esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparative Analysis of Local Differential Privacy Schemes in Healthcare Datasets
## 2 Preliminaries
### Generalizing the Problem  
Before describing our approach, we introduce preliminary concepts. In LDP approaches, users want to not only share their information with a central server but also maintain their privacy. Thus, users encode and perturb their data before sending it to the central server, and in doing this, they preserve their anonymity. In this work, we follow the user steps proposed by [PERSON] [6], where we generalize the LDP problem; there are \(N\) users, and \(U=\{u^{1},u^{2},u^{3},\ldots,u^{N}\}\) is a set of users. All users have an equal number of attributes, denoted as \(d\). Each attribute has a specific domain, represented by \(\Omega_{i}=\{\omega_{i}^{1},\ldots,\omega_{i}^{|\Omega_{i}|}\}\), where \(i\) ranges from \(1\) to \(d\).
## 2 Materials and Methods  
### Study Design/Sample  
This study followed the guidelines of the Declaration of Helsinki, and our institutional review board approved this retrospective study and waived the requirement for patient-informed consent. The study sample was composed of subjects who presented skeletal Class II malocclusion and underwent mandibular advancement surgery with genioplasty from March 2005 through February 2022 in this institution.  
The inclusion criteria were as follows: age at surgery \(\geq\) 18 years; skeletal Class II malocclusion with ANB > 4\({}^{\circ}\); requirement for conventional orthognathic bimaxillary surgery. The exclusion criteria were as follows: patients with syndromes; no record of maxillary arch expansion; Menton deviation > 4 mm from the facial midline; a known history of temporomandibular joint disease; an incomplete series of lateral cephalometric radiographs or CBCT images.  
Among patients who were treated with the aforementioned surgery, 29 patients were treated with \"transpalatal arch (TPA)\", \"rapid palatal expander (RPE)\" or \"miniscrew-assisted RPE (MARPE)\". In total, 3 patients were excluded due to lack of CBCT records; 1 patient received surgery before comprehensive orthodontic treatment; 3 patients had a known history of fibromatosisis, hemifacial macrosomia or idiopathic condylar resorption. Eventually, 22 patients (8 male, 14 female) who fulfilled the inclusion criteria were enrolled in this study (Figure 1).  
Horizontal change at Infradentale (Id) in the lateral cephalograms 1 year after surgery was the primary predictor variable in this study. The study sample was divided into two groups according to the amount of Id change (T3-T2): group S including patients with changes within 2.0 mm, and group LS including patients with changes equal to or more than 2.0 mm [5].
# Dual-Mic Speech Enhancement Based on TF-GSC with Leakage Suppression and Signal Recovery
## 2 Summary of TF-GSC and Postfiltering
The TF ratio is updated when the desired signal is present in the last \(L\) frames as:  
\[H_{2}(n,k)=\dfrac{\left\langle\[PERSON]_{X_{1}X_{1}}(n,k)\[PERSON]_{X_{2}X_{1}}(n,k) \right\rangle-\left\langle\Phi_{X_{1}X_{1}}(n,k)\right\rangle\left\langle \Phi_{X_{2}X_{1}}(n,k)\right\rangle}{\left\langle\[PERSON]_{X_{1}X_{1}}^{2}(n,k) \right\rangle-\left\langle\[PERSON]_{X_{1}X_{1}}(n,k)\right\rangle^{2}} \tag{12}\]  
in which:  
\[\left\langle\[PERSON](n,k)\right\rangle\triangleq\dfrac{1}{L}\sum_{l=1}^{L}\[PERSON](n -l+1,k) \tag{13}\]  
where \(\hat{\[PERSON]}_{X_{p}X_{1}}(n,k)\) (\(p=1,2\)) is the estimate of the cross-power spectral density between \(X_{p}\) and \(X_{1}\) given by:  
\[\hat{\[PERSON]}_{X_{p}X_{1}}(n,k)=\rho_{P}\hat{\Phi}_{X_{p}X_{1}}(n-1,k)+(1-\rho_{ P})X_{p}(n,k)X_{1}(n,k)^{H} \tag{14}\]  
where \(\rho_{P}\) is a smoothing factor. However, the TF ratio estimation suffers from diffuse or nonstationary noises, resulting in steering error, which causes leakage of speech components through the BM and speech distortion in the FBF output. One way to mitigate this problem is to apply a postfilter based on the OM-LSA estimator [12; 13; 14; 15; 16]. The first step of this postfiltering is the hypothesis test, which determines if the output of the TF-GSC contains desired speech, transient interference, or stationary noises using the TBRR [31]. The result of the hypothesis test is utilized to determine a priori signal absence probability and, finally, the spectral gain function. Additionally, the hypothesis test result from the postfilter is further used to control the update of the parameters of the TF-GSC in [15; 16] as follows:  
