esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
In recent years, new-generation SAR constellations such as the PIESAT constellation, Siwei Gaojing constellation, Taijing constellation, and Tianyi constellation have been successively established, featuring high revisit rates and high-resolution imaging capabilities, further expanding the practical applications of InSAR in disaster monitoring, urban management, and national land surveying. Looking forward, China is actively planning new systems, including P-band SAR, dual-antenna InSAR, geosynchronous orbit satellites, and High-Resolution Wide-Swath (HRWS) satellites, continuously promoting the enhancement of constellation deployment and multi-frequency collaborative observation capabilities. This article examines emerging trends in interferometric synthetic aperture radar technology and systems. It mainly starts with repeat-pass interferometry and single-pass interferometry and goes on to explore new technologies of synthetic aperture radar interferometric measurement. Figure 1: Development history of the world’s major space-borne InSAR systems and technologies.
###### Abstract  
Microbially induced carbonate precipitation (MICP) driven by _Sporosarcina pasteurii_ was highly efficient for heavy metal (i.e., Cd\({}^{2+}\), Cu\({}^{2+}\) and Pb\({}^{2+}\)) removal in the range of 50 to 800 mg/L. _Sporosarcina pasteurii_ bacteria were sequentially inoculated in nutrient bronds amended with increased concentrations of heavy metals separately to improve the resistance to heavy metal environments. In the absence of Ca\({}^{2+}\), the increasing urea concentration was conducive to Cd\({}^{2+}\) removal with the best removal ratio 89.9-99.7% at a urea concentration of 2.0 mol/L, but had little positive effect on Cu\({}^{2+}\) and Pb\({}^{2+}\) removal, with a removal ratio of 62.6-64.4% and 71.4-97.6%, respectively, at a urea concentration of 0.5 mol/L. The heavy metal coprecipitated with Ca\({}^{2+}\), leading to much more effective heavy metal removal, and the removal efficiency of Cd\({}^{2+}\), Cu\({}^{2+}\) and Pb\({}^{2+}\) could reach 98.0-99.0, 78.1-82.1 and 98.0-100.0%, respectively. The Cu\({}^{2+}\) deposit aggregated and cemented to form clusters, different from Cd\({}^{2+}\) and Pb\({}^{2+}\) deposits with comparatively dispersed microstructure. For all the three heavy metal precipitates, the predominant mineral was identified as calcite, the most thermodynamically stable polymorph of CaCO\({}_{3}\).  
microbially induced carbonate precipitation (MICP); biomineralization; _Sporosarcina pasteurii_; heavy metal Article
# Dimensioning of Reactive Power Compensation in an Autonomous Island System
###### Abstract  
In this paper, a method for sizing the reactive power compensation in a non-interconnected island power system is presented and applied to determine the necessary inductive reactive power compensation for the autonomous power system of Rhodes Island, Greece. The Rhodes power system is often confronted with an excess of reactive power, as a result--inter alia--of underground high-voltage (HV) cable lines and distributed generation penetration. Reactive power compensation is typically a local issue in power systems, usually aiming at maintaining an acceptable voltage profile on specific transmission segments, e.g., long underground or submarine cables. In autonomous systems, however, where network lengths are relatively short, reactive power compensation is meant to address the overall reactive power equilibrium of the system. The proposed method follows a three-step approach. First, power flow analysis is conducted to determine the size of the maximum compensation that may be necessary, i.e., the compensation size that practically allows unit commitment to be conducted without being constrained by reactive power considerations. Then, a unit commitment and economic dispatch model is executed over the course of a year to determine the optimal compensation size, using the output of the power flow analysis to formulate reactive power balance constraints. Finally, the results of the economic optimization are assessed in terms of dynamic security to verify the feasibility of the optimal solution.  
