esa-sceva/satcom-chunk-collection huggingface dataset:
# Cellular Effects of Silver Nanoparticle Suspensions on Lung Epithelial Cells and Macrophages
## 2 Materials and Methods
### Determination of Intracellular Silver Concentration  
Cells were seeded in a 6-well plate to determine the intracellular silver ion concentration. Culture medium was replaced with a silver nanoparticle suspension (10 \(\upmu\)g/mL), or an AgNO\({}_{3}\) solution (100, 500, and 1000 \(\upmu\)mol/L) was applied and incubated for an additional 24 h. The suspension or solution was removed, and cells were washed twice with PBS to remove loosely bound silver nanoparticles on the cell surface. Next, cells were collected by 0.25% trypsin treatment, suspended in hypotonic buffer (20 mM Tris, 10 mM NaCl, 3 mM MgCl\({}_{2}\) and 0.5 mM dithiothreitol), and incubated for 15 min on ice. The cell lysate was supplemented with Nonidet P-40 and centrifuged at 4 \({}^{\circ}\)C, 1000\(\times\)\(g\), for 10 min. The supernatant was collected to measure the cytosolic silver concentration. Silver ion concentration was determined using ICP-MS XSERIES (Thermo Scientific).
# Technology Acceptance in Healthcare: A Systematic Review
## 6 Conclusions
### Practical Implications  
The study provides various practical implications for the healthcare domain. First, this review differs from the other reviews by including various technology acceptance models, various technologies, and various users. This diversity is valuable for other researchers and decision makers in different research areas, countries, and settings. For instance, virtual clinics can have great potential through telemedicine, cloud computing solutions, and mobile applications. Decision makers need to provide the necessary support for implementing these solutions to help physicians and healthcare professionals in providing many healthcare services (e.g., consultation, follow-up) without meeting the patient, especially in rural areas.  
Second, the review shows a gap in the new technology trends in the healthcare sector. The decision makers and IT corporations should employ Internet of Medical Things (IoMT) and virtual reality (VR) solutions. IoMT can help to digitize the process, develop resource allocation, and provide real-time data to drive decisions. Virtual reality solutions can help to train resident physicians and young nurses to feel integrated with situations they may face in reality. Additionally, such augmented solutions can enable the physicians to access the patients' reports without leaving their current location, and using hands-free mode (voice commands).  
Third, we believe that the results would assist policy makers in reviewing the current regulations and policies concerning data confidentiality and privacy. Additionally, these regulations should be announced and published. End-users need to be educated and aware of their roles and responsibilities to enhance their acceptance by improving the levels of trust and anxiety.  
Fourth, information technology corporations (system analysts and developers) and healthcare organizations can utilize the findings related to the influential factors as a type of lessons learned. Consequently, this review can help to improve the currently implemented solutions and consider enhancements in future technology to be more user-friendly and innovative. Using information technology solutions with fewer efforts can encourage end-users to gain the maximum benefits without fear of making mistakes.  
Fifth, the review addressed gaps in the technology acceptance literature by considering the regions of implementation. It has been observed that inadequate attention is paid to implementing cloud computing, telemedicine, and medical informatics applications in developing countries. Therefore, IT corporations need to concentrate on Arab and African countries, as there is potential to implement those new information technologies within the healthcare sector in these countries.
## 5 Engineering Application of the Proposed Method
### Optimization of Hydraulic Parameters According to the Objective II  
For subsea tunnels, the main objectives of reinforcement include two aspects: (i) improvement in the surrounding rock conditions to control displacement field (objective I), (ii) plugging water to control the water quantity (objective II). It implies that the choice of the permeability coefficient of the reinforcement can influence on both displacement and seepage quantity. According to the mechanics of groundwater seepage, by using the separation of variables technique to solve Equation (9) and by considering the seepage continuity assumption, the seepage quantity \(Q\) was derived by:  
\[Q=\frac{2\pi kh_{0}}{\frac{k}{k^{\prime}}\ln\frac{r_{a}}{r_{0}}+\ln\frac{R_{0}}{ r_{a}}}, \tag{15}\]  
where \(h_{0}\) denotes the depth of the tunnel center below the sea level.  
