esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methodology and Application to a Case Study
### Main Socio-Economics Impacts
From this information and by means of a numerical analysis, a multiplication factor of 5 on the average employment ratio in Table 6 was estimated for distributed hydrogen production at a small scale (both reforming and electrolysis) and a multiplication factor of 0.2 for nuclear electrolysis and thermochemical production at a high scale. The resulting employment factors for distributed installations, as shown in Table 6, were used as a reference in this paper. Finally, employment factors were extrapolated to the years 2025, 2030, and 2050, using values of 2.37, 2.16, and 1.48 FTE per ton per day, respectively. These values were used for both electrolyzer and methanizer systems, where t/d refers to the hydrogen produced in the electrolyzer and converted in the methanization reactor. Employment factors of 1.8, 1.8, and 1.6 FTE per installed photovoltaic kilowatt in 2025, 2030, and 2050, respectively, were estimated from the model developed by [PERSON] et al. (2013) [63]. After applying the above employment factors to the parameters of a PtG basic unit (3.5 MW and 1.5 t/d of hydrogen production), we estimate that the commissioning of one PtG basic unit involves 13.4 full-time jobs for a one year's work during the 2020-25 period. We calculate 12.8 full-time jobs in the 2025-30 period and 10.1 full-time jobs in the 2030-50 scenario. This labor considers not only operation and maintenance activities, but also manufacturing, installation, etc., which are distributed over the lifetime of the plant.
## 5 Comprehensive Cost Computation Model  
A comprehensive model for a data breach cost and hence the cost of annual security is shown in Figure 4. It incorporates the concepts from the current computational models. Some data breach costs are direct financial expenses, and indirect costs such as the time, effort, and others according to Ponemon Institute terms. Therefore, there are five partial costs that comprise the total data breach cost: incident investigation, crisis management, regulatory and industry sanctions related to governmental procedures, a class-action lawsuit, and opportunity cost.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Crisis Management Cost**} \\ \hline
**Data** & \multicolumn{2}{c}{**Significant Factors**} & \multicolumn{2}{c}{**Options with Breach Cost and Probability Values**} \\ \hline
\begin{tabular}{c} \\  
The total security cost is made up of two parts: the total direct cost of a data breach and the cost of security maintenance and upgrades, which would be required even if the breach had not occurred. These two costs participate in an organization's expected annual security cost (3) in the event of a security data breach. Expected annual security cost (ESC) is the addition of annual expected cost due to breaches (EB) and cost regardless of any breaches (RB).  
\[\text{ESC }=\text{ EB}+\text{RB} \tag{3}\]  
The overall risk evaluation model, as in Figure 4 allows us to analyze the cost of the data breach through the available data. Many risks influence the costs of a data breach, including various types of security technologies and practices.  
Figure 4: Overall risk evaluation model (Data breach cost and probability).  
The expected annual cost of potential data breaches is determined by the probability of a particular type of data breach (4). Therefore, if there are n types of data, EB is the multiplication of the likelihood of data breach type (P\({}_{i}\)) and the total cost per breach for type (A\({}_{i}\)).  
\[\text{EB}=\sum_{i=1}^{n}\text{P}_{i}\text{A}_{i} \tag{4}\]  
The expected costs due to the breach could cover the past data breach that occurred or the data breach that could occur in the future. For the past breach, the data breach probability is 1, and the actual cost of a data breach is computed normally. However, for future data breach, the data breach probability is less than 1.
