esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Transcriptional Regulation in Integrons
### Integrase Expression in Class 3 Integrons  
Different from classes 1 and 2 RIs, there are little information concerning the class 3 integron functionality. Although the _intl3_ expression had never been experimentally determined as extensively performed for _intl1_, [PERSON] et al. [55] proved that Intl3 was active in recognizing and recombining different gene cassettes within its cognate _attl3_ site and at secondary sites in lower frequencies. Indeed, in spite of sharing 59% identity with Intl1 [55], none of the amino acid alterations occurred in the conserved residues of the Intl3 integrase. Moreover, two potential Pint3 promoters were identified in the _attl3_ site of class 3 integrins [55; 56]. However, as found for class 1 integrins, the Pc3 promoter is located within the _intl3_ gene (see Section 2.1.3), face-to-face with Pintl3 promoter [55]. Therefore, transcriptional interference could also take place in class 3 integrins [20; 26], in which transcripts starting from Pc could affect _intl3_ expression, and hence class 3 integrase recombination activity.
# Post-Quantum Key Exchange and Subscriber Identity Encryption in 5G Using ML-KEM (Kyber) 1
## 2 Motivation and Background
### Background on 5G AKA and Cryptographic Primitives
#### 2.2.3 Post-Quantum, CRYSTALS-Kyber  
CRYSTALS-Kyber [7] is the only PKE/KEM cryptographic algorithm selected by NIST in the fourth round of the post-quantum cryptography standardization process. Kyber is specifically a post-quantum cryptographic algorithm, which means that it provides security against attacks from both classical and quantum computers. The mathematical hardness of the Kyber relies on problems believed to be hard even for quantum computers. One such problem is the hardness of solving certain instances of the learning with errors (LWE) problem over module lattices. These problems involve finding a secret vector given some noisy linear equations.  
When the protection scheme ID is 1, then X25519 is used, and when the ID is 2, secp256r1 is used. 3 GPP also standardizes protection scheme ID 3\(\sim\)11 for future use, while it standardizes 12\(\sim\)15 for the use of the proprietary home operator.
# Performance and Challenges of Service-Oriented Architecture for Wireless Sensor Networks
## 6 Service-Oriented Middleware (SOM) Architectures Approaches for WSNs
### TinySOA  
TinySOA enables programmer access to WSNs from an application by using Service-Oriented API [53]. This approach helps integrate a WSN with the internet application, providing an abstraction for the developers' applications. The TinySOA acts as a basis for the middleware system and has the ability to allow application developers (that do not deal with low-level of WSNs) to obtain data from the sensors. The middleware helps integrate all the elements into the architecture.  
TinySOA consists of two types of services: internal and external, as shown in Figure 8. They are provided by the node, gateway, server, and register components. The mechanism of TinySOA provides node discovery and gateway for the WSN infrastructure. The gateway component is a bridge between external applications and the WSN. The hardware platform of TinySOA includes MicaZ motes (Crossbow Technology, Inc., Milpitas, CA, USA) [53].
# Rapid In-Field Volatile Sampling for Detection of _Botrytis cinerea_ Infection in Wine Grapes
## 3 Materials and Methods  
### Chemical and Materials  
Analytical-grade chemicals and reagents for preparing standard solutions for GC-MS analysis were used without further purification. Standard 1-octen-3-one (96%), 1-octen-3-ol (\(\geq\)98%), 3-octanone (\(\geq\)98%), benzaldehyde (\(\geq\)99.5%), _trans_-2-hexen-1-ol (96%), benzyl alcohol (99%)+, 1,5-dimethyl naphthalene (98%), 3-methyl-1-butanol (99%+), 1,5-dimethyltetralin (\(\geq\)90%), phenylethyl alcohol (\(\geq\)99%), 4-methyl-2-pentanol (98%), glucose (\(\geq\)99.5%), fructose (\(\geq\)99%), tartaric acid (99%), naphthalene-d8 (99 atom% D, \(\geq\)98% (CP)), 3-octanol (99%), 2-octanol (\(\geq\)99.5%), zinc nitrate hexahydrate (98%), 2-methylimidazole (98%), and glass wool were purchased from Sigma-Aldrich (Sydney, NSW, Australia).  
