esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Earth Surface Modelling Advances and Links with EO Datasets
### Land-Surface Reservoirs
#### 3.1.4 Vegetation and Carbon Cycle
Recently, the Copernicus Global Land Service (CGLS) products of surface albedo and LAI based on observations from the SPOT-VEGFATION and PROBA-V sensors [145] have become available in near real-time (NRT) with an operationally-maintained production chain. However, the direct use of these products within a NWP system is not possible without quality checks given the spatial and temporal discontinuities they may contain. A direct assimilation of LAI and surface albedo products using optimal interpolation analysis with the ECMWF NWP system was explored and evaluated for anomalous years [146]. It was shown that: (i) the assimilation of these products enables detecting/monitoring extreme climate conditions where the LAI anomaly could reach more than 50% and the albedo anomaly could reach 10% (Figure 11), (ii) extreme LAI anomalies have a strong impact on the surface fluxes, while for the albedo, the impact on surface fluxes is small, (iii) neutral to slightly better agreement with in situ surface soil moisture observations and surface energy and CO\({}_{2}\) fluxes from eddy-covariance towers is obtained, and (iv) in forecast mode, the assimilation of LAI reduces the near-surface air temperature and humidity errors both in wet and dry cases, while the albedo has a small impact, mainly in wet cases, when albedo anomalies are more noticeable.
## 5 Clinical Application
### Computer-Aided Manufactured Mentoplates  
Conventional _Mentoplates_ were shown to be effective, especially in case of maxillary protraction in early class III treatments [28; 29]. Using computer-aided manufacturing, _Mentoplates_ can be designed to hold supra-constructions with various functional elements of high precision, including sliding mechanics for distalization or mesialization of posterior teeth, which increase the range of treatment options (Figure 9).  
Both conventional and digitally manufactured appliances with a submucosal extent can be made from titanium alloys. Under local anesthesia or narcosis, the oral surgeon prepares a mucoperiosteal flap, revealing the bone structures of the chin. Conventional _Mentoplates_ are adapted by bending them manually to fit the chin bone. The two extension arms are shortened and formed either straight or bent into a hook. Depending on the purpose of the treatment, they should penetrate the soft tissue at the mucogingival border or within the attached mucosa to avoid infection and eventually loss of the appliance.  
3D-printed appliances do not require adaptation within surgery as they are already customized regarding the individual anatomical situation. While guides for palatal appliances lead the drill during the implants' insertion, osteosynthesis screws are directly applied into their connectors. Therefore, the guide must stabilize the _Mentoplate_ in the correct position while the screws are inserted. For this purpose, it proved efficient to assemble the _Mentoplate_ with its supra-construction and employ the posterior shells as orientation. To achieve stable triangular support, a printed guide can be mounted onto the lower incisors as well as on the supra-construction, ensuring vertical control (Figure 10). After fastening the screws, the guide can be removed, and the active elements can be adjusted as indicated. After the screws are applied, the flap can be adapted and sutured.  
Figure 9: 3D-printed _Mentoplate_ with mesial-slider supra-construction: (**A**) Digital design. (**B**) Finished printed appliance (software: Blender, Blender Foundation).
# First Lidar Campaign in the Industrial Sites of Volta Redonda-RJ and Lorena-SP, Brazil
## 2 The Campaign Sites and Instrumentations
### Instruments
#### 2.2.1 Lidar System  
The laser remote-sensing techniques, such as lidar, are very important due to their long-range non-invasive probes of the chemical composition and physical properties of the atmosphere. The lidar technique is based on the emission of a pulsed collimated laser beam in the atmosphere and on the detection of the backscattered radiation by the suspended  
Figure 1: **(a)** Map of the region of the Paraiba valley with Lorena and Volta Redonda marked in red color. The Rio de Janeiro and São Paulo cities are also marked, as well as other important regions along the Presidente Dutra highway. **(b)** Lorena local map showing the lidar position (red pin) and nearby companies. **(c)** Volta Redonda local map. The lidar location is marked by a red pin while the yellow contour indicates the CSN area. One of two blast furnaces of the company, marked by a yellow pin, is 700 m away from the lidar position.  
