esa-sceva/satcom-chunk-collection huggingface dataset:
# Agreement Between Tele- and Face-to-Face Assessment of Neuromotor Development in High-Risk Children
## 2 Materials and Methods
### Data Analysis  
The statistical analyses were performed using Statistical Packages for the Social Sciences (SPSS, v. 23.0) software (IBM Corporation, Armonk, NY, USA). Descriptive statistics were used for data analysis. The values were expressed as mean \(\pm\) standard deviation or frequency and percentages. We analyzed the agreement between the face-to-face as sessment and tele-assessment for the AIMS and its subscales by applying the two-way random-effects intraclass correlation coefficient (ICC) (\(\rho\)). Confidence intervals were calculated for the interrater reliability trials. A value of \(\rho<0.5\) was considered poor reliability; 0.5 to 0.75, moderate reliability; 0.75-0.9, good reliability, and \(>\)0.90, excellent reliability [30]. Agreement between the face-to-face assessment and tele-assessment for the AIMS total score was also analyzed using the Bland-Altman limits of agreement.  
Values of kappa were calculated to analyze the categorical data from the NEM assessment. A value of Kappa of 0 was considered poor reliability; 0.01 to 0.20, slight reliability; 0.21 to 0.40, fair reliability; 0.41 to 0.60 moderate reliability; 0.61 to 0.80, substantial reliability; and 0.81 or higher, almost perfect reliability [31].  
A minimum sample size of 44 patients was required to detect an expected mean difference between methods of 0.29 (based on a previous exploratory assessment) in the total score of the AIMS. Considering a drop-out of 15%, a sample size of 50 participants was estimated.
###### Abstract  
Broadband over Power Lines (BPL) is considered a promising communication technology in the concept of Smart Grids. This paper evaluates networks based on BPL, with a focus on the impact of repeaters in the linear topology of distribution substations. In large-scale Smart Grids network planning, positions of repeaters have to be carefully chosen. This article should help to determine such positions and limitations of BPL linear topology networks. Laboratory and on-field measurements and their results are presented in this article. Results show the impact of repeater's deployment for different testing methodologies also with regard to other already presented studies. Measured values and the determined impacts of repeaters are later used as input data for simulation of the linear BPL topology in terms of network throughput with multiple streams and bottlenecks. These occur especially on lines shared by multiple communicating nodes. Furthermore, the simulation investigates the balancing time of multiple data streams throughput. The simulation shows that the throughput balancing can occupy a significant time slot, up to tens of seconds before the throughput of different streams balances. Also, the more data is generated, the more time the balancing time takes. Additionally, the throughput drop caused by a repeater is determined into the range of 35-60%. Based on the measurement and simulation results, lessons learned are presented, and possible performance improvements are discussed.  
power line communication; smart grid; distribution substation; repeater; broadband over powerline; simulation; measurement; performance evaluation
## 3 Methodology
### Selected Influencing Factors
#### 3.1.8 Regolith Thickness  
In general, regolith in the mountainous area of Taiwan consists of colluvium deposits with a large pore space, which may have great groundwater storage potential and affect changes in groundwater levels. Thus, the groundwater storage potential may positively vary with the regolith thickness (RT). Thus, the factor of the regolith thicknesses was chosen for the GWLF potential analysis.  
To construct the spatial distribution of the regolith thickness of the study area from limited survey data, a regression analysis was performed to estimate the regolith thickness (RT) based on two factors: slope (S) and groundwater elevation (GE), which are also suggested by [PERSON] et al. [7]. The data required for the regression analysis were obtained from the survey results of 18 borehole logs in the study area. The following equation provides the regression model with a coefficient of determination of 0.75. The spatial distribution of the regolith thickness factor is illustrated in Figure 10.  
\[\text{RT}= \frac{382}{\left(1-\frac{\text{GE}-387}{329}\right)^{2}\times\left(1- \frac{\text{S}+18}{5}\right)^{2}} \tag{3}\]  
Figure 8: Porosity distribution of the study area.
# Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications
## 3 Smart Meter Technological Solutions in Europe and Projects for Their Implementation
### United Kingdom
Although the situation is more or less clear as to the telecommunications technologies used in the above countries, this is not the case everywhere, either because there is vague information about the utilized technologies or because many countries are at the primary stage of smart meters deployment.
## 3 Data Sources and Preprocessing  
The datasets utilized in this study are MCD12Q1 and GlobeLand30 (Table 2), with the former used as the verified data and the latter as the reference data. The overall accuracy of \"74.8% \(\pm\)1.3%\" indicates the accuracy ranges of the five data layers of MCD12Q1, e.g., the overall accuracy of IGBP is 74.8%. With the best spatial resolution of 30 m, GlobeLand30 is currently considered to be the most suitable GLC product for evaluating the consistency of MCD12Q1. In addition to these two datasets, shape format data regarding China's provincial administrative regions and China's state sector datasets are also employed.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Item** & **MCD12Q1** & **GlobeLand30** \\ \hline Data Format & HDF-EOS & Geotiff \\ Projection & Sinusoidal & UTM \\ Total Accuracy & 74.8\% \(\pm\)1.3\% & 83.5\% \\ Acquisition website & [[http://reverb.echo.nasa.gov](http://reverb.echo.nasa.gov)]([http://reverb.echo.nasa.gov](http://reverb.echo.nasa.gov)) & [[http://www.globallandcover.com](http://www.globallandcover.com)]([http://www.globallandcover.com](http://www.globallandcover.com)) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of the data items between MCD12Q1 and GlobeLand30.  
Figure 1: Location of Anhui Province and the Wanbei, Wanzhong and Wannan regions.
## 2 Materials and Methods
### Headspace Solid-Phase Microextraction-Gas Chromatography (HS-SPME-GC)  
The two authentic sesame oil samples and 37 randomly selected commercial samples (19 hot-pressed samples and 18 small-milled samples) were analyzed by headspace solid phase microextraction-gas chromatography (HS-SPME-GC). The experiment was performed at Wilmar (Shanghai) Biotechnology Research & Development Center. 2-Heptanol was used as the internal standard for semi-quantitative analysis. N-alkanes (C4-C30) were used to calculate the linear retention index (LRI). For VOC analysis, 5 g of sesame oil and 20 \(\upmu\)L of the 2-heptanol solution (1000 \(\upmu\)g/mL) were placed in a 20 mL vial. The vial was tightly capped with polytetrafluoroethylene (PTFE)/silicome septum. Equilibration was performed at 80 \({}^{\circ}\)C for 20 min. The VOCs were extracted at 50 \({}^{\circ}\)C for 50 min using a 50/30 \(\upmu\)m divinylbenzene-carbosen-polydimethylsiloxane (DVB/CAR/PDMS) StableFlex fiber (Supelco Inc., Belfonte, PA, USA) from the headspace of the vial (the vial was under orbital shaking at 450 rpm). The fiber was immediately desorbed for 2 min in a GC injection port operating in splitless mode at 250 \({}^{\circ}\)C. The fiber was conditioned at 300 \({}^{\circ}\)C under helium flow for 1 h in accordance with the manufacturer's recommendations prior to use.  
Periodic fiber blanks were run to ensure the absence of contaminants and/or carryover.  
