esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis of Finite Element Simulation Results  
### Hysteresis Curve and Skeleton Curve  
The reaction-displacement (P-\(\Delta\)) hysteresis curves and the skeleton curves of the structure under a low reciprocal circumferential load are shown in Figure 4. The hysteresis curves reveal that during the initial stage of loading, the curves appear mostly straight and overlap. The absence of noticeable changes in the joint stiffnesses further supports the conclusion that both the prefabricated joint and the cast-in-place joint remained in the elastic stage. As the horizontal displacement increases, the hysteresis curves begin to bend, resulting in a gradual decrease in the stiffness of both joints. In both hysteresis loops, the area of the hysteresis loop increases, and the structure begins to exhibit residual deformation through the curve. At this stage, the maximum bearing capacity of the prefabricated joint is noticeably higher than that of the cast-in-place joint.  
Figure 4: Hysteresis and skeleton curves of the joints: (**a**) hysteresis curves; (**b**) skeleton curves.  
Figure 3: Boundary conditions and loading method.  
The displacement-load skeleton curves show that the ultimate bearing capacity of the prefabricated joint was 141.77 kN under a low circumferential reciprocal load, and the ultimate bearing capacity of the prefabricated joint was 107.62 kN. In other words, the prefabricated joint exhibited a 31.7% higher ultimate bearing capacity compared with its cast-in-place counterpart. The reason for this is that the prefabricated joint restricted the deformation of the concrete members due to the addition of steel sections, thus delaying the breaking of the concrete, while the steel sections themselves had higher strengths, so the ultimate bearing capacity of the pre-fabricated joint was increased. It is evident that the cast-in-place joint experienced a more pronounced decrease in its bearing capacity after reaching its ultimate bearing capacity. The subsequent loading cycles showed a 16.6% decrease in the bearing capacity compared with the final bearing capacity cycle. In contrast, the prefabricated joint showed a lesser decrease in its bearing capacity, with a decrease of only 8.9%. This shows the better ductility of the prefabricated joint, as it was able to support a higher percentage of its ultimate bearing capacity even under subsequent load cycles.
## 3 Results and Discussion
### Comparison of the Spatial Distribution of Errors in Estimating Soil Temperature
Based on T\({}_{\text{mean}}\), the factor R\({}_{\text{s}}\) had a greater influence on the accuracy of each model than several other meteorological factors, followed by RHand U\({}_{2}\). Because this research estimated T\({}_{\rm s}\) at 0 cm depth, the air temperature was most closely related to T\({}_{\rm s}\)[64]. However, the greater degree of influence of R\({}_{\rm s}\) might be due to the source of soil heat. T\({}_{\rm s}\) is one of the components of soil heat. However, soil heat is mainly formed by solar radiation, heat emitted from the Earth's interior, and heat generated by the decomposition of microorganisms in the soil [65]. Of these, solar radiation dominates. Therefore, R\({}_{\rm s}\) had a greater degree of influence in estimating T\({}_{\rm s}\). [PERSON] et al. [66] and [PERSON] et al. [67] also concluded that T\({}_{\rm mean}\) was significantly relevant in estimating T\({}_{\rm s}\). It suggested that the input combination of T\({}_{\rm mean}\) and R\({}_{\rm s}\) was the most generalizable for studies estimating T\({}_{\rm s}\) in the different climatic zones of China.
## 3 Risk Identification during Navigation
### Collision Risk Judgment Method  
If the OS and the TS maintain their course and speed, ultimately, the TS will eventually enter the OS's ship domain, and a potential collision risk (PCR) is thought to exist. In this study, the term \"keep course and speed\" also means that ships in the TSS consistently follow the channel's general direction of traffic flow. The time threshold for entering the OS's ship domain, as well as the PCR between OS and TS, are utilized to assess if a collision risk exists in the TSS waters. The threshold value (\(T_{s1}\)) can be modified by the master based on the ship's actual sailing conditions. In this study, it is set as 1800 s.  
The collision risk index (CRI) is a physical quantity determined by the relationship between the maneuvering features, locations, and motions of the two ships to indicate the risk of collision and the necessity of implementing anti-collision actions. It is separated into a two categories-time collision risk index (TCRI) and a space collision risk index (SCRI). TCRI and SCRI are combined to describe CRI. Equation (15) illustrates it:  
\[CR=CR_{t}\cdot CR_{s} \tag{15}\]  
where \(CR\) is the CRI value, \(CR_{t}\) is the TCRI value, and \(R_{s}\) is the SCRI value. When \(CR>0\), it shows the collision threat is arising, and a collision danger alert can be issued to remind the ship navigators.  
