esa-sceva/satcom-chunk-collection huggingface dataset:
# Drag and Attitude Control for the Next Generation Gravity Mission
###### Abstract  
The Next Generation Gravity Mission (NGGM), currently in a feasibility study phase as a candidate Mission of Opportunity for ESA-NASA cooperation in the frame of the Mass Change and Geo-Sciences International Constellation (MAGIC), is designed to monitor mass transport in the Earth system by its variable gravity signature with increased spatial and temporal resolution. The NGGM will be composed by a constellation of two pairs of satellites, each providing the measurement of two quantities from which the map of Earth's gravity field will be obtained: the variation of the distance between two satellites of each pair, measured by a laser interferometer with nanometer precision; and the relative non-gravitational acceleration between the centers of mass of each satellite pair, measured by ultra-sensitive accelerometers. This article highlights the importance of the second \"observable\" in the reconstruction of the lower harmonics of Earth's gravity field, by highlighting the tight control requirements in linear and angular accelerations and angular rates, and the expectable performances from the drag-free, attitude, and orbit control system (DFAOCS) obtained through an end-to-end (E2E) simulator. The errors resulting from different mission scenarios with varying levels of drag-free control and pointing accuracy are then presented, demonstrating that a high-performance accelerometer alone is not sufficient to achieve the measurement quality necessary to achieve the mission objectives, if the spacecraft does not provide to this sensor a suitable drag-free environment and a precise and stable pointing. The consequences of these different mission scenarios on the gravity field retrieval accuracy, especially for the lower spherical harmonic degrees, are computed in order to quantitatively justify the rationale for these capabilities on the NGGM spacecraft.  
gravity field recovery; satellite-to-satellite tracking; non-gravitational acceleration measurement; drag-free control Article
## 2 Materials and Methods
### Magnetotelluric Sounding (MT)  
The magnetotelluric method studies the penetration and propagation of electromagnetic waves inside the Earth, associated with the action of electrical storms and/or the incidence of the solar wind on the Earth. The method is based on measurements of the natural electric fields on the Earth's surface (by means of 2 perpendicular electric dipoles, \(E_{x}\) and \(E_{y}\)) and magnetic (using 3 coils or triaxial magnetometers, \(B_{x}\), \(B_{y}\), and \(B_{z}\)).  
Among the advantages of the magnetotelluric method is the fact that it is based on using a natural electromagnetic source. The Earth's surface partially reflects the fluctuating electromagnetic fields originating in the ionosphere, and the ionosphere reflects the returning fields again due to its conductive characteristics. This happens repeatedly, so that the fields eventually have a strong vertical component and can be considered as vertically propagating plane waves, characterized by covering a broad spectrum of frequencies. These fields penetrate the ground and induce telluric (electric) currents, which generate secondary magnetic fields. The telluric currents, detected by two pairs of electrodes that make up each pair of dipoles, are oriented in the N-S and E-W directions. The three components of the magnetic fields are measured: the vertical component and two horizontal components, parallel to each one of the electrical components [6; 20].  
This method provides information about resistivity (conductivity) values for much greater depths than artificial source induction methods. Using long-period signals in the range from 10 to 1000 s, the MT method is relevant to the investigation of the crustal and upper mantle structure [20].  
The two electrical and three magnetic components of an MT sounding are recorded continuously during long observation intervals, which can last hours or days. The registered magnetic fields have external contributions from the ionosphere and internal ones related to the distribution of the induced currents. Although an MT sounding can be carried out in a range of infrasound frequencies (\(f\approx 10\)-100 Hz), its main application is the determination of electrical conductivity (resistivity) values at great depths, using very low frequencies (\(f\approx 1\) Hz) [6; 20].
## 3 Results and Discussion
### Reasons behind the Failures of the Contemporary Approaches
#### 3.2.1 Unavailability of High-Quality Data  
Image quality is often considered an important, frequently faced challenge in machine vision systems. Image quality refers to the high resolution and chrominance of the image. Commonly, machine vision systems are trained and tested on a high-quality image dataset, yet the high quality of the dataset cannot always be assumed [40]. For this reason, several contemporary machine vision algorithms underperform in the real world. Quite expectedly, we also found that the detection quality of a deep CNN model's performance strongly depends on the quality of the samples.  
