esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Conductive Polymers
In [60], knowing that the PEDOT:xanthan gum scaffolds can efficiently facilitate cell culture, the electrical properties has been investigated by means of electrochemical impedance spectroscopy (EIS) and studied their evolution during cell growth as a tool to monitor cell growth. In [60], the PEDOT:xanthan gum scaffold is combined with electrode based device and there overall experimental setup has been reported in Figure 1. Specifically, gold electrodes were patterned on top of glass substrates, while a polydimethylsiloxane (PDMS) \"well\" was used to confine the scaffolds inside the electrode area. The Ag/AgCl/KCl (3 M) reference electrode and platinum (Pt) mesh counter electrode were immobilized inside the wells. The impedance data (presented as Bode plot) revealed a significant increase in the impedance value that was modeled as additional capacitance elements in the equivalent circuit, which corresponds to the growth of insulating cell layers in the pores of the scaffold [61]. A less pronounced change can be observed for mid to high frequencies, with a slight increase in the impedance values most likely associated with the presence of cells contributing to the increase of the Ohmic resistance at the working electrode-electrolyte interface. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Conductive Polymers** & **Manufacturing Techniques** & **Conductivity (Scm\({}^{-1}\))** & **References** \\ \hline PPy or PPy & \
\begin{tabular}{c} Electrospinning, freeze drying, \\ in situ polymerization \\ \end{tabular} & \(10^{2}\)–\(7.5\times 10^{3}\) & [62; 63; 64; 65; 66; 67; 68] \\ PAN or PAN &
\begin{tabular}{c} Electrospinning \\ \end{tabular} & \(30\)–\(200\) & [62; 69; 70] \\ PEDOT or PEDOT & Freeze drying, vapor-phase & \(10\)–\(10^{3}\) & [60; 62; 71; 72] \\ Composites & polymerization, solvent casting & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Properties of different conductive polymers and corresponding techniques used in manufacturing scaffolds.
# A Web-Based Application for Smart City Data Analysis and Visualization
## 5 Results
### Evaluation
Longer sessions occur less frequently, exhibiting a heavy right-tail characteristic of usage skew. Figure 13: Daily number of vehicles vs. average sound pressure level. This plot illustrates the relationship between the daily number of vehicles (blue bars, left axis) and the average sound pressure level (orange line, right axis) recorded at a monitoring location. Horizontal dashed lines represent the median values of each respective dataset. A strong alignment between peaks in vehicle count and elevated noise levels suggests a correlation between traffic intensity and urban sound pollution. The dual-axis chart effectively highlights how increased traffic volumes tend to coincide with higher average decibel levels over time.
## 3 _Apergillus_ Is a Microbial Chassis for Natural Product Synthesis
### A. nidulans as a Chassis for Natural Product Synthesis  
Similar to _A. oryzae_, _A. nidulans_ has also been widely used in synthetic biology to study gene clusters from other species. As one of the most popular fungal hosts for the reconstitution of fungal biosynthesis pathways, _A. nidulans_ has abundant secondary metabolite production capacity and an efficient gene targeting system with simple nutritional requirements and rapid growth and reproduction rates, so it is the most advanced and efficient molecular genetic system and a well-established model organism among filamentous fungi [57; 130]. Furthermore, due to the successful expression of many types of natural products in _A. nidulans_, the application of _A. nidulans_ as a versatile chassis has greatly facilitated the complete characterization and reconstruction of biosynthetic pathways for diverse natural products, as well as the discovery of new compounds [10; 131]. In recent years, the _A. nidulans_ expression system has successfully produced many fungal natural products. For example, by heterologously reconstructing the biosynthetic pathways in _A. nidulans_, the [PERSON] group successfully biosynthesized a set of natural products, including two polykeptides ((M)-viriditoxin from _Paecilomyces variotii_[132] and stemphyloxin II from _Parastagonospora nodorum_[133]) and a benzazepine (alkaloid nanangelenin A from _Aspergillus nanangensis_[134]). [PERSON] et al. achieved the biosynthesis of cosmosporaside C, a fungal hybrid terpenoid saccharide, and elucidated the assembly line, which contained several unusual steps [135]; a group of dimeric indole piperazine alkaloids was also heterologously synthesized in _A. nidulans_ by the combination of the non-ribosomal peptide synthetase (NRPS)-like gene _cpsA_ and other genes, and one of them, campesine G, has been shown to have insecticidal activity [136]. [PERSON] et al. identified a biosynthetic gene cluster (_bgt_) in the genome of _Trichoderma erinaceum F1-1_, a marine-derived fungus, which encodes the UbiA terpene synthase BgtA; then, they achieved the transcriptional activation of the silent _bgt_ gene cluster through successful heterologous expression in _A. nidulans LO8030_, resulting in the isolation of eight previously unreported bergamotene-derived sesquiterpenoids [137].
