esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### The Effect of SBF Immersion on the Microstructure of an HA/WS Skeleton
The macroscopic morphology and interconnected pore structure of the sintered three-dimensional porous HA/WS skeleton obtained using Micro-CT are illustrated in Figure 8. The Micro-CT analysis reveals  
Figure 7: Diverse types of apatite nanocrystals. (**a**) The cavity wall is covered mostly by the impermeable glass phase of wollastonite. (**b**) Miniature caves with different SBF contact conditions. (**c**) Thin wall between two fully filled cavities. that both freeze-drying and non-pressure sintering methods yield a characteristic three-dimensional porous HA/WS skeleton with an interconnected pore structure extending from the external to the internal regions, exhibiting a diverse distribution of pore sizes ranging from approximately 100 to 500 \(\upmu\)m. The interconnected porous structure and high porosity of the three-dimensional HA/WS skeleton provide an optimal environment for cellular cultivation, proliferation, and tissue growth. The results demonstrate the occurrence of active biomineralization processes within the three-dimensional porous HA/WS skeleton, revealing nanoscale microstructure details of the inner surface that are seldom observed on the exposed outer surface. In a clinical context, it is anticipated that the internal pore structure and morphology of bone implants will gradually evolve due to the formation of ever-changing apatite nanocrystals during biomineralization. This suggests that conducting bone cell experiments on skeletons with an internal porous structure at different time points after SBF infiltration will provide further insights into the effects of bone cell and bone tissue regeneration. In vitro cell culture tests should be performed on the internal structure of the three-dimensional porous HA/WS skeleton exposed after SBF infiltration, which will determine how these hidden internal apatite nanocrystals interact with bone cells and thus determine the bone regeneration process. Therefore, it is crucial to pay close attention to relevant SBF simulations and in vitro cell experiments. To our knowledge, this aspect has not been systematically investigated.
## Flight Test Result for the Ground-Based Radio Navigation System Sensor with an Unmanned Air Vehicle  
**[PERSON] *, [PERSON], [PERSON], [PERSON] and [PERSON]**  
The 3 rd R&D Institute-4, Agency for Defense Development, Yuseong P.O. Box 35, Daejeon 305-600, Korea; E-Mails: [EMAIL_ADDRESS] (W.-G.A.); [EMAIL_ADDRESS] (S.S.); [EMAIL_ADDRESS] (J.Y.L.); [EMAIL_ADDRESS] (J.-P.P.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +82-42-821-3643; Fax: +82-42-823-3400 (ext. 16108).  
Academic Editor: [PERSON]  
_Received: 16 September 2015 / Accepted: 2 November 2015 / Published: 11 November 2015_  
**Abstract:** The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study, a periodic pulsed sequence was used instead of the randomized pulse sequence recommended as the RTCM (radio technical commission for maritime services) SC (special committee)-104 pseudolite signal, as a randomized pulse sequence with a long dwell time is not suitable for applications requiring high dynamics. This paper introduces a mathematical model of the post-correlation output in a navigation sensor, showing that the aliasing caused by the additional frequency term of a periodic pulsed signal leads to a false lock (_i.e._, Doppler frequency bias) during the signal acquisition process or in the carrier tracking loop of the navigation sensor. We suggest algorithms to resolve the frequency false lock issue in this paper, relying on the use of a multi-correlator. A flight test with an unmanned helicopter was conducted to verify the implemented navigation sensor. The results of this analysis show that there were no false locks during the flight test and that outliers stem from bad dilution of precision (DOP) or fluctuations in the received signal quality.  
**Keywords:** pseudolite; pulsed signal; false lock
# Visual and Phonological Feature Enhanced Siamese BERT for Chinese Spelling Error Correction
## 3 Approach
### Model Overview  
The framework of the proposed method is depicted in Figure 1. It consists of two components, i.e., a Feature-enhanced BERT (FE-BERT) for visual and phonological errors and a vanilla BERT for visually and phonologically irrelevant typos. The prediction results of the BERT and the FE-BERT are summed up through a dynamic soft pointer to reach a balance between semantic constraints and external feature constraints. The details are shown in Algorithm 1.  