It is obvious from Equation (15) that by increasing \(r_{a}\) or decreasing \(k^{\prime}\) would result in a reduction of the seepage quantity \(Q\). If the allowable water inflow is designed to be 0.4 m\({}^{3}\)/(m-d), substituting the optimal \(t_{a}\) (\(t_{a}=r_{a}-r_{0}\)) into Equation (15), the critical permeability coefficient \(k^{\prime}\) is readily obtained as \(2.86\times 10^{-6}\) cm/s. Hence, \(k^{\prime}\) must be less than the critical value to meet the plugging requirements (objective II). The permeability coefficient of reinforcement in this section of the Jiaozhou bay subsea tunnel was measured to be \(1.7\times 10^{-6}\) cm/s, which met the requirements of water plugging.
## 4 Results and Discussion
### Prediction of Time-Series Synthetic NDVI
The synthetic NDVI time series described more detailed spatial variations of NDVI at a resolution of 30 m. The temporal information from MODIS and the spatial information from Landsat were integrated in the predicted synthetic NDVI data set, and it was expected that such data can provide superior input for accurate estimations of AGB time series.
# A Sentiment Analysis Model Based on User Experiences of Dubrovnik on the Tripadvisor Platform
## 3 Materials and Methods
### Data Preparation and Preprocessing
#### 3.3.2 Collecting the Data  
This subsection describes the process of extracting data from the Tripadvisor website using the web-scraping technique. Web scraping is an automated process of accessing websites and downloading their content. Additionally, web content can be considered as a valuable data source for empirical research. Furthermore, web scrapers can be implemented  
Figure 2: An example of a Tripadvisor review.  
by programming a script or by using tools such as the following: ScrapeHub, Requests, and Selenium [63; 64; 65].  
For this study, a Python script, based on Selenium and the web-scraping technique, was created to download reviews from the Tripadvisor website _Old Town_ and to save them to a file in CSV (Comma-Separated Values) format. Table 1 shows part of the CSV file with the Tripadvisor reviews. In this table, each row represents a single review, while the columns correspond to the different attributes associated with each review, such as _review title, rating, date the review was published_, etc.  
A total of 5208 reviews of Dubrovnik were collected, covering the period from July 2017 to December 2023. For the research purposes of this study, 371 reviews, written between 1 January 2022 and 31 December 2023, were excluded from the dataset used for training and testing in order to conduct a sentiment analysis with them later. The dataset includes 4835 reviews after the reviews from the specified period were excluded.  
Negative reviews were considered as those with a rating of 1 or 2, neutral reviews were considered as those with a rating of 3, while positive reviews were considered as those with a rating of 4 or 5. An attribute called \"_Sentiment_\" was added to the dataset to reflect the sentiment of each review (_negative/neutral/positive_).
## 2 Experimental Test Overview  
### Design and Fabrication of Specim  
As part of the specimen configuration, the electrical cabinet model was anchored to a concrete foundation with a design strength of 27 MPa and a thickness of 150 mm, considering the structural design of NPP facilities and testing requirements. Field surveys confirmed that typical electrical cabinets are anchored using 4 to 8 anchor bolts, generally ranging from M10 to M12 in size. To represent a conservative and more vulnerable anchor age condition, four M10 anchor bolts were employed. The anchor bolts were fabricated in accordance with ACI standards and ASTM A36 specifications and installed using a cast-in-place method integrated into the concrete foundation [38; 39]. The embedment depth was set at 80 mm, considering the concrete foundation thickness.  
In grouped installations of multiple electrical cabinets, collective systems exhibit internal damping and energy dissipation. Accordingly, the ICRS and dynamic behavior can be reasonably represented by evaluating a single cabinet [40; 41; 42]. To simulate a vulnerable condition, the specimen was configured as an independent, single-bay installation, deliberately excluding grouping effects. The dynamic characteristics of the electrical cabinet model were designed with reference to previous shaking table tests conducted to assess the seismic performance of safety-related electrical equipment in Korean-type NPPs [43; 44]. As synthesized in Table 1, this equipment exhibits an average resonant frequency of approximately 18 Hz. Moreover, field tests using an impact hammer on actual NPP equipment indicated an average frequency range of 15-17 Hz. The specimen adopted an MCC configuration, and the target natural frequency range was set between 15 and 18 Hz, based on both experimental and field measurements. Stiffeners were installed at the anchorage to establish directional stiffness along weak and strong axes in the horizontal plane, ensuring that the first and second mode frequencies fell within the designated range. A preliminary numerical model was created using the numerical analysis software ABAQUS version 6.14 to guide the design and fabrication process. Rectangular hollow sections conforming to KS D 3568 were selected, with adjusted dimensions and mass properties to achieve the target dynamic characteristics [45]. For the eigenvalue analysis, the cabinet base was modeled as a fully fixed support. The final specimen geometry and configuration, as illustrated in Figure 3, were determined based on stiffness and mass distribution.  