\[H_{2}(n,k)=\left\{\frac{\left\langle\hat{\[PERSON]}_{X_{1}X_{1}}(n,k)\hat{\[PERSON]}_{X_{2}X _{1}}(n,k)\right\rangle-\left\langle\hat{\[PERSON]}_{X_{1}X_{1}}(n,k)\right\rangle \left\langle\hat{\[PERSON]}_{X_{2}X_{1}}(n,k)\right\rangle}{\left\langle\hat{\[PERSON]}_ {X_{1}X_{1}}(n,k)\right\rangle-\left\langle\hat{\[PERSON]}_{X_{1}X_{1}}(n,k)\right \rangle^{2}},\right. \tag{15}\]  
in which:  
\[\left\langle\Phi(n,k)\right\rangle\triangleq\frac{1}{|\mathcal{L}|}\sum_{l \in\mathcal{L}}\Phi(l,k) \tag{16}\]  
where \(\mathcal{L}\) is a set of frame indices that contain the desired signal component in the analysis interval from the \(n-L+1^{th}\) frame to the \(n^{th}\) frame, \(|\mathcal{L}|\) is the size of \(\mathcal{L}\), and \(N_{d}\) is the threshold for the TF ratio update. It is noted that the value of \(L\) should be carefully chosen to provide accurate estimates of ensemble averages with a large enough number of frames, while the quasi-stationary assumption for the acoustic TF is not violated by too big of an \(L\)[15; 16; 18]. It has the effect of relaxing the assumption on the stationarity of the TF ratio, which reduces the steering error to an extent. Even with the improved TF ratio estimation, however, a certain amount of the steering error is practically inevitable, leaving room for improvement in the performance.
## 2 Materials and Methods  
### Research Method  
Figure 1 presents a flowchart outlining the structure of this research. This diagram illustrates the key stages of the study, from the literature review and selection of soil parameters to the numerical modeling in Plaxis 2D and the analysis of results.  
In this regard, a literature review was conducted, consulting various relevant scientific and technical articles. Studies were selected that investigated the influence of rainfall intensity and duration on slope stability [11; 12; 19; 20], the behavior of unsaturated soils under water infiltration conditions [9; 39; 40], and oil types and geometries susceptible to failure due to rainfall on slopes [41; 42; 43]; publications providing specific geotechnical parameter values, such as permeability, cohesion, friction angle, elasticity modules, and the hydraulic parameters of the van Genuchten model (Sres, Ssat, ga, gn, gl) for the soil types studied, were also included [32; 33; 44; 45].  
These articles were selected based on their importance for understanding the physical behavior of slopes, the analytical methodologies used, such as the finite element method, and their presented conclusions regarding critical factors influencing slope stability, such as rainfall intensity and duration [11; 19]. This literature review provides a solid foundation for developing a robust methodological approach for numerical modeling using Plaxis 2D. Plaxis 2D was selected as the modeling tool for this study because of its ability to model the complex behavior of slopes under rainwater infiltration conditions, using the Fully Coupled Flow Deformation analysis [46]. This finite element software is widely recognized in geotechnical engineering for its ability to simulate the combined effect of infiltration and soil mechanical properties, as highlighted by several previous studies [11; 12].
# Feature-Based Approach to Change Detection of Small Objects from High-Resolution Satellite Images
## 2 Feature Point-Based Change Detection Method
### Feature-Based Change Analysis  
Feature-based change analysis is carried out using the unmatched feature points and a pixel-based change map. A region of interest (ROI) of a small pixel size, say 3 \(\times\) 3 pixels, is defined at a feature point as its center. The ratio of changed pixels to all pixels within the ROI is calculated. This ratio can represent the magnitude of change or the probability of change for the feature point. This ratio can be analyzed further for optimal change detection performance. In this paper, we set a ratio of 0.5 as the threshold of change for the sake of simplicity and to focus on the theme of the paper. Figure 3 shows the process of classifying changed feature points using one ROI. Figure 3a shows a pixel-based change map over a test site. Figure 3b is an enlarged sub-image around a ship, and Figure 3c is a selected ROI showing changed pixels in white and unchanged pixels in black.