Figure 4: Correlation coefficient for _B. cinerea_ infection levels measured with LFD scores (12–97) and the peak area counts of volatile metabolites detected by thermal desorption GC-MS, using ZIF-8 as absorbent materials, using low-flow-rate in-field sampling. Green shows positive correlation, red shows negative correlation, and the dot sizes represent the absolute values of correlation coefficients. LFD, lateral flow device; 1,5-DMT, 1,5-dimethyltetralin; PEA, phenylethyl alcohol; 1,5-DMN, 1,5-dimethylhaphthalene.  
Hexanal (98%), 1-hexanol (99%), menthol (HPLC), and \(N\),\(N\)-dimethylformamide (DMF) (99%) were purchased from Alfa Aesar (Scoresby, VIC, Australia). Hexanal-d12 (98.5 atom % D) and 2,4,6-tribromoantisol-d5 (99 atom % D) were purchased from CDN Isotopes (Pointe-Claire, Quebec, Canada). Milli-QTM water (18 M\(\cdot\)cm) was collected through a MilliporeTM water purification system (Merk, Bayswater, VIC, Australia). Synthetical grape juice was made using 100 g glucose, 100 g fructose, and 4 g tartaric acid. All solutions were prepared in Milli-QTM water, with the pH adjusted to 7.0.
## 3 Comparative Validation
### Analysis of Calculation Results  
The opening of circumferential joints is significantly affected by thrust and stratum friction, but little by water and soil pressure. Considering factors such as the assembling position of segments and unsolidified synchronized grout in actual engineering, it is assumed in the simulation that the first four-ring segment is not affected by the formation friction. Figure 9 is a cloud diagram of the longitudinal displacement of the segment lining without any reinforcement measures after thrust unloading. In Figure 9, the left side is the front section of the tunnel. It can be seen from the figure that longitudinal stress relaxation occurs in the segment lining after thrust unloading. The whole tunnel has a longitudinal displacement towards the front section of the tunnel. Meanwhile, the circumferential joints change significantly, which is manifested as the opening of circumferential joints in the front section of the tunnel increases significantly.  
Figure 10 is the relationship curve of the opening of circumferential joints after thrust unloading. The simulation results show that thrust unloading causes longitudinal stress relaxation in approximately 18 ring segments. The maximum longitudinal displacement reaches 73.33 mm, and the initial opening of the circumferential joints x\({}_{0}\) is 3.124 mm. The maximum opening is 20 mm in the first four rings, which then decreases by 0.071 mm one by one. After 18 rings, the openings of the circumferential joints are reduced to 3.124 mm and does not change.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Material** & **Dry Density** & **Elasticity** & **Poisson’s** & **Cohesion** & **Frictional** & **Lateral** \\  & **(kg/m3)** & **Modulus** & **Ratio** & **(kPa)** & **Angle (\({}^{\circ}\))** & **Pressure** \\  & & **(MPa)** & & & & **Coefficient** \\ \hline Silt & 1800 & 40 & 0.3 & 2 & 31.6 & 0.7 \\ Silty clay & 1600 & 20 & 0.25 & 22 & 16 & 0.65 \\ Strongly weathered tuff & 2200 & 2580 & 0.21 & 180 & 13 & 0.6 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Formation parameters.  
Figure 9: Cloud diagram of the longitudinal displacement of the segment lining without any reinforcement measures after thrust unloading.
# Voxel-Based Navigation: A Systematic Review of Techniques, Applications, and Challenges
## 4 Key Techniques for Voxel-Based Navigation
### Voxel-Based Modeling  
Voxel modeling is a crucial step in acquiring environmental information. Various data sources, such as Building Information Modeling (BIM), LiDAR, Computer-Aided Design (CAD), and CityGML, can be used to construct voxel models. Researchers have developed different voxelization algorithms and techniques to adapt to different application scenarios.
## 4 Results
### Case of Small Concentrations
#### 4.3.2 Discussion  
It is possible that, in industrial applications, these uncertainties are accepted. However the error would be to consider the PCM as pure with a fixed melting temperature evaluated at \(T_{\text{onset}}\). The fact that these PCM are solutions has more important consequences as we can already guess with Figure 19 clearly showing that the melting does not take place at fixed temperature but over a wide range of temperature.  
Figure 24: DSC curves at \(\beta=0.5\,\text{K}\,\text{min}^{-1}\) for solutions at various concentrations and for pure water. (a) Very dilute cases; (b) Classical dilute cases.  