aerosol particles, molecules and atoms present in the air. The intensity of the backscattered light is recorded as a function of time, and thus provides the required spatial resolution of the measurement. The mobile MSP-lidar II setup (Commercial Raymetrics LR101-V-D200) used in this work consists of a Q-Switched Nd:YAG laser (CFR 200 by Quantel SA) operating at the second harmonic frequency of 532 nm, with 6.7 ns pulse duration, 20 Hz repetition rate, and a maximum pulse energy of 130 mJ. The emitted laser beam is expanded (4\(\times\)) and pointed vertically to the zenith. The beam has a divergence of less than 0.5 mrad. The backscattered laser light is detected by a 20 cm diameter Cassegrainian telescope (F# = 4.5) with 1 mrad Field of View (FOV) that provides the full overlap around 180 m. This FOV value, in accordance with the detection electronics, permits probing the atmosphere up to the free troposphere (12-15 km). The backscattered laser radiation is sent to the signal acquisition unit, consisting of two Hamamatsu R7400 Photo Multiplier Tubes (PMTs) coupled to narrow band (1 nm FWHM) interference filters for the elastic backscatter channel, at 532 nm. The PMT output signal is digitized by a lidar Transient Recorder TR-20-160 (LICEL) with an acquisition analog channel with 12 bits resolution at 20 MHz sampling rates. Each data profile is acquired using an integrated time of 100 s, with a typical spatial resolution of 7.5 m. This mobile system is part of the Latin America Lidar Network (LALINET) [43; 44] and has been used in other studies [32; 45].
# Iterative MLFMA-MADBT Technique for Analysis of Antenna Mounted on Large Platforms
## 2 Method Overview  
Consider an antenna mounted on a large perfect electric conducting (PEC) platform. The structure can be divided into two parts: the MLFMA region and the BT region. As shown in Figure 1, to solve the strong coupling problem, namely the antenna connected with the platform, a part of platform surrounding the junction is allocated as the transition region. The transition region and the antenna are together classified as the MLFMA region, and the remaining part of the platform is allocated to the BT region. Usually, the accuracy and computational complexity improves with the increment of the area of transition region. The rule to estimate the size of the transition region is presented in Section 3.1.  
A general flowchart in Figure 2 is presented to illustrate the iterative MLFMA-MADBT method for the radiation analysis of an antenna mounted on a large-scale platform. The method mainly consists of four parts:  
1. The MLFMA region (antenna and transition region) is analyzed by the MLFMA and regarded as a point source.
2. The initial beams are generated from the point source and the MADBT method is performed on the BT region.
3. The iterative process is used to handle the coupling interaction between the MLFMA region and BT region.  
4. The far field is obtained as the superposition of the MLFMA region and BT region. Details of each part are described in the following sections.  
Figure 1: The division of the MLFMA region and BT region for the whole structure.  
Figure 2: A general flowchart of the iterative MLFMA-MADBT method.
# Windowed Joint Detection and Decoding with IR-HARQ for Asynchronous SCMA Systems
### Related Work to SCMA Systems with HARQ Schemes  
The SCMA system has seen an increase in usage and research, but few studies have examined its performance with the hybrid automatic repeat quest (HARQ) scheme. [PERSON] et al. demonstrated the efficiency of this scheme in improving decoder performance for fifth-generation mobile communication technology (5G) transmission strategies in [17]. Building on this idea, the authors in [18] explore an SCMA-oriented HARQ scheme that enhances the reliability of new information by retransmitting correctly decoded codewords. However, this scheme may not be suitable for random access scenarios, as it requires immediate retransmission by users experiencing transmission failure in the current slot. To address this issue, ref. [19] presents an improved HARQ scheme dedicated to SCMA under grant-free random access scenarios. However, these two schemes have drawbacks, such as wasting resources and limited use of fixed-rate codes, which restricts the use of Chase combining (CC) HARQ for the SCMA system. Since the IR-HARQ scheme is a promising alternative to the CC-HARQ scheme for SCMA systems to improve throughput, [PERSON] et al. showed that the combination of rate-compatible (RC) codes and an IR-HARQ scheme performs well in [20; 21]. Moreover, the binary RC-LDPC codes have been accepted as standard codes for the enhanced mobile broadband (eMBB) data channel of 5G communication in [22]. Thus, it is worth studying the performance of the RC-LDPC code-based IR-HARQ scheme for SCMA systems.
## 3 Results and Discussion
### Capacity Mapping  
Services, medical resources, equipment, and other resources related to health care facility locations are mapped in order to more easily assess the readiness of the public health system to respond effectively to the current epidemic situation. Important quantitative information mapped are:  
* hospital locations;
* total number of beds in hospitals;
* available beds;
* total number of ventilators in hospitals; and
* available ventilators in hospitals.  
Figure 5: Elements of the system interface in Epidemic Location Intelligence System. The diagram shows the cumulative total number of infected (proportional to the size of the red dots).