## 1 Introduction
While the first investigation on using remote antennas in the mmWave band was introduced in Reference [11], where the author has demonstrated the importance of remote antennas on minimising the shadow fading of wireless networks in the Local Multipoint Distribution Service (LMDS) band. In Reference [12], the authors have investigated how to support MTC services through HetNets with relay deployments and Carrier Aggregation (CA) in the Long Term Evolution (LTE) network. Figure 1: Cisco VNI, MTC data growth rate [4]. However, they only considered fixed (stationary) sensors such as weather sensors and used a single base station that is equipped with omnidirectional antenna. The authors in Reference [13] have proposed a mechanism for the traffic engineering of MTC through multi-objective optimization and enhances the performance of both machine traffic and human traffic. The impact of MTC traffic on cellular network has been considered by Reference [14], where the authors have proposed a general framework to evaluate the MTC performance in cellular network. In mmWave bands, however, there are few contributions on MTC traffic in these bands. In Reference [15], MTC communication has been studied at a 40 GHz carrier frequency with 5 m link distance and the study has been conducted for healthcare sector. An experimental channel measurement has been conducted at 60 GHz for an indoor scenario [16], which shows channel interdependency that can help predict channel parameters in Machine-to-Machine (M2M)/MTC sensor network. Also in Reference [17], a 60 GHz channel capacity and bit rate analyses has been presented and compared with the sub 6 GHz links from IoT perspectives--the authors have found that the use of the mmWave band is a viable solution for the provision of a high performance links to support IoT. This paper, however, investigates the joint use of DBS network architecture and the adoption of mmWave, particularly 26 GHz, to cope with the massive traffic of MTC connections, where fixed sensors and wearable sensors are supported by 5G in the IoT environment. The rest of the paper is structured as follows: Connected Health (CH) is discussed in Section 2. In Section 3, the DBS structure is clarified, while the network model is described in Section 4. In Section 5, the problem formulation is discussed, followed by the resource assignment algorithm in Section 6. The simulation result is presented and discussed in Section 7. The gain of using DBS network architecture is discussed in Section 8. Finally, the conclusions are drawn in Section 9.
# Resolution Aspects for Near-Field Projections
## 3 Results
### Analysis of the Perceived Resolution
The graphs also include the study's raw data to which the logistic regression (Equation (3)) is fitted for the viewing distances of 1 m, 3 m and 5 m. The 90% threshold is equivalent to the 90% value of the satisfaction probability, displayed for all combinations in Table 2.  
Furthermore, Figure 5a,b display, similar to Figure 4a,b, the study data points at 1 m, 3 m and 5 m viewing distances. The resulting logistic regression for each viewing \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Resolution (px/\({}^{\circ}\))** & **1 m** & **3 m** & **5 m** \\ \hline Symbol PGS & 18.70 (18.12; 19.84) & 29.45 (28.71; 30.86) & 39.62 (38.35; 42.12) \\ Text PGS & 20.89 (20.11; 22.45) & 31.70 (30.64; 33.93) & 47.46 (46.07; 50.31) \\ Symbol DDS & 25.41 (24.78; 26.34) & 40.71 (39.53; 42.46) & 52.62 (51.34; 54.50) \\ Text DDS & 31.72 (30.92; 32.88) & 39.92 (39.05; 41.22) & 51.40 (50.14; 53.30) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Effective resolution on the ground for a 90% threshold level evaluated by the participants for text- or symbol-based projection content under different adaptation luminance levels defined in pixels per degree (px/\({}^{\circ}\)). The numbers in brackets indicate the confidence intervals of 95%, with the lower bound as the first number and the higher bound as the second number of the perceived resolution on the street for every distance, ambient lighting and projection content. Figure 4: Results of the analyzed data by using the logistic regressing Equations (3) and (4) for extracting the 90% threshold for the resolution in px/\({}^{\circ}\) with the corresponding probability of satisfaction in the PGS. (**a**) Detailed illustration of the logistic regression of the symbol-based projection in the PGS, including the raw data, which is marked with “X” for 1 m data, with circles for 3 m data and triangles for 5 m data; (**b**) Detailed logistic regression of the text-based projection in the PGS including the raw data, which is marked with X for 1 m data, with circles for 3 m data and triangles for 5 m data. distance for the symbol- and text-based projections in the DDS is displayed in the graphs in Figure 5a,b. In the following section, the consideration of the dependency analysis is coupled with the effective resolution on the ground to deduce resolution requirements for near-field projections in the automotive sector.
