esa-sceva/satcom-chunk-collection huggingface dataset:
# An Insight into the Chemistry of Cement--A Review
## 3 Hydration Step Involving OPC
### Mechanism and Heat of Hydration of OPC
#### 3.3.1. Pre-Induction Period  
Once cement interacts with water, ionic species rapidly go in the solution allowing the formation of hydrates. From the dissolution of alkali sulphates, there is the release of free potassium, sodium, and sulphate ions. Gypsum dissolves until saturation, releasing Ca\({}^{2+}\) and SO\({}_{4}\)\({}^{2-}\).  
The literature evidences the creation of a coating growing over the surface of the cement grains immediately after contact with water [67; 68]. This product is recognized as being C-S-H. The layer of C-S-H grows, covering most of the grain surface, until the exhaustion of reactants available at the surface. According to [PERSON] et al. [69], when the content in the C\({}_{3}\)S product is higher than the CaO/SiO\({}_{2}\) ratio, during this first step of hydration, there is an increment in the concentration of Ca\({}^{2+}\) and OH\({}^{-}\) in the liquid. Furthermore, adding water to the cement leads to the rapid dissolution of both gypsum and clinker minerals, producing Ca\({}^{2+}\), OH\({}^{-}\), SO\({}_{4}\)\({}^{2-}\) ions, and ionic concentration differences through steps in the liquid phase, and causing the supersaturation phenomenon necessary for the formation of the ettrinigite phase.  
Moreover, [PERSON] et al. [70] pointed out that the formation of octahedral [Al(OH)\({}_{6}\)]\({}^{3-}\) is the time-determining step in controlling the AFt growth. Furthermore, it has been  
Figure 3: Graph reporting the progress of hydration as a function of the hydration time for the principal components of an OPC: consumption of clinker phases ((**a**), top), and formation of hydrate phases ((**b**), bottom). Reprinted with permission from [1].  
demonstrated that the ionic concentration affects the kinetic rate of the reaction. Among the different ions forming ettringe, \([\text{AlO}_{2}]^{-}\) is the one with the lowest concentrated one, and is consequently the limiting species. There are only a small quantity of C\({}_{2}\)S hydrates within this first step. Furthermore, the belite (i.e., C\({}_{2}\)S) reaction rate is similar, but slower, in respect to that of C\({}_{3}\)S, and this is probably attributable to both belite's high thermodynamic stability in respect to alite, and its different crystalline structure. Lastly, C\({}_{2}\)S presents high density, and the presence of holes/pores/channels in the structure of C\({}_{3}\)S facilitates the reaction with water [71].
# Measurements of Room Acoustic and Thermo-Hygrometric Parameters--A Case Study +
## 3 Data Analysis and Results
### Thermo-Hygrometric Parameters Analysis  
The temperature, relative humidity, and air velocity values are shown in Figure 5.  
Figure 5 clearly illustrates how the relative humidity changed in response to changes in temperature and vice versa. This is consistent with the basic principle that there is a negative association between temperature and humidity. In order to capture the greatest amount of temperature variance, the experimental parameters were monitored throughout a 25 h period that included the whole day. Table 1 shows that during the experiment, the difference in room temperature between the maximum and minimum values was close to 5 \({}^{\circ}\)C, the difference in maximum and minimum relative humidity values was roughly 17%, and the change in air velocity was 0.55 m/s.  
\begin{table}
\begin{tabular}{c c c c} \hline  & **Temperature** & **Relative Humidity** & **Air Velocity** \\  & [\({}^{\circ}\)**C]** & **[\%]** & **[m/s]** \\ \hline Average & 30.25 & 45.15 & 0.15 \\ Max & 31.74 & 54.30 & 0.55 \\ Min & 26.78 & 37.50 & 0.00 \\ Range & 4.96 & 16.80 & 0.55 \\ \hline \end{tabular}
\end{table}
Table 1: Temperature, humidity, and airflow within the room.  
Although the relationship between changes in acoustic characteristics may be understood by fluctuations in air temperature and relative humidity in the current inquiry, further trials in winter to examine the effects of varied temperatures, relative humidity, and more complicated environmental elements arising from human interaction on the primary acoustic parameters of the space are also required.  