# Measuring Gas Flaring in Russia with Multispectral VIIRS Nightfire
## 2 Method
### Flare Locations from Clusters in the VNF Detections Database
The problem is further intensified by the thermal \"halo\" of Nightfire detections around the largest gas flares, which has been observed in Russia and Venezuela. In the catalog, 2012-2016 entries remained unmodified. For 2017-2020, several manual corrections were implemented. In 2017-2018, new annual gas flares contours (i.e., those having no successful cross-match with the previous annual datasets) recognized as \"duplicates\" or \"halo\" based on available high spatial resolution imagery had their estimated flared volumes summed together. For 2019-2020, the same procedure was applied to all the identified gas flare contours which in 2019 resulted in a drop in flare tally from 1185 to 994 compared with the original watershed results.
## 5 Complexity Analysis  
The computational complexity of DSP algorithms has a significant impact on hardware resource consumption and power usage, making it a crucial consideration in the design process. The complexities of various algorithms are compared in Table 2. Using 16 QAM as an example, we analyzed the number of multipliers required for each algorithm and evaluated the implementation complexity of different methods, focusing on complexity calculations and comparisons for a single polarization state.  
Figure 12: Performance comparison between the proposed algorithm and the QPSK algorithm in terms of NMSE under both weak and strong turbulence conditions across different frequency offset ranges: (**a**): NMSE comparison curve under weak turbulence conditions, (**b**): NMSE comparison curve under strong turbulence conditions.  
In terms of complexity, multipliers are considerably more resource-intensive than additions. Therefore, the number of multipliers is a key metric in hardware implementation design. For \(N=1024\) (where \(N\) represents the length of the frequency offset estimation block), the proposed scheme requires approximately \(27.2\%\) of the multipliers needed for QPSK partitioning [25]. This significant reduction in complexity compared to QPSK partitioning indicates that the proposed scheme is more favorable for hardware implementation.
## 3 Results and Discussion
### Characterization of Cockleshell Powder
#### 3.1.4 X-ray Diffraction Analysis (XRD)  
The use of XRD gives information on the molecular structure and morphological shape of the cockleshells. Figure 5 shows the XRD of cockleshell powder before and after the adsorption of the Direct Red 81 dye.  
Figure 5 shows the presence of CaCO\({}_{3}\) (aragonite) at positions 2 theta of 26.03, 27.25, 33.07, 36.11, 38.54, 41.09, 42.90, 45.82, 48.37, 52.38, and 53. These two positions correspond to the crystal planes (1 1), (0 2 1), (0 1 2), (1 0 2), (1 1 2), (0 2 2), (1 3 1), (2 2 0), (2 2 1), (0 4 1), (1 3 2), (1 3), and (0 2 3), respectively. Other parameters include a = 4.95410 A, b = 7.94940 A, and c = 5.71860, with an orthorhombic crystal system.  
The assignments of position 2 and other parameters for aragonite from XRD were in agreement with the reference code [96-901-5718] of a hexagonal crystal system, with the characteristic peak positioned at 2 theta = 26.03 and the crystal plane of (1 1 1). A similar study was conducted by [32].  
There was also no change in the cockleshell powder's peaks after the adsorption of DR-81. This latter observation indicates that the adsorption of DR-81 dye does not change the physicochemical properties [34] of the CS adsorbent.
# Improving Spatial Reuse of Wireless LAN Uplink Using BSS Color and Proximity Information
## 4 Performance Evaluation
### Simulation Results
#### 4.2.2 Varying Number of APs  
In the second experiment, we have varied the number of APs in the network while keeping the number of stations fixed. The area size is also fixed to 100 m \(\times\) 100 m. Thus, when the number of APs is increased, the average distance between a station and its AP decreases. The number of APs is varied from 16 to 169. The results are shown in Figure 10.  
Figure 10: Performance of methods varying number of APs. (**a**) Total throughput; (**b**) Bottom 50% throughput; (**c**) Bottom 25% throughput; (**d**) Fairness; (**e**) Non-starvation Ratio; (**f**) Delivery Ratio.  
The total throughput shown in Figure 10a shows a similar trend to the previous experiment. In this case, the throughput increases with number of APs because more parallel transmission can be initiated when the distance between a station and its associated AP is shorter. The PSR and PSC-UL increase the gap with other methods as the number of APs grow larger, because they use a more fine-grained information to determine whether parallel transmission will be successful. Similar to the previous experiment, the PSR achieves higher total throughput compared to PSC-UL, but its fairness and non-starvation ratio are much lower than PSC-UL.  