The separation of VOCs was performed with an Agilent 8890 GC system coupled with a 5977B Mass Selective Detector (MSD) (Agilent Technologies Inc., Santa Clara, CA, USA), using an FFAP column (60 m \(\times\) 0.25 mm, 0.25 \(\upmu\)m, Agilent Technologies Inc., Paolo Alto, CA, USA). Helium was used as the carrier gas at the flow rate of 1 mL/min. The column temperature was initially held at 40 \({}^{\circ}\)C for 1.5 min, increased to 100 \({}^{\circ}\)C at the rate of 10 \({}^{\circ}\)C/min, and held for 5 min; the temperature was then increased to 150 \({}^{\circ}\)C at the rate of 2 \({}^{\circ}\)C/min, held for 8 min, increased to 185 \({}^{\circ}\)C at the rate of 10 \({}^{\circ}\)C/min, and then increased to 240 \({}^{\circ}\)C at the rate of 20 \({}^{\circ}\)C/min and held for 16 min. The GC-MS interface temperature was 250 \({}^{\circ}\)C, and the ion source temperature was 230 \({}^{\circ}\)C. Electron impact mass spectra were generated at 70 eV and acquired in full-scan mode with the range of 35-350 \(m/z\). Data were collected and processed using the NIST 17 Mass Spectral Library. For the preliminary identification of the compounds, a matching factor score greater than 800 was accepted. Further confirmation of the tentative identification results was achieved by qualitatively comparing the retention indices with those of the standard compounds.
# Erosion Rate Measurements for DART Spacecraft Ion Propulsion System +
###### Abstract
This is the case for NSTAR, AIPS, and NEXT ion engines. Other materials, especially titanium and pyrolytic graphite (carbon) grids, are replacement candidates. NASA's NEXT ion engine has a relatively low grid sputter rate and long lifetime [3]. Because molybdenum plume density is approximately proportional to wear rate, for a given geometry, the low erosion rate of NEXT limits its molybdenum plume density and makes in situ detection more challenging. NEXT was designed with two extraction grids: screen and accelerator. Erosion occurs primarily on the accelerator grid, due to xenon ion impingement. Age of the grids is a factor, and operating hours were relatively low in the present case. Erosion rate can be studied by various techniques, including real-time imaging of grid apertures, post-test dimensional measurements, and real-time monitoring of erosion/deposition products. Fixed position and rotating quartz crystal microbalances (QCMs) were used previously to study plume deposition rates for NEXT [6], and laser induced fluorescence (LIF) was also utilized [7]. Real-time monitoring of plume molybdenum density via LIF or deposition via QCM can be challenging from a detection standpoint. The interpretation of witness plate and QCM data is more complex if molybdenum arrival rate is low, due to surface reactions with residual gas. The back-sputter of carbon from facility walls to thruster grids will alter their erosion rate if carbon deposition is fast enough. Carbon back-sputter has been measured previously and its effect analyzed [8; 9]. For the present study, previously described in a conference paper [10], LIF Doppler profiles were obtained across the grid face for several DART operating points, and the effect of flow variation over the envelope possible for DART was evaluated. In addition, relative Doppler profile data were collected at the grid center covering the full range of potential DART operating points, and the effects of elevated background pressure and accelerator grid voltage changes were explored. The focus was on only density and velocity profile variation across the grid face, including its dependence on parameters such as throttle point, and these results are complementary to quartz crystal microbalance deposition measurements. Combining LIF and QCM measurement data from the same location would allow direct conversion of LIF signal to absolute density, but this is difficult to achieve. An alternate approach was taken here, which also combines LIF and QCM data.
## 1 Introduction
* A creative pricing model is proposed. The pricing model includes two functions: price setting and pricing. A flexible set of pricing methods based on the p-norm [14] is proposed to provide the possibility of tuning and adapting to the pricing strategy for the data market. The pricing model satisfies three required properties: arbitrage-free, monotonic, and bounded. * Our pricing model first sets prices for source tuples according to their importance and then makes query pricing based on data provenance, which considers both the importance of the data itself and the relationships between the data. * An exact algorithm is used to calculate the exact price of a query with exponential complexity. Furthermore, an easy approximate algorithm that can calculate the approximate price of a query in polynomial time is devised. The paper is organized in the following way. Section 2 introduces the existing relational data provenance semantics. Section 3 proposes a creative personal data pricing model that is based on minimal provenance. The exact algorithm and approximate algorithm are proposed to calculate the price of the query respectively in Section 4. Section 5 presents the experimental and evaluation results. Section 6 briefly reviews the related work. Section 7 concludes the paper.