## 2 Characteristic Signal Selection and Wavelet Denoising Processing
### Wavelet Denoising
#### 2.2.3 Choice of Decomposition Scale  
In this paper, a three-layer wavelet structure is adopted. The original signal is divided into the low-frequency approximation, part A1, and the high-frequency detail, part D1, and the high-frequency is not subdivided. Then, the low-frequency part A1 is further divided into low-frequency A2 and high-frequency D2 in low frequency, and the high-frequency is no longer decomposed, and so on [10]. Then, the original signal is expressed as the sum of the low-frequency of the last layer and the high-frequency decomposed by each layer, recorded as S = A3 + D3 + D2 + D1. After the decomposition and denoising of the three layers, the original waveform has gradually separated from the noise signal. The problem of signal extraction is solved, and the denoising effect is good.
## 6 Numerical Example: Trajectory Tracking of a Wheeled Mobile Robot
### Simulation Conditions  
To confirm the effectiveness of the proposed controller, we perform a computer simulation with the following circular trajectory:  
\[x_{d}(t)=\begin{bmatrix}-r\sin\omega t\\ r\cos\omega t\\ \omega t\end{bmatrix},\ u_{r}(t)=\begin{bmatrix}-r\omega\\ \omega\end{bmatrix}, \tag{99}\]  
where \(r>0\) is the radius of the circle and \(\omega\) is the angular velocity. Here, we set \(r=2.0\ [\mathrm{m}]\) and \(\omega=-\pi/4\ [\mathrm{rad}/\mathrm{s}]\). The initial condition of simulation is \(e(0)=[-3,\ 2,\ -\pi/3]^{\top}\) (or equivalently, \(x(0)=[-3,\ 4,\ -\pi/3]^{\top}\)). Moreover, \(\beta\) in (86), which characterizes the input constraint, is set to \(\beta=6.0\). The functions \(C(\|L_{g}V(t,e)\|)\) and \(Q(e)\) in the proposed controller are  
\[C(\|L_{g}V(t,e)\|)=\|L_{g}V(t,e)\|^{2}, \tag{100}\] \[Q(e)=0.25(e_{1}^{2}+e_{2}^{2}+0.25\sin^{2}e_{3}). \tag{101}\]  
For comparison, we also apply the following two existing controllers:  
* Sontag-type (unconstrained) tracking controller: We can construct the unconstrained tracking controller by substituting \(\omega_{1}(t,e)\) and \(L_{g}V(t,e)\) given by (89) and (90) into (10)-(11).
* Constrained tracking controller based on norm input constraints: The following norm constraint is available as a sufficient condition for the convex constraint (85): \[\bar{U}^{\prime}(t):=\{\ u\in\mathbb{R}^{2}\ |\ \|u\|^{2}\leq(\beta-\|u_{r}(t)\|)^{2}\} \subset\bar{U}(t).\] (102) Then, we can construct the following constrained tracking controller based on the asymptotically stabilizing controller proposed in [6]: \[\bar{k}_{2}(t,e) =\mu_{2}(t,e)\bar{k}_{2}(t,e),\] \[\bar{k}_{2}(t,e) =-\frac{\beta-\|u_{r}(t)\|}{\|L_{g}V(t,e)\|}L_{g}V^{\top}(t,e),\] \[\mu_{2}(t,e) =\begin{cases}\frac{P_{2}(t,e)\!+\!|P_{2}(t,e)|\!+\!C(\|L_{g}V\|) }{2\!+\!C(\|L_{g}V\|)}&(L_{g}V(t,e)\
eq 0)\\ 0&(L_{g}V(t,e)=0)\end{cases},\] (103) \[P_{2}(t,e) =\frac{\omega_{1}(t,e)+Q(e)}{(\beta-\|u_{r}(t)\|)\|L_{g}V(t,e)\|}.\]
## 3 Results  
### Maize Starch-Based Process (MS-bp)  
The first alternative to be evaluated was the production of glucose from maize starch, considered as the benchmark because of its widespread use in the current industry. Figure 4 depicts the influence of the different stages in several environmental impact categories, starch production being the most relevant one, as it accounts for the major contributions to all the evaluated environmental impacts (higher than 60% for all of them). The hydrolysis stage led to relevant contributions to the OD (ozonedepletion), FD (fossil depletion), and CC (climate change) categories. These results are related to the low starch concentration required for the enzymatic hydrolysis reactors (5 wt%) [2], a quite typical feature of biotechnological processes, which involves significant energy requirements for water heating to the optimal operating temperature for enzymes.  