# SVM-Based Sea Ice Extent Retrieval Using Multisource Scatterometer Measurements
## 3 Characteristic Parameters for Sea Ice Monitoring
For example, on a calm seawater surface, \(\sigma^{0}_{VV}\) is larger than \(\sigma^{0}_{HH}\). For rough surface dielectric layers with randomly oriented scatterers such as ice or snow, multiple reflections of the incident radiation tend to depolarize it. Therefore, \(\sigma^{0}_{VV}\) and \(\sigma^{0}_{HH}\) are closer. As shown in Figure 2e, \(PR\) is usually higher over sea ice than that over sea water. However, the increased surface roughness of sea water caused by high sea surface winds may lead to a higher \(PR\). Since the ASCAT and CSCAT scatterometers are able to measure the same pixel of the sea ice map at various incidence angles, the dependence of measurements on incidence angle can be represented by the slope (denoted as \(K_{VV}\)) of a linear fitting function. In general, the backscattering amplitude of sea water decreases more rapidly with increasing incidence angle than that of sea ice [13]. This is in line with the plots shown in Figure 2f, i.e., most slope values are negative, and the slopes of sea water are relatively steeper than those of sea ice. In this study, we propose a new parameter named band ratio (\(BR\)). \(BR\) is defined as the ratio of vertically polarized backscatter measurements from the Ku-band to that from C-band. More specifically, \(BR\) is the ratio of the CSCAT \(\sigma^{0}_{VV}\) measurement to the ASCAT  
Figure 2: Normalized distribution of the characteristic parameters over open seawater and ice in the Antarctic; the period over which statistics were obtained was from December 2019 to February 2020. **(a)**\(\sigma^{0}_{HH}\) (dB), **(b)**\(\sigma^{0}_{VV}\) (dB), **(c)** standard deviations of HH measurements, \(\Delta\sigma^{0}_{HH}\) (dB), **(d)** standard deviations of VV measurements, \(\Delta\sigma^{0}_{VV}\) (dB), **(e)** polarization ratio of backscatter measurements \(PR\), **(f)** backscatter dependence on incidence angle \(K_{VV}\), and **(g)** band ratio of VV backscatter measurements, \(BR\). \(\sigma_{VV}^{0}\) measurement. As shown in Figure 2g, the \(BR\) of open water is mostly larger than that of sea ice.
## 3 Conventional Frequency-Offset Estimation Method
### Conventional Scheme C  
A simple WMSE scheme is presented [26; 27; 28], which works robustly against the frequency selectivity of the channel. Assigning a different weight to each CP subcarrier and performing LS regression lead to:  
\[\hat{\varepsilon}=\frac{1}{2\pi\beta\sum_{k\in\mathcal{S}_{f}}|\tilde{H}_{l}( k)|^{2}}\sum_{k\in\mathcal{S}_{f}}|\tilde{H}_{l}(k)|^{2}\angle Y_{l}(k) \tag{18}\]  
and:  
\[\hat{\xi}=\frac{1}{2\pi\beta\sum_{k\in\mathcal{S}_{f}}k^{2}|\tilde{H}_{l}(k)| ^{2}}\sum_{k\in\mathcal{S}_{f}}k|\tilde{H}_{l}(k)|^{2}\angle Y_{l}(k) \tag{19}\]  
where \(|\tilde{H}_{l}(k)|^{2}\) is the weight that is involved to compensate for frequency-selective fading on the different subcarriers. Note that this scheme depends on some information about the channel statistics \(|\tilde{H}_{l}(k)|^{2}\).
# Recent Progress and Challenges Regarding Magnetic-Based Nanoparticles for Targeted Drug Delivery
## 4 Multifunctional Magnetite-Based Nanomaterials
PEGylated poly(lactic-_co_-glycolic acid) microcapsules were used to load DOX and Prussian blue photothermal agent. The core-shell structure demonstrated excellent photothermal conversion properties, which resulted in much higher tumor inhibition efficiency, but also was capable of simultaneous enhancement in ultrasound imaging (USI), photoacoustic tomography (PAT), and MR imaging. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Components of Magnetite-Based Delivery System** & **Application in Cancer Therapy * &
\begin{tabular}{c} **Loaded Drug/Targeted** \\ **Cancer** \\ \end{tabular} & **Reference** \\ \hline Tragacanth gum, poly acrylic acid, & HT & DOX/breast & [98] \\ cystamine, FA & & & \\ \hline \(\beta\)-cyclodextrintrin, poly(2-ethyl-2-oxazoline) & HT & DOX/breast & [99] \\ \hline Poly (lactic-_co_-glycolic acid), alginate & MHT & DOX/lung & [100] \\ \hline Graphene oxide, maltodextrin, FA & PTT & DOX/liver & [101] \\ \hline Carbon, ZnO, FA & PTT & DOX/liver & [102] \\ \hline Hydroxypropyl cellulose, carboxymethyl chitosan, black phosphorus & PTT & ART/liver & [103] \\ \hline Graphene oxide, \(\beta\)-cyclodextrintrin, cholic acid, & PTT & CPT/liver & [104] \\ \hline Graphene oxide, hydroxyphenyl cellulose & PTT & PTX/breast & [105] \\ \hline liposome & PTT & BFL/breast & [106] \\ \hline Gelatin, CuS, FA & PTT & CUR/breast & [107] \\ \hline Poly(ethylene)glycol-poly(\(\beta\)-amino esters), & & & \\ dipalmitoyl phosphatidylcholine & & MHT, PTT & DOX/breast & [108] \\ \hline Poly(\(N\)-isopropylacrylamide-acrylic acid-(ethylene glycol) methacrylate), hereeptin & & & \\ \hline Carbon quantum dots & MRI & DOX/breast & [110] \\ \hline Poly(glycidyl methacrylate-polyethylene glycol), salep dialdehyde & & & \\ \hline \(\beta\)-cyclodextrintrin, Pep42 & MRI & DOX/breast & [112] \\ \hline Poly (\(\epsilon\)-caprolactone), chitosan & MRI & GEM/breast & [113] \\ \hline Polyvinylpyrrolidone & MRI, MHT & DOX/osteosarcoma & [114] \\ \hline _Punica ggnatum_ fruit peel extract & MRI, MHT & 5-FU/colorectal & [115] \\ \hline Gold nanoparticles & MRI, PTT & DOX/cerical & [116] \\ \hline Polyethylene glycol, poly(lactic-_co_-glycolic acid), Prussian blue & MRI, PAT, USI, PTT & DOX/osteosarcoma & [117] \\ \hline \hline \end{tabular}  
* Each drug delivery system demonstrates potential application in chemotherapy.  