1. TCRI  
When there is a PCR exited, CRI is defined as the urgency with which one of the two ships in an encountering situation approaches the latest steering point [12]. The value of TCRI (\(CR_{t}\)) is calculated by Equation (16).  
\[CR_{t}=\begin{cases}1\ \  
be included in the computation. The aim of it is to prevent frequent steering decisions by the system caused by the targets very far away for which no collision avoidance actions are actually needed.
## 3 Measurement Results
### Tests of Medical Devices
#### 3.1.2 Infusion Device Analyser--Fluke IDA-1S  
The investigated Fluke IDA-1S a portable battery-powered (on-the-go) analyser that allows straightforward measurement of infusion pump performance. This device is used in hospitals, for example, to calibrate the large number of syringe pumps. With the IDA-1S it is possible to perform flow tests and occlusion pressure tests in a very simple way. The IDA-1S operates in a flow range from 0.5 mL h\({}^{-1}\) to 1000 mL h\({}^{-1}\) and a volume range from 0.06 mL to 999 mL. Furthermore, it has an occlusion pressure of up to 45 psi (3 bar). The measuring principle is essentially based on a miniature burette with infrared sensors along its length and sophisticated electronics basically track the flow, which is immediately displayed by the device. The manufacturer recommends the use of distilled water for the tests. The additional use of low concentration detergent (Micro-90) reduces the surface tension, which leads to an improved accuracy. During a test, the measurement data is continuously updated and stored in the device. The complimentary software (HydroGraph) allows for operating the unit remotely and storing the data on a computer.  
Figure 8 shows a typical graph during a test, which is produced on the computer and displayed in real time by means of the HydroGraph software. The constantly updating graph directly helps to assess the performance of the infusion device under test. It is recommended by the manufacturer to perform tests with a volume delivery of 10 mL or 20 mL depending on the flow rates to be tested. The example shows a measurement at a flow rate of 1 mL h\({}^{-1}\) over a period of about 2 h. Despite the much lower volume delivered (2 mL), the use of a very stable flow generator along with calibrated syringes shows that, in most cases, even shorter measurement times provide sufficiently accurate measurement results.  
Figure 7: Measurement results of the BBraun syringe pump for measurements over three day (72 h) for a preset flow rate of 0.01 mL h\({}^{-1}\) using a 10 mL disposable syringe.
# State-of-the-Art DC-DC Converters for Satellite Applications: A Comprehensive Review
## 3 Review of DC-DC Converters for Satellites
### DC-DC Converters for Electric Propulsion
[125] proposed a combined dual modulation scheme for an all-electric propulsion system. The lower RMS or peak current under ZVS due to the combined dual modulation helps achieve high efficiency and good transient response throughout the whole operating range of the converter. Furthermore, it performs well against EMI noise as well. The control scheme was validated using a 1 kW-5 kW DAB converter [125]. A two-stage DC-DC converter comprising a four-switch interleaved buck-boost converter and an LLC resonant converter was proposed in [126] for high-power PPU in an ion propulsion system. The interleaving method used in the first stage reduced the magnitude of the magnetic components, and the soft-switched LLC resonant converter improved efficiency. Furthermore, using transformer leakage inductance as resonant inductance offered a high power density. A 1.2 kW prototype demonstrated good efficiency and power density. The first stage of the converter is shown in Figure 19, and a comparison of topologies for EP based on switching frequency, component count, and power is presented in Table 4.  
Figure 19: Four-switch interleaved buck–boost converter.
## 3 Experimental Results and Discussion
### Pore Structure  
Due to the fact that NMR could only measure the pore size distribution of the repaired concrete specimens, the remediation effect of surface reinforcer under different layer depths could not reveal the effect that four applications and 7 d action duration had, and the pore structure of the specimen repaired by surface reinforcer type A was estimated by measuring the pore structure on the surface (0 mm in depth), at a depth of 10 mm and at a depth of 20 mm, respectively. Specim cutting positions were shown in Figure 6.  
