esa-sceva/satcom-chunk-collection huggingface dataset:
# Enabling Role-Based Orchestration for Cloud Applications
## 3 TOSCA Model-Based Approach to Cloud Application Orchestration  
In this section, we start off by proposing an orchestration approach which is based on a TOSCA orchestration model and OAM application specification model [16]. As depicted in Figure 5, our approach permits platform builders to identify common configurable components and package them as platform capabilities with minimal configuration fields through an abstraction layer between underlying platform resources and applications at the top. Application builders, including application developers and operators, no longer directly manipulate underlying platform resources. Instead, they utilize platform capabilities to develop, test, and deliver their applications, as the capability layer shields the details of resource configurations and usages from them. Moreover, the capabilities are thought to belong to either of the two generic roles of application developers and operators. By establishing a set of capabilities as modeling constructs, our approach allows TOSCA-based application topology itself and its orchestration needs to be specified in a way to provide a more targeted support for different needs and concerns of application developers and operators. With support for features like application topology model, platform capability, and role-awareness for cloud application orchestration, our approach significantly reduces the complexity of application orchestration on cloud platforms.  
Our proposed approach can be realized by extending state-of-the-art technologies for cloud orchestration. As introduced in Section 2, TOSCA offers rich primitives and  
Figure 5: Role-based cloud application orchestration.  
extensible types but has no support for role-awareness and separation of concerns. Focused on a model specification for cloud applications, TOSCA remains neutral with regard to run-time implementations or how a TOSCA-conforming orchestration system may deploy orchestration manifests on cloud platforms. By contrast, OAM provides role-awareness support and an official runtime implementation based on Kubernetes. However, it lacks a comprehensive and robust meta-model to build an orchestration system, including interface, policy, and workflow definitions. In particular, without support for application topology definition, OAM hardly makes for a promising candidate technology for cloud orchestration models. Therefore, complementing each other's shortcomings for cloud application orchestration, a combination of TOSCA and OAM would provide a solid foundation on which to build up our model-driven, role-based cloud orchestration system.
# Upscaling Customer Access Network Using Spectrum Conversion-Slicing-Duplication Technique
## 2 Methodology  
For this study, the FTTH network that has been modified was implemented using Optisystem 18.0 software simulation, to enable us to see the final signal that reaches the users and determine whether the signal is good or not. Optisystem represents an optical communication system as a set of interconnected blocks. Each block is simulated independently using user-defined parameters for that block and signal information sent to it from other blocks. Through this software, we can gain experience of how to build the network, set the parameters, calculate the power and bandwidth and evaluate the eye diagram.
###### Abstract  
Researchers are concentrating on discovering reducing treatments for bacterial infections due to the worrisome and quick rise of drug-resistant microbial-related illnesses. Metallic ion doping and co-doping mesoporous bioactive glass (MBG) can defend against drug-resistant pathogens of _Escherichia coli_ (_E. coli_) infection of wounds and solve the issues of bone deformities. In this study, un-doped MBG, silver-doped MBG (Ag-doped MBG), cerium-doped MBG (Ce-doped MBG), and silver-cerium co-doped MBG (Ag-Ce co-doped MBG) have been successfully synthesized via the spray pyrolysis method. In addition, various characterization techniques, including X-ray diffraction, field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, and nitrogen adsorption-desorption, were used to investigate the phase compositions, surface morphologies, chemical compositions, inner structure morphologies, chemical bonds/functional groups, and specific surface areas, respectively. The antibacterial efficacy against _E. coli_ was assessed using the colony count technique. All types of MBG with Ag, Ce, and Ag-Ce were effective against _E. coli_. Furthermore, when immersed in simulated body fluid, the MBGs formed hydroxyapatite and could be used to improve bone defects. Only 5.75 mol% Ag-doped MBG showed toxicity in the MTT assay test. According to our analysis, the 80S-Ag-Ce-MBG was the first Ag-Ce co-doped MBG.  