# Seamless Indoor-Outdoor Localization Through Transition Detection
## 3 Handover Strategy Based on Three State Density Functions  
The positioning environment is categorized into three distinct states: indoor, transition, and outdoor, as illustrated in Figure 2. The transition state is defined symmetrically around the transitional features such as doors or building entrances that serve as physical boundaries between indoor and outdoor areas. When a state change is detected, a handover strategy is triggered, transferring both the latest estimated position and the corresponding error covariance matrix from the current positioning engine to the next.  
A state handler continuously evaluates the probabilities \(P(s)\) for each possible state \(s\in S=\{\)indoor, transition, outdoor\(\}\). The state with the highest probability is selected as the current operating state such that  
\[s^{*}=\arg\max_{s\in\{\textit{in,transition,out}\}}P(s). \tag{1}\]  
The state probabilities are derived from three independent estimation models: an RSSI-based model, a position-distribution model, and a GNSS-based distribution model. Each model produces a probabilistic estimate for the current state, reflecting different aspects of the environment. The final state probability is calculated as a weighted sum of these individual model outputs.  
\[P(s)=w^{\textit{rssi}}P^{\textit{rssi}}(s)+w^{\textit{position}}\textit{position }(s)+w^{\textit{gsns}}P^{\textit{GNSS}}(s) \tag{2}\]  
The weights assigned to each model are manually tuned through empirical evaluation to achieve optimal state classification performance. This approach is necessary because each building features a unique configuration of WiFi and BLE access points, which affects \(P^{\textit{rssi}}(s)\), and distinct structural characteristics around transition zones, which influence \(P^{\textit{GNSS}}\). Therefore, in this paper, the weights are experimentally optimized for each environment.
# Optically Transparent Nano-Patterned Antennas: A Review and Future Directions
## 2 Transparent Antennas: A Review
### Copper Nanowires  
Copper nanowires (CuNW) can be coated on various substrates (film, glass, silicon wafer, etc.) by dispersing nanoparticles in solvent and applying wet coating and roll-to-roll coating technology, as compared to existing ITO films. In addition, it has excellent conductivity and flexibility, and is applicable to almost all applications where excellent conductivity and optical transmittance are required, for example, electromagnetic interference (EMI) shielding films, solar cells, transparent electrodes, antennas, and the like. Also, the line spacing between the patterns is so small that it is invisible and usually maintains an interval of 100 to 200 \(\upmu\)m.  
In Reference [30], a transparent dual-band meandered-monopole antenna with a micro metal mesh conductive film is studied. Using nonconductive glue, the antenna pattern is glued on glass with a 1.09-mm thickness and a relative permittivity of 5.5. The overall dimensions of the fabricated antenna are 40 mm \(\times\) 40 mm. The micro metal mesh conductive film has a low sheet resistance of 0.05 \(\Omega\)/sq and a high optical transmittance of above 75%, as given in Figure 8a. The \(S_{21}\) in Figure 8b shows the little effect of mutual coupling between two antennas since \(S_{21}\) is lower than \(-\)15 dB at the operating frequency. Moreover, it offers high efficiencies of 43% and 46% and peak gains of 0.74 and 2.30 dB at 2.44 and 5.5 GHz, which are much higher than those of other materials such as TCOs.  