To evaluate, with these small concentrations, this spreading of melting over the temperature, we present in Table 1 for each concentration, \(T_{\rm liquidus}\) (calculated by Equation (19)), \(T_{\rm onset}\), the temperatures where the mass fraction of liquid (calculated by Equation (17)) are \(X_{w}^{L}\) = 10%, 50% and 90% respectively and finally this mass fraction at the evaluated \(T_{\rm onset}\).  
The example of the small concentrations described in this section corresponds to PCM with good, even very good, purity. However, Table 1 indicates that is not pertinent to consider this PCM as pure. For example, for \(y_{0}\) = 1%, for the \(T_{\rm onset}\) given by the PCM sellers or given by own experiments, about 45% are already melted at this temperature and the melting has begun about 10 K before this onset temperature. We are not sure that it corresponds to an optimized latent heat storage.
# Micro-Satellite Systems Design, Integration, and Flight
## 3 ChipSat RTOS and RF Development  
This section discusses the testing and modification of the RF system on the ChipSat picosatellites, one of the systems that was worked on. The system level requirements for Alpha are shown in Table 4 below.  
\begin{table}
\begin{tabular}{c c c} \hline
**ID** & **Requirement** & **ID** & **Requirement** \\ \hline
1.0 & The systems SHALL communicate over RF & 5.0 & The system SHALL add a preamble \\ \hline
2.0 & The system SHALL capture IMU data in a packet & 5.1 & The preamble SHALL consist of 4 8-bit barker codes \\ \hline \end{tabular}
\end{table}
Table 4: Requirement table for the ChipSat RF subsystem.  
Figure 9: (a) Integration testing flight hardware; (b) flight-ready electronics aboard the CubeSat.
# Unleashing the Potential of 5G for Smart Cities: A Focus on Real-Time Digital Twin Integration
## 2 Current Trends for 5G in Smart Cities
### Technological Overview
The number of devices supported per square kilometer highlights how each generation has improved in handling network congestion, especially with 5G's advancements in massive MIMO and network slicing. Network slicing, enabled by 5G, introduces a layer of customization to smart city infrastructure [28; 29]. By creating dedicated virtual networks for specific applications or services, operators can prioritize critical functions like emergency response systems, ensuring that they receive the necessary bandwidth and low-latency connections for optimal performance [30; 31]. For less urgent tasks, such as entertainment or routine environmental monitoring, a different network slice can be allocated, allowing for a more efficient use of available resources. This flexibility helps to maintain a high level of service across all urban functions, from transportation to public safety, by guaranteeing that essential services are not impacted by non-essential network traffic [28; 29; 30; 31]. 5G's network slicing ensures that smart cities remain highly adaptable, scalable, and capable of managing diverse and evolving demands.
## 3 Biorefinery Strategies for Upcycling Coffee By-Products
### In Vitro Research  
In vitro studies play a crucial role in the initial evaluation of the bioactivity and safety of coffee by-product-derived ingredients, as they provide a controlled laboratory environment to examine their effects on biological systems [170]. Given the abundance of bioactive compounds found in coffee by-products and their diverse biological effects, employing multiple experimental approaches is necessary to gain a comprehensive understanding of their activity [171]. These in vitro studies allow for the assessment of various properties, including antioxidant, anti-inflammatory, and antimicrobial activities of coffee by-product-derived compounds. Of particular interest is evaluating the antioxidant activity, as coffee by-products are known to contain phenolic compounds which exhibit potent antioxidant properties [15]. Phenolic compounds from coffee by-products have been recognized as bioactive components with antioxidant properties [58; 115; 172]. In vitro studies have also been conducted to compare the phytochemicals from coffee by-products and their potential to reduce markers of inflammation, oxidative stress, adipogenesis, and insulin resistance [41; 119; 173]. Coffee silverskin melanoidins, formed via the Maillard reaction, have been assessed for their bioactivity [174]. The coffee hus has been evaluated as an innovative antioxidant dietary fiber ingredient [42]. Additionally, in vitro assays can determine the potential of coffee by-product-derived ingredients to inhibit the growth of pathogenic bacteria [175]. Moreover, in vitro studies serve as a valuable tool to optimize the processing conditions and formulation of food ingredients or nutraceuticals [176]. For example, researchers can investigate the effects of different processing parameters, such as temperature and pH, on the bioactivity and stability of the final product. In vitro studies also aid in determining the optimal concentration of coffee by-product-derived compounds to maximize their bioactivity in the formulation [89].  