The only independent characteristic that could be artificially changed by the ventilation system was the wind speed. Figure 5 makes it abundantly evident that the most prominent peaks and lowest values of temperature and humidity occurred when the air velocity was close to its lowest value. This was due to the laboratory's extremely high ceilings, which forced hot air to ascend and generate uneven room temperatures. Thus, a more uniform distribution of temperature was achieved throughout the lab when the ventilation system was turned on. When the fans were turned off, the lower levels of air were closer to the measurement equipment, resulting in lower temperatures and higher relative humidity.
## 4 Results and Discussion
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Authors** & **Technology** & **Objectives** & **Contribution** & **RQ1** & **RQ2** & **RQ3** \\ \hline [PERSON] et al. [102] & NOMA, OMA & This study compared the effectiveness of NOMA and OMA structures in a single-cell setting with randomly dispersed cellular operators while taking cooperative relays into account for increased system dependability. & The outcomes proved that the NOMA structure beats the OMA structure in performance. & Yes & \\ \hline [PERSON] et al. [103] & Unmanned Aerial Vehicle, Edge network, intelligence, Copting node & They proposed a combined task and energy offloading issue under an intelligent edge network with UAV assistance and energy constraints, comprising a high-altitude platform (HAP), several UAVs, and on-ground fog computing nodes (FCNs). & To overcome the issue previously identified, the authors suggest a multiple-agent soft actor-critic (MASAC) founded solution. Numerical simulation results demonstrate the superiority of our recommended strategy compared to benchmark approaches. & Yes & Yes \\ \hline [PERSON], [PERSON], and [PERSON] [104] & Orthogonal Frequency Division Multiplexing, NOMA & Precoding and dummy sequence insertion (DSI) techniques are recommended to overcome the earlier restrictions to reduce PAPR. A brand-new way for creating mock arrangements is also developed for the suggested strategy. & & \\ \hline [PERSON] et al. [105] & RAN, 6G & The paper focuses on the requirements-compliant intelligent massive RAN (mRAN) architecture and essential technologies. & The researchers look at potential AI solutions for network and resource administration problems in 6G & Yes & \\ [PERSON] et al. [106] & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline [PERSON] et al. [106] & Vehicular application, MEC, vehicle users & An immediate electricity-aware contracting approach powered by MEC has been suggested for automobile systems to effectively utilize connectivity and computing capabilities, decrease electricity use, and mitigate interrupptions. & Based on the computational findings, the suggested bi-level optimizing technique minimizes the entire burden by roughly 40\% compared to a comparable method. & Yes & Yes \\ \hline [PERSON] et al. [107] & MIMO, NOMA, communication deep neural network (CDNN) & The authors provide a MIMO-NOMA structure for increasing total data throughput and energy proficiency based on deep learning. & The CDNN framework uses training algorithms to handle the power allocation issue to increase MIMO-data NOMA’s throughput and energy efficiency. & Yes & \\ \hline [PERSON] et al. [108] & Edge computing, Multi-access edge computing, 5G & This study provides a comprehensive, in-depth, and well-organized evaluation of edge computing and its supporting technologies. & Future worries about green energy and standards were highlighted with edge computing. & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._
# Silicon 3D Microdosimeters for Advanced Quality Assurance in Particle Therapy
## 3 Silicon on Insulator (SOI) Detector for Microdosimetry
### Design of SOI Detectors
#### 3.1.3 Trenched-3D Mushroom Microdosimeter with a Planar Core Electrode  
The trenched-planar Mushroom microdosimeter consists of 3D SVs with a cylindrical shape and a planar n\({}^{+}\) core produced by ion implantation. Each SV is 5 or 10 \(\upmu\)m in height and 20, 30 or 50 \(\upmu\)m in diameter and is surrounded with a complete p\({}^{+}\)-doped trench filled with polysilicon (Figure 4a). It can be seen in the SEM image of this device structure (Figure 4b) that the trench is filled with polysilicon. In order to avoid breakage in the metal line connections, the polysilicon regions on the surface of the SVs were etched to make a  
Figure 3: (**a**) Simplified schematic of a trenched-3D microdosimeter with a voided p\({}^{+}\) trench and a voided n\({}^{+}\) trench and (**b**) SEM image of the trenched-3D design of a single 3D Mushroom microdosimeter SV [21].  