## 2 Mathematical Model
They are then stimulated to become mature or activated APCs, \(A_{M}\), at rate \(s_{AU}\) or \(s_{AI}\) due to the interaction with either uninfected or infected tumour cells. They decay at a fast rate \(d_{S}\), where \(d_{S}>>d_{L}\). * In Equation (5), long-term immature DCs, \(D_{L}\), enter the system at rate \(fu_{DC}(t)\), where \(u_{DC}(t)\) is the rate of injection or release from the hydrogel and \(f\) is the fraction of the initially loaded DCs that are long-term DCs, \(0<f<1\). Similarly to short-term DCs, they become activated APCs at rate \(s_{AU}\) and \(s_{AI}\). These DCs decay slowly at rate \(d_{L}\). * In Equation (6), immature APCs, \(A_{I}\), are recruited to the tumour site by infected cells at rate \(r_{AI}I\). Immuture APCs are then stimulated at the same rate as immature short-term and long-term DCs. The immature APCs decay at rate \(d_{AI}\). * In Equation (7), mature APCs are generated through the maturation of introduced long-term and short-term DCs and immature DCs recruited by uninfected tumour cells at rate \(s_{AU}\) and infected tumour cells at rate \(s_{AI}\). These cells decay at rate \(d_{A}\). * In Equation (8), helper T cells, \(H\), are stimulated by mature APCs at a rate \(s_{H}\). These cells decay at a rate \(d_{H}\). We assume the rate APCs stimulate helper cells and helper cells stimulate killer cells is independent of antigen. * In Equation (9), killer T cells, \(K\), are activated by helper T cells and mature APCs at rates of \(s_{KH}\) and \(s_{KA}\), respectively. These cells either die or leave the tumour site at a rate \(d_{K}\). As the virus was administered either intrutumourally or from the gel, there is no need to model the virus in the organs and blood (discussed by [PERSON] et al. [40]). Additionally, the influence of interferon-mediated antiviral immunity is not considered crucial. Note that this is the same killer T cell population that was considered by [PERSON] et al. [36], but this time the activation mechanism is modelled in more detail. The above model is similar to the model used by [PERSON] et al. [35]. We consider two populations of immature dendritic cells (\(D_{L}\) and \(D_{S}\)) in the initial administration as the in vitro release curve depicted a biphasic exponential decay profile for the DCs, see Section 3.1. We separated this population from the immature DCs already present in the mice, as we did not want to impose the assumption that the same separation in the survival rates would exist in this population. If a gel is used to release the DCs and/or virus the initial conditions for system are  
\[ \begin{array}{l}U(0)=U_{0},\quad\;I(0)=0,\quad\;V(0)=0,\quad\;D_{L}(0)=0,\\ D_{S}(0)=0\quad\;A_{I}(0)=0,\quad A_{M}(0)=0,\quad H(0)=0,\quad K(0)=0,\end{array}  \tag{10}\]  
where \(U_{0}\) is the initial tumour size, whereas, for a single injection of virus or DCs, the initial conditions change to \(V(0)=V_{0},D_{L}(0)=fD_{0}\) and \(D_{S}(0)=(1-f)D_{0}\) for the virus and DCs, where \(V_{0}\) and \(D_{0}\) are the initial number of viruses or DCs, respectively.
# Access Control and Pilot Allocation for Machine-Type Communications in Crowded Massive MIMO Systems
## 3 Dynamic Access Control and Pilot Allocation Algorithm  
In this section, we use ACB scheme for access control and use SUCRe protocol for pilot allocation. At first, we formulate an optimization problem to maximize the access success rate. In massive MTC systems, the random access of a huge number of MTCDs would not be affordable; therefore, the resource cost should be considered. Here, the access success rate is defined as the ratio between the number of MTCDs that successfully access the BS and the total number of MTCDs that contend to become active in an observation time.