silver; cerium; bioactive glass; spray pyrolysis Article
## 3 Results and Discussion
### Elemental Composition of Medicinal Plants
Thus, for medicinal plants from Jordan, the level of K was lower compared to the data recorded in the current study, being between 665 and 880 ppm [30], while other authors determined a potassium content similar to that reported in this study, being between 2450 and 14,991 ppm [26]. The calcium content varies between 2748.35 ppm, the minimum value recorded in OV, and 7575.43 ppm in LA. The previous analysis of the elemental composition of some medicinal plants revealed a calcium intake between 82 and 2223 ppm, with maximum values recorded in the case of the Lamiaceae family (1656 ppm for SO and 2223 ppm for OV) [30]. The magnesium content varies within tight limits (357.61-463.01 ppm), except for LA, for which a maximum value of 605.26 ppm is recorded. Magnesium content varies widely in medicinal plants from different geographical areas. A content between 1292 and 45,460 ppm has been reported in medicinal plants from Pakistan [26], while in samples from Spain, Bulgaria, and Egypt, the level of Mg was between 1616 and 6405 ppm [29]. No significant differences regarding the Mg content were recorded (\(p<0.05\)) between the pairs: Mp/HP/EP, TS/AM/OV, and MO/CO. Regarding the microelement composition of the plant matrices studied, it is noted that plants from the _Lamiaceae_ family (MP, SO, LA, OV, MO) are characterized by a high intake of iron, zinc, and EP copper. Maximum values of trace elements were recorded: for manganese in MP (46.1 ppm), for zinc in LA (35.71 ppm), for iron in TS (489 ppm), and for copper in HO (14.57 ppm). No significant differences regarding the Mn content (\(p<0.05\)) were recorded between the pairs: AM/OV/HO/LA/MO/HP, TS/SO1, and Zn content (MP/HP, TS/OV, SO1/CO, SO2/LA). Literature studies indicate an iron content between 89-853 ppm [29], 166.5-479.5 ppm [27], copper between 5.5-9.74 ppm [31] and 89-853 ppm [29], zinc between 23-68 ppm [29] and 3.3-5.12 ppm [27], respectively, and Mn between 46-2134 ppm [29]. The content of elements in plants is influenced by the preferential absorption of plants, the content of elements in the soil, its characteristics, and the culture technology.
# Improving Low-Frequency Panel Absorbers with Two-Dimensional Acoustic Black Hole
## 3 Simulation Results
### Position
#### 3.1.1 X-Axis  
The normalized mean surface velocity \(\overline{v}_{x,y}\) results from placing the ABH centered on the y-axis and moving it to different positions on the x-axis are shown in Figure 5 (P11, P21, P31). The blue dots at the top of the graph represent the first four modal frequencies of the reference panel \(f_{1,1}=84\,\mathrm{Hz}\), \(f_{2,1}=147\,\mathrm{Hz}\), \(f_{1,2}=192\,\mathrm{Hz}\) and \(f_{3,1}=250\,\mathrm{Hz}\). The dashed line represents the normalized mean surface velocity \(\overline{v}_{x,y}(f)\) of the reference panel without an ABH. Due to the symmetry of the mode shapes for \(f_{2,1}\) and \(f_{1,2}\), they do not appear on the frequency response. However, the mode shapes for \(f_{1,1}\) and \(f_{3,1}\) are unsymmetrical; therefore, they are visible in the plotted frequency response.  
It can be seen from the graph that the position of the ABH has much influence on the frequency response of the normalized mean surface velocity \(\overline{v}_{x,y}\). In general, the desired effect of increasing the surface velocity \(\overline{v}_{x,y}\) is achieved for all three positions. However, there are multiple effects introduced by the ABH. The first to mention is the increase in the frequency of the fundamental mode \(f_{1,1}\approx 85\,\mathrm{Hz}\) with a position further away from the center. Because the aim is low-frequency improvement, this effect is not desired. The second peak in \(\overline{v}_{x,y}(f)\) of the ABH panels is at the same frequency for all three configurations. This occurs due to a new modal frequency which is introduced by the ABH structure itself. The thin material inside the ABH is vibrating in the first circular mode; this frequency \(f_{\mathrm{ABH}}\approx 120\,\mathrm{Hz}\) is also known as the cut-on frequency. Therefore, it does not depend on the position and needs to be investigated separately. The changes seen at the second panel mode \(f_{2,1}\approx 150\,\mathrm{Hz}\) indicate the ability of the configuration to disturb the symmetry of the panel.  