More specifically, shape embeddings for visual features and pronunciation embeddings for phonologically features of each character are provided for the Feature-enhanced BERT as clues for selecting the best candidate. Shape embeddings of all Chinese characters are retrieved from a Chinese character glyph graph. In the glyph graph, Characters with the same components in the structure are connected and the edges are given different weights in terms of the number of character strokes and node neighbors. The pronunciation embeddings are initialized according to Chinese Pinyin, which serves as a romanization system providing phonetic-based information for Chinese characters.  
In the following subsections, we describe (1) the Feature-enhanced BERT(FE-BERT) for errors similar in pronunciation or shape. (2) the combination of BERT and FE-BERT.  
Figure 1: The Feature-enhanced Siamese BERT. Shape, pronunciation, token, segment, and position embeddings are summed up as input for FE-BERT in the left side. The pointer to combine BERT and FE-BERT is conditioned on CLS representation of BERT and token representations of BERT and FE-BERT.  
```
0: Chinese characters \(X=\{x_{1},x_{2},\ldots,x_{l}\}\)
0: The corrected characters \(Y=\{y_{1},y_{2},\ldots,y_{l}\}\)
1: Construct the glyph graph G according to structure information of Chinese characters.
2: Pre-train the glyph graph G to generate the shape embedding: \(E_{shape}\gets Node2 vec(G)\)
3: Randomly initialize the pronunciation embedding: \(E_{pron}\)
4: Token embeddings \(E_{token}\gets Embeds_{token}(X)\)
5: Segment embeddings \(E_{segment}\gets Embeds_{segment}(X)\)
6: Position embeddings \(E_{position}\gets Embeds_{position}(X)\)
7:\(H_{fe}=\{h_{feCLS},h_{fe1},h_{fe2},\ldots,h_{fel}\}\gets BERT(E_{shape} +E_{token}+E_{pron}+E_{segment}+E_{position})\)
8:\(H=\{h_{CLS},h_{1},h_{2},\ldots,h_{l}\}\gets BERT(E_{token}+E_{segment}+E_{ position})\)
9:\(P_{sem}\gets Sigmoid(W_{p}[H;H_{fe};H_{CLS}]+b_{p})\)
10:\(logits\gets softmax(p_{sem}W_{1}H+(1-p_{sem})W_{2}H_{fe}+b_{1}))\)
11:\(Y=\arg\max logits\)
```  
**Algorithm 1** The Feature-enhanced Siamese BERT
## 2 Key Features of the Temperature Field
### Definitions of Key Features
#### 2.1.2 Key Features from Multi-Images of the Same Powder Layer  
The cooling rate, maximum temperature distribution, average temperature distribution, thermal diffusivity, and sputtering activity are extracted from multiple temperature images of the same layer. The cooling rate refers to the temperature gradient in the concept of time. If it is too high, severe non-equilibrium solidification takes place, while if it is too low, the relevant area is always in a high temperature state, leading to the agglomeration of powders. Both situations affect the quality of the molding parts.  
The maximum/average temperature distribution information is formed by the processing results of all of the pixel points. The information is a comprehensive reaction of the current layer's process state, which can describe the temperature statistics of each point in the powder layer. Thermal diffusivity describes the ability of heat diffusion within an object, i.e., the ability of the temperature within the object to tend to be uniform. If the heat accumulation in the powder layer cannot be diffused, it will lead to a high temperature in a small area, and the powder will be agglomerated or burned.  
Sputtering refers to the situation in which there is a rapid change of boundary conditions due to rapid energy absorption and diffusion, which leads to the presence of ejecta in the melting pool. Sputtering results in changes in the powder particles' diameter, the thickness of the local powder layer, or the thickness of the cured region. Sputtering particles falling in the uncured region cause an increase in the volume of the melting pool and a sudden change in thermal conductivity, leading to process instability.