As for transportation, this is only referred to the transference of the starch to the glucose production plant, being the primary maize grains transportation included in the starch production process, as explained in Section 2.2.1. Contributions of this stage are better appreciated in Figure 5, in which the starch production has been removed from the analysis, allowing it to perform a more comprehensive analysis of the rest of the process. At this juncture, transportation contributed to 10% of the overall impact on the acidification (TA) and toxicity (HT) indicators and more than 15% of the particle formation (PMF) category, due to the emissions coming from the diesel engines used in the used load transportation media.  
Besides transportation, Figure 5 depicts the contribution of some sub-processes considered in the hydrolysis stage: filtration units (ultrafiltration and nanofiltration), dilution (used to adjust the concentration of solids) and the hydrolysis reaction itself. These results confirmed the relevant influence  
Figure 4: LCA results obtained for the relative contribution of process stages to the evaluated impact categories in glucose production from maize starch.  
Figure 5: LCA results obtained for the relative contribution of process stages to the evaluated impact categories in glucose production from maize starch, excluding starch manufacture.  
of the reaction steps, due to the heating needs of the hydrolysis reactors. Unexpectedly, despite the huge amount required to reach the required solids concentration, the use of water for dilution during the hydrolysis stage also revealed to exert an important contribution to the human toxicity (HT) indicator when starch is not considered. This fact is related to some input flows of the inventory of the water generation process existing in the Ecoinvent v2.2 database. More information about this inventory is provided in the supporting information (see Table S8).
# A Comparative Evaluation of Cement and By-Product Petrit T in Soil Stabilization
## 3 Results and Discussion
### Particle Size Distribution (PSD)  
Table 1 present the results of the laser PSD analysis for natural soil and treated soil with cement and Petrit T after 28 days of curing.  
For both binder types, the general tendency is that the percentage of the clay size particles is reduced while the percentage of silt-sized particles is increased after treatment. Cement has more effect compared to Petrit T by lowering PSD curves towards the granular side. The changes in the PSD after treatment is attributed to flocculation and agglomeration of the fine particles during a short time after treatment. This is in addition to the pozzolanic reactions as a long-term effect [22].  
Flocculation leads to agglomerate the fine particles during a short period. Whilst over time, the pozzolanic reaction produces more cementitious materials of CSH and CSAH which coating the surface of soil particles. Both reactions are contributed to increasing the fraction of coarse-grained particles after treatment [47; 48]. Similar trends in changing the PSD are consistent with previous studies [22; 31; 49].
# Spiral-Resonator-Based Frequency Reconfigurable Antenna Design for Sub-6 GHz Applications
## 2 Antenna Design
### Parametric Analysis and Equivalent Circuit  
#### 2.2.1 Parametric Analysis  
Several critical design parameters are considered when developing the proposed antenna structure, including the dielectric constant, effective dielectric constant, wavelength, and characteristic impedance. To address potential issues, parametric analysis and theoretical calculations are performed. The effective dielectric constants are determined using equations from [PERSON] and [PERSON]'s study [50], which depend on the dielectric height and transmission line width. These equations demonstrate the importance of the effective dielectric constant, dielectric height, and transmission line width for the design. By using the above Equations (1)-(3), initial fundamental physical parameters are calculated to define the operating frequency ranges for different states of the antenna. Then, the geometrical parameters labeled in Figure 1a are studied through calculations and parametric analysis. By analyzing the reflection coefficient for each set of parameter values, the antenna's performances are assessed and compared. The goal is to find the combination of parameters that achieves the optimal antenna performance with the optimized values in Table 1.
