esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Experimental Results  
In this section, we perform segmentation experiments using our proposed system to demonstrate its effectiveness and efficiency. First, the dataset used in the experiments is described followed by a discussion of the experimental setup. Afterwards, qualitative evaluation is performed to directly show the results on different groups of tongue images to evaluate the quality of the segmentation results in an intuitive way. Next, quantitative evaluation is carried out using five different metrics to evaluate the performance of the proposed system in different aspects to prove the superiority of proposed method in a numerical way. Later on, TongueNet is compared with Floodfill [28] and Snake [15] as well as a state-of-the-art method entitled Region-based and Edge-based fusion approach (REF) [18]. Finally, an efficiency comparison is carried out to compute the computation time.
# Parametric Simulations on Leakage and Performance of a Miniature Free-Piston Generator (MFPG)
###### Abstract  
The miniaturization of electrical equipment and popularization of portable devices is an appealing motivation for the development of small-scale heat engines. However, the in-cylinder charge leaks severely as the engine dimension shrinks. The free-piston engine on a small scale provides better sealing than other miniature heat engines. Therefore, a miniature free-piston generator (MFPG) with a single-piston internal combustion engine (ICE) and a voice coil motor (VCM) was proposed in this work. A dynamic model with special attention on the heat transfer and leakage was established accordingly, upon which parametric studies of leakage and its effects on the performance of the MFPG system were performed. Four key parameters, including scavenging pressure, ignition position, combustion duration and piston mass, were considered in the model. The results showed that the mass leakage during the compression decreases with the rise of the motoring current. The indicated thermal efficiency can be improved by boosting scavenging pressure and increase motoring current. The critical ignition position is 2 mm before the top dead center. When ignition occurs later than that, the MFPG system is incapable of outputting power. The chemical to electric energy conversion efficiency is about 5.13%, with an output power of 10-13 W and power density around 4.7-5.7 W/cc.  
miniature free-piston generator; mass leakage; heat transfer; thermal efficiency; parametric study +
Footnote †: journal: Applied Sciences
# Lactic Acid Bacteria Co-Encapsulated with Lactobionic Acid:
## 3 Results and Discussion
### Rehydration Kinetics  
Capsules produced with AFB-L, chosen as the best from the bloom test and from the evaluation of viability over time (D-capsules: 0.5 M CaCl\({}_{2}\) and chitosan), were then freeze- or thermal-dried. The rehydration capacity over time of the capsules was evaluated as the ratio between the grams of water adsorbed by the dried capsules (freeze- or thermal-dried) compared to the grams of water measured in the fresh capsule, before drying, as described in the methods section. The results for rehydration capacity are shown in Figure 3.  
The freeze-dried capsules were more capable of rehydration than the thermal-dried ones, and the difference was statistically significant. Conversely, there was no difference according to the medium used for rehydration (saline solution or yogurt). In all cases, the rehydration reached a maximum level after 3 h and lasted until 24 h, when the rehydration percentages observed were 13.67 \(\pm\) 3.10% for the freeze-dried capsules rehydrated in saline solution; 14.12 \(\pm\) 1.80% for the freeze-dried capsules rehydrated in yogurt; 10.24 \(\pm\) 1.50% for the thermal-dried capsules rehydrated in saline solution, and 10.00 \(\pm\) 1.84% for the thermal-dried capsules rehydrated in yogurt.  
Figure 3: Rehydration capacity over time. Freeze- and thermal-dried capsules were placed in 0.9% NaCl solution (orange, purple, respectively) or in yogurt (light blue, green, respectively) and collected at specific sampling times (0, 0.25 min (15 s), 6 min, 60 min, 180 min, and 1440 min (24 h)) to evaluate their rehydration capacity, as described in the methods section. Bars represent standard deviation of three independent experiments. Different letters indicate significant differences (\(p<0.05\)).  
Figure 2: Probiotic viability over time. Microbial concentration measured for 30 days for the freeze-dried capsules (**A**) and for the thermal-dried capsules (**B**). For both cases, two parameters were studied: the broth used (AFB-G or AFB-L) and the capsule structure (if crosslinked in 0.1 M CaCl\({}_{2}\) for 10 min or in 0.5 M CaCl\({}_{2}\) for 10 min and then coated with chitosan). Bars represent standard deviation of three independent experiments. Different letters indicate significant differences (\(p<0.05\)).  
