esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Work
In the case of a 5G mobile network realization without network slicing, the realization of an autonomous vehicle service and standard mobile services in standard non-sliced 5G network do not reduce energy consumption, leading to a less energy-efficient network. The work addressing the impact of NS on E2E network EE is presented in [13] (Table 1). The optimization of throughput and resource allocation in the cloud was explored with the aim of minimizing the overall network energy consumption. The outcomes of the performed simulation demonstrate that comprehensive E2E network slicing is more energy-efficient than solely focusing on RAN slicing. According to their suggested methodology, there is the potential to achieve energy savings of up to 20% compared to relying solely on RAN slicing. Comparing the results from [12; 13], a rough conclusion can be drawn that one-third of the energy consumption savings are achieved through core and transport network slicing, while two-thirds of the energy consumption savings are achieved through RAN slicing. This is in line with the results and data presented in [1]. Paper [14] introduces a model for the energy optimization of NSs using Integer Linear Programming (ILP). This model is designed to address the challenge of optimizing energy consumption while constructing an E2E NS in implementations with stringent security requirements (Table 1). Through simulation experiments, it was demonstrated that the proposed model achieves significant energy savings while meeting stringent QoS and security requirements. As the authors claim, the proposed model is suitable only for static NS environments, which diminishes the possibility of its practical implementation since real-world telecommunication networks are highly dynamic. From the presented literature overview, it is evident that the use of network slicing allows for various strategies to save consumed energy and enhance the EE of 5G networks. Generally, significant differences in energy savings exist in NSs when E2E is applied comprehensively across all parts of the network. The presented research shows that there is an insufficient exploration of the impact of NS on the possible improvement in 5G networks' EE. Therefore, the aim of this review work is to highlight the possibilities for improving the EE of 5G networks through the application of NS and to describe the current standardization of KPIs and other aspects related to enhancing the EE of 5G networks using NS as a concept.
## 3 The Influence of Soiling on Photovoltaic Energy
### Experimental Assessment of PV Sailing Losses
In spite of the low degree of soiling underwent by the rooftop PV installation, Figure 8a shows that there was a slight difference between the \(PR_{\text{Isc}}\) values of the cleaned and the soiled modules, and Figure 8b clearly exhibits a slowly increasing trend over time of \(SR\) during the first rainless period (i.e., from 7 March to 28 March) as well as the performance recovery of the PV modules just after the rainy days of April. It might have been expected to observe higher soiling rates during February than during March due to the concurrent cypress pollen deposition, which was quite more evident than any other local pollen deposition issue at a later date. Nevertheless, the results during this season were not concluding because: (1) the measured soiling ratios were quite low, (2) the PV modules did not only accumulate pollen, but also dust and other urban pollutants, and (3) it was speculated that the dew events occurring during the cypress pollen season might have removed a fraction of the deposited pollen. Finally, we focused our interest on artificially analyzing soiling by cypress pollen due to several reasons. Firstly, cypresses are widely spread in the Mediterranean region and release such an enormous amount of pollen that they become responsible for a large part of the total annual amount of airborne pollen in several areas [106]. Secondly, soiling by cypress pollen became relevant to the PV installation, which is not surprising given its abundance in the nearby green areas, boundary hedgerows, etc. A third reason is that fresh pollen can be gathered in large amounts from cypress trees by simply shaking the mature male cones. In fourth place, based on the characteristics of the cypress pollen (i.e., medium grain size, spheroidal shape, release as solitary monads, absence of sticky surface coatings [34]), it seems reasonable to guess that their artificially-deposited soiling layers would fairly approximate to an ideal packaging of loose spherical particles, which facilitates the interpretation of the resulting optical impairment. Moreover, such features make cypress pollen a good representative for pollen of many anemophilous species.
## 2 Literature Review  
Efficient container terminals are considered the key factor for success of third generation of ports, due to the cost-effectiveness of transport and the specialization and efficient organization in the associated terminals [11].  