###### Abstract  
background: resin-bonded fixed dental prosthesis (RBFDP) represents a highly aesthetic and conservative treatment option to replace a single tooth in a younger patient. The purpose of this in vitro study was to compare the fracture strength and the different types of failure on anterior cantilever RBFDPs fabricated using zirconia (ZR), lithium disilicate (LD), and PMMA-based material with ceramic fillers (PM) by the same standard tessellation language (STL) file. Methods: sixty extracted bovine mandibular incisives were embedded resin block; scanned to design one master model of RBEDP with a cantilevered single-retainer. Twenty cantilevered single-retainer RBFDPs were fabricated using ZR; LD; and PM. Static loading was performed using a universal testing machine. Results: the mean fracture strength for the RBFDPs was: 292.5 Newton (Standard Deviation (SD) 36.6) for ZR; 210 N (SD 37.6) for LD; and 133 N (SD 16.3) for PM. All the failures of RBFDPs in ZR were a fracture of the abutment tooth; instead; the 80% of failures of RBFDPs in LD and PM were a fracture of the connector. Conclusion: within the limitations of this in vitro study, we can conclude that the zirconia RBFDPs presented load resistance higher than the maximum anterior bite force reported in literature (270 N) and failure type analysis showed some trends among the groups  
zirconia; digital dentistry; lithium disilicate; resin bonded bridge; fracture; adhesive restorations; CAD/CAM; PMMA
## 4 Discussion
### Possible Reasons for the Urbanization-Induced Forest SOC Changes
Some research uncertainty in this study should be pointed out, too. Firstly, laboratory-based basal respiration data may be dramatically different from those in field, although this kind of laboratory respiration measured is used as a routine method for basal respiration measurement [32]. SOC/respiration ratio is often used as an indicator of SOC turnover in instant measurements. In this paper, the scale-up from laboratory measurement to whole-year soil respiration, as well as SOC turnover time, might be different from some exact measurements, such as isotope measurements, although the patterns at urban-rural gradients in soil respiration, Q\({}_{10}\) and TT should be reliable in this paper. During field surveys, in situ soil respiration was not fully distinguishable between autotrophic and heterotrophic sources in such a large-scale survey, and ensuring the same environments (temperature and moisture, two important factors controlling respiration capacity) and field methods (such as the stretched-box method), were not possible in urban environments [12]. The laboratory incubation method should be the optimal way to measure the respiration differences among the 306 samples in the same environment, and also Q\({}_{10}\) values. Secondly, land use changes were not clear during the 100-year urbanization process. Our study manifested that land use alternations (such as LF proportion) are an important reason for the urbanized SOC pattern. The original land use in this region before urbanization was grassland/pasture. Owing to frequent disturbance in urban regions, the previous land-uses in some studied forests in this paper (such as roadside forest) were not recorded clearly. This may increase the uncertainty of this paper too, as for example, whether old city forest SOC increases or outer new city region SOC decreases, are the main contributors to the urban-rural pattern of carbon dynamics.
## 2 Analysis of Imaging Properties of HDOE in Wide-Bandwidth Spectrum  
The focus blur of visible spectrum bandwith is a long-standing problem in diffractive lens [2]. The research on the imaging characteristics of HDOE in the bandwidth spectrum and the quantitative analysis of its image quality degradation are of great benefit to the construction of its image post-processing algorithm. In this section, the spectral characteristics of HDOE were firstly analyzed, and then the image quality degradation model of HDOE under bandwidth spectrum was constructed.
## 2 Literature Review
### Research Gaps and Contributions  
Despite the research progress made in [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11], key gaps remain in effectively addressing noisy and incomplete data, in addition to high computational costs. Many traditional methods lack scalability and real-time capability. Drawing from our literature review, conventional curve approximation techniques, such as splines [20] and B-splines [21], have primarily been applied in computer graphics, rather than for terrain modeling. In contrast, our study repurposes these methods for robust terrain surface approximation under noisy conditions, which is critical for construction site management. Similarly, traditional implementations of the marching cubes algorithm [14] have been extensively used in static medical imaging but not in dynamic, large scale excavation site. Our integrated approach refines the marching cubes process for real-time volumetric reconstruction and soil volume estimation, offering a scalable and efficient solution tailored to autonomous excavation systems.