autonomous power systems; cost-benefit analysis; dynamic security; overvoltage stability; reactive compensation; unit commitment +
Footnote †: journal: Applied Sciences  
10 February 2022  
Accepted: 8 March 2022  
Published: 9 March 2022
## 1 Introduction
In addition to the above research, some scholars have also studied the displacement of the slope strengthened by supporting structure under the action of earthquake. Considering the reinforcement effect of a frame with a prestressed anchor on the slope, [PERSON] et al. [23; 24; 25; 26] established the analysis model of dynamic response and displacement of the slope under the action of earthquake, deduced its calculation theory, and put forward the analysis method of dynamic response and displacement of the slope strengthened by a frame with prestressed anchor under the action of earthquake. To sum up, it is not difficult to see that the existing research on the permanent displacement of slope under earthquake is mainly focused on the correction of the Newmark slider displacement calculation model, the development of empirical prediction models of permanent displacement, the establishment of the nested Newmark slider displacement calculation model with multiple slip surfaces and sliders, and the calculation for permanent displacement of single-stage slope strengthened by supporting structure. However, there are still some gaps in the theoretical calculation of the permanent displacement of multi-stage slope and multi-stage loess slope. At present, there are still some gaps in the theoretical calculation of the permanent displacement of multi-stage loess slope under the action of earthquake. Therefore, this paper firstly uses the GEO-Studio finite element software to explore the influence of the comprehensive slope rate on the permanent displacement when the slope rate of each grade of multi-stage loess slope changes and the stage of multi-stage slope changes. The results show that it is feasible to use the comprehensive slope rate to calculate the permanent displacement of the sliding body of multi-stage loess slope under the action of earthquake. On the basis of this conclusion, in order to simplify the calculation of permanent displacement of potential sliding soil, the other geometric parameters of multi-stage loess slope are replaced by the comprehensive slope rate, combined with Newmark slider displacement analysis method and energy conservation principle, and then the calculation method of permanent displacement of potential sliding soil of multi-stage loess slope under the action of earthquake is deduced. Through an example, the permanent displacement calculated by the proposed algorithm are compared with those calculated by PLAXIS 3D finite element software and GEO-Studio finite element software, and the rationality of the proposed method for calculating the permanent displacement of multi-stage loess slope under the action of earthquake is verified. The algorithm proposed in this paper provides a theoretical reference for the calculation of permanent displacement of multi-stage loess slope under the action of earthquake.
# Deterministic Coresets for \(k\)-Means of Big Sparse Data +
## 5 Coreset Construction  
Our main coreset construction algorithm \(k\)-\(\textsc{Mean-Coreset}(P,k,\varepsilon)\) gets a set \(P\) as input, and returns a \((k,\varepsilon)\)-coreset \((S,w)\); see Algorithm 1.  
To obtain running time that is linear in the input size, without loss of generality, we assume that \(P\) has \(|P|=k^{O(1/\varepsilon^{2})}\) points, and that the cardinality of the output \(S\) is \(|S|\leq|P|/2\). This is thanks to the traditional merge-and-reduce approach: given a stream of \(n\) points, we apply the coreset construction only on subsets of size \(2\cdot|S|\) from \(P\) during the streaming and reduce them by half. See Figure 1 and e.g., (4; 7) for details.  
Algorithm Overview  
In Line 1 we compute the smallest integer \(m=k^{t}\) such that the cost \(\text{opt}(P,m)\) of the \(m\)-means of \(P\) is close to the cost \(\text{opt}(P,mk)\) of the \((mk)\)-means of \(P\). In Line 3 we compute the corresponding partition \(\{P_{1},\cdots,P_{m}\}\) of \(P\) by its \(m\)-means \(Q_{m}=\{q_{1},\cdots,q_{m}\}\). In Line 5 a \((1,\varepsilon)\)-sparse coreset \(S_{i}\) ofsize \(O(1/\varepsilon^{2})\) is computed for every \(P_{i}\), \(i\in[m]\). This can be done deterministically e.g., by taking the mean of \(P_{i}\) as explained in Lemma 1 or by using a gradient descent algorithm, namely Frank-Wolfe, as explained in [22] which also preserves the sparsity of the coreset as desired by our main theorem. The output of the algorithm is the union of the means of all these coresets, with appropriate weight, which is the size of the coreset.  
The intuition behind the algorithm stems from the assumption that m-means clustering will have lower cost than \(k\)-means and this is actually supported by series of previous work [23; 24]. In fact our experiments in Section 7 evidence that in practice it actually works better than anticipated by theoretical bounds.  