## 4 Enrichment Ratio for Rill versus Inter-Rill Erosional Processes  
Despite the overall selectivity of hydric erosion, rill and inter-rill processes may have contrasting impacts on the SOC-ER of sediment. In general, inter-rill erosion (or soil splash) may indicate preferential removal over the rill process. Based on a laboratory rainfall and flume experiment, [PERSON] et al. [16] observed that SOC-ER was not affected by rill erosion but varied between 0.9 and 2.6 for inter-rill (splash) erosion, and it was inversely related to the unit sediment discharge. In addition, physicochemical differences between the liberated and mobilized material and the residual raindrop-stable soil aggregates can be an important determinant of the composition of sediments. Moreover, based on a rainfall simulation study, [PERSON] et al. [17] observed that liberated particles in all tilled (plowed) soil contained higher a concentration of oxidized lignin phenols, a lower proportion of cinn amyl to vanilllyl lignin, and a trend toward a higher proportion of microbially processed N, which indicates a more decomposed microbial processed SOC. These characteristics indicate the preferential removal of some constituents by inter-rill erosion.  
The water repellency of aggregates, caused by SOC content, may also affect aggregate stability [18] and thus, the properties of the liberated and mobilized materials during different erosional stages. For an ovsiol from Hawaii, [PERSON] et al. [19] observed the preferential detachment and transport of splashed aggregates within the size range of 250 to 2000 \(\upmu\)m. They also observed that the kinetic energy required to detach 1 g SOC varied from a median of 1870 J for the 2000-4000 \(\upmu\)m fraction to 120 J for the 425-850 \(\upmu\)m fraction. Crust formation by the raindrop impact is another factor that affects SOC-ER [8], and the loss of biocrust can increase the loss of SOC by erosion [20]. The SOC loss by inter-rill erosion is also affected by the initial SOC content, rainfall pattern, and the primary particle size distribution [21].  
Soil Carbon Dynamics at Different Stages of Soil Erosion and the Attendant Emission of Greenhouse Gases  
The multi-stage process of soil erosion has a variable effect on the properties and the fate of the liberated and mobilized constituents.
# Performance Evaluation of Laetitic Subgrade Soil Treated with Lime and Coir Fibre-Activated Carbon
## 2 Laboratory Investigations  
### Materials  
Lateritic soils are generally unsuitable and weak for the construction of infrastructure facilities. This study collected soil at Universiti Teknologi Malaysia, Johor campus. The soil is categorised as A-7-5 [44]. The chemical components of the lateritic soil are shown in Table 2. Moreover, Figure 1 depicts the particle size distribution of lime, AC, and soil. The soil distribution is within the ranges discovered in previous studies [45].  
Regarding Figure 1, laser diffraction (LD) tests were conducted for lime, AC, and soil particles less than 75 microns. While sieving was used for soil particles more than 75 microns. Due to time savings and high accuracy, this study combined laser diffraction with conventional techniques [46]. Moreover, laser diffraction is more precise in evaluating the fine contents of residual soil [47], and hence it was employed instead of the hydrometer method.  
In Table 2 chemical composition of additive materials is presented. AC coconut derivative was obtained from Evachem company, and lime was supplied by Lhoist company in Malaysia. AC is a kind of carbon that filters organic pollutants from the air, water, and other applications [41]. AC enhances the surface area for chemical reactions due to low-volume porosity [48]. The significant oxides of AC and lime were achieved by  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Composition**} & \multicolumn{3}{c}{**(\%) by Weight**} \\ \cline{2-4}  & **Soil** & **Activated Carbon** & **Lime** \\ \hline Fe\({}_{2}\)O\({}_{3}\) & 57.57\% & 11.27 & - \\ SiO\({}_{2}\) & 20.85\% & - & - \\ Al\({}_{2}\)O\({}_{3}\) & 19.507 & - & - \\ K\({}_{2}\)O & 1.72\% & 17.68 & 0.30 \\ MnO & 0.15\% & 2.57 & - \\ Cr\({}_{2}\)O\({}_{3}\) & 0.14\% & - & - \\ As\({}_{2}\)O\({}_{3}\) & 0.05\% & - & - \\ CaO & - & 39.77 & 98.85 \\ P\({}_{2}\)O\({}_{5}\) & - & 16.62 & - \\ SO\({}_{3}\) & - & 7.83 & 0.80 \\ ZnO & - & 3.47 & - \\ CuO & - & 0.62 & - \\ SrO & - & 0.18 & 0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Chemical composition of soil and additives.  