Figure 2: Scanning electron microscope (SEM) image of the 2-\(\upmu\)m-thick Mushroom microdosimeter. (**a**) A surface scan showing a number of SVs, (**b**) a zoomed-in image of a single SV and (**c**) a cross-sectional scan of a single SV.  
smooth surface before the deposition of metal contacts. Furthermore, the p-stop layer was connected to the outer p\({}^{+}\) trench (NO-GAP configuration) to avoid charge build-up in the oxide layer between the SVs after being irradiated with heavy ions. This fabrication process allows charge collection to be localised to the SV and helps avoid the build-up of charge in the oxide layer, which was observed in the previous version of the trenched planar Mushroom microdosimeter after irradiation with high-intensity ion beams (Figure 3).
# A Multi-Model Proposal for Classification and Detection of DDoS Attacks on SCADA Systems
## 4 Materials and Method
### Recommended Models for Attack Detection
#### 4.5.2 Recommended Models  
LSTM and CNN, which are important deep learning algorithms, were used alone and in combination with different algorithms in the literature. In this study, CNN and LSTM algorithms were evaluated and tested separately in order to contribute to the literature. Then, a hybrid model was created by considering these two algorithms together and tests were performed. Tests with different properties were applied to the LSTM model and CNN model. The parameter values in the LSTM-CNN hybrid model architecture were changed and different test procedures were performed. These models were analyzed separately and their attack detection success rates were discussed.  
In addition to these, machine learning algorithms that are frequently used in the literature were determined. By using these algorithms, suitable models for attack detection were obtained. All prepared models were compared according to the determined success metrics and the results are presented in the Section 5.1. Information about the models used, their architectural structures, and parameter values were given in this section.  
A 70% randomly selected dataset--that is, 15,937 rows of data--was used in the models' training. The remaining 30% was split into two to evaluate the testing and validation of the proposed model. Accordingly, 3415 rows were used for data validation and 3416 rows (including the class column) for testing. There were 22,768 rows of data (samples) in total.
# Optimal Control of Passive Cascaded Liquid Crystal Polarization Gratings
## 1 Introduction  
In contrast to other mechanical deflection devices, a Liquid Crystal Polarization Grating (LCPG) is a device that introduces a continuous gradient tilt phase distribution based on the geometric phase to produce beam deflection [1; 2]. It has the advantages of being tiny, light, and having low power consumption. In contrast to non-mechanical beam deflection devices such as liquid crystal space light modulators, fiber phased arrays, and optical waveguide phased arrays, which have the advantage of large deflection angles, orthogonal cascaded liquid crystal polarization gratings (OC-LCPGSs) can achieve two-dimensional deflection of beams with a large angle range and small angle intervals. There are numerous potential applications in industries including liquid crystal displays, laser communication, and others [3].  
The orthogonal cascade polarization grating's diffraction efficiency is a crucial parameter, and it decreases as the deflection angle increases. Diffraction efficiency refers to the ratio of light intensity in a certain diffraction direction to the incident light intensity. To address this issue, numerous researchers both domestically and internationally have conducted studies on how to use light control orientation technology and new light control orientation materials to improve LCPG's diffraction efficiency. The field of view of LCPG was expanded by the Hong Kong University of Science and Technology, who investigated the diffraction efficiency of LCPG at oblique incidence, examined the situation when converting the conventional oblique incidence LCPG to positive incidence distortion LCPG based on the equivalent distortion model at oblique incidence, and designed a double distortion structure similar to the former based on the theory of double layer compensation. However, there have been no reports of enhancing the liquid crystal phase delayer's control voltage and control coefficient to enhance the diffraction effectiveness of cascaded polarization gratings [4].  
In accordance with the theory of the liquid crystal polarization grating (LCPG) and liquid crystal variable retarder (LCVR) [5; 6; 7], the effect of the angle of incidence on the liquid crystal variable retarder is investigated, and the phase delay of the liquid crystal variable retarder (LCVR) controlled by different incidence angles is obtained.