The differences related to the drying treatment used could be due to the physical alterations (shrinkage, altered porosity and microstructure, and reduced ability in binding water) caused by thermal drying [40; 41; 42].
## Results
### Wide-Angle X-ray Diffraction (WAXD)  
The XRD diffractogram of C\({}_{\rm c}\) and C\({}_{\rm s}\) with CA fibers generated from them, along with the detector image of the relative microcrystalline cellulose are displayed in Figure 3. Five major diffraction peaks at 2\(\emptyset\) = 14.9\({}^{\circ}\) (101), 15.9\({}^{\circ}\) (101), 21\({}^{\circ}\) (021), 22.4\({}^{\circ}\) (002), and 34.5\({}^{\circ}\) (004) are observed for the microcrystalline cellulose which is in line with values known in the literature for cellulose [40]. However, the CA fibers show a diffractogram with the absence or significant reduction of all peaks corresponding to planes (101), and (002), the values of the Bragg angle characteristic of cellulose I, specifying an amorphous structure. Furthermore, the aerocellulose patterns display peaks in 2\(\emptyset\) = 13\({}^{\circ}\) and 20\({}^{\circ}\) which is the corresponding characteristic of cellulose II [27; 43]. It is also explicit that C\({}_{\rm c}\) had sharper peaks at (002) as well as more intense regions of radiation absorbance in the detector image and therefore higher crystallinity (Figure 3a) in contrast to C\({}_{\rm s}\) (Figure 3b) [44]. The crystallite index for the C\({}_{\rm c}\), F\({}_{\rm c}\), C\({}_{\rm s}\), and F\({}_{\rm s}\) was 81.15, 27.58, 42.13, and 12.78 (%), respectively. Therefore, it demonstrates that the degree of crystallinity of the F\({}_{\rm c}\) and F\({}_{\rm s}\) was extremely lower than of the original cellulose powder, but F\({}_{\rm c}\) had higher crystallinity than F\({}_{\rm s}\).  
Figure 3: (**a**) The XRD spectra of microcrystalline type C (C\({}_{\rm c}\), (a), black) and originated fiber (F\({}_{\rm c}\), (b), blue) with the detector image of the C\({}_{\rm c}\). (**b**) The XRD pattern of microcrystalline type s (C\({}_{\rm s}\), (c), red) and fabricated fiber (F\({}_{\rm s}\), (d), green) with the detector image of the C\({}_{\rm s}\). C\({}_{\rm c}\) had a higher crystallinity index than C\({}_{\rm s}\) and fibers regenerated from both cellulose went through cellulose I to cellulose II transformation and formed an amorphous structure.
# Efficient Adsorbent-Desiccant Based on Aluminium Oxide
## 2 Methods of Obtainment of Aluminium Oxide Used in Industry
### Methods of Alumina Obtainment  
#### 2.1.1 Bauxite Ore Treatment by the Baeyer Method  
As of today, about 90-95% of the world's aluminium hydroxide is extracted using the Baeyer process, which was proposed in 1887 [30]. The Baeyer method is a hydrochemical method of obtaining alumina from bauxites. Large pieces of bauxite, supplied from the mines, are first crushed, and then wet-ground in ball mills. Bauxite, caustic alkali and recycled liquor are fed to ball mills. Sometimes, a little lime is added to bauxite to facilitate their breakability. The pulp from the mills is collected in collectors, where the remaining amount of the recycled liquor with a concentration of Na\({}_{2}\)O = 300 g/l is fed. Then, it is heated there by separation steam to 90-100 \({}^{\circ}\)C and soaked for 4-8 h while stirring for preliminary bauxite desiliconization, i.e., there is a transfer of the most part of the active silica from bauxite to the liquor. The mixture of the ground bauxite and the recycled liquor (raw pulp) is sent to one of the main operations. This process is called the leaching or cooking of bauxite, which is carried out in autoclaves at a temperature of 230-240 \({}^{\circ}\)C. The purpose of this operation is to dissolve the aluminium oxide contained in bauxite, avoiding the transfer of other components of bauxite (silica, iron oxides, etc.) to the liquor. The silica is removed by subsequent slow heating when Na\({}_{2}\)Si(OH)\({}_{6}\) precipitates. The remaining pure liquor of NaAl(OH)\({}_{4}\) is cooled, diluted with water and neutralized with carbon dioxide. As a result, aluminium trihydrate Al(OH)\({}_{3}\) (gibbsite) is selectively deposited from the liquor without the residues of the dissolved silica.
