esa-sceva/satcom-chunk-collection huggingface dataset:
# Cellulose Recovery from Agri-Food Residues by Effective Cavitational Treatments
## 3 Biomass Treatments for Cellulose Recovery
### Cavitational Treatments in Comparison
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Biomass** & **Cavitation** & **Chemical** & **Added Value Products** & \multicolumn{2}{c}{**Process yield**} \\  & **Technology** & **Conditions** & **Added Value Products** & \multicolumn{2}{c}{**(Conventional**} & \multicolumn{1}{c}{**Ref.**} \\  & & & & & **Reference)** & \\ \hline \hline Carrot grass & US-probe & alkaline & Cellulose recovery a & 90\% (45\%) & [78] \\ Eucalyptus wood & US-bath & alkaline & Biochar & +10–20\% (respect to & [79] \\  & & & & raw) & \\ Rapeseed Straw (RapS) & US-probe & alkaline & Cellulose hydrolysis & 41.60\% & [80] \\ Rapeseed Straw (RapS) & US-probe & organosolv & Lignin recovery & high polymerization & [81] \\ Rapeseed Hulls & US-probe & alkaline & Cellulose hydrolysis & 36\% (33.5\%) & [82] \\ Olive tree pruning & US-bath & acid & Cellulose recovery a & 15.87\% (6.03\%) & [83] \\ Newspaper waste slurry & US-probe & alkaline & Cellulose recovery a & ca. 80\% (40\%) & [84] \\ Oil palm empty fruit & US-probe & acid & Xylose & 58\% (22\%) & [85] \\ bunch (OPEFB) & US-probe & acid & Bio-ethanol & 820 mg/mL & [86] \\  & US-probe & acid + alkaline & Bio-ethanol & 911 mg/mL & [86] \\  & US-probe & IL & Fermentable sugars & 177 mg/g biomass & [100] \\  & US-probe & IL + surfactant & Fermentable sugars & 255 mg/g biomass & [100] \\  & & Cellulose & & \\ Sugarcane bagasse (SCB) & HC (venturi) & alkaline & recovery—Cellulose & 60–97.2\% (67\%) & [110] \\  & & hydrolysis & & \\  & HC (venturi) & alkaline & Cellulose—Hemicellulose & 93–95\% & [111] \\  & & & & hydrolysis & \\  & & Cellulose recovery & & \\  & HC (venturi) & alkaline + H\({}_{2}\)O\({}_{2}\) & \({}^{a}\)–Fermentable & 27.2–95.4\%—0.49 g/g & [112] \\  & & sugars—Bio-ethanol & biomass & \\  & & & & 44\%—42 g/100 g & \\ HC (venturi), & alkaline + H\({}_{2}\)O\({}_{2}\) & Cellulose recovery & (121 g/100 g)— & [121] \\  & & & & (5.7 g/100 g) & \\  & & & & 48\%—35 g/100 g & \\ HC (venturi), & alkaline + H\({}_{2}\)O\({}_{2}\) & Cellulose recovery & (121 g/100 g)– & [121] \\  & & & & (5.7 g/100 g) & \\  & & & & 48\%—35 g/100 g & \\ HC (venturi), & alkaline + H\({}_{2}\)O\({}_{2}\) & Cellulose recovery & (121 g/100 g)– & [121] \\  & & & & (5.7 g/100 g) & \\  & & & & 48\%—35 g/100 g & \\ HC (venturi), & alkaline + H\({}_{2}\)O\({}_{2}\) & Cellulose recovery & (121 g/100 g)– & [121] \\  & & & & (5.7 g/100 g) & \\  & & & & 48\%—35 g/100 g & \\ HC (venturi), & & & & (12.1 g/100 g)– & [121] \\ semi-cont. & & & & (5.7 g/100 g) & \\  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Agri-Food Residues valorisation by cavitational treatments.