Previous research [9] has found that breaking the panel symmetry can be beneficial for improving the sound absorption. This effect also determines the selection of the best configuration from those shown here. Taking the above arguments into account, position P21 is selected as the best choice of the configurations shown in Figure 5.  
Figure 4: Representations for the position of the ABH: (**a**) Sketch of 9 different positions for finding the best ABH placement. The dashed circle represents the contour of the ABH for position P11. (**b**) CAD rendering of ABH with radius \(a=0.13\,\mathrm{m}\) located at position P22.
# A Network-Based Model for Optimization of Container Location Assignment at Inland Terminals
## 2 Literature Review
### Container Allocation at Inland Terminals  
In contrast to this substantial exploration of container positioning and storage at seaports, few studies have examined the same questions at inland terminals. This may be partly due to the fact that, although the technological processes for positioning and storing containers are similar between inland terminals and container seaports, container layout and yard space at inland terminals are subject to specific constraints. For example, inland terminals are usually smaller than seaports, creating more severe space constraints on container storage. Most studies of inland terminals, rather than deal directly with these constraints, have focused on the most efficient ways to transport containers to such terminals. Dynamic programming and genetic algorithms have been used to route vehicles and optimize container delivery to inland terminals [31,50]. A system for accelerating container documentation and transport to its storage location has been developed [51], and a mathematical model has been proposed to allocate a group of containers at an inland terminal, after their delivery by rail, in a way that minimizes unproductive manipulations and overall storage costs [52]. A mathematical model for optimizing the configuration and operation of terminal equipment to improve the efficiency and sustainability of an inland waterway terminal has been implemented by the authors of [53]. The authors of [16] used a bilevel programming approach to address the problem of how to price storage for outbound containers.  
In order to overcome the disadvantages and \"blind spots\" of previous models, the present study was undertaken to develop a mathematical model to determine the inbound container assignment location according to empirically determined potentials and ranks of parameters (criteria) that affect the storage allocation of containers at inland terminals when the container's departure time is unknown. Relatively few studies have aimed to develop a single model that integrates all important parameters (criteria), including the container's dimensions, its occupancy, cargo type, container owner, and distance to the final user. These parameters are important for the terminal operator so that they can determine container locations in a way that minimizes unproductive manipulations.
## 3 Raman Laser Spectrometer
### Spectrometer  
The scattered light was collected using an achromatic doublet lens (f = 55.9 mm) AR-coated for 420-680 nm. The Rayleigh scattered light was filtered out using a pair of notch filters (attenuation at 532 nm: \(\times 10^{-12}\)). Another achromatic doublet lens (f = 80.6 mm) was used to reimage the scattered light at the input slit of the spectrometer. It had the same AR coating as for the collecting lens.  
The spectrometer was based on a Czerny-Turner scheme. A diffraction grating with 1800 grooves per mm with a blazing wavelength of 500 nm was used. Its spectral efficiency at 330-860 nm exceeded 40%. The linear dispersion of the system was 1.52 nm/mm and the spectral resolution (the instrumental linewidth, full width at half maximum (FWHM)) was 0.05 nm. The reproducibility of the wavelength setting was 0.03 nm. To find a compromise between the spectral resolution and the signal-to-noise (SNR) ratio, the width of the entrance slit was \(\sim\)20 \(\upmu\)m during the experiments. For detecting the spectra, we used a complementary metal-oxide-semiconductor (CMOS) camera (Hamamatsu) with a \(2048\times 122\) pixel\({}^{2}\) grid (pixel size: \(12\times 12\)\(\upmu\)m). It was cooled by a Peltier element to \(-40\)\({}^{\circ}\)C. The exposure time varied from 10 \(\upmu\)s up to 10 min. The projected spectral range was as long as 35 nm (0.017 nm per pixel). It was possible to shift this range within the interval 530-635 nm. More details can be found in [31].  
