esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Methodology
#### 2.4.1 Selection of Spatial Quality Indicators for Streets  
In this study, the concept of \"street space quality\" pertains to the capacity of urban street environments to meet the needs of residents concerning both \"quality\" and \"quantity\", as well as the extent of individuals' recognition of these spaces [33]. The material composition and environmental characteristics of street space serve as the foundation for human activities, with individuals acting as both creators and users of these environments. The extent of individuals' perception of the space reflects their subjective understanding of street environments, influencing their willingness to visit or utilize these spaces [34]. This paper aims to investigate street space quality at an urban scale; consequently, accessible and quantifiable influencing factors are identified to facilitate a scientific and effective interpretation of street space quality. Individual micro-level factors, as well as aspects of street management and maintenance, will not be examined in detail within this paper.  
Drawing from relevant urban design theories and studies on spatial quality, this review synthesizes key design-related elements associated with street quality as proposed by both domestic and international scholars(see Table 2), ultimately establishing practical indicators for measuring spatial quality [35].  
\begin{table}
\begin{tabular}{c c c} \hline
**Model** & **Time** & **Mean Intersection Ratio (mIOU)** \\ \hline Fully Convolutional Networks & 2014 & 62.2 \\ (FCNs) & 2015 & 71.3 \\ Dilated Convolution & 2016 & 78.85 \\ SegNet & 2016 & 78.15 \\ PSPNet & 2016 & 78.15 \\ DeepLabV3+ & 2018 & 86.9 \\ U2 Net & 2020 & 82.2 \\ Segformer & 2021 & 79.43 \\ SegNeXt & 2022 & 82.98 \\ \hline \end{tabular}
\end{table}
Table 1: Semantic segmentation model performance comparison.  
Figure 2: Composition of DeepLabV3 algorithmic framework.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Scholars** & **Street Physical Space** & **Subjective Perception** \\ \hline [PERSON] [36] & Small-scale neighborhoods, diverse functions, continuous & Sense of security, interactivity \\  & pedestrian spaces & Sense of security, communicativeness, \\  & Appropriate scale, detailing, clear boundaries, varied elevations, & Sense of security, communicativeness, \\  & spaces to stay, appropriate microclimatic environments & pleasure \\  & & Sense of security, attractiveness, \\  & &  obstacles \\
# Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health
## 4 Ethical Considerations
### Non-Maleficence: Privacy, Security and \"Capability Caution\"
#### 4.2.1 Data Sharing  
The quality and completeness of the data on which the WHO relies depends on the capacity of its member states for surveillance and their willingness to share surveillance data. As the COVID-19 pandemic progressed, member states were asked by the WHO to submit detailed case data via line lists on more than 80 variables, the vast majority of which were incompletely reported [17]. This recent pandemic, in particular, has highlighted significant challenges in sharing, storing, and linking data from public, private, and quasi-public sectors, as well as between, across, and outside jurisdictions. Depending on the nature of the data, there may also be restrictions on linking or sharing outside of the geographical source of that data [19]. In the context of new technology and innovation, it is becoming increasingly important for people to share their data, so that disease prevention advances can be more impactful. For example, the sharing of SARS-CoV-2 genetic sequences has allowed scientists to track bio evolution and variants [37; 67].
###### Abstract  
From August to October 2018, a series of strong earthquake (EQ) events occurred in southeast Asia and northern Oceania (\(22^{\circ}\)S to \(0^{\circ}\)N, \(115^{\circ}\)E to \(170^{\circ}\)E) within 50 days. In this paper, we analyze the features of ionospheric plasma perturbations, recorded by the Plasma Analyzer Package (PAP) and Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES-01), before four EQs with magnitudes of Ms 6.9 to Ms 7.4. The ion parameters such as the oxygen ion density (\(No^{+}\)), the ion drift velocity in the vertical direction (\(V_{z}\)) under the conditions of geomagnetic storms, and strong EQs are compared. The results show that within 1 to 15 days before the strong EQs, the \(No^{+}\) and the electron density (\(No\)) increased while the electron temperature (\(Te\)) decreased synchronously. Meanwhile, the \(V_{z}\) significantly increased along the ground-to-space direction. The relative variation of \(No^{+}\) and \(V_{z}\) before the strong EQs is more prominent, and the \(V_{z}\) is not easily influenced by the geomagnetic storm but is susceptible to the seismic activities. Our results suggest that the anomaly of ionospheric plasma perturbations occurring in this area is possibly related to the pre-EQ signatures.  