Moreover, Coir fibre as reinforcement besides AC is used in this research. It is a waste and environmentally friendly material from a coconut's husk and is a fibrous material, cheap, and locally available. Coir fibre has higher tensile strength, is lighter, contains more hemicellulose and lignin, and degrades more slowly than other natural fibres. The coir fibre in this study has an average tensile strength of 125 MPa. Figure 2 presented an image of lateritic soil, lime, activated carbon, and coir fibre.
# Repurposing Olive Oil Mill Wastewater into a Valuable Ingredi for Functional Bread Production
###### Abstract  
Untreated olive oil milk wastewater (OOMW) from conventionally farmed olives was used in bread production to create a new functional product. Two types of bread were developed with 50% OOMW (EXP-1) and 100% OOMW (EXP-2) replacing water. Two leavening processes were tested: sourdough inoculum (\(S\)) vs. biga-like inoculum (\(B\)), with controls (CTR) without OOMW addition. The doughs were monitored throughout the acidification process by measuring pH, total tittatable acidity, and the development of key fermentative microorganisms. To assess the hygienic quality during fermentation, plate count techniques were employed. After baking, the breads were evaluated for various quality parameters, including weight loss, specific volume, crumb and crust colors, image analysis, and the presence of spore-forming bacteria. Volatile compounds released from the breads were identified using solid-phase microextraction coupled with gas chromatography-mass spectrometry (SPME-GC/MS). Polyphenolic compounds were analyzed via liquid chromatography-mass spectrometry (LC-MS). To assess the functional properties of the final products, the breads were homogenized with synthetic human saliva and subjected to in vitro digestion. OOMW did not significantly affect the growth of yeasts and lactic acid bacteria (LAB) or the acidification process. However, in terms of the specific volume and alveolation, breads from the \(S\) process and OOMW had poor quality, while those from the \(B\) process had better quality. Experimental breads (EXP\({}_{B}\)-1 and EXP\({}_{B}\)-2) contained higher levels of alcohols (especially ethanol and isobutyl alcohol), carbonyl compounds (like benzaldehyde), esters (such as ethyl caproate and ethyl caprylate), and terpen. OOMW introduced phenolic compounds like hydroxytyrosol, coumaric acid, caffeic acid, and trans-hydroxycinamic acid, which were absent in CTR\({}_{B}\) breads. Functionalization of EXP\({}_{B}\)-1 and EXP\({}_{B}\)-2 breads was demonstrated by a 2.4- and 3.9-fold increase in Trolox equivalents, respectively. However, OOMW did not reduce post-prandial hyperglycemia, as starch digestibility was similar between CTR\({}_{B}\) and EXP\({}_{B}\) breads. The sensory analysis, which focused solely on the visual, structural, and olfactory characteristics of the breads, excluding taste testing to prevent potential health risks from residual pesticides, showed a high appreciation for EXP\({}_{B}\)-1 and EXP\({}_{B}\)-2 breads, scoring higher than CTR\({}_{B}\) in the overall assessment.  