The wavelength grading was performed using an Hg-He arc-discharge spectral lamp (DRGS-12). The calibration of the Raman spectrometer was performed using a certified reference material of toluene with a known Raman spectrum [32]. The determined relative standard deviation (\(\Delta_{\rm rel}\)) between the measured and standard peak Raman shifts of toluene was \(<\)0.01% for the range of Raman shifts of 1000-3300 cm\({}^{-1}\) (for \(\lambda_{\rm exc}\) = 532.123 nm). The spectral resolution of the spectrometer was \(\sim\)1 cm\({}^{-1}\) (the instrumental linewidth, FWHM). The measurements were performed at room temperature (293 K).
## 3 Results and Discussion
### Scanning Electron Microscopy and Microanalysis (SEM-EDS)  
The surficial limestone appeared to be covered by a thin, darker layer with gray to black mottling, commonly discontinuous (Figure 5). The components (grains, crystals) that compose the surface layer include iron oxides, salts (sodium and calcium sulfates, sodium chloride) and carbonaceous particles, as well as organic components (biofilm, microorganisms). Salt crystals were also detected in more internal areas, in the porous system (Figure 5D), which contributes to the granular disintegration of the stone [6; 7; 8; 9].  
SEM-EDS analysis showed that the chemical composition of superficial layer is variable and includes (atom.%): O (66.3-64.93), C (11.64-17.44), S (1.38-5.42), Cl (0.16-0.26), Si (1.59-3.13), Al (0.61-0.92), Ca (5.56-8.63), Mg (1.17-1.53), Na (0.23), K (0.22-0.30), Ba (1.15-5.40), Fe (0.42-0.67) and Zn (0.14-0.41).  
These data point to the existence of silicates (clays), soot and sulfated minerals (gygsum, thenardite) in addition to the observed halite, which seem to indicate a strong impact  
Figure 5: SEM micrographs showing the limestone surface of the Cross of the Inquisition. (**A**) General view of limestone surface showing zones with preferential Fe-staining (mottling). (**B,C**) Detail of the high porosity (interparticle and intercrystalline pores) at the sample’s surface. (**D**) Detail of small idiomorphic halite (NaCl) crystals grown in interparticle porosity.  
due to environmental contamination from vehicle exhaust pipes. The effects of this contamination were described in the Cathedral of Seville, near the City Hall [10; 11; 12]. In some stone surfaces, a deep deterioration caused by biological colonization, with abundant pitting and channels produced by organisms, was observed (Figure 6).  
Indeed, Figure 6A shows the abundance of pitting in the limestone. Pitting is generally produced by cyanobacteria, algae and fungi, and has been widely described as a product of the dissolution of limestone caused by the biological activity of colonizing organisms [13; 14; 15]. The existence of pitting, without biological structures inside, as observed in Figure 6A, denotes that the colonization was ancient, and the organisms have disappeared.  
In addition to pitting, the dissolution of the limestone is produced by hyphae up to 3 microns in diameter, possibly from fungi, which are shown in Figure 6B, confirming that the colonization, in this case, was more recent.
## 1 Introduction  
During the last two centuries, the world population has been increasingly concentrating in urban areas. Today, around one half of all humans are living in cities, whereas the United Nations estimate that this figure will increase up to 75% by 2050. However, the current metropolitan growth model poses significant concerns in terms of environmental and economic sustainability [1]. Advances in a variety of technical fields offer the possibility to provide cities with _smart_ mechanisms in order to allow efficient resource management and improved life quality for the citizen. In view of this opportunity, substantial efforts from municipalities, government agencies, the industry, standards development organizations and academia are being devoted to enable the _Smart City_[2; 3; 4; 5; 6; 7; 8; 9; 10; 11].  
In the last few years, numerous definitions of the Smart City term have been given [2; 6; 12]. However, as acknowledged by several authors in recent works, since the Smart City concept itself is developing, and because it involves actors from a variety of domains, a formal and widely accepted definition of Smart City does not exist yet [2; 5; 13]. Nevertheless, a commonly recognized, and in our opinion the crucial Smart City enabler is the use of Information and Communication Technologies (ICT) \"to make the critical infrastructure components and services of a city more intelligent, interconnected, and efficient\" [14].  