Figure 7: **(a)** Model of the investigated patch antenna and microscopic image of a single silver nanowire (AgNW) coating with 67.9% optical transmission at 550 nm; **(b)** simulation radiation pattern of the patch antenna operating at 61 GHz [27]. (With permission from IEEE).  
In [31], a transparent 3 dB Branch-Line Coupler based on a micro metal mesh conductive film is investigated, operating at 2.45 GHz. This antenna pattern is printed on a stacked substrate which has PET/glass/PET layers. The thickness of the glass substrate is 2 mm with a dielectric constant of 5.7. Owing to the large thickness (2.25 mm) of the overall substrate, a wide band property is obtained. It can reduce the low sheet resistance to 0.7 \(\Omega\)/sq, but it has a transmittance of 75% and also yields a return loss of 20.2 dB and an isolation of 23.5 dB.
# Enhancement of the Purcell Effect by the Wire Metamaterials Formed by the Hexagonal Unit Cells
###### Abstract  
The dependence of the Purcell factor on nanowire metamaterial geometry was analyzed. Calculations made about the Purcell factor in realistic composites, operating at an optical spectral range, are provided. We applied a metamaterial, aiming to mitigate the negative effects of absorption in metals on the Purcell effect in nanowire structures. A nanowire metamaterial was treated as an anisotropic composite in the long-wavelength limit. We investigated the mode patterns of the surface waves, propagating at the boundary separating such a structure and a dielectric material, along with the position of the peak in the local density of states, for the various filling factors of the periodic structure. By calculating the frequency dependence of the Purcell factor, we showed an increase in the peak value in comparison with the conventional plasmonic structure in the (1-100 THz) frequency range. Moreover, an optimal set of the parameters, needed to obtain the two topological transitions in the frequency range under investigation, is proposed.  
Purcell factor; metamaterial; nanowire Article
## 1 Introduction
The experimental results showed that this method could enhance the angular color uniformity of LEDs. [PERSON] et al. proposed the addition of SiO\({}_{2}\) scattering particles into the phosphor layer of a multi-chip white light LED. The simulation showed that SiO\({}_{2}\) particles could significantly enhance the CCT uniformity and luminous flux [13]. While these methods of improvement have been confirmed by achieving high CCT uniformity, they also engender significant fabrication difficulties for mass production. It is necessary to find a remote phosphor packaging method that not only realizes high CCT uniformity but is also cheap and easy to fabricate. For this reason, we are interested in a more convenient method of manufacturing for remote phosphor packaging, for example, nanoparticle diffuser-loaded encapsulation methods-- encapsulation containing nanoparticle diffusers cause light to reflect, refrac, and scatter, thereby randomizing the propagation direction and isotropizing the far-field distribution. [PERSON] et al. proposed an innovative method consisting of mixing SiO\({}_{2}\) and Sr\({}_{2}\)Si\({}_{5}\)N\({}_{8}\):Eu\({}^{2+}\) phosphor particles into the YAG:Ce phosphor of remote phosphor LEDs to improve the color uniformity and color rending index (CRI) [14]. By fixing the concentration of SiO\({}_{2}\) particles at 5%, the simulation results showed that color uniformity and CRI significantly improved with a rising concentration of Sr\({}_{2}\)Si\({}_{5}\)N\({}_{8}\):Eu\({}^{2+}\) phosphor particles. [PERSON] et al. investigated the luminous efficiency of the generated white light from Polydimethylsiloxane (PDMS)/phosphor composites through employing various glassy scattering particles, such as glass beads, glass bubbles, or SiO\({}_{2}\) nanoparticles [15]. It was demonstrated that the luminous efficiency of remote phosphor LEDs could be improved and controlled by the morphology of the scatter, the volume fraction of the scatters, and the thickness of the PDMS/YAG:Ce\({}^{3+}\) composite samples. In this study, we used TiO\({}_{2}\) diffuser-loaded encapsulation to improve the CCT uniformity and decrease the CCT variance in remote phosphor white LEDs. The TiO\({}_{2}\) diffuser can provide superior scattering capability for light. The effects of different positions and concentrations of diffusers on the spatial CCT distribution, light extraction efficiency, and CCT of remote phosphor white LEDs were investigated to find the optimized solution.