However, as discussed earlier, the proposed pixel-wise k-IN is robust in this situation because of its exhaustive search mechanisms to locate the dark pixels and their k-immediate dark neighbours deterministically. This approach helps pixel-wise k-IN identify the rock pores and fractures in each image sample. Other model parameters, such as \(\alpha,\ \beta,\ \gamma\) and \(\delta\), are responsible for classifying \(\mathcal{H}_{i}\) as a pore or a fracture. The values of the model parameters depend on the problem statement, sample rock porosity and its other necessary geophysical properties.
## 2 Materials and Methods
### MALDI-TOF MS
#### 2.2.2 MALDI-TOF MS Oenological Laboratory Specific Database (OLS-DB)  
The yeast strains chosen to enhance the new laboratory specific database, provided by CRB Oeno (centre de Ressources Biologiques, Unite de Recherche Oenologie, Villenave d'Omon, France), are listed in Appendix A Table A1. These strains were previously identified by sequencing of 265 rDNA using NL1-NL4 primers [37] (Table A1). An oenological microorganism mass profiles database was created with the MTB Compass Explorer Module (Version 4.1) and Flex Analysis (Version 3.4) (Bruker Daltonics, Bremen, Germany) as follows. A complete extraction was carried out for each strain added to the database. The strains were grown and subcloned on YPG medium. For each isolate, yeast protein extraction was carried out in duplicate in order to generate the reference MALDI-TOF MS spectra for a given strain.  
For yeast protein extraction, one fresh colony of each previously-purified isolate was transferred into an Eppendorf tube containing 300 \(\upmu\)L of High Performance Liquid Chromatography (HPLC) quality water (VWR Prolabo, Fontenay-sous-bois, France), and a cloudy suspension was obtained after stirring. A total of 900 \(\upmu\)L of absolute ethanol (VWR Prolabo, Fontenay-sous-bois, France) was added and then centrifuged at 13,000-15,000 rpm for 2 min. The supernatant was removed, and the resulting pellet was allowed to air dry at room temperature for 5 min. A total of 25 \(\upmu\)L of 70% formic acid was added and mixed using a pipette until the pellet was completely dissolved, then 25 \(\upmu\)L of 100% acetonitrile (VWR Prolabo, Fontenay-sous-bois, France) was added and all vortexed. Finally, the mixture was centrifuged for 2 min at 13,000-15,000 rpm and 1 \(\upmu\)L of the supernatant was deposited onto an MSP 96 target polished steel BC (Bruker, Germany) and allowed to dry at room temperature. All the samples were overlaid with HCCA (1 \(\upmu\)L) matrix for crystallization.  
For a given strain, four separate deposits from each of the two protein extractions were distributed on the plate. These eight deposits allowed 24 MALDI-TOF MS spectra to be obtained per strain. A baseline check was then performed for each of the 24 spectra, which were compared in pairs: this allowed the homogeneity of the spectra for a given strain to be assessed. The 70 most intense peaks of all spectra of each strain were listed, taking their frequency of occurrence into account.
# Circulating Current Reduction in MMC-HVDC System Using Average Model
###### Abstract  
Modular multilevel converters (MMCs) are quickly emerging as a suitable technology for a voltage-source converter-based high-voltage direct-current (VSC-HVDC) transmission systems due to its numerous advantages as reported in literature. However, for a large DC-network, MMCs require large numbers of sub-modules (SMs) and switches, which makes its modeling very challenging and computationally complex using electromagnetic transient (EMT) programs. Average Value Model (AVM) provides a relatively better solution to model MMCs by combining cells as an arm equivalent circuit. Circulating current is an important issue related to the performance and stability of MMCs. Due to circulating currents, power loss in a converter increases as root mean square (RMS) values of the arm current increases. The traditional method for inserting SMs in each arm is based on direct modulation, which does not compensate for the arm voltage oscillations, and generates circulating current in each leg of a three-phase MMC. This paper presents a new method for reducing the circulating current by adding 2 nd and 4 th harmonics in the upper and lower arm currents of an MMC. Less capacitor energy variations are obtained by the proposed method compared to traditional direct modulation methods. The proposed method is tested on a common symmetrical monopole (point-to-point) MMC-HVDC system using vector current control strategy in PSCAD/EMTDC software. Analytical and simulation results show the effectiveness of the new method in minimizing the circulating current and arm voltage oscillation reductions as compared to the direct modulation approach.  