```
Input: A weighted set \(P\) of points in \(\mathbb{R}^{d}\), integer \(k\geq 1\), and error parameter \(\varepsilon\in(0,1/4)\). Output: A \((k,\varepsilon)\)-coreset \(S\) for \(P\) that satisfies Theorem 1.
1 Compute the smallest integer \(t\geq 0\) such that \(\operatorname{opt}(P,k^{t})-\operatorname{opt}(P,k^{t+1})\leq\varepsilon^{2} \cdot\operatorname{opt}(P,k)\) /* \(\operatorname{opt}(P,m)\) is the \(m\)-mean cost of \(P\). */
2 Set \(m\gets k^{t}\) Set \(\{P_{1},\ldots,P_{m}\}\leftarrow\) the partition of \(P\) by \(\operatorname{opt}(P,m)\) for\(i:=1\)to\(m\)do
3 Compute a \((1,\varepsilon)\)-coreset \(S_{i}=(S_{i}^{\prime},w_{i},\phi_{i})\) for \(P_{i}\)
4 Set \(w(\mu(S_{i}))\leftarrow\sum_{p\in S_{i}^{\prime}}w_{i}(p)\) Set \(S^{\prime}\leftarrow\bigcup_{i=1}^{m}\mu(S_{i})\) Set \(\phi\leftarrow\sum_{i=1}^{m}\operatorname{cost}(S_{i},\mu(S_{i}))\) Set \(S\leftarrow(S^{\prime},w,\phi)\) return\(S\)
```  
**Algorithm 1**\(k\)-Mean-Coreset\((P,k,\varepsilon)\)
## 1 Introduction  
The construction and operation of DEMO is probably the most important step in the path towards fusion electricity [1]. Indeed, DEMO has the important and strategic mission of demonstrating that electric power can be produced by a nuclear fusion power plant in a sustainable and reliable way. To achieve this ambitious goal, DEMO has to be equipped with a system that is able to at least produce the tritium necessary to sustain fusion reactions. This duty is mainly carried out with a breeding blanket (BB). In addition to this important function, the breeding blanket shields the vacuum vessel (VV) and the toroidal field coils (TFC) from neutrons and \(\gamma\) rays removes the heat power arising from plasma by means of a proper coolant medium.  
At the end of the pre-conceptual design phase in 2020, two breeding blanket concepts were under evaluation for their adoption as the driver-blanket of the EU-DEMO reactor [2]: the Helium-Cooled Pebble Bed (HCPB) concept [3], adopting helium as the coolant and ceramic lithium-beryllide compounds in the form of pebbles as the breeder and neutron multiplier, and the Water-Cooled Lead-Lithium (WCLL) concept. The WCLL BB relies on the adoption of water in pressurized water reactor (PWR) conditions as the coolant and PbLi liquid metal alloy as the neutron multiplier, tritium breeder, and carrier medium, where Li acts as the breeder material and Pb acts as the neutron multiplier. For this purpose, in order to maximize tritium production, the lithium present in the alloy will be enriched at 90% in \({}^{6}\)Li. An atomic lithium percentage of 15.7% allows for eutectic conditions to be reached. The BB structural material is the Reduced Activation Ferritic-Martensitic (RAFM) steel named EUROFER97, a particular steel purposely developed in Europe for fusion applications [4].  
The design of such a component fulfilling the aforementioned functions while respecting requirements prescribed by design codes and other system interfaces is a challenging mission. For this purpose, the DEMO BB was designed following a holistic approach. The following sections report a detailed description of the WCLL BB layout and the studies that led to the current design and were presented at the gate review meeting held at the end of the DEMO pre-conceptual design phase. Remaining issues and R&D activities connected with their mitigation are reported and discussed as well.
## 2 Materials and Methods
### Splitting Test  
Table 6 shows the test results for the split strength of junctions at different clamping distances. The splitting strength of the 50 mm and 100 mm clamping distances increased by 0.10% and 1.3% compared to the 25 mm clamping distance. In terms of peak elongation, the peak elongation of the 50 mm clamping distance increased by 3% over the peak elongation of the 25 mm clamping distance. The peak elongation of the 100 mm clamping distance increased by 8.21% over the peak elongation of the 50 mm clamping distance. In terms of overall elongation, the overall elongation of the 50 mm is 7% less than the overall elongation of the 25 mm. The overall elongation of the 100 mm is 0.62% less than the overall elongation of the 50 mm. The splitting strength and elongation both increase or decrease slightly with a change in the clamping distance. Hence, increasing the distance between clamps has little bearing on the split strength test.  