## 5 Discussion
In our study, the number of living cells was significantly greater on 60 nm and 96 nm silver particle-sized modified titanium surfaces, where the measured contact angle was lower than 70\({}^{\circ}\). As the higher contact angle meant lower wetting ability, which can directly affect the adhesion of cells [38; 39], we hypothesize that the observed reduction in cell number on the modified surfaces covered by 149 and 368 nm silver particles was directly associated with this phenomenon caused by the reduction of the interactive material surface. Data of this paper reveal that 60 and 96 nm particle sizes of AgNP do not significantly alter cell adhesion, which is a key clinical factor for successful dental implant therapy. These features can play a high role in unambiguously identifying the exact silver nanoparticle diameter range created on the surface of titanium implants. However, due to another crucial factor, it is important to properly adjust the diameter of the nanoparticles; such a key consideration is economy. The amount of silver applied to the surface of the implants in clinical use is greatly influenced byfinancial considerations, as it has become essential for the economical aspect to use the minimum amount of silver required. Thus, it became important to apply as little silver to the implants as is optimal for antibacterial effect, with the minimum amount of silver being used. Data reveal that silver nanoparticle coated titanium surfaces with 60 nm particle diameter have a good antibacterial feature, good biocompatibility, do not alter hydrophilicity, and contain less silver; thus, they may be optimal for dental practice in long-term use. Data also suggest that a bigger particle diameter decreases biocompatibility and cell viability and negatively alters hydrophilicity. [PERSON] explains the phenomenon by the fact that it is due to the hydration layer formed around each AgNP that negatively affects the viability of the cells deposited on the surface [40]. The deposition of AgNPs on the titanium surface creates a surface that is increasingly hydrophilic depending on the decreasing size of AgNPs. This hydrophilic growth is greatly influenced by roughness of the surface [41], silver coverage, surface growth, and air bubbles on the surface trapped under the cells [38]. Another presentation of these two papers [38; 41] is that AgNPs deposited to the surface are negatively charged, as shown in Figure 9 as an illustration. A multi-contact negative charge has a positive effect on hydrophilicity. In summary, our research showed the diameter of the AgNPs formed as a function of the applied layer thickness and selected the diameter of the AgNPs as a function of the layer thickness, which was the least damaging to cell viability. Based on this, we can determine the amount of silver and the treatment necessary for these AgNPs to get the most optimal physical conditions for the highest cell viability.
# Genomic Insights into Two Endophytic Strains:
###### Abstract  
Endophytic microbiota are being researched as a vital source of beneficial attributes that are of immense importance for enhancing agroecological crop production. In this study, two endophytic strains: _Pseudomonas carnis_ NWUBe30 and _Stentrophonomas geniculata_ NWUBe21, were isolated from cowpea tissue, and their plant growth-promoting attributes were assessed. The 165 rRNA gene, as well as the key plant growth-promoting genes that they contain, were subjected to polymerase chain reactions (PCR). Furthermore, their genome was sequenced using the Illumina NovaSeq 6000 systems platform. The results indicated that they possess multiple plant growth-promoting attributes, including the solubilization of phosphates, the production of auxin, siderophore, hydrogen cyanide, exopolysaccharide, ammonia, and 1-aminocyclopropane-1-carboxylic acids. Additionally, the plant growth-promoting genes GCD and ASB were amplified via PCR at their expected base pair value. The genome bioinformatics analysis revealed assemblage sizes of 5,901,107 bp for _P. carnis_ NWUBe30, with an average G+C content of 60.2%, and for _S. geniculata_ NWUBe21, 512,0194 bp, with a G+C content of 64.79%. Likewise, genes, such as exopolyphosphatase, ferribacilibactin, betalactone, and lassoeptide, that are responsible for promoting plant growth were identified. This study highlights the biotechnological potential of _Stentrophonomas geniculata_ strain NWUBe21 and the _Pseudomonas carnis_ strain NWUBe30, which can be harnessed to achieve improvements in sustainable agroecological crop production.  
whole genome explorations; Illumina sequencing platform; plant growth-enhancing genes; endophytic _Stentrophonomas geniculata_; endophytic _Pseudomonas carnis_; agroecological crop improvement; leguminous crop--_Vigna unguiculata_; plant probiotic endophytes