\end{table} 
Table 5: Multifunctional magnetite-based nanosystems for potential application in the treatment of different cancers.
# Research Progress of Polysaccharide-Gold Nanocomplexes in Drug Delivery
## 3 Preparation of polysaccharide Gold Nanoparticles
AuNRs are rod-like gold nanomaterials that are commonly utilized in light-induced photothermal (photodynamic) therapy [80], gold nanocages, characterized by hollow interiors and porous walls, are considered more preferable drug delivery vehicles [81]; gold nanostars possess three distinct surface curvatures, making them exceptionally valuable for biological sensing, imaging, and localized chemical manipulations [82], gold nanoclters, are ultra small in size (typically less than 3 nm in diameter) and possess unique fluorescent properties. These nanoclters exhibit remarkable tumor accumulation and efficient renal clearance properties, rendering them agile probes for in vivo imaging [83]. The longitudinal surface plasmon resonance (LSPR) peaks of AuNR nanorods are absorbed in the NIR region, causing them to produce NIR light-induced photothermal effects that kill tumor cells and thus are used for tumor PTT [84; 85]. However, such nanomaterials are less stable under physiological conditions and tend to aggregate and form precipitates. Isolation and purification of homogeneous polysaccharide BCP50-2 from _Belamcanada chinensis_ (L.) DC can be used to stabilize gold AuNRs and prepare  
Figure 4: Green synthesis method for gold nanoscale. (**A**): CAO-reduced Au3+ ions and capped AuNPs. Reproduced with permission from Ref. [74]. (**B**): Mushroom \(\beta\)-glucan-modified AuNRs under NIR for photothermal therapy of cancer. Reproduced with permission from Ref. [75]. Copyright 2017, American Chemical Society. (**C**): Tea-assisted synthesis of gold nanoflowers. Reproduced with permission from Ref. [76]. Copyright 2022, Tsinghua University Press. to generate polysaccharide-AuNPs with good stability and high efficiency of photothermal conversion, which is an excellent guide for tumor therapy and has a better prospect of application in the treatment of hepatocellular carcinoma [86]. Gold nanoparticles (AuNPs) have unique properties that make them potentially useful for biomedical applications, including drug delivery, imaging, and therapy. However, there are several reasons why AuNPs are not yet widely used in clinical applications. First, there is the issue of safety; while AuNPs are generally considered biocompatible, their long-term effects on human health and their potential to accumulate in the body have yet to be thoroughly investigated. Secondly, the lack of standardized production does not ensure that the gold nanoparticles produced have consistent particle sizes, surface properties, etc. Again, there is limited understanding of its distribution, metabolism, and clearance in the body. Finally, there is the challenge of scaling up the production of AuNPs. Although the technology for small-scale synthesis of AuNPs has matured, there are still a number of technical challenges that need to be resolved in order to scale up the production to meet the needs of clinical use.
# An Artificial Neural Network Autoencoder for Insider Cyber Security Threat Detection
## 1 Introduction
### Security Information and Event Management Attack  
Although organizations integrate the different SIEMs in their security measures, business organizations are mostly affected by insider cyberattacks. In practice, an SIEM system has the role of a security management tool that gathers all data from network interfaces, servers, domain controllers, and other assets present in an organization [5]. The SIEM system workflow is related to logging, correlation and analysis, incident monitoring, sending alerts, and compiling and reporting. The main use cases of SIEM are basic security monitoring, advanced threat detection, log collection, security incident detection, and follow-up alerts.  