average-value model; electromagnetic-transient (EMT) program; HVDC transmission; modular multilevel converter; voltage-source converter (VSC) +
Footnote †: journal: Applied Physics Letters
## 3 Results and Discussion  
### Effects on Crystalline Phase  
Figure 3a shows XRD profiles of the samples obtained from aqueous chemical growth without annealing. The broad diffraction peak around 20\({}^{\circ}\) is assigned to amorphous SiO\({}_{2}\) (JCPDS 51-1593), which is the matrix of FTO glass. The diffraction peaks marked with bold dots belong to SnO\({}_{2}\) (JCPDS 46-1088), a conductive film on the glass matrix. In addition to these background peaks, characteristic diffraction peaks of crystalline \(\beta\)-FeOOH (JCPDS 34-1266) also exist. Figure 3b displays XRD profiles of the samples after annealing at 500 \({}^{\circ}\)C for 1 h. By comparing Figure 3a,b, it was found that annealing led to the transformation from \(\beta\)-FeOOH to \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) (JCPDS 33-064). Such a phase transformation was also indicated by the color change of the sample from yellow to red (see Figure 4). In order to find out whether the \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) are oriented, the intensity ratio of each characteristic peak relative to the (1 0 4) peak, which shows the largest intensity, was calculated, and compared with the standard data in JCPDS 33-064. The two sets of data are almost consistent with each other, indicating the \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) are not oriented.  
Figure 3 also shows that the XRD profiles of the Co-doped and the Ni-doped samples are almost the same as that of the undoped one. Neither dopant-related phases nor a shift of the \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) diffraction peaks was observed in the XRD profiles of the doped samples. This suggests the doping of Co or Ni has few influences on the crystal structure of \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\). This is probably because Co or Ni is successfully doped into the crystal lattice of \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) due to their similar atomic structures and the amount of the dopants was small. Similar results have been reported by others [(36; 39)]. [PERSON] et al. [(36)] believed that Co could be easily incorporated into the crystal lattice of \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) and hence considered Co to be a suitable dopant for \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\). [PERSON] et al. [(39)] synthesized \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) nanowires on a FTO substrate and diffused Sn from FTO to \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) by high-temperature sintering. Their SEM and XRD results revealed that neither the structure nor the crystal phase of the \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) changed after Sn was incorporated.  
Figure 2: Structural drawing of a three-electrode photoelectrochemical cell.
## 2 Optimized Geometric and Operational Design of an Induction Motor  
The first key element for the comparative investigation in our study was the appropriate design configuration based on the specific selection data. A numerical approach using finite element analysis (FEA) approximation was used to visualize the magnetic field of the motor and its operational characteristics under specific loading conditions such as the torque, nominal current, and power factor. For the purpose of design and simulation, Ansys Maxwell 2023R1 software was used, while modeling was performed in Matlab 2023a environment.  
The electric propulsion system studied included two identical induction motors with a short-circuited cage rotor with an output power equal to 10 MW. The motors were powered through an AC/DC/AC inverter with pulse width modulation (PWM) and polar voltage equal to 6600 Volt at a frequency of 60 Hz. Their nominal mechanical rotational speed was equal to 504 rpm, giving an output torque of 189,512 Nm. The efficiency of the final topology developed was 95.20%.  
High-power electric propulsion motors for ships, particularly those rated at 10 MW, must meet strict requirements to ensure efficiency, reliability, and performance. These motors need to exhibit high efficiency across various load conditions to minimize operational costs and energy consumption. Compact design and high power density are essential to save space and reduce weight in a ship's propulsion system. Durability and resistance to harsh marine environments, including humidity, vibrations, and temperature variations, are critical for reliable long-term operation. Smooth torque delivery, fast response, and low acoustic noise are necessary for precise maneuvering and passenger comfort. Additionally, motors must support advanced control systems for optimal performance, while maintenance should be straightforward to minimize downtime. As such, the design and optimization process for an induction motor for marine electric propulsion contains several key steps [38].