# Timing Performance Testing and Regularity Analysis of eLoran System
###### Abstract  
Accurate time synchronisation is critical in modern communication, navigation, and scientific research. In this context, the eLoran receiver, which is an advanced timing device, has attracted increasing scholarly attention. This study aims to comprehensively analyse the performance and potential applications of eLoran systems for timing monitoring and to specifically explore the relevant indices of two eLoran receivers. To this end, we evaluated the performance of these receivers in receiving time signals through both simulated and empirical data and conducted a regularity analysis to uncover their potential value in practical applications. The findings demonstrate that the eLoran receiver excels at timing monitoring and provides highly accurate time information. An analysis of the timing performance of the eLoran system improved its accuracy and integrity.  
eLoran timing; timing performance; system synchronisation +
Footnote †: journal: Applied sciences
## 3 Materials and Methods
### Generation Ensemble Models  
The sounding-level models described in Section 3.5 give us an instantaneous estimate of the power plant activity in a single satellite image. Collecting these instantaneous estimates creates an irregular time series of on/off classification and capacity factor regression estimates for each plant. In order to estimate emissions of a plant over a given period of time, we built a set of second-stage models (\"generation models\") responsible for aggregating the sounding model time series into features and predicting a rolling 30-day average capacity factor for each plant (predicting one value for each day, that value being the average capacity factor over the preceding 30 days). We then multiplied this capacity factor with each plant's capacity to obtain the plant's estimated generation. Afterward, the estimated generation was multiplied by an emissions factor, as described later in Section 3.7, to estimate emissions.  
Separate generation models were trained for NDT and FGD plants and only for the years 2018 to 2022 inclusive. This is because there is very limited PlanetScope data available prior to 2018, making rolling 30-day predictions difficult due to the sparsity of soundings. Each generation model is an L1-regularized linear regression model with features formed from aggregating the sounding model predictions (described in Appendix C). To calculate features for each plant at each point in time, we aggregated the predictions from the sounding-level models over multiple lookback windows. In total, the NDT model had access to 162 features, while the FGD model had access to 324 features (see Appendix C for the list of features). All features were standardized to a mean of zero and unit standard deviation prior to model training. The same standardization factors were applied for inference.  
The lookback windows over which we aggregated predictions for the NDT generation model were 30, 60, and 180 days. Due to the lower number of soundings for the FGD generation model, its lookback windows were 30, 60, and 365 days. In addition to including more plant-specific information, these longer windows also allowed our models to account for the longer-term behavior of the plant when making a prediction. The generation models were trained with L1-regularization weights of 0.01 and 0.005 for FGD and NDT, respectively. Figure 5 shows an example of FGD and NDT model predictions compared with the capacity factor calculated from reported electricity generation.
# An Introduction of NoSQL Databases Based on Their Categories and Application Industries +
## 3 The Categories of NoSQL Databases
### Key Value Store  
The data in this category of NoSQL databases is stored with the format of \"Key \(\rightarrow\) Value\" [5], where  
1. Key is a string used to identify a unique value;
2. Value is an object whose value can be a simple string, numeric value, or a complex BLOB (binary large object), JSON object, image, audio, and so on;
3. In key value store databases, operations on values are derived from keys. Users can retrieve, set, and delete a value by a key;
4. A namespace is a logical data structure that can contain any number of key-value pairs.  
Suppose that an online shopping website uses a key value store database to store data as shown in Figure 3. This database includes several namespaces, such as \"products\" and \"customers\" [5], where  
1. The key in the namespace \"Products\" is the ID of products, and the value is the details about products;
2. The key in the namespace \"Customers\" is the ID of customers, and the value is the details about customers.  
Figure 2: An example of a collection in a document store database.  
According to the statistics of the DB-Engines Ranking Website [15], both Redis and DynamoDB are the more widely discussed ones of the key value store databases.
## 3 Experiments  
### Datasets and Preprocessing  
In this section, we describe our benchmark dataset GF_Sen, which consists of imagery obtained from Sentinel-2 and GaoFen-2. Simultaneously, three publicly available datasets, UC_Merced, WHU-RS19, and USC-SIPI, are introduced.