An efficient planning of container terminals, considering the allocation of equipment, fuels and facilities is vital to achieving the climate and environmental goal of green port construction [12]. Traditional studies of port emissions are generally applied to existing solution. In this respect, several scholars developed different models in order to evaluate the environmental performance of container terminal. [PERSON] et al. [13] evaluated environmental performance of container terminals in term of CO\({}_{2}\), SO\({}_{2}\), NOx and particle emissions with a model based on French standards and guidelines for emissions evaluations and applied it to the port of Tanger Med; [PERSON] et al. [14] developed a tool based on DEA (Data Envelopment Analysis) to evaluate environmental and operational performance of containers port in terms of CO\({}_{2}\) emissions and TEUs (twenty-foot equivalent units); [PERSON] and [PERSON] [15] and [PERSON] [16] developed simple models to estimate CO\({}_{2}\) emissions in container terminals based on type of equipment and transport mode.  
[PERSON] et al. [4] estimated a composite environmental index and applied it to the container terminal of the Port of Rijeka based on analytic hierarchy process evaluation of several environmental indicators (air and noise emissions, waste, energy consumption, water quality). [PERSON] et al. [16] developed a model for the evaluation of energy efficiency and CO\({}_{2}\) emissions of port container terminal equipment.  
A literature review shows that there are few studies focusing on the planning of the terminal, and very few papers focus on a comprehensive analysis of environmental issues due to port operation. Based on this premise, in this study the authors decided to propose a simplified framework to help port decision-makers in deciding the best infrastructure provisions to foster the efficiency of container terminals without neglecting environmental impacts.  
In summary, our framework is intended to help decision makers answer the question: how should container terminals equip themselves to achieve new container traffic objectives and how can they limit the environmental effects that would be generated by these new port operations? The authors answered to this question by proposing a simplified terminal decision-making tool and showed its use by applying it in the case of the Port of Augusta.
## 3 Results and Discussions
### Typical Samples of the Raw Data Collected During the Measurement Campaign
#### 3.3.3 Error Analysis in the Akure Environment
The optimized model obtained an improved RMSE of 7.815 compared to the value of the untuned model, with 9.877 dB. The optimized model is recommended for prediction in Akure or any similar environment. Comparison plots of the variations in the measured path loss between the untuned Hata and the optimized Hata models for Ikorodu are presented in Figure 8. There was significant improvement in the optimized model compared to the untuned model. Similarly, the variation in the measured path loss with distance of the untuned COST-231 and optimized COST-231 models for Akure is presented in Figure 9. There was marginally significant improvement in the optimized model over the untuned one because the untuned RMSE of 9.877 is significantly within the acceptable range of 7-15 dB for suburban areas. The improvement in the optimized over the untuned models is clearly depicted. The optimized models have demonstrated better performances based on their lower RMSE values compared to the untuned models. They will provide a valuable approach to wireless communication planning in tropical urban and suburban environments, with the aim of enhancing the quality of transmission and reception (QoTnR) over UHF channels in Nigeria and similar environments in Africa.
## 2 Materials and Methods  
### Materials  
Salmeterol xinafoate (SLX) CAS number 94749-08-3 purity \(>\) 98%, terbutaline (TER) CAS number 46719-29-3 purity \(>\) 98%, and salbutamol hemisulfate (SAL) CAS number RN 51022-70-9 purity \(>\) 98% were purchased from Tokyo Chemical Industry (Tokyo, Japan). 2-Hydroxethyl methacrylate (HEMA) CAS number 868-77-9 purity 97%, ethylene glycol dimethacrylate (EGDMA) CAS number 97-90-5 purity 98%, trimethylolpropane trimethacrylate (TRIM) CAS number 3290-92-4 purity 98%, and benzoyl peroxide (BPO) CAS number 94-36-0 purity 75% were obtained from Sigma-Aldrich (Singapore). HPLCgrade methanol CAS number 47-56-1 purity 99.8%, isopropanol CAS number 67-63-0 purity 99.5%, and acetonitrile CAS number 75-05-8 purity 99.9% were purchased from Fisher Scientific (New York, NY, USA). Acetic acid CAS number 64-19-7 was purchased from Sigma-Aldrich (Singapore). Blood samples were obtained from the Indonesian Red Cross. Empty SPE cartridges were purchased from Supelco (Bellefonte, PA, USA). The Chromabond ABC18 (C18) sorbent solid phase extraction columns were purchased from Macherey-Nagel (Duren, Germany). If not otherwise specified, all chemicals are analytical grade. The morphological evaluation analysis of the polymer was carried out by JSM-6610 LV JEOL Ltd. (Tokyo, Japan). BET Surface Area Analyzer Quantachrome NOVA 2200E BET was used in the analysis of the surface area of polymers (Florida, FL, USA). Blood analysis, after extraction with MI-SPE, was performed using HPLC (Waters Alliance e2695 with UV detector) (Florida, FL, USA) with gradient elution, using a water/acetonitrile mixture as the mobile phase. Acetonitrile concentration was changed from 10% to 20% of acetonitrile from minutes 2 to 5, 20% to 50% from minutes 5 to 7, 50% to 10% from minutes 7 to 15. The HPLC column was a Zorbax Eclipse XDB-Column C18 (4.6 \(\times\) 150 mm, 5 \(\upmu\)m) from Agilent Technologies (Santa Clara, CA, USA). The injection volume of the HPLC analysis was 20 \(\upmu\)L, using 0.8 mL min\({}^{-1}\) as the flow rate, and the UV detection wavelength was set at 252 nm. IR analysis was performed using a Nicolet 380 FT-IR from Thermo Fisher Scientific (Waltham, MA, USA). SPE was conducted using SPE manifold purchased from Phenomenex (Torrance, CA, USA).