Figure 3: Drawings of specimens.
# An Innovative and Efficient Method for Reverse Design of Wheel-Rail Profiles
## 3 Reverse Profile Design Method  
Reverse profile design comprises three parts: reverse design of wheel profiles, reverse design of symmetric rail profiles and reverse design of non-symmetric rail profiles. The three methods for designing profiles are similar; the following shows the reverse design of wheel profiles for reference.  
Figure 4: Wheel-rail contact for wheel profile of Line 2.  
A reverse design model for wheel profiles can be established based on the given rolling radius difference, initial wheel-rail contact point and its wheel profile shape away from the flange side (the wheel profile gradient is greater than 0). The initial wheel-rail contact point and its wheel profile shape away from the flange side are adopted herein for constraining the profile at one side, thus the designed wheel profile can meet the requirement through adjusting the profile of the other side.
# Evaluating Preprocessing Techniques for Unsupervised Mode Detection in Irish Traditional Music
## 4 Results and Discussion
### PCP Configuration Experiments
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **Simple+LLE** & **Weighted+LLE** & **Simple+UMAP** & **Weighted+UMAP** \\ \hline \multirow{2}{*}{**K-Means**} & NMI & 0.3333 & 0.1838 & **0.5322** & 0.3868 \\ \cline{2-6}  & ARI & 0.2442 & 0.0793 & **0.4339** & 0.2942 \\ \hline \multirow{2}{*}{**Agglom.**} & NMI & 0.3453 & 0.1216 & 0.5081 & 0.4048 \\ \cline{2-6}  & ARI & 0.2752 & 0.0342 & 0.4110 & 0.3270 \\ \hline \multirow{2}{*}{**DBSCAN**} & NMI & 0.0 & 0.0 & 0.4702 & 0.0 \\ \cline{2-6}  & ARI & 0.0 & 0.0 & 0.3085 & 0.0 \\ \hline \multirow{2}{*}{**Mean Shift**} & NMI & 0.0 & 0.0 & 0.4625 & 0.0 \\ \cline{2-6}  & ARI & 0.0 & 0.0 & 0.2986 & 0.0 \\ \hline \multirow{2}{*}{**SOM**} & NMI & 0.0 & 0.0 & **0.5165** & 0.3647 \\ \cline{2-6}  & ARI & 0.0 & 0.0 & **0.4672** & 0.2387 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: NMI and ARI scores for different classifiers using simple and weighted PCPs combined with LLE and UMAP reduction algorithms. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & & **Simple PCP** & **Weighted PCP** & **Binary PCP** \\ \hline \multirow{2}{*}{**K-Means**} & NMI & 0.2535 & 0.2535 & **0.5807** \\ \cline{2-5}  & ARI & 0.65 & 0.1657 & **0.5626** \\ \hline \multirow{2}{*}{**Agglom.**} & NMI & 0.2348 & 0.2348 & **0.5976** \\ \cline{2-5}  & ARI & 0.52 & 0.1909 & **0.5756** \\ \hline \multirow{2}{*}{**DBSCAN**} & NMI & 0.0 & 0.0 & 0.0 \\ \cline{2-5}  & ARI & 0.98 & 0.0 & 0.0 \\ \hline \multirow{2}{*}{**Mean Shift**} & NMI & 0.0 & 0.0 & 0.0 \\ \cline{2-5}  & ARI & 0.75 & 0.0 & 0.0 \\ \hline \multirow{2}{*}{**SOM**} & NMI & 0.0 & 0.0 & 0.5105 \\ \cline{2-5}  & ARI & 1.00 & 0.0 & 0.4065 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: NMI and ARI scores for different clustering methods across PCP representations. reinforce that the best-performing configurations not only achieved higher purity but also exhibited superior cluster alignment, as reflected in their NMI and ARI scores.
# Application of Fly Ash Obtained from the Incineration of Municipal Solid Waste in Agriculture
## 4 Physico-Chemical Properties of Fly Ash  
The bulk density of fly ash (0.95-1.75 g/cm\({}^{3}\)) decreases with decreasing ash separation temperature; fly ash has a specific gravity of 1.1-2.7 [47].  
The higher the temperature, the more the structural aspect of the ash particles has a spherical shape, crystalline salts precipitate on the silicate spheres; at low temperatures, the particles have an irregular shape [48,49].  