Urban Automation Networks (UANs) are emerging as a central ICT component of the Smart City. UANs comprise fixed sensor (and/or actuator) nodes, backhauls and gateways that connect these nodes to core networks such as the Internet. Sensor nodes used in the Smart City are capable of detecting critical events and monitoring physical magnitudes relevant in the urban context. The collected information is transmitted to remote management centers where it can be processed and actions can be taken as a result, including the activation of urban actuators and publishing real-time or long-term information of interest to the citizen.  
For the first time to our knowledge, this paper tackles the design, performance and economic cost of UANs under a comprehensive approach by: (i) introducing the UAN requirements, concept and architecture; (ii) presenting the main current and emerging UAN classes; (iii) evaluating their suitability for Smart City applications; and (iv) providing guidelines for UAN design and/or choice. The remainder of the paper is organized as follows. Section 2 illustrates UAN use cases and requirements. Section 3 describes the UAN generic architecture. Section 4 overviews the five main current and emerging UAN classes, which are discussed and evaluated in Section 5. Section 6 discusses the relationship between UANs and emerging mobile data collection networking paradigms in the Smart City context. Section 7 reviews Smart City modeling related work. The final section concludes the paper.
## 3 Results and Discussion
### In Vitro Bioactivity Investigation  
SEM and EDX analyses 7, 14, and 21 days after immersion in SBF on PCL_45S5, PCL_BG10, and PCL_BGZn were performed. In case of wound dressing applications, mineralization is not of pivotal importance as it is for biomaterials used mainly for bone regeneration. However, its role and relevance in wound-healing applications is still a matter of discussion [73]. For this reason, considering that in vitro bioactivity tests have been commonly performed also on films or hydrogels developed for wound-healing applications [74; 75], the same test was performed on the developed PCL composite fibers. FTIR spectra after soaking in SBF solution showed the bands that correspond to HCA layer. At around 600 cm\({}^{-1}\) the P-O bending vibration (Figure 6a-d) was detected [76]. PCL_45S5 spectra (Figure 6b) showed a broad band at around 1046 cm\({}^{-1}\) which could be the overlap of PCL peak (1046 cm\({}^{-1}\)) and the P-O asymmetric stretching vibration at around 1030 cm\({}^{-1}\) correlated to the presence of HCA on electrospun mats [77]. The P-O asymmetric stretching vibration at around 1030 cm\({}^{-1}\) in addition to P-O bending vibration at around 600 cm\({}^{-1}\) was detected for PCL_45S5 1 day after immersion in SBF. While P-O asymmetric stretching vibration was detected 7 days after immersion for PCL_BG10 and PCL_BGZn samples (Figure 6c,d). Furthermore, FTIR spectra at 14 days and 21 days after immersion in SBF, showed P-O bending vibration but it was difficult to detect the broader peaks at around 1040 cm\({}^{-1}\). The lower bioactivity of PCL_BGZn could be ascribed to the lower bioactivity of BGMS_2 Zn bioactive glass compared to 45S5. The presence of a relatively low amount of HCA indicates a slow ion exchange with the surrounding solution. It is reported that Zn ions hinder ions involved in the exchange with the surrounding environment delaying HCA precipitation [78]. ZnO could behave both as a network modifier and as an intermediate oxide. It is supposed that ZnO behaves as a network modifier because it replaces CaO [79], forming tetrahedral species (ZnO4\({}^{2-}\)) which required Ca ions for charge balancing. This behavior decreases glass bioactivity by reducing glass dissolution [80] because cations from silica network are removed. Additionally, by increasing the amount of Zn ions, a decrease in the releasing of alkaline earth ions (i.e., Ca\({}^{2+}\), Mg\({}^{2+}\)) and alkali ions (i.e., Na\({}^{+}\), K\({}^{+}\)) occurs [81; 82; 83]. This behavior is verified by the low oscillation of pH during soaking time which leads to a low interchange between alkaline, alkali ions, and H\({}_{3}\)O\({}^{+}\) ions of the surrounding solution, as outlined in previous studies [81; 82; 83]. Therefore, Zn ions decrease the degradation of bioactive glass and consequently the formation of HCA on PCL_BGZn was delayed.