CSES; ionospheric disturbance; plasma; earthquake precursor; ion density; ion drift velocity
## 5 Results and Discussion
### Comparative Analysis of the CVROSS  
To verify the performance of the proposed system, a comparison of before and after the use of the CVROSS was made, considering three aspects: (i) severity of traffic congestion, (ii) energy savings  
Figure 19: Accuracy comparison for parking-gap measurement.  
Figure 20: Accuracy comparison for estimation of time of stay.  
of vehicles and (iii) driver satisfaction. The results were obtained by interviewing 50 drivers and 10 representatives of property management companies in the selected areas. These were selected because they were frequent users of Shing Yip Street and Hing Yip Street and had considerable management responsibility. Table 2 shows the findings from the interviews with property management company representatives and individual drivers. In summary, the effects obtained by implementing the proposed system appear to be positive. According to property management companies, the severity of traffic congestion on specific roads and incidences of double-parking were reduced by 41.2% and 33% respectively. Moreover, companies can save on the labour force costs of controlling the busy roadside situation, reducing numbers of workers from 10 per shift to six per shift. Monitoring and control of roadside situations can be conducted in the back office, and real-time traffic information can be provided to truckers and drivers via the proposed system. Drivers and truckers commonly agreed that average fuel consumption was reduced, and that the average time to locate suitable parking spaces could be decreased by 51.6%, as they were able to go to specific parking areas after receiving information from the proposed system. In addition, truckers and drivers were generally satisfied with the proposed system, as it could improve the poor situation regarding double-parking and traffic congestion in busy districts.
# State-of-All-the-Art and Prospective Hydrogel-Based Transdermal Drug Delivery Systems
## 3 Fundamentals of Hydrogels  
Hydrogels are known to be the first biomaterials developed for human use [18; 19]. The first hydrogels were developed in 1960 using polyhydroxy ethyl-methacrylate (pHEMA) [20]. They were employed as fillers after eye enucleation [19]. Since then, hydrogels have been exploited for drug delivery and bioactive compound releases. One such important application of hydrogel polymer is modern contact lenses. In recent years, hydrogels have evolved into various forms, including smart hydrogels, shape memory hydrogels, injectable hydrogels, polymer hydrogel scaffolds, supramolecular hydrogels, self-healing hydrogels, actuators, and injectable hydrogels [7]. These find extensive applications in tissue engineering, targeted drug delivery, bone regeneration, surgical devices, gene therapy, vaccines, immunotherapy, corneal treatment, sensors for cancer therapy, absorbable bone plates, and wound healing [7].  
Hydrogels are substances consisting of interconnected three-dimensional networks of hydrophilic polymers that are physically or chemically crosslinked [11]. Hydroxy groups like carboxyl (R-COOH), hydroxyl (O.H'), and amino (-NH\({}_{2}\)) groups form the hydrophilic polymers. They are interlinked in an aqueous medium. Hydrogels exhibit properties like swelling, collapse, softness, biocompatibility, and biodegradability [21]. Due to these properties, hydrogels closely resemble natural tissues. The presence of hydrophilic polymers enables this material to store and retain water content while remaining undissolved. They also possess attractive properties like sensitivity to pH, temperature, and other external stimuli [22]. These properties play a wide role in many hydrogel-based applications like wound healing, drug delivery, and tissue engineering. The broadening applications of hydrogels call for intricate control over aspects like their mechanical properties, the spatiotemporal distribution of active substances, and the refinement of their shape, structure, and overall architecture using advanced engineering techniques [23]. Advances in technology have paved the way for the development of functional hydrogels with enhanced physicochemical characteristics [23]. Key improvements in hydrogel technology involve fine-tuning their mechanical traits to make them responsive, self-repairing, and capable of shear-thinning. Furthermore, modifying the shape, structure, and architecture of hydrogels enhances their spatial precision and control [23].