## 3 Results and Discussion
### Permeability  
The permeability of the samples before and after treatment is presented in Figure 9. Permeability is a more sensitive indicator of changes in the properties of the sample attributes than porosity. The permeability of the samples increased after the cyclic hydrogen exposure, indicating changes in the pore network. Unlike the porosity results, the permeability of the samples showed a significant increase after each exposure cycle on all the samples. Sample 1Y1 exhibited the most increase in permeability values, while 18M1 demonstrated the least increase in permeability. After three cycles, the permeability of 18M1 increased from 0.14 uD to 1.1 uD. For 18M2, the permeability increased from 0.21 uD to 1.79 uD. Samples 1Y2, LW1, and LW2 have a minimal increase in permeability after the second exposure cycle. The dissolution of pore throats can lead to significant changes in permeability, whereas the corresponding modifications in porosity may be minimal. [PERSON] et al. [30] evaluated field samples' permeability before and after hydrogen injection, where they concluded an increase in permeability of 0.0442 mD when Class G cement was exposed to pure H\({}_{2}\) gas. However, considering this change in permeability in our results, the resulting values are considered appropriate for tight cement being able to make a good seal. [PERSON] et al. [41] mentioned in their study that cement is considered to make a good seal if its permeability is less than 0.01 mD. Further long-term hydrogen exposure of cement samples is required to evaluate the effect of hydrogen in permeability altercations.
# Yeast Starter Culture Identification to Produce of Red Wines with Enhanced Antioxidant Content
Most of the anthocyanins in wine exist in a glycosylated form, i.e., bound to a sugar. In this state, they are much less susceptible to chemical or enzymatic oxidation. Therefore, the action of \(\beta\)-glucosidase, which generates the respective aglycones (anthocyanidins) in the wine, can promote their removal during winemaking [12]. Finally, some yeast strains release polysaccharides capable of binding with polyphenols, forming stable complexes over time. The presence of these complexes is directly related to the sensations of volume and roundness in the mouth, as well as the stability of wine over time. Research has demonstrated that several yeast metabolites, including pyruvate acid, can react with anthocyanins in grapes to form stable pigmentation and contribute to the aging of red wines. Unfortunately, the absorption of these molecules onto yeast cell walls, and consequently, their decrease in the produced wine, poses a significant challenge in the fermentation process. This issue has garnered attention from researchers and winemakers. In this light, to prevent or reduce the loss of bioactive molecules through absorption, we studied the absorption capacity of some indigenous yeast strains selected in the Apulia region (Southern Italy). The use of autochthonous selected yeasts initially gained popularity in white wine production and later extended to the crafting of red wines [13]. In recent years, several studies have underlined the pivotal role played by the microbiota associated with the \"terroir\" where a particular grape cultivar is cultivated. This microbiota imparts unique sensory properties to the resulting wine [14; 15]. The employment of selected autochthonous yeast strains emerges as a powerful tool to enhance the organoleptic and sensory attributes of distinctive regional wines, establishing a stronger connection between these wines and their terrorir [16]. The natural biodiversity of Apulian autochthonous yeast strains has been widely investigated [17; 18; 19; 20; 21; 22; 23; 24; 25]. It therefore appeared important to exploit our knowledge to identify yeast strains able to enhance the phenolic compound content and, consequently, the functional properties of produced wines. As a first step, we proceeded with the characterization of a population of selected starter cultures according to their ability to minimize the reduction in the concentration of polyphenic compounds during a micro-scale must fermentation. Then, the performances of the most effective strains were further validated through larger-scale vniification, and the resulting wines were analysed for their polyphenic profiles. To the best of our knowledge, this study represents the first clonal selection of yeast strains directed towards the production of regional wines enriched in their polyphenic content, to be used in the near future for the development of \"functional\" fermentation starter.
## 3 Results and Discussion
### TEM Analysis  
TEM is one of the cutting-edge analytical measurement technologies used to image and analyze nanoparticles to determine their size and shape [15]. Figure 4A,B show the TEM image of Se NPs prepared by the green synthesis method. The images show nanoparticles are an excellent uniform spherical shape of Se NPs and the distribution behavior with less aggregation, therefore, shown as an individual particle. Figure 4C explains the histogram size distribution on Se NPs, and the average size is about 22 nm. This result is in good agreement with the crystallite size determined from XRD analysis. A similar result is published by [PERSON] et al. in 2022 [29].
## 6 Methods
### Vessel Enhancement Filters
#### 6.1.3. Frangi Vesselness Filter  
The Frangi [33] approach uses all three eigenvalues to discriminate the local orientation pattern. These three eigenvalues serve in the differentiation of blobs \(R_{b}\), and plate-like and line-like structures \(R_{a}\). To decrease the influence of noise \(S\), a Hessian norm measure was developed.  
