the presence of brain dysfunction, errors occur when intact individuals are labeled as having brain dysfunction. The TADPOLE dataset is not a population-based sample. We can have by design, people with MCI and dementia over-sampled. We may infer that the results may not generalize to the community-dwelling population.
## 3 Application of AIEgens in the Detection of Pesticide Residues in Fluorescence Sensors
### Detection of pesticides Using Organic Fluorescent Small-Molecule Sensors Based on AIEgens
Inset: Variation of PL intensity with different water contents, with corresponding photos showing A3 solutions in THF/water mixtures with 0% and 90% water content; (**c**) Fluorescence spectra of A3 (1 uM) in the presence of increasing concentrations of trifluralin (20–1000 ug L\({}^{-1}\)); (**d**) Fluorescence images of A3 upon the addition of trifluralin (0–90 ug L\({}^{-1}\)), along with a schematic diagram showing the real-time recognition of RGB values of the A3 probe using a smartphone color recognizer. (Reproduced with permission from ref. [70]. copyright 2024 Elsevier). Figure 4: (**a**) Fluorescence intensity of A4 as a function of water content. Inset: Fluorescence photographs of A4 in water fractions of 0%, 80%, and 95%; (**b**) Fluorescence spectra of A4 (\(1.0\times 10^{-5}\) M) in DMSO/H\({}_{2}\)O (5/95) solution with various pesticides and metal ions (\(1.0\times 10^{-5}\) M each, \(\lambda\)ex = 380 nm). The labeled peaks correspond to: 1 = A4, 2 = 1 + Na+, 3 = 1 + K+, 4 = 1 + Ca2+, 5 = 1 + Mg2+, 6 = 1 + Al3+, 7 = 1 + thiamethoxam, 8 = 1 + hexazinone, 9 = 1 + fluoroxypyr, 10 = 1 + clopyralid, 11 = 1 + carbendazim, 12 = 1 + quizalofop-ethyl, 13 = 1 + glufosinate-ammonium, 14 = 1 + N-(Phosphomethyl) glycine 2-propylamine, 15 = 1 + mancozeb, 16 = 1 + thiophanate-methyl, 17 = 1 + sulfometuron-methyl, 18 = 1 + triclopyr 2-butoxyethyl ester, 19 = 1 + triadimefen, 20 = 1 + monosultap, 21 = 1 + molesultz, 22 = 1 + metaldehyde, 23 = 1 + bromoxynil octanoate, 24 = 1 + paclobutrazol. Inset: Photographs showing A4 alone and A4 with paclobutrazol; (**c**) Proposed sensing mechanism of A4 for paclobutrazol detection; (**d**) Photographs of real leaf samples (_Ophiopogon japonicus_, loquat tree, longan tree and guava tree) treated with paclobutrazol and A4, under daylight and UV light (365 nm). The samples were sprayed with a solution of paclobutrazol followed by A4; (**e**) Application on A4 (\(1.0\times 10^{-5}\) M) for the detection of paclobutrazol in lotus pond soil soaking solution samples. (Reproduced with permission from ref. [71]. copyright 2024 Elsevier). The studies above employ fluorescent probes made from organic small molecules with specific structures. Using mechanisms like AIE and PET, these probes achieve highly sensitive and selective detection of pesticides, including OPs, carbamates, and trifuralin. The development of portable detection platforms for use in complex environments further highlights the potential of composite materials combining AIEgens and organic small molecules for effective pesticide detection.
## 2 Theoretical Supports
### Failure Risk Assessment (FR-Assessment)  
The failure risk quantification of a structure can be possible by the concept of failure risk assessment. This can be measured via the mean annual of failure (\(\lambda_{c}\)) (either as a limit state or performance-based), which is the combination of the structural failure probability analysis for different failure states and the seismic hazard analysis [3].  
The structural failure probability is defined as the probability of failure, that the seismic demand placed on the structure is greater than the capacity of the structure [45]. In another word, the fragility curves are defined as the seismic capacity of mechanical and structural systems in the form of a probability distribution function, usually as a function of the intensity measures such as peak ground acceleration, spectral acceleration, peak ground velocity, spectral intensity, spectral velocity, etc. [46]. The GM of IM is scaled by the IDA method, where according to [PERSON] and [PERSON] [5], the fragility curve is calculated from data sets by taking logarithms of each GM's value corresponding to the onset of the collapse. Equations (16) and (17) show the mean and standard deviation of the fragility curve:  
\[ln\theta=\frac{1}{n}\sum_{i=1}^{n}ln\overline{M_{i}} \tag{16}\]  
\[\beta=\sqrt{\frac{1}{n-1}\sum_{i=1}^{n}\left(ln\left(\overline{M_{i}}/\theta \right)\right)^{2}} \tag{17}\]  
where \(n\) is the number of considered GM's and IM is the \(IM\) value associated with the onset of collapse for the \(i\)th GM. The mathematical explanation of PSHA has been done previously and the failure risk assessment curve can be explained by the combination of fragility function and PSHA function as follows:  
\[\lambda_{C}=\int_{0}^{\infty}P(C|IM)|\frac{d\lambda_{IM}(IM)}{d(IM)}|d(IM) \tag{18}\]  
where \(P(C|IM)=\phi\frac{1}{n}\ln\left(\frac{IM}{\theta}\right)\) is the failure probability of the structure, the ground motion intensity is indicated by IM and \(\frac{d\lambda_{IM}(IM)}{d(IM)}\) is the slope of the seismic hazard curve [3,36].