## 4 Case Study
### IPC-Based Coordinate System and Opportunity Identification
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Patent Number** & **Application Date** & **Title** & **Description** \\ \hline CN103869442B & 1 April 2014 & Focusing device, shooting device and air vehicle & A method to remotely control camera zoom, for adapting multi-scene shooting \\ \hline CN103973941B & 14 May 2014 & Method and system for adjusting dynamic contrast of digital image or video & A method for high-quality digital image or video, to dynamically adjust the image contrast by calculating the conditional distribution function of the pixel brightness of the image \\ \hline CN104168403B & 27 June 2014 & High dynamic range video recording method and device based on Bayer color filter array to capture the image blur caused by high-speed continuous shooting \\ \hline CN105793892B & 9 December 2014 & Image processing method and apparatus and photographing device & Correct camera distortion of wide-angle lenses \\ \hline CN105874779B & 31 March 2015 & An image forming apparatus, a light filling control method thereof, a system, and a movable object & A supplementary light filing control method using the imaging system’s exposure parameters \\ \hline CN105519093B & 29 April 2015 & Follow focus, remote control follow focus system with same and aircraft & Dynamic adjustment and tracking of the focus during mobile shooting \\ \hline CN107113376B & 31 July 2015 & Image processing method, device and camera & A method for anti-shaking, using the shake angle \\ \hline CN105554480B & 1 March 2016 & Unmanned aerial vehicle image shooting control method and device, user device and unmanned aerial vehicle & A method to improve the flexibility of shooting, by dynamically adjusting the position of the target on the tracking screen \\ \hline CN107079104B & 24 August 2016 & Wide angle photograph shooting method, apparatus, holder, unmanned aerial vehicle and robot & A method for ultra-wide-range shooting by controlling the rotation and angle of the lens in horizontal and vertical directions \\ \hline CN110313174B & 15 May 2019 & Shooting control method and device & The control information is detected from the voice information, to meet the automation and intelligent needs of user shooting control \\ \hline CN112106341B & 30 August 2019 & Shooting method, device and shooting equipment & Quickly respond to shutter opening information to more accurately record shooting moments \\ \hline CN112513731B & 28 February 2020 & Exposure unit, lens assembly, photographing equipment, and method of assembling the exposure unit & Partially block the light entrance, to adjust exposure parameters \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Patents with radical invention features in the executive system of UAVs.
## 2 Materials and Methods
### Variance-Covariance Regularization  
Figure 1 depicts the whole proposed framework in this paper. As can be seen in this figure, Variance--Covariance Regularization is applied to both branches of the architecture separately, thereby preserving the information content of each embedding at a certain level and preventing informational collapse [43] independently for the two branches. The Variance preservation term ensures that the embedding vectors do not collapse toward zero by explicitly preventing shrinkage. It employs a hinge loss to maintain the standard deviation of each embedding dimension above a specified threshold within a batch. Equation (4) enforces differentiation between the embedding vectors of samples within the batch,  
\[v(Z)=\frac{1}{d}{\sum_{j=1}^{d}max\left(0,1-\sqrt{Var\left(z^{j}\right)+ \epsilon}\right)} \tag{4}\]  
where \(\epsilon\) is a small scalar to prevent numerical instabilities. This criterion ensures that the Variance within the current batch equals one along each dimension, thus avoiding a collapse where all inputs are mapped onto the same vector.  
The Covariance criterion avoids informational collapse by tackling redundancy among the embedding variables [49]. It includes a term that minimizes the Covariances between every pair of embedding variables within a batch toward zero. Equation (5) promotes decorrelation among the variables within each embedding and avoids situations where the variables vary together or are highly correlated, thus preventing informational collapse. This regularization does not impose the constraint of weight sharing between the two branches.  