## 2 Materials and Methods
### Thermodynamic Methods
#### 2.2.2 Surface Energy and Work of Adhesion  
Considering a liquid of known surface tension \(\gamma_{l}\) in contact with a simple solid, smooth, homogeneous, non-deformable, and isotropic surface, the corresponding work of adhesion \(W_{a}\) can be then written as follows:  
\[W_{a}=\gamma_{s}+\gamma_{l}-\gamma_{sl} \tag{4}\]  
where \(\gamma_{sl}\) is the solid-liquid interface tension.  
[PERSON] [48] proposed the following equation:  
\[\gamma_{l}\ cos\theta=\gamma_{s}-\gamma_{sl} \tag{5}\]This was obtained by defining the concept of the contact angle \(\theta\) formed between the liquid drop and the plan solid surface.  
On the other hand, [PERSON] [17] used [PERSON]'s equation [48] and expressed the work of adhesion by Equation (6):  
\[W_{a}=\gamma_{l}\;(1+cos\theta) \tag{6}\]  
[PERSON] [18] applied the geometric mean of the dispersive components of the solid and liquid and proposed a new expression of the work of adhesion:  
\[W_{a}=\gamma_{l}\;(1+cos\theta)=2\sqrt{\gamma_{s}^{4}\gamma_{l}^{4}} \tag{7}\]  
where Equation (7) is only valid for dispersive interactions.  
Later, the [PERSON]'s equation [18] was extended to an approach taking into account the polar contribution (hydrogen bonding) [19] in the expression of the work of adhesion:  
\[W_{a}=2\sqrt{\gamma_{s}^{4}\gamma_{l}^{4}}+2\sqrt{\gamma_{s}^{\mathrm{P}} \gamma_{l}^{\mathrm{P}}} \tag{8}\]  
The values of \(\gamma_{s}^{p}\) and the Lewis acid \(\gamma_{s}^{+}\) and base \(\gamma_{s}^{-}\) surface energies of solid copolymers were obtained using [PERSON] et al.'s method [10] and applying Equation (9):  
\[-\Delta G_{a}^{p}(T)=2\mathcal{N}a(T)\bigg{(}\sqrt{\gamma_{l}^{-}\gamma_{s}^{ +}}+\sqrt{\gamma_{l}^{+}\gamma_{s}^{-}}\bigg{)} \tag{9}\]  
This allowed for obtaining the polar (or acid-base) surface energy \(\gamma_{s}^{AB}\) of the modified copolymers using Equation (10):  
\[\gamma_{s}^{AB}=\gamma_{s}^{p}\;=2\sqrt{\gamma_{s}^{+}\gamma_{s}^{-}} \tag{10}\]  
Therefore, the work of adhesion can be expressed as follows:  
\[W_{a}=2\bigg{[}\sqrt{\gamma_{s}^{4}\gamma_{l}^{4}}+\sqrt{\gamma_{l}^{-}\gamma _{s}^{+}}+\sqrt{\gamma_{l}^{+}\gamma_{s}^{-}}\bigg{]} \tag{11}\]  
The different surface energy components of the modified copolymers were previously determined. The work of adhesion was then calculated with the help of Equation (11).  