# Time Shared Optical Network (TSON): A Programmable Network Edge Solution for Multi-Access Support
## 2 TSON, the Past
### Evolution Stage 3: TSON NC for Resilient C-RANs  
The third stage of the TSON evolution enables TSON to support NC for resilient C-RANs. The goal is to protect the bandwidth demanding C-RAN services from possible optical network and/or baseband unit (BBU) failures. The NC-based approach is developed to tackle the issue with increased resource efficiency. A reduction in utilisation of 33% has been identified when using the NC approach compared to the traditional 1 + 1 protection scheme. However, in order to adopt NC-based resilient FH networks there are three main challenges:  
* Coding--providing module-2 sum and replication operation at FH line rate, as these factors may degrade the performance of C-RANs in practical systems.
* Storage--the operation of the decoding process at the edge imposes significant buffering requirements due to the high data rate of FH streams.
* Synchronisation--synchronisation between flows reaching decode nodes.  
TSON is extended [13] to address these challenges and execute the coding and decoding processes at line rate, as well as minimising buffering requirements adopting a purposely developed synchronisation scheme to make it suitable for C-RAN implementation. We considered a butterfly network for NC. Figure 8 presents the butterfly network consisting of two TSON nodes. In this scenario, each TSON node maps three source nodes of a butterfly network for NC. The TSON node 0 receives two different FH traffic streams (A and B) and sends the streams A, B, and their modulo 2 sum (XOR) of both traffic streams to the TSON node 1. The TSON node 1 receives the three traffic streams and transmits each traffic stream A and B simultaneously to two destinations of the TSON node 1.  
Figure 9 presents the TSON data plane architecture with extra pipelines to support NC for FH considering the butterfly network. The marked extended pipelines in the figure follow the other TSON pipelines legacy with extra coding/decoding capability. In the ingress node of these pipelines, the incoming traffic parses to two flows: X and Y. The output ingress node contains three different wavelengths (X, Y, and X XOR Y) that can be configured on the fly using SDN to address different programmable parameters. The egress edge nodes include the reverse functionality with extra replication outputs to support a butterfly network. The IEEE-1588-v2 synchronisation is employed for accurate synchronisation. The TSON architecture supporting NC is prese  
Figure 8: Butterfly network for network coding (NC) and its mapping on TSON edge nodes.
## 2 Results
### DisA Bound to HJ DNA Inhibits RuvAB-Mediated Fork Restoration  
In vitro, both RuvAB\({}_{E\alpha}\) and RuvAB efficiently branch migrate an HJ-like structure to restore a replication fork [30; 31; 41]. We showed that in the presence of ATP, RuvAB (15 nM), bound to a HJ (HJ-J4 DNA), produced the flayed duplex product, but it failed to further unwind the flayed duplex intermediate to render an ssDNA substrate (Figure 3C, lane 5 vs. 12). Similar results were observed when RuvAB was incubated with HJ DNA that cannot spontaneously branch migrate (HJ-J3 DNA) [41]. DisA did not unwind the HJ-J4 DNA (Figure 3C, lanes 2-4).  
We tested whether DisA affects RuvAB-mediated fork restoration. DisA pre-incubated with HJ-J4 DNA significantly inhibited RuvAB-mediated branch migration (\(p<0.01\)) even at a DisA:RuvAB molar ratio of 0.8:1 (Figure 3C, lane 9 and 3D). When DisA was added to the pre-formed RuvAB-HJ-J4 DNA complexes, however, no inhibition was observed at a DisA:RuvAB molar ratio of 0.8:1, but at a 1.6:1 DisA:RuvAB molar ratio, \(\sim\)50% of the HJ-J4 DNA was not unwound (Figure 3C, lanes 6 and 7 and 3D). In the presence of an excess of DisA (DisA:RuvAB molar ratio of 3:1), RuvAB-mediated branch migration was significantly inhibited (\(p<0.01\)) (Figure 3C, lane 11 and 3D). The different outcome observed by altering the order of protein addition reveals a genuine activity associated with DisA rather than any inhibitory component present in the protein preparation (e.g., a protease). We envision that DisA bound to the HJ DNA blocks branch migration. Alternatively, DisA acting as a potent roadblock inhibits any translocase, including RuvAB. Nevertheless, we consider this hypothesis unlikely, because the replicative accessory DNA helicase PcrA (a member of the conserved UvrD-FBH1 family of 3\({}^{\prime}\)\(\rightarrow\)5\({}^{\prime}\)DNA helicases) efficiently processes a tailed HJ-DNA even in the presence of a 6-fold excess of DisA relative to PcrA [27]. Furthermore, DisA neither compromises PriA-dependent replication initiation nor affects replication elongation using an in vitro reconstituted replication assay [13]. These results confirm that the inhibitory action exerted by DisA is specific for RuvAB.