Furthermore, it is essential to conduct in vitro bioaccessibility, bioavailability, and toxicological studies to evaluate bioactive compounds' release, absorption, and safety [177]. Bioaccessibility studies have been conducted to evaluate the release and absorption of bioactive compounds from coffee by-products and the changes in antioxidant activity during in vitro gastrointestinal digestion [33; 120; 153]. Safety studies allow for a comprehensive assessment of potential allergenicity, genotoxicity, and other safety aspects associated with coffee by-product-derived ingredients [37]. While in vitro research provides valuable insights into the bioactivity and safety of coffee by-product-derived compounds, it is important to acknowledge its limitations in predicting their effects in vivo [178]. Hence, conducting subsequent in vivo studies using animal and human models is necessary to confirm the bioactivity and safety of these ingredients.
## 5 Quantitative Assessment of Roadway Rock Burst Risk
### Quantitative Analysis of Roadway Rock Burst Risk  
Based on the above simulation results from 10 groups of parameters for roadway tunneling, a quantitative analysis of rock burst risk was conducted using critical expression (2), based on the method for the stress difference gradient change rate. The coefficients of variation (COV) for the mechanical parameters of coal mass were adjusted to 0.1 and 0.2.  
\[f_{(c,\varphi,E)}=\left[D_{gc}\right]-D_{gc(c,\varphi,E)} \tag{2}\]  
where \(f_{(c,\varphi,E)}\) is the index of coal mass burst risk; \([D_{gc}]\) is the critical value of the change rate of the stress difference gradient under engineering experience, where the value 13 is employed; and \(D_{gc(c,\varphi,E)}\) is the change rate of the stress difference gradient for coal seams with different groups of parameters.  
When \(f_{(c,\varphi,E)}<0\), rock burst damage occurs; by contrast, when \(f_{(c,\varphi,E)}\geq 0\), there is no rock burst damage, and other mine pressure phenomena, such as instability or the static failure of coal mass, may apply under specific \([D_{gc}]\) values determined by similar engineering project.  
Figure 10 presents the gradient value curves for the stress difference in the coal mass of the roadway side, considering different elastic moduli, internal friction angles, and cohesion values under various COVs. It can be noted that the \(D_{gc}\) trends obtained are different.  
Figure 9: Plot of gradient of stress differences and change rates for 10 groups of parameters.  
Despite the COVs for the internal friction angle and cohesion change, \(D_{gc}\) surpasses the critical value across various parameter sets, suggesting that both factors exert a comparable influence on \(D_{gc}\). Conversely, the \(D_{gc}\) curves under varied COV for the elastic modulus nearly overlap, indicating that the variation of the elastic modulus has a minimal burst effect on \(D_{gc}\).  
It can be concluded from Figure 10 that as the COV for the internal friction angle increases, the curves of \(D_{gc}\) decline with the amplitude fluctuation. In contrast, the curves for the cohesion rise with an increase in the COV, and amplitude fluctuation also exists. The relationship between the COV and \(D_{gc}\) suggests that the cohesion and the internal friction angle of the coal mass exert opposing effects on the burst tendency in the roadway side. An increased COV for cohesion is more likely to induce significant deformation in the surrounding coal and rock during roadway tunneling, thereby increasing the risk of rock burst. Therefore, in practical roadway tunneling, it is crucial to monitor the variation trends of cohesion in coal seams across different sections and to implement appropriate measures to mitigate the occurrence of rock burst.
# Enhanced Performance of nZVI/MXene@CNTs for Rapid As(III) Removal from Aqueous Solutions
## 3 Results and Discussion
### Removal of As(III) from Aqueous Solutions
#### 3.2.2 Effect of Initial pH and Dosage  
The impact of the initial pH value on As(III) removal by nZVI/MXene@CNTs was studied at room temperature and different pH values in the range 3-11 in an aqueous solution containing 200 mg/L As(III) (Figure 4b). The results clearly showed that the initial pH of the solution had an apparent effect on the remaining concentration and removal rate of As(III). The adsorption capacity of As(III) fell from 443.32 mg/g to 144.95 mg/g when the pH increased from 3.0 to 11.0. The result further demonstrated that the removal of As(III) was limited as the pH levels rose. Under acidic conditions, there were rapid corrosion rates of Fe\({}^{0}\), accelerating the migration of the electrons in the solution and increasing the reaction rate. Meanwhile, when the pH of the solution was lower than the isoelectric point of the material, the hydroxyl groups on the surface were protonated to produce OH\({}_{2}\)\({}^{+}\) to enhance the adsorption of As(V) [56]. At pH > 9.0, the removal effect of As(III) decreased significantly, because of the corrosion rate of Fe\({}^{0}\), and the electron migration rate slowed down, resulting in less H\({}_{2}\)O\({}_{2}\), \(\bullet\)OH, \(\bullet\)O\({}_{2}\)\({}^{-}\), etc. produced. Meanwhile, As(III) occurred mostly in the form of H\({}_{2}\)AsO\({}_{3}\)\({}^{-}\), and the removal rate decreased due to electrostatic repulsion. Therefore, As(III) was better removed by the nZVI/MXene@CNTs under acidic conditions.  