Figure 7 presented the pore morphology and pore parameters of the repaired specimens at different depths. It could be observed that air content, spacing, and average chord length on the surface of repaired specimens increased gradually, and the specific surface area decreased gradually with increased depth. Specifically, the air content was 12.3% on the surface of repaired concrete specimens, and the values were 13.95%, and 15.77% at depths of 10 mm and 20 mm, respectively, with increases of 13.4% and 28.2%, respectively. The spacing factor and average chord length of the repaired specimens at 20 mm depth  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Specimen Number** & **Harmless Pores** & **Less-Harmful Pores** & **Harmful Pores** & **Multi-Harmful Pores** \\ \hline S-1 & 70 & 16 & 2 & 12 \\ D-1 & 67 & 17 & 5 & 11 \\ A-4-7 & 70 & 17 & 5 & 8 \\ B-4-7 & 70 & 17 & 3 & 10 \\ C-4-7 & 69 & 17 & 4 & 10 \\ A-4-3 & 69 & 17 & 5 & 9 \\ A-4-14 & 77 & 14 & 2 & 7 \\ A-2-7 & 71 & 16 & 4 & 9 \\ \hline \hlinewere 1.33 times and 1.43 times higher than those at the surface position. Additionally, the specific surface area decreased from 6.15 mm\({}^{-1}\) to 4.3 mm\({}^{-1}\) when the depth increased from 0 mm to 20 mm, which reduced by a larger scale of 30%.  
The above data clearly illustrate that the repair effect of surface reinforcers gradually decreased with an increase in the action depth. In addition, in this research the pore structure parameters could be significantly improved within 10 mm depth.
## 2 Materials and Methods
### Continuous-Time Problem Setting  
The continuous-time case is formulated around the variables that stand for the start moments of each operation \(i\) of each order \(f\): \(x_{if}\geq 0\), \(i=1,\ldots,|J|\), \(f=1,\ldots,|F|\)[3]. The variables \(x_{if}\geq 0\) can be combined into \(|F|\) vectors \(\overrightarrow{x_{f}}\geq 0\). The main constraints of the optimization problem in that case are:  
* Precedence graph of the manufacturing procedure: \[G\overrightarrow{x_{f}}\geq(\overrightarrow{x_{f}}+\overrightarrow{\tau}),\qquad f=1,\ldots,|F|.\]
* Meeting deadlines for all orders \[x_{|J|f}+\tau_{|J|}\leq d_{f},\qquad f=1,\ldots,|F|.\]The constraints above do not take into consideration the competition of operations that try to allocate the same resource. We can distinguish two types of competition here: competition of operations within one order and competition of operations of different orders. The competition of operations on parallel branches of one order is considered separately by modelling the scheduling problem for a single order (this is out of the scope of this paper). The main scope of this research is to address the competition of operations from different orders. Assuming we have the rule (constraint) that considers the competition of operations within one and the same order let us formalize the competition between the operations of different orders. Consider we have a resource, which is being allocated by \(K\) different operations of \(|F|\) different orders.  
For each resource \(r=1,\ldots,|R|\) let us distinguish only those operations that allocate it during their run. The set of such operations can be found from the corresponding column of the resource allocation matrix \(Op=<op_{ir}>,\;\;i=1,\ldots,|I|,\;\;r=1,\ldots,|R|\).  
\[x^{r}=x|col_{r}(Op)=1.\]  
The example for two competing operations of two different orders is shown in Figure 1.  
For each resource \(r=1,\ldots,|R|\) each competing operation \(i=index(x^{r})=1,\ldots,K\) of order \(f=1,\ldots,|F|\) will compete with all other competing operations of all other orders, i.e., going back to the example depicted in Figure 1 we will have the following constraint for each pair of operations:  
\[x_{i\varphi}\geq x_{j\psi}+\tau_{j}\ XOR\;x_{j\psi}\geq x_{i\varphi}+\tau_{i},\]  
where indexes are as follows \(i,j=1,\ldots,K\); \(\varphi,\psi=1,\ldots,|F|\); \(\varphi\
eq\psi\). Implementing an additional Boolean variable \(c_{k}\in\{0,1\}\) will convert each pair of constraints into one single formula:  
\[c_{k}\cdot x_{i,\varphi}+(1-c_{k})\cdot x_{j\psi}\geq c_{k}\cdot(x_{j\psi}+ \tau_{j})+(1-c_{k})\cdot(x_{i\varphi}+\tau_{i}).\]  
From the above precedence constraints, we can form the following set of constraints for the optimization problem:  
where the variables \(x_{if}>0\), \(f=1,\ldots,|F|\), \(i=1,\ldots,|J|\) are continuous and represent the start times of each operation of each order; and variables \(c_{k}\in\{0,1\}\), \(k=1,\ldots,K\) are Boolean and represent the position of each competing operation among other competitors for each resource.