When the number of APs becomes large, we can observe that the bottom 25% throughput as well as the non-starvation ratio of PSC-UL is lower than other compared methods except PSR. This means that stations at the edge experience very low throughput and some may even starve. This is because when PSC-UL estimates SNR at the receivers, only the two potentially parallel transmissions are considered. If there exists additional interference at the receivers, the SNR can become lower than expected, and to the point where packet losses occur. One solution to address this problem is to control the margin parameter based on density. A larger margin value can be used for a very dense network to account for additional interference. We use a fixed margin in this paper, and finding the optimal margin for the environment is left as a future work.
# Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems
## 3 Massive MIMO Performance Gains
### Spatial Multiplexing Gain
#### 3.3.2 Multiplexing Gain under Imperfect CSI
Then, the achievable sum rate for \(\ell\)th cell in multi-cell system under imperfect CSI is given by  
\[R_{\ell}=\sum_{k=1}^{K}R_{\ell k}=\sum_{k=1}^{K}\left(\frac{T_{coh}-\tau}{T_{ coh}}\right)\log_{2}(1+\mathrm{Y}_{\ell k}). \tag{54}\]  
Multiplexing Gain under imperfect CSI is defined as the deviation of the average achievable sum rate as a function of the logarithmic transmit power [33]  
\[G_{MUX}^{imperf.CSI}=\frac{dE(R_{\ell})}{d\log_{2}p_{d}}=\frac{d}{d\log_{2}p_ {d}}\sum_{k=1}^{K}E\left(\left(\frac{T_{coh}-\tau}{T_{coh}}\right)\log_{2} \left(1+\frac{Mf_{MRT}p_{p}p_{d\ell k}\beta_{\ell k\ell}^{2}}{Mf_{MRT}p_{p} \sum_{j\
eq\ell}^{L}p_{djk}\beta_{jk\ell}^{2}+\sigma_{n}^{2}}\right)\right). \tag{55}\]For massive MIMO system as the number of base station antennas \(M\) increases without limitation, the effects of received noise and fast fading are eliminated, just the effect of inter-cell interference remains due to the imperfect channel estimation, then the multiplexing gain can be given as  
\[ \begin{array}{c}G_{MUX}^{imperf.CSI}=\frac{d}{d\log_{2}p_{d}}\sum\limits_{k=1 }^{K}E\left(\left(1-\frac{\tau}{T_{coh}}\right)\log_{2}\left(1+\frac{p_{d\ell }\delta_{R\ell}^{2}}{\sum\limits_{j\
eq\ell}^{L}p_{d\phi}\delta_{j\ell}^{2}} \right)\right)\\ G_{MUX}^{imperf.CSI}=\left(1-\frac{\tau}{T_{coh}}\right)\frac{tr(D_{\ell\ell} ^{2}\left[tr(p_{dj})-tr(p_{d\ell})\right]}{\sum\limits_{j\
eq\ell}^{L}\left[ tr(p_{dj}D_{\ell j})^{2}+tr(p_{d\ell}D_{\ell\ell}^{2})tr(p_{dj})\right]}\end{array} . \tag{56}\]  
The detailed derivative of expression (56) can be shown in Appendix A. Expression (56) represents the multiplexing gain under the effect of undesirable interference between cells due to pilot contamination which is in term of the undesirable signal power from neighbor cells. All these are because of the BS in \(\ell\)th cell suffers from delay in channel estimation between the uplink pilot sequences during the training phase and data transmission in downlink phase. In addition, error channel estimation that all affect precoding matrix and this is why the transmission signals from other BSs to their users interfere with the received signal of \(k\)th user in \(\ell\)th cell from its BS.
# Quantitative Evaluation of the Clinical Evolution of Traumatic Onycholysis after Laser Treatment
## 3 Results  
Patients had a mean age of 52 \(\pm\) 15 years (range 30-80 years), 6 female and 2 male.  
A microbiological culture was performed to rule out fungal infection for all nails analyzed, and the result was negative three times.  