Today's attackers have developed sophisticated techniques and tactics, which are more difficult for SIEM tools to detect. As a result, SIEM shows the following limitations:  
* Due to centralized logging, when an insider threat is detected and alerted, security analysts cannot find out how and where to start an intruder search. Meanwhile, the attack goes deep into the network before being detected, and incident forensics are ineffective.
* The SIEM tools protect against most external threats, and they are defenseless against insider threats.
* The SIEM tools generally are not accurate for a particular security threat event. Mostly, they fail to detect the actual occurrence of an event.
* The SIEM tools are difficult to control and manage.
* Predefined correlation rules make the SIEM system unable to detect new attack techniques.  
To address these limitations of SIEM tools, different approaches for improving organizations' cyber security have been proposed, and they can be classified as approaches based on user behavior analysis (UBA) or on user and entity behavior analysis (UEBA).
# Evolution of V2X Communication and Integration of Blockchain for Security Enhancements
## 5 Issues and Challenges in 5G and Edge-Based V2X
### Wireless Resource Management  
When incorporating new technologies, such as MEC into 5G V2X, resource allocation strategies tend to be systematic. For instance, to facilitate high-speed transmission of data, two neighbor vehicles may use D2D communication mode to communicate directly with each other. It increases spectral reuse, obtain hop gains and enhance network efficiency. However, D2D connectivity, typically leads to interference in C-V2X induced by the re-use of the bandwidth of the cellular user. Several methods for maximizing the spectrum use have been developed in various settings in order to solve this issue [48]. In the 5G-based MEC, edge computing with fast processing and low latency plays a major role in enhancing the efficiency of vehicle services. The distribution of resources for edge computing is of great significance for increasing QoS and system robustness.
# Impacts of Arc Length and ECOM Solar Radiation Pressure Models on BDS-3 Orbit Prediction
## 2 Orbit Prediction Method and Data Collection  
### Orbit Prediction Method  
Satellite orbit prediction accuracy relies on the satellite's initial conditions and solar radiation pressure parameters. Hence, in the following paragraph, we will indicate the solution of the satellite's initial conditions and solar radiation pressure parameters over an arc period using the least-squares method.  
Let the position, velocity, and dynamic parameters of the satellite at the initial time \(t_{0}\) be \(\left(r_{0},\dot{r}_{0},p_{0}\right)\). By considering the influence of various perturbation forces, the position and velocity \(\left(r,\dot{r}\right)\) of the satellite at epoch \(t\) can be obtained by integrating the satellite dynamics equation. We can predict the satellite orbit at the epoch \(t\) as follows:  
\[\left(r,\dot{r}\right)=F\left(t,r_{0},\dot{r}_{0},p_{0}\right) \tag{1}\]  
where \(F\) is the nonlinear integral function. The observation equation can be described by Equation (2):  
\[r_{t}-r=\Phi(t,t_{0})\left[\Delta r_{0}\quad\Delta\dot{r}_{0}\quad\Delta p_{0 }\right]^{T} \tag{2}\]  
where \(\Phi(t,t_{0})=\left[\frac{\partial r}{\partial r_{0}}\quad\frac{\partial r} {\partial r_{0}}\quad\frac{\partial r}{\partial p_{0}}\right]\) is the state transition matrix; \(\Delta r_{0},\Delta\dot{r}_{0},\Delta p_{0}\) denote the correction value of the initial position, velocity, and dynamic parameters, respectively.  
Assuming that the satellite position at the epoch \(t_{i}\) in the precise ephemeris is \(r_{i}\) during an arc length \([t_{i},t_{m}]\), the m-dimensional observation equation can then be constructed as follows:  
\[Y=\theta\big{(}\Delta r_{0},\Delta\dot{r}_{0},\Delta p_{0}\big{)} \tag{3}\]  
where the following is the case.  