Additionally, integrating Variance preservation into other self-supervised joint-embedding methods enhances training stability and improves downstream task performance [43].  
\[C(Z)=\frac{1}{n-1}{\sum_{i=1}^{n}}(z_{i}-\underline{z})(z_{i}-\underline{z})^{T},\text{ }\text{where }\underline{z}=\frac{1}{n}{\sum_{i=1}^{n}}z_{i} \tag{5}\]  
\[c(Z)=\frac{1}{d}{\sum_{i\
eq j}}[C(Z)]_{i,j}^{2} \tag{6}\]  
The Covariance regularization term in Equation (6) can be defined as the summation of squared off-diagonal coefficients in the Covariance matrix \(C(Z)\) and scaled by a factor of \(1/d\) where \(d\) is the dimension of vector. This regularization term helps to mitigate excessive correlation among dimensions. The purpose of this term is to enforce the off-diagonal coefficients of the Covariance matrix \(C(Z)\) to approach zero. Doing so aims to reduce the correlation between different dimensions of the embeddings and prevent them from encoding redundant information. Equation (7) is the average of the Variance and Covariance terms as an overall VCR loss function.  
\[L_{VCR}=\frac{1}{2}(v(Z)+c(Z)) \tag{7}\]
# Unified Ciphertext-Policy Weighted Attribute-Based Encryption for Sharing Data in Cloud Computing
## 8 Conclusions  
In this paper, we have proposed a novel UCP-WABE scheme for sharing data in cloud computing environments. The scheme optimizes the encryption of data that are encrypted under the multi-providers' access policies where these policies have a mutual sub-policy. UCP-WABE utilizes a mutual information extractor to extract the mutual sub-policy and produce mutual information, which assists in optimizing the encryption. UCP-WABE also takes advantage of weighted attribute-based encryption to avoid too complex of an access structure. We analyse the computational complexity of UCP-WABE theoretically and experimentally. The analyses indicate that UCP-WABE has a better efficiency of encryption. The security analysis shows that UCP-WABE is selectively secure. It should be noted that we only consider the case of two data providers. In practice, UCP-WABE will  
Figure 8: Encryption time cost for the changed weight of attributes in the access tree. Figure 7: Encryption time cost for the changed number of access tree attributes. have a more efficient data sharing if the more providers' access policies have a mutual sub-policy. In our future work, we will optimize the system implementation and conduct comprehensive experiments with real-life cases in cloud computing. [PERSON] proposed the main idea and conceptualization. He also performed experiments, results analysis, and scientific discussions and wrote the paper. [PERSON], [PERSON] and [PERSON] helped to revise the clarity of the work, as well as write and organize the paper. Finally, [PERSON] assisted in English corrections and submission of the article. This work was supported in part by the National Key R&D Program of China under Grant 2017 YFB0802300, in part by the National High-tech R&D Program of China (863 Program) under Grant 2015 AA016005 and Grant 2015 AA017201, in part by the Applied Sci-Tech R&D Special Fund Program of Guangdong Province under Grant 2015B010131007 and in part by the China Scholarship Council under Grant 201506470040. The authors thank the reviewers for their valuable comments and suggestions, which improved the technical content and the presentation of the paper. The authors declare that they have no conflict of interest. The following abbreviations and notations are used in this manuscript:  
UCP-WABE unified ciphertext-policy weighted attribute-based encryption  
\(M_{i}\)  
the data that provider \(i\) wants to share  
\(\Gamma_{i}\)  
the weighted access tree relates to \(M_{i}\)  
\(\tilde{e}(\cdot)\)  
a bilinear mapping  
\(\mathcal{G}_{1}\)  
\(\tilde{e}(\cdot)\)'s input group  
\(\mathcal{G}_{2}\)  
\(\tilde{e}(\cdot)\)'s output group  
\(p\)  
\(\mathcal{G}_{1}\)'s order, namely there are \(p\) elements in \(\mathcal{G}_{1}\)  
\(\mathbb{Z}_{p}\)  
the set of integers \([0,p-1]\)  
\(g\)  
\(\mathcal{G}_{1}\)'s generator.