\[R_{b}=\left|\lambda_{1}\right|/\sqrt{\left|\lambda_{2}\lambda_{3}\right|} \tag{4}\]  
\[R_{a}=\left|\lambda_{2}\right|/\left|\lambda_{3}\right| \tag{5}\]  
\[S=\sqrt{\lambda_{1}^{2}+\lambda_{2}^{2}+\lambda_{3}^{2}} \tag{6}\]  
They propose the following combination of the components to define a vesselness function,  
\[F=\begin{cases}0&if\lambda_{2}>0 or\lambda_{3}>0,\\ (1-\exp(-\frac{R_{a}^{2}}{2\alpha_{2}}))\exp(-\frac{R_{b}^{2}}{2\beta_{2}})(1- \exp(-\frac{S^{2}}{2\epsilon_{2}}))\end{cases} \tag{7}\]  
The parameters \(\alpha\), \(\beta\), \(\gamma\) are the thresholds that control the sensitivity of the filter to the measures \(R_{a}\), \(R_{b}\), and \(S\).
## 4 Experimental Tests  
### Experimental Setup  
Numerous long-duration tests under constant operation points (_P_, \(Q\), and _U_) were carried out on a special 4-salient pole, 5-kVA, 400-V BSM. A simplified diagram of the machine is shown in Figure 7.  
This BSM was modified by adding 5 slip rings and brushes to permit access to the field winding of the main machine and to the \"rotating\" diodes (which were actually made static in this setup and placed outside of the machine). This modification allows for the measurement of the voltage (_U_) and the current (_I_) of the field winding of the main machine and consequently the temperature by observing variations in its resistance. Additionally, two Pt\(-\)100 type temperature sensors were installed at both ends of the armature windings of the main synchronous machine, and these temperatures were also recorded.  
From the armature currents and voltages, the values of stator voltage (_U_), active power (_P_), and reactive power (_Q_) are measured by a commercial 3-channel programmable transducer, SINEAX M563. Finally, the exciter field current is measured using a Hall effect sensor. All these measurements are recorded on a computer through an Arduino(r) microcontroller, communicating via the COM port of the computer.  
During the long-duration test, the temperature of the rotor and the stator of the main synchronous machine increased. To maintain the machine at the same operating point, the exciter excitation current (_I_) needs to be increased as the temperature rises.  
The ratings of the main machine and the exciter are detailed in Tables 2 and 3, respectively.  
There are five slip rings and brushes (4): three are connected to the armature winding of the exciter, and the other two are connected to the main machine's field winding. The voltage and current of the main machine's field winding are measured (5). The temperature of the main machine's armature windings is monitored by two Pt\(-\)100 sensors (6). These sensors are placed in the end winding of the machine at both sides of the generator, the non-drive end NDE and the drive end DE. In element 6 of Figure 8, there is a zoom of this area. This is the best non-invasive location of the temperature sensors that allows estimating an average temperature with which to compare the estimations of the DNN.  
Figure 7: Simplified diagram of the experimental setup.
# Embedding Equality Constraints of Optimization Problems into a Quantum Annealer +
###### Abstract  
Quantum annealers such as D-Wave machines are designed to propose solutions for quadratic unconstrained binary optimization (QUBO) problems by mapping them onto the quantum processing unit, which tries to find a solution by measuring the parameters of a minimum-energy state of the quantum system. While many NP-hard problems can be easily formulated as binary quadratic optimization problems, such formulations almost always contain one or more constraints, which are not allowed in a QUBO. Embedding such constraints as quadratic penalties is the standard approach for addressing this issue, but it has drawbacks such as the introduction of large coefficients and using too many additional qubits. In this paper, we propose an alternative approach for implementing constraints based on a combinatorial design and solving mixed-integer linear programming (MILP) problems in order to find better embeddings of constraints of the type \(\sum x_{i}=k\) for binary variables \(x_{i}\). Our approach is scalable to any number of variables and uses a linear number of ancillary variables for a fixed \(k\).  