Figure 4: Effect of the (**a**) different materials, (I–VI representing CNTs, functionalized CNTs, MXene, nZVI/MXene, MXene/CNTs and nZVI/MXene@CNTs, respectively); (**b**) initial pH; (**c**) dosage of nZVI/MXene@CNTs; (**d**) coexisting ionic on the As(III) removal from aqueous solution by nZVI/MXene@CNTs; and (**e**) reusability of nZVI/MXene@CNTs.  
As shown in Figure 4c, the solid-to-liquid ratio of the system would be affected by the dosage. The removal of As(III) by nZVI/MXene@CNTs grew from 12.99% to 97.98% with the increase of the dosage from 0.1 g/L to 1.0 g/L, and the maximum value of adsorption at 0.4 g/L was 336.33 mg/g. That is because, at the same initial concentration, the effective adsorption sites would be enhanced with the dosage appropriately increased. There was a high concentration of As(V) in solution at the lower dosing levels owing to the restricted adsorption sites and the full oxidation of As(III). In contrast, because the adsorption sites were more sufficient at larger dosage, less As(III) and As(V) remained in the solution.
# Homogeneous Data Normalization and Deep Learning: A Case Study in Human Activity Classification
## 3 Results
### Normalized Data with MaxAbsScaler  
Initially, MaxAbsScaler was used to normalize the data acquired from the accelerometer data related to the analyzed human activities, in particular, walking upstairs, walking downstairs, standing, and walking. Table 1 presents the confusion matrix related to the experiments performed with the accelerometer sensor included in the dataset used. It was verified that the most correctly identified activities are walking upstairs, walking downstairs, and walking.  
Next, the classification results of the data acquired from the accelerometer sensor after the application of MaxAbsScaler were analyzed, verifying that the DNN method implemented reported an accuracy of 53.12%, a precision of 51.59%, a recall value of 51.90%, and an F1-Score of 51.74%.  
In continuation, MaxAbsScaler was used to normalize the data acquired from the gyroscope data related to the different human activities. Table 2 presents the confusion matrix related to the experiments performed with the gyroscope sensor included in the dataset used. It was also verified that the most correctly identified activities are walking upstairs, walking downstairs, and walking.  
Besides, the classification results of the data acquired from the gyroscope sensor after the application of MaxAbsScaler were analyzed, verifying that the DNN method implemented reported an accuracy of 59.71%, a precision of 66.82%, a recall value of 56.63%, and an F1-Score of 61.31%.
## 3 Optimization Problem
### Sum Rate  
On the basis of the aforementioned constraints in Equations (9) and (10) and sum rate representation and the fact that there is a single antenna at the BS and user equipment, the standard optimization problem can be normally expressed as follows [21,22]:  
\[\max\limits_{\alpha}R_{sum}=\sum\limits_{k=1}^{N}\log_{2}\left(\frac{\left|h_{ k}\right|^{2}P_{t}\sum\
olimits_{j=1}^{k-1}\alpha_{j}+\sigma^{2}+\left|h_{ k}\right|^{2}P_{t}\alpha_{k}}{\left|h_{k}\right|^{2}P_{t}\sum\
olimits_{j=1}^{k-1} \alpha_{j}+\sigma^{2}}\right) \tag{14}\]  
such that:  
\[\begin{array}{l}\sum\limits_{x=1}^{N}\alpha_{x}\leq 1\\ \log_{2}(1+\delta_{n})\geq R_{min}\\ \alpha_{k}\geq 0\ \forall k=1,2,\ldots,N\end{array}\]