## 9 A Complete Pattern: WS-Trust
### Solution
#### 9.5.1 Structure  
Figure 5 describes the structure of this pattern. **Claim** is a statement made about the attributes of a client, service or other resource (e.g., name, identity, key, group, privilege, capability, _etc._). Claims are assertions, for example: \"I am [PERSON]\", \"I am an authenticated user and I am authorized to print in printer P\". Claims are used to validate the requests made by a sender and need to be verified. A **Security Token** is a collection of claims. It is possible to add signatures to tokens. **Security Token** also is a generalization of two types: **Signed Security Token** that is cryptographically endorsed by a specific authority (e.g., an X.509 certificate or a Kerberos ticket) and **Proof-of-Possession (PoP) Token** that contains a secret _data_ parameter that can be used to prove authorized use of an associated security token and provides the function of adding digital signature. Usually, the proof-of-possession information is encrypted with a key known only to the recipient of the PoP token.  
The **Security Token Service (STS)** is a web service that issues security tokens. It makes decisions based on evidence that it trusts. The **STS** is responsible for generating security tokens and, providing challenges for the requester to ensure message freshness (the message has not been replayed and is currently valid), verification of authorized use of a security token, and finally establishing, extending and removing trust in a domain of services. The **STS** is the heart of WS-Trust and forms the basis of trust brokering. The main output of the **STS** is a trust relationship between the requester and the receiver expressed as a security token. It represents the characteristic that one entity is willing to rely upon a second entity to execute a set of actions and/or to make set of assertions about a set of subjects and/or scopes in a secure, reliable and time-relevant manner.  
Each **STS** has a **Trust Engine** that evaluates the security-related aspects of a message using security mechanisms and includes policies to verify the requester's assertions. The **Trust Engine** is responsible for verifying security tokens and verifying claims against policies. A **Policy** is a collection of policy assertions that have their own name, references, and ID. Policies form the basic conditions to establish a trust relationship. Verifying the requester's claims against policy assertions generates an approval to use the target service. A policy may reference another policy (ies), in order to check the tokens sent by the requester or verified by the receiver.
## 5 Conclusions  
A comparison among several signal processing techniques for the diagnostics of the first rolling bearing dataset released by NASA IMS Center was carried out. It was found that the combination of Cepstrum Pre-Whitening and Squared Envelope Spectrum provides a very efficient diagnostic method. In particular, CPW turned out to be a powerful tool to pre-whiten the signal, removing all masking components and noise, and therefore highlighting the fault signatures within the SES. Moreover, it was found that also the Improved Envelope Spectrum allows the harmonics of the fault frequencies of the defective bearings to be properly identified. The IES, as a second-order cyclostationary technique, is directly applied on the raw signal, thus providing a response from a different point of view, deeply related to the true nature of the signal under test.  
In the Authors' opinion, the successful application of traditional as well as more advanced and non-conventional vibration signal-based condition monitoring techniques to analyze the first of the three datasets made available by NASA IMS Center can be considered as a positive example of the efficacy of these mathematical tools to accomplish the predictive maintenance of rotating machineries.  
To conclude, the Authors' point of view is that, despite the large and recent diffusion of data-driven approaches, which represent promising methods particularly appreciated for fault prognosis, vibration signal-based techniques still remain essential and irreplaceable in light of the deep and detailed information they provide on the actual nature of the signal; therefore, the best way to perform condition monitoring should be the combined use of classical signal-based and new data-driven techniques.  
Conceptualization, D.S. and M.S.; Methodology, M.S.; Software, D.S.; Validation, D.S., M.S. and C.S.; Formal Analysis, M.S.; Investigation, D.S.; Resources, M.S.; Data Curation, D.S.; Writing--Original Draft Preparation, D.S.; Writing--Review and Editing, M.S. and C.S.; Visualization, M.S.; Supervision, C.S.; Project Administration, M.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the Corresponding Author.  
The Authors would like to thank [PERSON] for the valuable advice provided during the development of this work.