Furthermore, the dispersive \(W_{a}^{4}(T)\) and polar \(W_{a}^{\mathrm{P}}(T)\) contributions of the work of adhesion can be determined using the following equations:  
\[\left\{\begin{array}{l}W_{a}(T)=W_{a}^{\mathrm{d}}(T)+W_{a}^{\mathrm{P}}(T) \\ W_{a}^{\mathrm{d}}(T)=2\sqrt{\gamma_{s}^{4}(T)\gamma_{l}^{4}(T)}\\ W_{a}^{\mathrm{P}}(T)=2\bigg{[}\sqrt{\gamma_{l}^{-}\gamma_{s}^{+}}+\sqrt{ \gamma_{l}^{+}\gamma_{s}^{-}}\bigg{]}=2\sqrt{\gamma_{l}^{\mathrm{P}}(T)\gamma _{s}^{\mathrm{P}}(T)}\end{array}\right. \tag{12}\]
# Microencapsulation of Polyphenols and Their Application in Food Technology
###### Abstract  
Microencapsulation of polyphenols is an innovative approach in food technology by which to protect these bioactive compounds from degradation and increase their bioavailability. Polyphenols, naturally occurring in plants, exhibit potent antioxidant, anti-inflammatory and anticancer properties, which make them valuable functional ingredients in foods. However, their susceptibility to external factors, such as light, temperature and pH, presents a significant challenge for their incorporation into food products. Microencapsulation, based on various techniques and carriers such as polysaccharides, proteins and lipids, allows polyphenols to be stabilized and released in a controlled manner in the digestive system. This article reviews the different microencapsulation techniques, carrier properties, and the applications of microencapsulated polyphenols in food products, including bakery, dairy and functional beverages. Additionally, the article discusses the benefits and challenges associated with this technology, highlighting its potential to improve the stability, nutritional value and sensory acceptance of food products.  
polyphenol microencapsulation; encapsulation carriers; functional food; food fortification +
Footnote †: journal: Applied sciences  
range of applications in various sectors of the food industry. For example, microencapsulated polyphenols are used as ingredients in functional products, such as beverages, dairy products, and bakery items, where they serve both an enriching and a protective role [8]. Additionally, microencapsulation technology has been applied to enhance the shelf life of food products by inhibiting oxidative and microbial processes [9]. Consequently, microencapsulation not only improves the stability of polyphenols but also increases the value of food products, making them more attractive to consumers seeking healthy and durable food solutions [10].  
Therefore, the aim of this review article is to discuss the technology of polyphenol microencapsulation, focusing on the various encapsulation methods and their applications within the food industry. Moreover, the health benefits of microencapsulated polyphenols and the future prospects of this technology will also be discussed.
# Fault Parameter Estimation Using Adaptive Fuzzy Fading Kalman Filter
## 2 Parameter Estimation with Kalman Filter
### Extended Kalman Filter  
The basic idea of EKF is to linearize the state space model at each time instant around the most recent state estimate, which is taken to be either \(\hat{x}_{k}\) or \(\hat{x}_{k}^{-}\). Once linearized model is obtained, the standard KF technique can be applied. Consider the nonlinear discrete-time stochastic system represented by  
\[\begin{array}{l}x_{k+1}=f(x_{k},u_{k})+w_{k}\\ z_{k}=h(x_{k},\theta_{k})+v_{k}\end{array} \tag{11}\]  
Taking the linearization process with Jacobian operator given by:  
\[A_{k}=\left.\frac{\partial f}{\partial x}\right|_{x=\hat{x}_{k-1}}\quad H_{k} =\left.\frac{\partial h}{\partial x}\right|_{x=\hat{x}_{k-1}^{-}} \tag{12}\]  
then, the standard Kalman filter equations can be applied.  
**3. Adaptive Fuzzy Fading Kalman Filter for Fault Parameter Estimation**  
The optimality of the Kalman filter can be ensured when _a priori_ knowledge of the process/measurement noise matrices, \(Q/R\), and the state transition matrix \(A\) are completely known. In practical applications, however, these matrices are often insufficiently known. It is known that incomplete information makes estimations biased or even diverged [13; 14]. To overcome this problem, various adaptive techniques have been studied. As mentioned before, component faults can be modeled as the change in the value of the dynamic system parameter. See (1). Therefore, to estimate the fault parameter via a Kalman filter, an adaptation procedure is required to handle the incompleteness of _a priori_ information. In this paper, an adaptive fuzzy fading Kalman filter is proposed so that the convergence property during the estimation of fault parameter can be improved.