# Design and Implementation of a Passive Optical Network for a Small Town +
## 4 Results
Signal distribution is handled by a 1\(\times\)32 optical splitter beyond the RE, allowing fiber access to remote housing clusters without deploying an OLT in the field. In the network design, the distribution cables in a given area are designed in a mixed topology model and star type, and the rays can be branched. In this structure, the star center for the distribution cables is the aggregation point, from which the radial routes emerge in different directions. The distribution of users is categorized according to the types of buildings that are served. Single-family homes (FH) include houses and small housing cooperatives with up to four households, while multi-tenant buildings (MT) include residential units with five or more households [23; 24; 25; 26; 27; 28]. **- DETAIL -**  
**Fiber exit from manhole to low voltage pole**  
Figure 6: Detail of fiber exit from manhole to low voltage pole for a PON on a pole. In the design of the network and the determination of the number of fibers required, this classification is useful for determining the types of splitters and the capacity of the connecting cabinets. This leads to resource optimization and ensures the resilience of the network.
## 3 Results and Discussion
### Development of Autogenous Shrinkage, Internal Relative Humidity, and Internal Temperature  
#### 3.2.1 Autogenous Shrinkage  
The modified deformation measurement set-up was used to investigate the autogenous shrinkage (AS), internal temperature (IT), and internal relative humidity (IRH) of the three groups' specimens for up to 7 days. nS0 was used to define specimens without nano-silica, and nS2 and nS4 were used to define specimens containing 2 wt.% and 4 wt.% nano-silica in cement.  
Figure 4 shows the effect of nS on the development of AS in UHSC. Firstly, the shrinkage rate of all specimens increased from the test start time (final setting time) for 2 days. Secondly, after 2 days, the autogenous shrinkage of nS0 developed very slowly, while that of nS2 and nS4 continued. Although the shrinkage speed of nS2 and nS4 reduced at an early age, it continued to occur. Finally, until 7 days, the autogenous shrinkage strains of nS0, nS2, and nS4 were \(-\)738.96, \(-\)879.04, and \(-\)1002.16 \(\upmu\)m/m, respectively. The total shrinkage increased as the nS content increased (in all specimens). The reason for this behavior was the initiation of the pozzolanic reaction, in which nano-silica reacts with Ca(OH)\({}_{2}\) to produce more compact and dense C-S-H gel, which leads to a reduction of capillary pores and a refinement of the pore structure of UHSC, resulting in the promotion of high shrinkage [12; 16].  
The experimental data measured by LVDT show that all three specimens underwent expansion at the beginning (1.2-6.7 h). Expansion and shrinkage were joint occurrences. All small positive peaks are expansions. Expansion occurred due to a combination of the formation of AFm, the internal variable temperature, and water absorption by hydration productions. The main reason for the shrinkage was that binder hydration consumed some of the water and IRH decreased, resulting in self-drying. Macro-phenomena lead to expansion when the factor where the expansion occurs dominates; otherwise, macro-phenomena lead to shrinkage when the factor where the shrinkage occurs dominates [35; 36]. Moreover, the expansion of nS2 was more pronounced compared to nS0. However, the expansion of nS4 did not show up more noticeably as the amount of nS increased.  
Figure 4: Autogenous shrinkages of UHSCs cast for 7 days.
## 2 The Principle and Element Design of the CPFRA  
### The Principle of the Proposed CPFRA  
Figure 1 shows the architecture of the proposed CPFRA, which is composed of three parts: a linearly polarized feed radiator, a primary reflector surface, and a sub-reflector surface. Here, the \(u\)-direction indicates the direction within the \(xoy\) plane that forms a \(-45^{\circ}\) angle with the positive direction of the \(x\)-axis, and the \(v\)-direction indicates the direction within the \(xoy\) plane that forms a \(45^{\circ}\) angle with the positive direction of the \(x\)-axis.  