Figure 16 exhibits the graphs of the split stress-elongation of the junctions under different clamping distances. All of the results show a similar nature. The splitting strength in the linear area pre-peak increases slowly, and the strength in the area post-peak decreases more rapidly. This is consistent with the peeling strength test, indicating that the loading process is mostly similar between the two tests. The failure processes of the sample photographed are shown in Figure 17. The two welded strips separated, with progressive ductile failure and sudden brittle failure, which matched the test curve well.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Clamping Distance** & **Splitting Strength** & **Peak Elongation** & **Overall Elongation** \\
**(mm)** & **(N\(\cdot\)cm\({}^{-1}\))** & **(mm)** & **(mm)** \\ \hline
25 & 204.12 & 14.094 & 21.318 \\
50 & 204.33 & 14.514 & 19.776 \\
100 & 206.85 & 15.706 & 19.654 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Splitting test results of the junctions.  
Figure 15: Weld fracture of the junction subjected to a peeling force.  
Figure 16: Split stress–elongation relationship of the junction subjected to a splitting force under various damping distances: (**a**) 25 mm, (**b**) 50 mm, (**c**) 100 mm.  
Figure 17: Failure modes of the junction subjected to a splitting force under various clamping distances: (**a**) 25 mm, (**b**) 50 mm, (**c**) 100 mm.  
However, the experiment results showed various failure modes (Figure 18b). The sample failed at the junction between the two sides of the junction and the strip, which was identical to how the peeling strength test fails. This was due in large part to the sample's stress changing during the tensile process. It can be found from the test that the junction tilted under a splitting force (the red arrow in Figure 18a; the dashed line is the junction's initial direction), changing the force of the junction from a simple splitting force to a combination force of shear and splitting.
# IEEE 802.11 ah: A Technology to Face the IoT Challenge
## 2 Challenges for IoT Applications and IEEE 802.11 ah
### Low Power Consumption  
Considering the fact that many IoT devices are battery driven and are meant to operate for days, weeks, months or years (depending on the application), the low power consumption becomes a crucial aspect to increase the battery life. IoT devices are equipped with embedded Network Interface Card (NIC) and thus have the ability to communicate autonomously within the network they belong to. The wireless NIC represents a large portion of the energy consumed by the device and thus, the definition of an efficient power management for the NIC is of paramount importance. This can be achieved by employing different wake up and doze timers.  
In legacy IEEE 802.11, the specified maximum idle period allows any station to maintain its association state for up to 18.64h of inactivity, while IEEE 802.11 ah aims to utilize different periods for different applications, up to a year scale.  
Many new features introduced by the IEEE 802.11 ah are intended to achieve more efficient transmissions, thus allowing energy savings. For example, the reduced overhead due to shorter headers and mechanisms such as the implicit acknowledgement (ACK control frames not required in some cases), the speed frame exchange (method that allows to exchange a bidirectional sequence of frames during a reserved Transmit Opportunity (TXOP)), extend battery life of stations by shortening transmission time, keeping them awake for shorter periods.
# Build Orientation Optimization Based on Weighted Analysis of Local Surface Region Curvature
## 3 Methodology
### Weight Distribution
#### 3.2.1 Cluster Weight  
In Section 3.1.3, the curvature of every cluster center is estimated. The curvature of center point in each cluster is set to represent the average change of the point set. If we get \(n\) clusters, the method of obtaining cluster weight is as follows:  
Step 1: Cluster the entire model using curvature shift strategy proposed.  
Step 2: Calculate the curvature of the center point in each cluster. The curvatures of \(n\) cluster are \(c_{1},c_{2},\ldots,c_{n}\).  
Step 3: Sort the curvature values for all center points and assumed \(c_{i}>c_{i+1},i=1,2,\ldots,n\).  
Step 4: Calculate the weight of \(i\)-th point by the following equation: \(w_{ci}=\frac{c_{i}}{\sum_{i=1}^{n}c_{i}}\).  