To evaluate the affected nails, we used the affected percentage of the axis. Before treatment, the mean percentage of the axis affected was 64.74 \(\pm\) 14.92, and at the six-month post-treatment check-up it was 45.51 \(\pm\) 24.12% (Table 1 and Scheme 1). Statistical analysis using the Student's t-test for related samples showed a statistically significant difference (\(p\) < 0.006). _[PERSON]'s \(d\)_ was calculated and obtained a value of 1302, indicating large changes despite the small effect size.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Subject**} & \multirow{2}{*}{**Gender**} & \multirow{2}{*}{**Age (Years)**} & \multicolumn{2}{c}{**Longitudinal Affected \% Axis**} & \multirow{2}{*}{**Culture**} & \multirow{2}{*}{**Clinical Signs**} & \multicolumn{2}{c}{**Anatomical Position of the Toe**} \\ \cline{5-8}  & & & & **Before** & & & & \\ \hline
**1** & Female & 61 & 73.33 & 71.43 & Negative & Distal onychosis & Hallux extensus \\
**2** & Female & 50 & 41.94 & 28.00 & Negative & Distal onychosis & Hallux extensus \\
**3** & Male & 56 & 68.57 & 20.00 & Negative & Lateral onychosis & Hallux abducts valgus \\
**4** & Female & 80 & 84.00 & 60.61 & Negative & Distal onychosis & Hallux extensus \\
**5** & Female & 44 & 63.16 & 51.35 & Negative & Lateral onychosis & Hallux abducts valgus \\
**6** & Female & 49 & 66.67 & 21.74 & Negative & Distal onychosis & Hallux extensus \\
**7** & Male & 46 & 79.55 & 76.47 & Negative & Distal onychosis & Hallux extensus \\
**8** & Female & 30 & 36.67 & 7.41 & Negative & Distal onychosis & Hallux extensus \\
**Mean** & 52 & 64.74 & 45.52 & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Detailed results by participant.  
Figure 1: Affected percentage of the longitudinal axis of the nail. The middle point (blue dots), the nail width (black arrow) at the onychocorneal band, and the hyponychium level were calculated. These two points were combined to define the longitudinal axis of the nail (red line). The shaded area simulates the nail lesion. The total length and the affected part of the longitudinal axis were measured (green arrow).  
Laser application achieved clinical improvement in 100% of the nails, although none showed complete remission of symptoms during the study period (Figure 2). No differences were found between the results according to the type of onycholysis and the alteration of the anatomical position of the toe.
## 3 Results
### Energy Consumption
#### 3.4.2 Electrical Energy Per Order (E\({}_{\text{EO}}\)) Analysis  
The energy per order of magnitude (\(E_{\text{EO}}\)) is a figure of merit introduced by [PERSON] et al. [48] to quantify the electrical efficiency of advanced oxidation processes.  
Although the degradation of organic pollutants by AOPs is a complex process involving many elementary reactions, the kinetics can often be approximated by simple zero or first-order expressions [48]. \(E_{\text{EO}}\) measures the amount of electrical energy (kWh) required to decrease the concentration of a target pollutant in 1 m\({}^{3}\) of water by one order of magnitude (approximately 90%). This performance metric provides a direct comparison of different AOPs regardless of their system types, and lower values indicate higher efficiency [40]. For a batch reactor system, \(E_{\text{EO}}\) can be calculated using Equation (1) [48],where \(t\) is the time required to reach 90% degradation (min), \(P\) is the system's power output (kW), \(V\) is the reaction volume (L), and \(c_{i}\) and \(c_{f}\) are the initial and final concentrations of the pollutant (mol/L).  
\[E_{\text{EO}}=\frac{P\cdot t\cdot 1000}{V\cdot 60\cdot\log\left(\frac{c_{i}}{c_{ f}}\right)} \tag{1}\]  
The energy required for the process can be calculated in two ways: (a) by accounting for the electrical consumption of both the lamp and the magnetic stirrer, or (b) by considering only the electrical consumption of the magnetic stirrer, under the assumption that electricity can be obtained from natural solar radiation in real-life scenarios. In case (a), the power meter reading yields \(p=499\) W (lamp + stirrer). The average reactor volume is \(V=0.100\) L, and it takes 101.5 min to achieve a 90% reduction. The resulting \(E_{\text{EO}}\) is 8441.4 kWh/m\({}^{3}\). In contrast, for case (b), the power consumption of the magnetic stirrer is only 10 W, with the same volume and time as in case (a). This results in a much lower \(E_{\text{EO}}\) of 169.2 kWh/m\({}^{3}\), when the energy required for the lamp operation is disregarded.  
It is worth noting that natural solar radiation can be used to provide the UV-A radiation required for TMP degradation and other organic pollutants. By utilizing solar radiation, the costs associated with generating UV-A radiation can be significantly reduced. This should be considered in future experiments and real-scale reactor design.  
To further improve energy efficiency, the size of the reactor should be adjusted to match the radiation source. Additionally, LED bulbs should be used instead of traditional lamps. However, the most important suggestion is to use natural solar radiation whenever possible, as there is no energy cost associated with it. Energy should only be accounted for the stirring process.