## 1 Introduction
### Advantages of Using SNN for Satellite On-Board Routing  
Reinforcement learning (RL) is suitable for highly dynamic space networks since it does not need prior training. The SNN uses temporal encoding of the data as an internal mechanism to learn the relationship between input variables related to spatio-temporal patterns that need to be learned, classified, and predicted. Hence, the SNN can be used for predicting early events such as strokes and heart failures in the medical field and earthquakes in environment monitoring [27]. Therefore, it is appropriate for detecting changes in the channel conditions and dynamic path selection in satellite routing. Since the SNN uses spikes, which are event-driven and sparse in time, SNN algorithms consume less energy than other neural networks [28]. Therefore, the SNN is advantageous to be used in on-board routing in satellites to save battery energy.
## 3 Results
### Annotation and Classification of Unigenes of G. sinensis Pods at Six Development Stages  
To further elucidate the molecular regulation of gleditsioside biosynthesis, RNA-seq analysis was performed on the six developmental stages of _G. sinensis_ pods. A total of 163,319 unigenes with a length greater than 3000 bp were identified (Figure 2A). By comparing and annotating the clean reads, 133,646 unigenes (81.83%) were deemed credible. Among these unigenes, the GC content was over 40% (43.84%), and the percentage of Q20 bases exceeded 95% (95.83%), suggesting high-quality RNA-seq data were obtained (Table S1). All unigenes were then functionally annotated in the NR, NT, Swiss-Prot, KEGG, COG, and GO databases. Moreover, 91,645 (56.11%) and 78,334 (47.96%) unigenes were annotated in the GO and KEGG databases, respectively (Figure 2B). Intriguingly, 31,739, 15,931, and 11,559 unigenes were separately annotated to exhibit high similarity to genes of Fabaceae family members, such as _Glycerine max_, _Glycine soja_, and _Cicer arietinum_ (Figure 2C). This result further confirmed that _G. sinensis_ belongs to the legume family. Unigene sequences were then matched with the COG database. A total of 54,258 unigenes were found in the COG database, and some gene functions were annotated in the category of \"secondary metabolites biosynthesis, transport, and catabolism\" (Q = 2352, 2.23%), suggesting that these genes were involved in secondary metabolite synthesis (Figure 2D).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & \multicolumn{6}{c}{**Pods**} & \multirow{2}{*}{**Leaves**} \\ \cline{2-2} \cline{5-7}  & **GS1** & **GS2** & **GS3** & **GS4** & **GS5** & **GS6** \\ \hline Absorbancy & 0.441 \(\pm\) 0.038 & 0.448 \(\pm\) 0.011 & 0.486 \(\pm\) 0.007 & 0.506 \(\pm\) 0.018 & 0.463 \(\pm\) 0.040 & 0.520 \(\pm\) 0.005 & 0.085 \(\pm\) 0.008 \\ Gleditsioside (\(\%\)) & 9.3 & 9.4 & 10.2 & 10.6 & 9.7 & 10.9 & 2.2 \\ \hline \end{tabular}
\end{table}
Table 1: Absorbance and gleditsioside content for _G. sinensis_ pods from GS1 to GS6 and approximately eighty-day-old leaves in June.  
Figure 1: Phenotype and gleditsioside content of _G. sinensis_ during pod development from GS1 to GS6. (**A**) _G. sinensis_ pod phenotype. The scale bar = 4 cm. (**B**) The length of the pods. Data are means (\(\pm\) SD) (\(n=3\)). Different letters above the bars indicate significant differences (\(p<0.05\)) as determined by one-way analysis of variance (ANOVA) and post hoc Tukey HSD analysis.
# Uncertainties and Perspectives on Forest Height Estimates by Sentinel-1 Interferometry
## 2 Materials and Methods  
Given the above-mentioned goals of this work, the analysis was performed according to the workflow of Figure 1. The first step was to develop a reasonable model to estimate forest height and define the conditions in which it can be adopted (see Section 2.2, Interferometric Phase Modelling). The second step was to model the theoretical uncertainty of the estimates (see Section 2.3, Modelling _dh_ Uncertainty). The third step to tune the involved parameters to optimize the operational conditions for minimizing the uncertainty of forest height estimates (see Section 2.4, Minimizing \(\sigma_{dh}\) through simulated scenarios). All simulations were performed according to Sentinel-1 data.