## 4 Results and Analysis
### Impact of Genetic Operators on Cryptographic Performance  
In genetic algorithm-based applications, genetic operators such as mutation rate and crossover significantly impact the convergence of a solution. The values of mutation rate and crossover are crucial for balancing exploration and exploitation [37]. High mutation rates may promote exploration but disperse the solution across generations. On the other hand, low mutation rates increase exploitation but risk premature convergence [73]. To evaluate the impact of these genetic operators, multiple single crossover points (1, 3, 5, 7 bits) and mutation rates were tested to observe the changes in decryption accuracy and encryption/decryption time. The results were recorded, as shown in Table 10. The recorded results reveal that with low mutation rates, decryption performance slightly decreases  
Figure 25: Byte occurrence pattern for standalone traditional algorithms: AES (**top-left**), DES (**top-right**), and RSA (**bottom-left**) analyzed against proposed hybrid algorithm (**bottom-right**), presenting the byte occurrence for respective algorithms at different byte positions.  
at longer crossover bit lengths. The accuracy drops from 90.00% at 1-bit crossover to 87.42% at 7-bit crossover. Additionally, computation times for encryption and decryption generally increases with longer crossover lengths. The decrease in decryption accuracy can be attributed to premature convergence to the solution.  
As the mutation rate increases to 0.05, the decryption accuracy also improves, reaching up to 99.20% with a 7-bit crossover, along with an increase in encryption and decryption time (represented as Total Time (s)). This is because a higher mutation rate allows for a more thorough exploration of the solution space, which leads to increased time but brings the algorithm closer to the optimal solution. Similarly, at a mutation rate of 0.10, the decryption accuracy peaks at above 99% for almost every crossover bit, making 0.10 the best mutation rate for encrypting alphanumeric data. However, for mutation rates higher than 0.10, decryption accuracy performs poorly, with a 0.0% accuracy score and a significant increase in time. This is due to the higher mutation rate promoting increased exploration, leading to greater randomness in the ciphertext but preventing convergence toward a balanced solution.
# IAACaaS: IoT Application-Scoped Access Control as a Service +
## 5 Implementation and Results
### Implementation
#### 5.1.2 Policy Administration and Decision Points  
This implementation integrates both _PAP_ and _PDP_ components in the same module providing two APIs:  
* Policy decision point API : provides an API for getting authorization decisions computed by a XACML-compliant access control engine;
* Policy administration point API : provides an API for managing XACML policies to be handled by the authorization service PDP.  
The full API (RESTful) is described by a document written in the Web Application Description Language format (WADL) and an associated XML schema. The name of the component is AuthZforce ([[https://catalogue.fiware.org/enablers/authorization-pdp-authorzforce](https://catalogue.fiware.org/enablers/authorization-pdp-authorzforce)]([https://catalogue.fiware.org/enablers/authorization-pdp-authorzforce](https://catalogue.fiware.org/enablers/authorization-pdp-authorzforce)) [Last accessed on 3 October 2017]) and has been developed by a group of developers belonging to the FIWARE Security Team, not directly by the authors of this work. The implementation provides an API to get authorization decisions based on authorization policies and authorization requests from PEPs. The API follows the REST architecture style and complies with XACML v3.0.  
This component is agnostic of the type of clients that manage and consume the policies. Therefore, its implementation does not offer relevant challenges to be considered.
## 2 Mechanical Modeling of the ISU System  
### System Overview and Working Principle  
The ISU system integrates the primary suspension components--the spring (elastic element) and damper (damping element)--within the arm structure. The ISU system comprises a main piston, a connecting rod, a compression piston, and a high-pressure nitrogen gas chamber, as shown in Figure 1. As the piston rod moves, the main piston compresses the nitrogen gas, generating spring forces through gas compression and expansion. The hydraulic fluid and lubricant within the cylinder form the damping system, dissipating energy through controlled fluid flow.  