Keywords:quantum annealing; D-Wave; QUBO; constrained optimization; mixed-integer programming +
Footnote †: journal: arXiv:1911.03390
## 5 Phenotyping and Monitoring of Trees' Biophysical Parameters  
Crop phenotyping can be defined as the monitoring of morphological, physiological, and biochemical traits which result from the interaction between genetic and environmental factors [115; 135]. The preferred agronomic traits in olive growing are those related to the earliness of production, high productivity and oil quality, and resistance to abiotic and biotic stresses [136; 137; 138]. Some characteristics of olive trees related to geometrical canopy measures, vegetative growth habits, and vigor are important in phenotyping trials because they are linked to aspects of management, such as the form of training, plantation pattern to be adopted, pruning, and harvesting [139; 140; 137; 138; 141]. Also, qualitative parameters of fruits and oil depend on the geometry of the foliage, its shape, and size, as it affects the penetration of sunlight in the canopy and its distribution [142]. High variability in selection crosses together to the long juvenile period of the olive tree, making it complex, lengthy, and expensive to find a genotype with all desirable traits (productivity, high oil quality, and diseases and pests) [143]. Traditional methods used in the field for collecting phenotypic data require experience and are time-consuming [115; 137; 144]. The manual measurement of the geometrical characteristics to estimate the area and volume of the canopy using empirical models generates results that are inconsistent both for human errors in the field and for model errors when the canopy is assimilated to a regular polygon or a spheroid [145; 146]. In this framework, the use of UAVs responds to the need to speed up and reduce costs thanks to their flexibility and high spatial, spectral, and temporal resolutions [147; 148; 135]. Several research efforts have focused on the use of UAVs in olive phenotyping [149; 140; 143; 145; 144; 146; 137]. [PERSON] et al. [137] calculated canopy traits measurements in different olive cultivars by comparing UAV with conventional ground measurements. In particular, in each tree, crown length radius, crown width radius, crown height radius, and tree height were measured. A further objective was to demonstrate the usefulness of UAV measurements for identifying differences between cultivars and olive trees of different ages within the same cultivar. [PERSON] et al. [149] tested some VIs obtained from MS UAV data and exploited them to discriminate olive cultivars with different scion/rootstock combinations. Data were processed through different statistical approaches, univariate (ANOVA) and multivariate (principal components analysis, PCA, and linear discriminant analysis, LDA). Results showed the efficacy of seven VIs (NDVI, Simple ratio SR [150], Green normalized difference vegetation index GNDVI [151], Green red normalized difference vegetation index GRNDVI [152], Simple ratio NIR green vegetation index GRVI [153], Normalized difference green/red difference vegetation index NGRDI [154], and RVI [155] in scion recognition while unsatisfactory results were obtained for discrimination between root
## 3 Results and Discussion
### Fluorescence Properties of GQDs  
The aqueous solutions of GQD1 and GQD2 are light brown under visible light, but they have different fluorescence under an excitation of a beam of 365 nm. GQD1 and GQD2 exhibit green and yellow fluorescence, respectively. Figure 9 demonstrates the PL spectra of the two GQDs. The emission spectra of GQD1 show obvious excitation-dependence. With the gradual increase of the excitation wavelength from 280 nm to 480 nm, the maximum emission wavelength of GQD1 is red-shifted from 408 nm to 500 nm. However, the emission wavelength of GQD2 keeps stable at about 535 nm during the excitation wavelengths we employed. The different PL properties of GQD1 and GQD2 may be attributed to their size and surface state, which are affected by functional groups [7; 36; 44; 45]. Surface decoration degree and size can change the energy gap of GQD, thus affecting the PL properties. Our analysis of HR-TEM shows that GQD1 are larger than GQD2 in size; this can lead to a red shift of GQD1 compared to GQD2, which is contrary to our result. Therefore, surface decoration is the major reason for the different PL properties. XPS analysis shows that N and O atoms exist in both GQD1 and GQD2; C 1s XPS indicates that the amounts of N and O are greater in GQD2 than GQD1 (Figure 7d,e). In addition, N atoms doped in GQDs with different forms: besides C-N-C and N-(C)\({}_{3}\), -NO\({}_{2}\) can be found in GQD2 (Figure 8c,d). From the above analysis, it is reasonable to conclude that the difference  
Figure 8: High resolution XPS spectra of N 1s for (**a**) O-GO, (**b**) R-O-GO, (**c**) GQD1 and (**d**) GQD2.  
in optical properties between GQD1 and GQD2 should be attributed to their differences in degree of oxidation and N doping.