## 2 Materials and Methods
### Calculation of FET Mobility and Four-Point Sheet Conductance Measurement  
We calculated the FET mobility based on the assumption that, above the threshold voltage \(V_{T}\), the drain current, \(I_{D}\), increases linearly with carrier concentration, \(C_{i}(V_{G}-V_{T})\), with the FET mobility being a proportional constant, as expressed in Equation (1),  
\[I_{D}=\frac{Z}{L}\mu C_{i}(V_{G}-V_{T})V_{D} \tag{1}\]  
where \(C_{i}\), \(Z\) and \(L\) are the areal capacitance, the width, and the channel length of the device, respectively. The FET mobility was calculated from the slope in the linear regime in which the drain current increases linearly with the gate voltage (\(V_{G}\)) in the \(I_{D}-V_{G}\) plot.  
To rule out the P3 HT/Au contact effect, we used gated four-contact geometry FET devices in which two voltage probes are placed between the source and drain electrodes to measure the potential in the P3 HT channel. We measured the potential difference (\(V_{diff}\)) from the voltages at two probes spaced by \(d\) with the FET being in \"on\" state, in which a gate voltage above the threshold voltage is applied to induce mobile charge carriers in the channel. The sheet conductance (\(\sigma_{sq}\)) was estimated at a certain drain current from Equation (2):  
\[\sigma_{sq}=\frac{d}{W}\frac{I_{D}}{V_{diff}} \tag{2}\]  
The four-contact field-effect mobility is calculated from the plot of the sheet conductance as a function of gate voltage, as shown in Equation (3):  
\[\mu=\frac{1}{C_{i}}\cdot\frac{d\sigma_{sq}}{dV_{G}} \tag{3}\]
# Recent Advances and Applications of Semiconductor Photocatalytic Technology
## 5 Methods for Improving Photocatalytic Efficiency
### Metal or Non-Metal Ion Doping
#### 5.3.2 Non-Metal Ion Doping
Multi-component non-metal doping can also improve the catalytic ability of TiO\({}_{2}\) to some extent. [PERSON] et al. [319] used a one-step hydrothermal method to synthesize C and N element co-doped TiO\({}_{2}\) photocatalysts, and they used different molar concentrations of glycine to make the materials contain different proportions of brookite/anatase. Under visible light irradiation, the degradation rate of pure TiO\({}_{2}\) to ibuprofen was only 11.1%, but the degradation rate of C-N-TiO\({}_{2}\) was 100%. Figure 7: **(A)** UV-Vis spectra of TiO\({}_{2\times}\)N\({}_{x}\) and TiO\({}_{2}\) and **(B)** the photocatalytic property of acetaldehyde [285]. [PERSON] et al. [320] synthesized a TiO\({}_{2}\) photocatalyst co-doped with fluorine and graphene oxide by the hydrothermal method. The decomposition rate of bromate by the complex TiO\({}_{2}\) photocatalyst was found to exceed 90% after UV irradiation for 15 min. The doping of fluoride ions can increase the number of high surface energy (001) crystal planes of TiO\({}_{2}\), while doped graphene oxide gives TiO\({}_{2}\) excellent conductivity and large specific surface area. Therefore, after introducing fluoride ions and graphene oxide, the transfer efficiency of photogenerated electrons can be effectively accelerated, and the photocatalytic efficiency can be improved.
## 3 Results
### Systematic Content Review Results for Sensors Monitoring Mine Tailings Storage Facilities
#### 3.3.1 Content-Based Data Perspective Analysis
The following abbreviations are used for various elements: (i) the space scale of data measurement (Remote, R; On-site, OS; or Not specified, NS), (ii) operation (Real-time automatic, RTA; Not real-time/manual, NRTM; or Not specified, NS), (iii) connectivity (Satellite, S; Zigbee, Z; 4G, 4G; SigFox, SF; Other, O; or Not specified, NS), (iv) TSF area (Dam, D; Reservoir level, RL; Tailings beach, TB; or Not specified, NS), (v) engineering discipline (Geotechnics, G; Mining, M; Civil, C; Other, O; or Not specified), (vi) use of cables or wireless (Cables, C; Wireless, W; or Not specified, NS), (vii) Industry 4.0 technology (Internet of Things, IoT; Cloud computing, CC; Artificial intelligence, AI; Unmanned aerial vehicles, UAVs; Other, O; or Not specified, NS), and (viii) cost (USD) (Yes, Y, or Not specified, NS). Based on the analysis summarized in Table 5, the following findings emerge:  
* Regarding the space scale of data measurements, 67% of the cases involve remote measurements, while 29% utilize on-site measurements, and the remaining 4% of the documents do not specify. There is a clear tendency toward remote systems with sensors (telemetry technologies) for mine TSF monitoring. * When studying the type of operation of sensor systems, 90% of the studies mention automatic applications with real-time data collection, and 2% indicate manual non-real-time data collection. Finally, 8% of the documents do not specify the operation information. This shows that monitoring mine TSF activities in real time is preferred. * Regarding the connectivity of sensor systems, 21% of the documents mention satellite, 15% mention Zigbee, 17% mention 