In this system, the connecting rod connects the suspension support at one end and the main piston on the other via a joint, thereby allowing multi-axis motion. A crank mechanism translates vertical wheel displacement from the load wheel into piston motion, compressing the gas to provide the suspension functionality.  
The initial values and physical parameters used in the modeling and simulation of the ISU system are listed in Appendix A. These parameters include geometric dimensions, thermodynamic constants, and damping characteristics, which served as baseline inputs for the numerical analysis.
## 1 Introduction
However, in the field of rolling-bearing fault diagnosis, the method of using a GAN to supplement data still has shortcomings in accurately learning data features and generating high-quality samples. Avoiding gradient vanishing and pattern collapse during model training is still a key challenge that urgently needs to be solved. In summary, machine learning [30], feature engineering, deep learning [31], and transfer learning [32] are very important aspects of the prognostics and health management (PHM) of various fields, such as aerospace technology [33] and smart factories [34]. Aiming at the problems of a sample imbalance and a shortage of labeled samples, this study focuses on the sample expansion and fault-diagnosis methods of rolling bearings. A GAN and a transformer were adopted as the structural foundation of the network model. The main contributions of this study can be summarized as follows. First, we propose a sample-expansion method--namely, CVAE-SKEGAN--which solves the gradient-vanishing and mode-collapse problems of a GAN, giving it superiority in the stability and quality of the generated samples. Then, a novel rolling-bearing fault-diagnosis method, called SSL-VCST, is proposed. By optimizing the attention mechanism of the transformer and introducing semi-supervised training, unlabeled samples are fully utilized to improve fault-diagnosis accuracy, overcoming the difficulty of a lack of labeled samples and avoiding the waste of unlabeled data. Moreover, the proposed sample-expansion method and fault-diagnosis method are validated for their superiority under diverse operating conditions. The remainder of this paper is organized as follows. In Section 2, a fault sample expansion method based on GAN is proposed, which improves the GAN network structure to make it more stable and generates high-quality data. This provides supplementary trained data with clear features for deep learning models for fault diagnosis and solves the problem of sample imbalance. In Section 3, a rolling bearing fault diagnosis method based on a transformer is proposed, which optimizes the attention mechanism and introduces SSL to fully utilize unlabeled samples to supplement labeled samples, avoiding waste of unlabeled data and improving the fault diagnosis accuracy of the network. In Section 4, the proposed method is experimentally validated under three operating conditions. Finally, conclusions are drawn in Section 5.
## 5 Computational Cost Reduction Methods
### AP Selection Methods
#### 5.1.2 Fisher Criterion  
In this technique, the statistical properties of RM fingerprints are exploited during the offline phase to choose the informative APs for positioning [40; 41; 42]. The time stabilization and spatial discrimination of each AP across RPs are computed and sorted in descending order. A score is assigned for each AP separately as Equation (7):  
\[\zeta^{i}=\frac{\sum_{j=1}^{M}{(\psi_{j}^{i}-\overline{\psi}^{i})}^{2}}{\frac{ 1}{T-1}\sum_{l=1}^{T}{\sum_{j=1}^{M}{(r_{j}^{i}(t_{l})-\psi_{j}^{i})}^{2}}},\ \ i=1,2,\ldots \ldots,L \tag{7}\]  
where, \(\overline{\psi}^{i}=\frac{1}{M}\sum_{j=1}^{M}{\psi_{j}^{i}}\), \(r\) represents an instantaneous vector at each RP, \(M\) represents a number of RPs in the RM, and \(T\) represents a number of time samples at each RP.
# Internet of Spacecraft for Multi-Planetary Defense and Prosperity
## 5 Multi-Planetary Detection, Communications, and Defense: Live Long and Prosper  
At this point, we can summarize several key points from previous investigations as follows:  
* First, due to many types of random events and their consequences, asteroids and comets can escape or change their former orbits and enter the near-Earth space, which increases the probability of their impact with Earth. The current asteroids/comets detection is focused on the NEO category, which may limit the preparation time allowed for humanity. Although more than 96% of total estimated large asteroids (with a diameter of 1 km and more) in the near-Earth space have been surveyed so far, the proportion of NEAs (with a diameter between 100 m and 1000 m) is still very low.