# Enhancing Route Guidance with Integrated V2X Communication and Transportation Systems: A Review
## 4 V2X Communication Architecture
### V2X Communications Protocols
#### 4.1.2 IEEE 802.11 bd V2X  
The present IEEE V2X specification IEEE 802.11p primarily relies on IEEE 802.11a for the PHY and MAC layers. Ensuring the existing and future requirements of vehicular applications and use cases is increasingly challenging, with lower reliability and higher delays in networks where density, speed, and transmission are increased. The IEEE 802.11 bd Work Group, formed in January 2019, aims to improve the IEEE 802.11 MAC and PHY layers to introduce Next Generation V2X (NGV) communications. The IEEE 802.11 bd protocol is an evolution of IEEE 802.11p; it leverages MAC and PHY layer improvements from IEEE 802.11n, IEEE 802.11 ac, and IEEE 802.11 ax. The goals are to double 802.11p's throughput, speed support, and coverage range while decreasing end-to-end latency. Other essential aspects of the new generation protocol are coexistence, backward compatibility, fairness between IEEE 802.11p and IEEE 802.11 bd devices, and cooperative locating methods [93]. Interoperability and backward compatibility need IEEE 802.11p devices decoding messages supplied by IEEE 802.11 bd devices and vice versa, as well as IEEE 802.11 bd devices performing in a fully interoperable mode with IEEE 802.11p devices. IEEE 802.11 bd specifications can greatly enhance bandwidth, meeting the throughput objective as twice that of 802.11p. It utilizes an adaptive retransmission technique and PHY signaling to increase the reliability. To complement long communication range, the protocol usesspace-time block coding from IEEE 802.11n. This takes two antennas to transmit the same information combined to achieve spatial diversity [94].  
The IEEE 802.11 bd is a wireless communication standard that supports vehicle-to-everything (V2X) communication. Using the IEEE 802.11 protocol, vehicles and infrastructure elements can communicate quickly, reliably, and securely. This standard can be used for direct vehicle communication, allowing them to share information like speed, location, and acceleration without a central infrastructure. This feature can be handy in areas with limited infrastructure or where instant communication is essential. Additionally, IEEE 802.11 bd can enable communication between vehicles and infrastructure elements, such as traffic signals, road signs, and toll booths. This can improve traffic flow, enhance safety, and give drivers real-time information about road conditions and traffic patterns. The standard can also support cloud-based communication, which involves connecting vehicles and infrastructure elements to remote servers via the Internet. These servers can provide real-time updates on traffic conditions, weather, and other relevant information.
## 4 Fatigue Wear Test
### Analysis of Fatigue Test Results  
#### 4.3.1 Analysis of Bearing Wear  
Figure 11 shows images of the bearing with the different wear times. Following the fatigue wear test, the bearing surface is shown to have different degrees of wear. The wear resistance of the aluminium alloy bearing was poor, and the surface was badly worn. The bearing displayed severe strain and burn marks after 10 h of testing. The surface of the copper alloy bearing was ternary electroplated; therefore, the nickel alloy wear-reducing layer was formed, which had better wear resistance. There was no obvious alloy exposure phenomenon on the surface of the copper alloy bearing after the 20 h test.  
Figure 11: The bearing pictures after the test.  
Figure 10: Comparison of different signals of copper alloy (1500 r/min, 10 MPa).  
Table 2 shows the results of the surface condition of the aluminium alloy bearing measured at different times. As the wearing time increased, the wear of the bearing increased. In Figure 12, the thickness of the bearing decreased by 0.11 mm, and the bearing gap increased by 0.10 mm in the first 10 h. The thickness decreased by 0.09 mm from hours 10 to 15, and the bearing gap increased by 0.08 mm. The thickness decreased by 0.14 mm from hours 15 to 20, and the bearing clearance increased by 0.14 mm. The image of the aluminium alloy bearing showed that following the 10 h fatigue wear test, the wear-reducing layer of the bearing was slowly peeling off. After the bearing was worn to the alloy layer, the wear amount increased more obviously, and severe wear of the bearing could be determined.  
Table 3 shows the results of the surface condition of the copper alloy bearing measured at different times. As the fatigue wear test time increased, the wear of the copper alloy bearing also increased. Figure 12 shows how the wear amount of the copper alloy increased slowly. With better wear resistance, the wear-reducing layer of the copper alloy bearing  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Time (h)**} & **Bearing Clearance** & **Lower Bearing** & **Lower Bearing** \\  & **(mm)** & **Thickness (mm)** & **Roughness (\(\mu\)m)** \\ \hline
0 & 0.141 & 1.818 & 0.707 \\ \hline
5 & 0.146 & 1.812 & 0.778 \\ \hline
10 & 0.148 & 1.808 & 0.882 \\ \hline
15 & 0.154 & 1.798 & 1.232 \\ \hline
20 & 0.162 & 1.788 & 2.332 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The measurement results of the surface condition of the aluminium alloy bearing at different times.  
Figure 12: Bearing wear at different wear test times.  
was still there, and there was no peeling of the alloy layer. After 20 h of the wear test, the bearing clearance only increased by 0.012 mm, and the thickness of the lower was reduced by 0.010 mm. The hardness of the copper alloy was lower, and its surface roughness increased by 1.545 \(\upmu\)m.