The cluster weight is effectively estimated by the curvature shift. However, in each cluster, some points with relatively big curvature changes are missed. Actually, it is lack of sufficient credibility just based on the curvature of one center point in each cluster. Therefore, the curvature weight of each point is further defined to guarantee each point with big curvature participating in the calculation of volume error function.
## 3 Nonlinear Dynamic Inversion Control Law
### UAV Speed Control Loop  
For strengthening the path-following ability of a UAV to keep tracking the desired position along the given required path, the UAV velocity holding must be taken into consideration. Applying a PI controller for the velocity error to get the desired thrust command \(\delta_{t}\) given in Equation (27), the gains of PI controller are selected by trial and error to fulfill the accepted holding cruise speed, as illustrated in Figure 5.  
\[\delta_{t}=\left(k_{p}+\frac{K_{i}}{s}\right)\left(V_{c}-V_{a}\right) \tag{27}\]  
where \(V_{c}\) is the desired cruise speed and \(V_{a}\) is the current UAV airspeed.
# Angular Dependence of Photonic Crystal Coupled to Photovoltaic Solar Cell
###### Abstract  
Photonic crystals have the advantage of minimizing thermal losses from solar cells, reflecting the solar radiation that is not absorbed by the photovoltaic device. To optimize this optical response, photonic crystals are designed considering the relative position of the Bragg peak and the bandgap of the solar cell, under normal incident irradiation conditions. The aim of this research article was to determine experimentally the optical limits of a solar cell coupled to a photonic crystal acting as beam splitter. For that purpose, the photovoltaic system was characterized under indoor and outdoor conditions; angular dependence of the irradiation source was determined in each case, and both results were compared with good agreement. Moreover, other parameters such as irradiation spectrum and polarization of the light were investigated. The main conclusion is that photovoltaic performance is highly affected by the Bragg peak shifting and the profile is distorted, due to the angular dependence with the sun. These experimental limits must be considered at the early design stage to avoid performance losses.  
spectral radiation; photonic crystal; photovoltaic; polarization; beam splitter; solar energy Article
# Radiometric Method for Determining Canopy Stomatal Conductance in Controlled Environments
## 5 Conclusions  
The controlled-environment experiments conducted in this study provide a new methodology for measuring canopy stomatal and aerodynamic conductances. A radiometric method for determining canopy aerodynamic conductance from changes in vegetation temperature and energy balance was developed in controlled environments using a canopy-level gas exchange system. The gas exchange system measured canopy gas fluxes (CO\({}_{2}\) and water vapor), energy balance (net radiation, latent and sensible heat fluxes), and canopy temperatures as CO\({}_{2}\) concentration was varied. Two key assumptions of this method are that radiative canopy temperature is approximated by canopy brightness temperature and that the difference between aerodynamic and radiative canopy-to-air temperature differences is constant during the photoperiod. Once canopy aerodynamic conductance was determined from a plot of sensible heat flux versus the radiative canopy-to-air temperature difference, canopy stomatal conductance was calculated from measurements of canopy transpiration. The method was used to determine the curves of the response of canopy stomatal conductance and canopy ET to increased CO\({}_{2}\) concentration in wheat (Table 3; Figure 11). Predictions of canopy ETmade from the measured response of G\({}_{\text{S}}\) to elevated CO\({}_{2}\) are comparable to land surface model predictions and to observed changes in ET found in FACE studies [50; 51]. Future work should focus on studying how canopy stomatal conductance measured using this methodology responds to drought, vapor pressure deficit, and temperature to provide data sets for calibrating global climate models. The method should also be used to characterize how canopy aerodynamic conductance changes during the growth cycle of different crop species.  
[PERSON] and [PERSON] conceived the study. [PERSON] wrote the original manuscript. [PERSON] and [PERSON] reviewed and revised the manuscript. Project administration and funding acquisition: [PERSON]. All authors read and approved the manuscript.  
This research was supported by the Advanced Life Support Program of the National Aeronautics and Space Administration and by the Utah State Agricultural Experiment Station, Utah State University. This manuscript has been approved as journal paper number 9178.  
The authors would like to thank [PERSON], [PERSON], and [PERSON] for critically reviewing the manuscript.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.