**Keywords:** functional bread; in vitro digestion; lactic acid bacteria; olive wastes; polyphenols; sourdough
###### Abstract  
To overcome the limitation of traditional elastic phase field models that neglect plastic deformation in rock compressive-shear failure, this study developed an elastoplastic phase field fracture model incorporating plastic strain energy and established a coupling framework for plastic deformation and crack evolution. By introducing the non-associated flow rule and plastic damage variable, an energy functional comprising elastic strain energy, plastic work, and crack surface energy was constructed. The phase field governing equation considering plastic-damage coupling was obtained, enabling the simulation of the energy evolution in rock from the elastic stage to plastic damage and unstable failure. Validation was carried out through single-edge notch tension tests and uniaxial compression tests with prefabricated cracks. Results demonstrate that the model accurately captures characteristics such as the linear propagation of tensile cracks, the initiation of wing-like cracks under compressive-shear conditions, and the evolution of mixed-mode failure modes, which are highly consistent with classical experimental observations. Specifically, the model provides a more detailed description of local damage evolution and residual strength caused by stress concentration in compressive-shear scenarios, thereby quantifying the influence of plastic deformation on crack driving force. These findings offer theoretical support for crack propagation analysis in rock engineering applications, including hydraulic fracturing and the construction of underground energy storage caverns. The proposed plastic phase field model can be effectively utilized to simulate rock failure processes under complex stress states.  
Keywords:phase field method; rock elastoplastic damage; crack propagation; plastic strain energy; rock engineering +
Footnote †: journal: Applied sciences
## 4 Implementation and Results  
### Implementation Environment  
The structure of our PCB smart factory system was defined and Figure 9 depicts the configuration of the hardware (H/W) system that was and the H/W system architecture. The configuration was broadly classified as follows: server operations; office or field operations; manufacturing application operations for workers; IoT operations; and real-time feedback operations.  
Figure 8: The structure of our smart factory monitoring system.  
The hardware was set up to build and run an MES on a cloud platform that was simple to secure, use, and manage. Keyed in data were automatically collected and sent to the MES or data acquisition (DAQ) server via a monitor or a manufacturing application that was run using this information. In addition, it was configured to enable real-time monitoring and to manage abnormal occurrences and support real-time decision-making. The smart factory software was created by integrating all manufacturing-related processes, from product order to shipment. It integrated all aspects of factory operations, not only including application systems but also field automation and control automation. Figure 10 depicts the software (S/W) configuration with these characteristics.  
Various IoT data from different devices, such as PLCs, barcode readers, temperature and pressure sensors, machine logs, etc. were automatically collected using OPC-UA, FTP, and TCP/IP by the edge computer. The smart factory software is created by integrating all manufacturing-related processes, from product order to shipment. It will integrate all aspects of factory operations, including not only application systems but also field automation and control automation [42; 43; 46; 47; 48]. Figure 11 depicts the S/W configuration diagram with these characteristics in mind.  
Figure 9: The hardware configuration.
## 3 Fibre Bragg Grating
### Operational Principle  
The communication between the FBG and the computer is established via the serial USB 2.0 interface. To adjust the Bragg wavelength, a dynamic link library (DLL) is available. This contains various functions, which can step-wise measure and control the wavelength, temperature or speed. The manufacturer of the FBG, Advanced Optics Solutions GmbH has a software which is developed for this purpose and can be controlled directly [50]. Using this software, the Bragg wavelength can be adjusted through the speed of the stepper motor (for stretching or compressing). In addition, a temperature compensation mechanism in the software is implemented, through which the set Bragg wavelength is monitored every 60 s, depending on the temperature, and adjusts with the help of a compensation function underneath.  
For an automated control in the overall system, the software of Advanced Optics Solutions can not be used because no programming interfaces are available. For this reason, the three main functions (setting the Bragg wavelength, controlling the speed control of the stepper motor, and temperature compensation) are simulated using the dynamic library in LabVIEW. LabVIEW is used for this purpose in version 18.0.1. [51], which recognizes the individual functions in the DLL and executes them appropriately.  
Both for characterization and for use in the sensor setup, the FBG can be modelled by a series of parallel processes [52; 53]. A process controls the setting of the Bragg wavelength, and the stepper motor speed, while the other process performs temperature compensation. Here, the Bragg wavelength is adjusted at any time, whereas after a certain time \(t_{\text{K}}\), a temperature compensation step is performed. For the laboratory setup, a time constant of \(t_{\text{K}}=45\) s is used.  
To model these parallel processes, it is suitable to use them particularly as descriptions of the discrete Petri net. With the possibility to run several states in Petri nets at the same time, this is preferred automatically by the state machines.