## 2 Theoretical Frameworks
### Reliability Block Diagram (RBD)  
The RBD is a mental model developed from the FTA to attempt to visualise the relationship between basic events to identify vulnerabilities in the model. A summary of rules on how to develop an RBD from an FTA model is shown below [10].  
1. OR relationships in the FTA become series configurations on the equivalent RBD
2. AND relationships in the FTA become parallel configurations in the equivalent RBD
3. Extraction is performed from the top of the tree
4. Only the basic events are modelled
5. The order does not matter on the RBD
6. Real root causes should be identified
7. Both the FTA and RBD are mental models for risk analysis, not risk assessment  
Appendix A shows the theoretical foundation for mapping FTA to RBD. Further analysis from the RBD model can be performed by applying axioms of Boolean algebra to identify the cut sets, which are a group of basic events on the FTA whose occurrence will lead to the occurrence of the top event [3]. The Boolean algebra rules are applied to determine the cut set for the analysis. Various studies [2; 3] have used this analysis to identify vulnerable aspects of models.
## 8 Conclusions
By integrating our scheme into actual IoT-based smart farming systems, we aim to enhance the security and privacy of sensor data communications, which are critical for ensuring the reliability and efficiency of automated farming operations. This approach would contribute to building a more resilient and secure smart agriculture infrastructure. In the future, we plan to design a better protocol that considers AI attacks and quantum attacks based on the proposed protocol. The more advanced protocol can adopt lattice-based cryptographic techniques to ensure post-quantum security. In addition, since the proposed protocol performs AI-based data analysis after authentication, there is a potential risk of AI attacks, such as data poisoning. To address this issue, future enhancements of the protocol may incorporate defensive mechanisms, such as anomaly detection, or adversarial training to secure AI-based analysis. Furthermore, to evaluate the practicality and performance of the protocol, experimental validation will be conducted not only using the AVISPA tool but also in a real smart farming testbed environment. Conceptualization, H.J. ; methodology, H.J. ; software, D.K. and S.S.; validation, J.C., S.S., and Y.P. ; formal analysis, H.J., J.C., and D.K. ; writing--original draft preparation, H.J. ; writing--review and editing, J.C., S.S., D.K., and Y.P. ; supervision, Y.P. ; project administration, Y.P. All authors have read and agreed to the published version of the manuscript. This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (RS-2024-00450915). Not applicable. Data Availability Statement: Data are contained within this article. The authors declare no conflicts of interest.
# Three-Dimensional Obstacle Avoidance Strategy for Fixed-Wing UAVs Based on Quaternion Method
## 3 Improved 3D-VO Method for UAV Collision Avoidance  
Under the guidance framework proposed in this work, all subtasks are described by position vectors in the \(n\)-frame. In this section, we introduce obstacle avoidance points resulting from the improved 3D-VO algorithm.
## 3 Experimental Results
### Analysis and Comparison of Experimental Results
#### 3.2.1 Load-Carrying Capacity  
Table 3 lists the measured maximum strengths (\(V_{peak}\)) of the tested specimens. The IP specimen shows 24.5% greater \(V_{peak}\) values than the SSP specimen, because the screw pull-out failure that occurred in the SSP specimens prevented sufficient loading. Additionally, the IP-IS and IP-OS specimens show 19%-30% greater \(V_{peak}\) values than those of the IP specimen. This is because the stud member was attached to the integrated member, increasing the capacity to accommodate compressive force and the bending moment in the left and right portions of the stud-reinforced specimens. Table 3 also lists the nominal strengths \(V_{n,AISI}\) of the specimens, as described in Section 1.3, calculated using the effective width method. The nominal strengths, indicated by dashed lines, are presented in Figure 6. The nominal strengths of IP, IP-IS and IP-OS specimens are 83%, 145%, and 160% of the yield strengths \(V_{y}\), respectively. The nominal strength \(V_{n,AISI}\) of the IP specimen is similar to the yield strength, although the web slenderness of the integrated member is nearly 400. The IP-IS and IP-OS specimens show 133% and 134% higher \(V_{n,AISI}\) values than those of the IP specimen, because the flanges--which are vulnerable to the bending of the integrated member--were reinforced. However, as a result of the test, the yield strengths \(V_{y}\) of the stud-reinforced specimens (IP-IS and IP-OS) were 31% and 37% lower than the nominal strength \(V_{n,AISI}\), indicating that the nominal strength prediction formula described in Section 1.3 is incorrect. The cause of this is analyzed in Section 3.2.5.