4G, 10% do not specify a connectivity method, and 42% mention other applications. This shows a tendency to use wireless sensor connections in mine TSF monitoring applications. * Analyzing the area of the mine TSF where sensor systems are applied reveals that 27% are applied in the dam area, 23% in the reservoir level area, 13% in the tailings beach area, 17% in unspecified areas, and 19% in other areas of the TSF. This affirms that the current monitoring emphasis in TSFs with sensor systems is on the dam and reservoir areas. * Regarding engineering disciplines, the discipline mentioned most often is geotechnics, at 19%, then mining at 15%, civil engineering at 13%, and others at 52%, including the emerging discipline of data science. This shows that structural stability aspects are a priority in the use of sensor systems in mining. * Considering the use of sensors with wired or wireless connections, 67% of the cases indicate wireless connections, while 13% correspond to cable connections, and 19% are unspecified. This demonstrates a clear trend toward the use of wireless sensor systems, reflecting the application of IoT and Industry 4.0 technologies.
## 4 Experimental Results  
### Datasets and Processing Platform  
Even though there are extensive color video/image datasets for pedestrian detection, only a small number of thermal infrared pedestrian datasets are available. In this study, we evaluate our proposed AED-CNN on the widely used KMU [21] and CVC-09 [22] pedestrian datasets.  
The KMU was captured by a far infrared (FIR) camera from moving vehicles (at 20 to 30 km/h) during the summer and winter nights for pedestrian detection. The training data contains 4474 positive images and 3405 negative images. The positive images include pedestrians with various sizes and postures. The negative images were generated through random cropping from the background. The testing data contains 5045 images of the same size of \(640\times 480\), including pedestrians with various activities under different weather conditions, such as walking down the sidewalk or crossing the road in hot summer as well as in cold winter.  
The CVC-09 FIR sequence pedestrian dataset was collected using a FIR camera mounted on a car roof during summer days. This dataset is more challenging since it comprises pedestrians with varying moving speeds, a variety of motions, all types of poses, changeable thermal energy, and partial or full occlusions at night. The CVC-09 contains 5309 positive images and 2115 negative images for training, 5763 images for testing, with the same size of \(640\times 480\).  
For both KMU and CVC-09 datasets, the pedestrian images of different scales are combined for training. The experiments are performed on a standard computer under Ubuntu 14.04 with a core i7-6850k 3.6 GHz central processing unit (CPU) and 64 GB random-access memory. For the graphics processing unit (GPU), we used three NVIDIA Titan X for training and a single Nvidia Titan X for testing. Our codes are built on Caffe which requires a compute unified device architecture (CUDA) and CUDA deep neural network library (cuDNN).
# A Web-Based Application for Smart City Data Analysis and Visualization
## 4 Experimental Protocol: System Implementation
### Dataset Management and Description
#### 4.1.2 Traffic and Vehicle Data  
Transportation-related sensors enable analysis of mobility patterns and congestion:  
Vehicle counts register the number of vehicles passing through monitored zones, frequently broken down by type, e.g., cars, trucks, motorcycles.  
Speed measurements capture average and peak vehicle speeds, supporting traffic jam analysis and evaluating traffic control policies.
# Vibration Compensation of the Frequency-Scanning-Interferometry-Based Absolute Ranging System
## 3 Experiments and Results
### Vibration in Natural Environment  
When the target and the measurement system were placed on the same platform, there was a little effect of vibration on a distance value. On the other hand, when the target and collimation lens were placed on two optical platforms having different heights, as shown in Figure 7, the effect of vibration in the natural environment was not negligible. Other experimental facilities and parameters are the same as previous experiments. The measurement results are shown in Figure 8. Obviously, the tiny displacement of the target was magnified, which resulted in a reduction in the ranging accuracy. For 20 repeated measurements, after the vibration compensation, the standard deviation was 11 \(\upmu\)m, which was a much better result than that without the vibration compensation; namely, the standard deviation before vibration compensation was 289 \(\upmu\)m.  
Figure 5: Error and standard deviation at different average velocities (after the vibration compensation).  
Figure 6: Error and standard deviation at different vibration frequencies (after the vibration compensation).