The working principle of this antenna is as follows: When the EWs along the \(u\)-polarization direction from the feed radiator are incident on the bottom of the sub-reflector surface, they are reflected back and incident on the primary reflector surface. The elements on the primary reflector surface receive the EWs polarized along the \(u\)-polarization direction and perform phase compensation and polarization rotation by 90\({}^{\circ}\). Then, the modulated EWs polarized along the \(v\)-polarization direction are incident on the primary reflector surface again. At this time, the element based on the transmissive linear-to-circular polarization converter on the sub-reflector surface can pass through the EWs polarized along the \(v\)-polarization direction and convert them into CP EWs for radiation. To summarize, the requirements for each part of the antenna are as follows in this architecture: For the primary reflector surface, the functions of phase compensation and polarization rotation are required. For the sub-reflector surface, the functions of reflecting EWs polarized in the \(u\)-axis direction, transmitting EWs polarized in the \(v\)-axis direction, and converting EWs polarized in the \(v\)-axis direction into circularly polarized EWs are required. A 3D diagram of the final design for the folded reflectarray antenna is shown in Figure 2.
# A 3D Estimation Method Using an Omnidirectional Camera and a Spherical Mirror
## 5 3D Estimation of Observation Scene  
### Lightpass Estimation to the Object Reflected in Mirror Image  
Figure 6 shows an overview of the 3D estimation in the observation scene. Here, the reflection point \(\mathbf{X_{s}}\) on the spherical mirror and the direction \(\mathbf{v_{i}}\) of incident rays from the object to the reflection point on the spherical mirror are obtained by Backward Projection. The equations for the sphere and the reflection point are given by Equations (9) and (10), where \(d_{s}\) is the distance from the camera to the reflection point. The reflected ray \(\mathbf{v_{r}}\) from  
Figure 5: The shape of a spherical mirror that allows for the estimation of its 3D position. When the radius of the 3D circle is unknown: On the **left** and in the **middle**, tangent lines can be drawn, allowing for estimation of the mirror’s position. On the **right**, tangent lines cannot possibly be drawn, making estimation impossible.  
the spherical mirror to the omnidirectional camera is normalized, and solving for \(d_{s}\) in Equations (9)-(11) can be carried out.  
\[\|\mathbf{X_{s}}-\mathbf{C_{s}}\|^{2}=R^{2} \tag{9}\] \[\mathbf{X_{s}}=d_{s}\mathbf{v_{r}}\] (10) \[d_{s}=\mathbf{v_{r}}^{T}\mathbf{C_{s}}\pm\sqrt{(\mathbf{v_{r}}^{T}\mathbf{C_{s}})^ {2}-(\|\mathbf{C_{s}}\|^{2}-R^{2})} \tag{11}\]  
After substituting \(d_{s}\) into Equation (10), \(\mathbf{X_{s}}\) is derived. Because the incident angle \(\theta_{i}\) and the reflection angle \(\theta_{r}\) are equal with respect to the normal \(\mathbf{N_{s}}(\|\mathbf{N_{s}}\|=\mathbf{N_{s}}^{T}\mathbf{N_{s}}=R^{2})\) at the reflection point \(\mathbf{X_{s}}\) on the mirror surface, the direction of the incident ray \(\mathbf{v_{i}}\) from an object to the reflection point on the spherical mirror is determined by Equation (12).  
\[\mathbf{v_{i}}=\mathbf{v_{r}}-\frac{2\mathbf{v_{r}}^{T}\mathbf{N_{s}}}{\mathbf{N_{s}}^{T}\mathbf{N_{s} }}\mathbf{N_{s}}=\mathbf{v_{r}}-\frac{2\mathbf{v_{r}}^{T}\mathbf{N_{s}}}{R^{2}}\mathbf{N_{s}} \tag{12}\]
## 5 Conclusions and Outlook  
We showed that radar information along the x-axis can improve EIT reconstructions up to a certain point. The resolution increases along the x-axis; this can be seen especially in Figure 9, as the two targets are better distinguishable. This is due to the fact that the EIT data need to be truncated in the _ka_-space, while the radar data are less noisy. Thus, the added information in the _k_-space introduces more high-frequency components into the reconstruction, which leads to more detail in the resulting images.  