* Second, the detection capability of on-ground telescopes highly depends on their geological and meteorological conditions. Only several specific locations on Earth can fulfill such challenging requirements for high-quality observation. Moreover, most on-ground observatories operate in visible light and radio frequencies. Just a few ground-based telescopes work in infrared wavelengths, and many infrared telescopes are space-based to minimize the Earth's interference and background noise.
* Third, the ground-based observatories are usually powerful with abundant facilities and local technical support, while space-based ones normally depend only on the solar array and remote debugging. On the other hand, space-based telescopes have obvious advantages over the on-ground ones to survey the sky in infrared wavelengths, thus playing a crucial role in identifying and locating NEOs. For example, most asteroids are black, and small ones are difficult to see in the blackness of outer space with an optical telescope. Still, a telescope operating at infrared wavelengths is sensitive to asteroids' surfaces warmed by the Sun.
## 2 Materials and Methods  
### Data Collection  
Crown defoliation data were provided by the ICP Forests network (Level I monitoring plots) for the main European tree species over the time period 2000-2010. In Europe, crown condition is the most widely applied indicator for forest health and vitality assessments [43; 44; 45; 46; 48; 49; 50; 51]. Crown defoliation of the dominant tree species is visually estimated as the relative amount of foliage (expressed as percentage) in the tree crown compared to a reference tree of the same species with full foliage, growing in the same stand and site conditions [52; 53]. Crown defoliation is estimated annually for 1623 monitoring plots of Level I according to the Manual on methods and criteria for harmonised sampling, assessment, monitoring, and analysis of the effects of air pollution on forests [53]. Mean annual values of crown defoliation were calculated for each Level I monitoring plot and for all considered species as reported in Figure S1 in the supplementary material. In particular, we considered nineteen tree species: six conifers (_Larix decidua_ [PERSON], _Pica abies_ L., _Pinus halepensis_ [PERSON], _Pinus nigra_ [PERSON]. [PERSON], _Pinus pinaster_ [PERSON], and _Pinus sylvestris_ L.), twelve broad-leaf deciduous trees (_Acer pseudoplatanus_ L., _Alhus glutinosa_ [PERSON], _Betula pendula_ [PERSON], _Betula pubescens_ [PERSON], _Carpinus betulus_ L., _Castanea sativa_ [PERSON], _Fagus sylvariatica_ L., _Frazinus excelsior_ L., _Populus tremula_ L., _Quercus petraea_ [PERSON], _Quercus pubescens_ [PERSON], and _Quercus robur_ L.) and one broad-leaf evergreen species (_Quercus ilex_ L.) distributed across four European bio-geographic areas (Boreal, Atlantic-Temperate, Continental-Temperate, Mediterranean). Furthermore, the crown defoliation database included site characteristics such as latitude, longitude, and altitude.  
Mean annual temperature data (T mean, \({}^{\circ}\)C) were obtained from the European Climate Assessment & Dataset (ECA&D) for the time period 2000-2010. The ECA&D consists of a daily series of observations collected at several meteorological stations (>2000) throughout Europe. The nearest meteorological station to each ICP Forests site was used to provide temperature data.  
GPP data (gC m\({}^{-2}\) day\({}^{-1}\)) were provided by MODI7 product of the MODIS (MODerate Resolution Imaging Spectroradiometer) instrument aboard the Terra satellite, as modified by [54]. MODI7 is the first continuous satellite-driven dataset monitoring global vegetation productivity at 1 km of spatial resolution, providing 8-day, monthly, and annual GPP averages. The GPP component of the algorithm is estimated by a light use efficiency model and requires daily inputs of incoming photosynthetically active radiation (PAR) and climate variables [55; 56; 57]. The Collection5 MOD17 products, temperature, and crown defoliation data were used with a temporal resolution of 1 year, over the time period 2000-2010. All analyses were separately performed for all considered years in the 1623 plots.