Spherical particles of ash have a diameter smaller than 10 \(\upmu\)m, a low density, and a light texture. The ash contains the following nutrients for the soil: silicon, magnesium, calcium, iron, aluminum, sodium, and potassium.  
Onions were planted on soil to which different concentrations of ash were added; no ash was added to the control soil, then ash was added from 1 t/ha to 15 t/ha (Table 3). When adding ash to the soil, the pH values increased from 7 to 8.2, the electrical conductivity of the soil increased, but the cation exchange capacity (CEC) remained almost unchanged. The values of organic carbon and organic matter increased slightly, the water holding capacity (WHC) of the soils also increased [50] (Table 3). The addition of fly ash to soil improves the physical [51], chemical, and biological properties of the soil, soil texture, bulk density, soil porosity, reduces soil compactness, changes particle size distribution, and can improve soil affected by mining activities [52; 53]. Soil porosity and water retention capacity in sandy soils increased when a percentage of 40% fly ash was added to the soil, improving plant growth [51].  
Fly ash was added in the proportions of 10, 20, 30, 40, and 50% to the soil to see the variation of the pH and electrical conductivity of the soil where leguminous crops grow. The specific gravity of the fly ash sample was 2.21 g/cm\({}^{2}\) and the bulk density was 1.32 g/cm\({}^{2}\) in the dry state and 1.22 g/cm\({}^{2}\) in the wet state. It was observed that the pH of the fly ash sample was 7.56 and that of the soil was 6.65. With the increase in fly ash concentration in the soil, the pH increases, and the electrical conductivity also increases from 281 to 600 \(\upmu\)s/cm [54] (Table 4).
# A Study on Tomato Disease and Pest Detection Method
###### Abstract  
In recent years, with the rapid development of artificial intelligence technology, computer vision-based pest detection technology has been widely used in agricultural production. Tomato diseases and pests are serious problems affecting tomato yield and quality, so it is important to detect them quickly and accurately. In this paper, we propose a tomato disease and pest detection model based on an improved YOLOv5n to overcome the problems of low accuracy and large model size in traditional pest detection methods. Firstly, we use the Efficient Vision Transformer as the feature extraction backbone network to reduce model parameters and computational complexity while improving detection accuracy, thus solving the problems of poor real-time performance and model deployment. Second, we replace the original nearest neighbor interpolation upsampling module with the lightweight general-purpose upsampling operator Content-Aware ReAssembly of FEatures to reduce feature information loss during upsampling. Finally, we use Wise-IoU instead of the original CIoU as the regression loss function of the target bounding box to improve the regression prediction accuracy of the predicted bounding box while accelerating the convergence speed of the regression loss function. We perform statistical analysis on the experimental results of tomato diseases and pests under data augmentation conditions. The results show that the improved algorithm improves mAP50 and mAP50:95 by 2.3% and 1.7%, respectively, while reducing the number of model parameters by 0.4 M and the computational complexity by 0.9 GFLOPs. The improved model has a parameter count of only 1.6 M and a computational complexity of only 3.3 GFLOPs, demonstrating a certain advantage over other mainstream object detection algorithms in terms of detection accuracy, model parameter count, and computational complexity. The experimental results show that this method is suitable for the early detection of tomato diseases and pests.  
identification of pests and diseases; object detection; YOLOv5; WIoU Loss; CARAFE; EfficientViT 2023
# Compact Midwave Imaging System: Results from an Airborne Demonstration
## 4 Discussion  
The CMIS instrument provides three angular views at 3.75 um, wide-swath coverage and day-night sensing, compatible with a compact 6U-CubeSat design to enable global coverage of the winds and cloud heights in the free troposphere and PBL. Stereo sensing at a wavelength of 3.75 um permits 24/7 day/night sensing to observe diurnal variation of PBL structures. However, when the clouds are moving in the direction of the spacecraft velocity vector, the stereo technique applied to a single LEO satellite suffers from an aliasing problem in which errors in AT wind and CTH are highly correlated, as is known from MISR [9] and now discussed here. To resolve this ambiguity, stereo imaging requires independent observations from multiple platforms (i.e., joint retrievals). This joint technique can be applied to LEO-LEO platforms or LEO-GEO platforms. It would also be most relevant for a series of CubeSats in a leader-follower configuration (i.e., pearls on a string).  