\[Y=\begin{bmatrix}r_{t_{1}}-r_{1}\\ r_{t_{2}}-r_{2}\\ \vdots\\ r_{t_{m}}-r_{m}\end{bmatrix}\]  
\[\theta\big{(}\Delta r_{0},\Delta\dot{r}_{0},\Delta p_{0}\big{)}=\begin{bmatrix} \theta_{1}\big{(}\Delta r_{0},\dot{\Delta r}_{0},\Delta p_{0}\big{)}\\ \theta_{2}\big{(}\Delta r_{0},\dot{\Delta r}_{0},\Delta p_{0}\big{)}\\ \vdots\\ \theta_{m}\big{(}\Delta r_{0},\dot{\Delta r}_{0},\Delta p_{0}\big{)}\end{bmatrix} =\begin{bmatrix}\Phi(t_{1},t_{0})\big{[}\Delta r_{0}\quad\Delta\dot{r}_{0} \quad\Delta p_{0}\big{]}^{T}\\ \Phi(t_{2},t_{0})\big{[}\Delta r_{0}\quad\Delta\dot{r}_{0}\quad\Delta p_{0} \big{]}^{T}\\ \vdots\\ \Phi(t_{m},t_{0})\big{[}\Delta r_{0}\quad\Delta\dot{r}_{0}\quad\Delta p_{0} \big{]}^{T}\end{bmatrix}\]  
The satellite's position, velocity, and dynamic parameters at the initial epoch \(t_{0}\) can be calculated by applying least-squares estimations in Equation (3). Finally, the predicted orbits are generated through orbit integration using precise satellite initial conditions.
# Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads
## 4 Results: Optimal Power Flow Solution Considering Heuristic and Analytical Algorithms
### Nine-Node IEEE System  
#### 4.1.1 Nine-Node IEEE System Description  
The nine-node system is shown in Figure 4:  
For the case of the nine-node system in the metaheuristic algorithms, five continuous decision variables are used, corresponding to the value of the voltage at the slack node and the active and reactive powers of the other generators different to the slack.
## 4 Conclusions  
The optimal pH tested for IPA adsorption was 7.0. This was very close to the point of zero charge of the activated carbon (6.7), which suggests that hydrogen-bonding between the hydroxyl group on the IPA molecule and the oxygen groups on the surface of activated carbon was a key part in the adsorption mechanism of IPA on activated carbon. A higher ultrasonic intensity led to more IPA being desorbed but also led to greater attrition of the activated carbon, with the optimum intensity at 24.5 W/cm\({}^{2}\). The regeneration efficiency increased with temperature up to 45 \({}^{\circ}\)C, which was not exceeded in order to protect the ultrasonic probe. Addition of 10% wt. ethanol improved the regeneration efficiency of IPA-saturated activated carbon, but a higher ethanol concentration decreased IPA desorption. Surface morphology of regenerated activated carbon was observed to be similar between these cycles, but surface area and total pore volume decreased. The optimum operating parameters in this study were an ultrasonic intensity of 24.5 W/cm\({}^{2}\), a solution temperature of 45 \({}^{\circ}\)C and an ethanol concentration of 10% (_v_/_v_), which led to a regeneration efficiency of 83%. This regeneration efficiency dropped to 81%, 71% and 64% after two, three, and four regeneration cycles. Conclusively, ultrasonic regeneration of IPA-saturated activated carbon was demonstrated to be feasible with regeneration efficiency comparable to current technology.  
Conceptualization, Y.K. and H.-Y.H.; methodology, Y.K.; validation, Y.K. and N.M.M.; investigation, H.-Y.H., N.M.M., Y.K. and H.-Y.L.; resources, Y.K.; data curation, H.-Y.H. and Y.K.; writing--original draft preparation, H.-Y.H. and N.M.M.; writing--review and editing, Y.K., H.-Y.L. and N.M.M.; visualization, H.-Y.H. and N.M.M.; supervision, Y.K.; project administration, Y.K. and H.-Y.L.; funding acquisition, Y.K. All authors have read and agreed to the published version of the manuscript.  
This research was supported by Grant MOST 108-2218-E-011-005- from the Taiwan Ministry of Science and Technology.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Data Analysis  
STATA (Intercooled Stata(r) Version 14; StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX, USA) was used to analyze descriptive and inferential data. We used complete case analysis to identify the participants with missing data during analysis. Descriptive statistics were computed and the results are presented as means \(\pm\) standard deviation (SD). A chi-squared test was used to compare variables by gender and blood pressure status, and the results are presented as frequency (n) and percentage (%). To investigate and compare the ability of obesity indicators to predict overall hypertension and either increased SBP or increased DBP, we used receiver operating characteristic curves (ROC). The area under the ROC curve (AUC) was used to assess a certain indicator's potential to predict overall hypertension and either increased SBP or increased DBP. The closer the AUC is to 1, the better the model, and the closer it is to 0.5, the poorer the model. Multivariate logistic regression analysis used dichotomous data to determine the relationship of hypertension with overweight/obesity indicators by gender and adjusted odds ratios (AOR) for age, smoking, alcohol, marital status, education, old age grant and family history of hypertension. The study adjusted for confounders by entering them as covariates in the model. A probability of \(p<0.05\) was considered significant.