Adding too much radar information in this setting can result in a worse performance of the reconstruction algorithm. When trying to reconstruct a single object with conductivity higher than the background, an overestimation of the conductivity tends to be more forgiving than underestimating the conductivity.  
The shape of the truncation in the k-space needs to be investigated more in future work. Shapes other than a circle may lead to even better results, and may potentially be able to overcome some disadvantages when only additional information along the x-axis is used. However, it is not clear what this shape might look like, as the k-space representation has no humanly interpretable link to the real domain.  
An improvement of the shape correction term used for the DN-map may even further improve the results.  
A more sophisticated construction of the prior might also lead to better results; for this paper, however, we followed the steps for the EIT reconstruction as it is easier to follow and does not change the findings.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/a16010043/s1](https://www.mdpi.com/article/10.3390/a16010043/s1)]([https://www.mdpi.com/article/10.3390/a16010043/s1](https://www.mdpi.com/article/10.3390/a16010043/s1)).  
Conceptualization, J.R., J.M., and C.N.; methodology, J.R. and C.N.; software, J.R. and D.H.N.; validation, J.R., J.M., and C.N.; formal analysis, J.R. and D.H.N.; investigation, J.R. and S.L.; resources, S.L. and J.M.; data curation, J.M. and D.H.N.; writing--original draft preparation, J.R.; writing--review and editing, J.R. and C.N.; visualization, J.R.; supervision, C.N. and S.L.; project administration, S.L.; funding acquisition, J.M. and S.L. All authors have read and agreed to the published version of the manuscript.  
The authors gratefully acknowledge financial support provided by the project InDiThera (13 GW0361D, 13 GW0361E) through the Federal Ministry of Education and Research.  
Not applicable.  
The authors declare no conflict of interest.
# Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions
## 3 Online Investigations
### Data Mining
#### 3.3.2 Social Network Analysis  
Social network analysis is the use of technologies to learn about the network among criminal organizations and platforms. This method uses tools to scrape information about a criminal or terrorist organization and their connections from an online source [14]. The information for social network analysis is obtained from only one information source, text, but it is still one of the most helpful tools for open-source intelligence investigations.  
Investigators have various tools and methods they can use in analyzing social networks. One of the most useful method is scraping data from blog posts and forums that are known to have criminal activity. Another method used by investigators is mining data from graphical information, such as YouTube's social graph. This graph reveals connections between extremist videos and communities.  
In social network analysis, it can also be important to employ natural language processing techniques, such as emotion detection [16]. This can help investigators determine the relationship between individuals and groups, helping them know who is associated with the group and their activities.  
There are two main areas where social network analysis is used in investigations: terrorism/extremism cases and criminal organization cases [15]. Both of these crime types rely on the identification of organizations and attributing crimes to organizations. Because social network analysis is mainly used to determine the relationships between individuals and entities, it is well suited for these cases because they focus on the structure of the organizations being investigated.  
Social network analysis can be used in terrorism and extremism cases when analyzing the activity found on dark web forums of individuals involved in these organizations. This will give investigators the ability to know who is in these organizations, who the key people are, and potentially give them insight into the past and future activity of the organization [14]. A method applied to this area focuses on the process of online radicalization, searching forums based in various locations to determine who the recruiters of an organization are.  
When this method is applied to investigations into criminal organizations, the tools and methods are similar to those for terrorism and extremism cases. However, the sources of information are more likely to be news articles and other text-based pages. Investigators can search for terms, names, and geolocation data to learn about the social network that exists between criminals and criminal organizations.