The stereo methodology applied to LEO-LEO satellites is particularly valuable for the polar regions where detection of low-level clouds and semi-transparent clouds is a major challenge for satellite remote sensing. The most accurate method for retrievals at high latitudes could potentially be leader-follower satellites if favorable viewing geometries and optimized spacecraft separation times are maintained. The airborne flights presented here proved the sensitivity of CMIS to detect patterns in PBL clouds for stereo retrievals in the mid-latitudes. Provided sufficient variability in cloud radiance exists for pattern matching, this technique should also work well in the Arctic and Antarctic. Due to frequent turbulence and course corrections, retrievals from an aircraft are much more difficult to do accurately than from space.  
Figure 19: Histograms show the wind retrievals passing the quality criteria. The AT winds are very close to the prior value used.
# BeiDou Geostationary Satellite Code Bias Modeling Using Fengyun-3C Onboard Measurements
## 3 Results
### The Effect on Single-Frequency BDS Orbit Determination of Fengyun-3C
In addition, the relatively lower precision of BDS products is also an inevitable problem for orbit determination. \begin{table}
\begin{tabular}{c c} \hline \hline
**Items** & **Description** \\ \hline Gravity model & EIGEN-06\(C\), up to degree and order 120 for static \\  & field and 50 for time-varying gravity \\  & IERS 2010 [23] \\   Earth orientation & IERS C-04 [24] \\   Solid Earth tide and pole tide & IERS 2010 [23] \\   Ocean tide & FES2004 30 \(\times\) 30 [25] \\   Ocean pole tides & Desai [26] \\   N-body perturbation & JPL DE405 \\   Relativity & IERS 2010 [23] \\   Solar radiation pressure & Box-wing model \\   Atmosphere drag & DTM2013 [27], piece-wise drag coefficients estimated \\   Attitude & Normal \\ Fengyun-3C PCO (X/Y/Z: m) \& PCV \\   BDS PCO \& PCV \\   Empirical forces & piece-wise periodical terms in along- and cross-track \\   Direction estimated every 360 min \\   BDS observation type & B1 \\   Observation interval & 30 s \\   BDS orbit and clock & Wuhan University precise products (30-s clock) \\   ionosphere delay & Graphic combination \\   orbit determination arc length & 30 h \\   Elevation cutoff & 0\({}^{\circ}\) \\   Fengyun-3C initial state & Position and velocity at initial epoch \\   Receiver clock & One per epoch as process noise \\   Ambiguities & One per pass \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of the dynamical and measurement models employed for the Fengyun-3C orbit determination solutions based on onboard BDS data.
# Medical Applications of the GEMPix
## 5 Proton Tomography  
With the increasing number of proton therapy centres there is a renewed interest in proton tomography [48; 49; 50]. Preliminary tests with two GEMPix operated as TPCs were performed to measure the position, direction and energy of protons traversing an object in order to reconstruct an image of it. The setup consists of two GEMPix-based TPCs with a Timepix3 (instead of the usual Timepix) quadboard as tracker and a BaF\({}_{2}\) crystal for measurement of the residual proton energy. The results presented in this section are published in [25].  
Figure 11 shows the setup. A phantom was placed between the two tracking devices to try and measure the performance and spatial resolution of the system. The phantom and the reconstructed image are shown in Figure 12. Although the sensitive volume of the TPC is 5 \(\times\) 5 \(\times\) 5 cm\({}^{3}\) (yielding sufficiently long tracks for measuring the incident angle of the particle) and the improved temporal resolution of the Timepix3 is included (drift coordinate precision), the angular resolution is still not optimal for the phantom image reconstruction. These uncertainties on the track reconstruction are dominated by the clustering effect of the triple-GEM structure and the inhomogeneity of the electric field inside the TPC.  
Figure 11: The experimental setup for proton radiography [25].  
Figure 10: In this 3D representation of the dose, the carbon ion beam enters from the left. Lateral spread out, Bragg peak and fragmentation tail are visible.  
In order to improve the performance of the system, an algorithm finding the location of the primary ionization would be needed. The track fit using only the location of the primary ionization will be more realistic than using all the hits of the clusters. Another possible improvement could be an optimized triple-GEM configuration and the use of a gas mixture generating less lateral diffusion. The final angular resolution obtained with the current set-up is 30.7 mrad in the xy-plane and 23.4 mrad in the xy-plane. Once the above-mentioned issues are solved and an angular resolution below 1 mrad is reached, a step towards proton-CT can be investigated by irradiating the phantom from different angles. A 3-dimensional energy density map could then be reconstructed to improve future proton therapy treatment plans.