esa-sceva/satcom-chunk-collection huggingface dataset:
# Supporting Privacy of Computations in Mobile Big Data Systems +
## 2 A High-Level Overview of Our System  
In our proposed system, the client utilizes a set of \((n+2)\) servers, \(\{p_{1},p_{2},\ldots,p_{n},p_{c},p_{e}\}\), in the cloud. To each server \(p_{i}\)\((1\leq i\leq n)\), the client initially sends a description of the desired computation (simple examples of which could be addition of two numbers, computation of hamming distance between two bit sequences, _etc._), and a unique seed value \(s_{i}\). Each of the \(n\) servers first creates (or retrieves from its repository, if available already) a corresponding Boolean circuit (\(B\)) for the requested computation. Each server \(p_{i}\)\((1\leq i\leq n)\), uses the unique seed value \(s_{i}\) to generate a private pseudorandom bit sequence whose length is proportional to the total number of wires in the Boolean circuit (\(B\)). Then, these \(n\) servers use their private pseudorandom bit sequences and the Boolean circuit (\(B\)) as inputs, communicate with one another, as well as perform some local computations, according to a secure multiparty computation protocol, to create their shares (\(GC_{i}\), \((1\leq i\leq n)\)) for an one-time program called a \"garbled circuit\".  
Once the shares for the garbled circuit are created, the client instructs all of the \(n\) servers, \(p_{i}\)\((1\leq i\leq n)\), to send their shares, \(GC_{i}\), to the server \(p_{c}\). Applying an \(XOR\) operation on these shares, the server \(p_{c}\) creates the desired circuit, \(GC=GC_{1}\oplus GC_{2}\oplus\ldots\oplus GC_{n}\). Subsequently, the client instructs the server \(p_{c}\) to send the garbled circuit \(GC\) to another server \(p_{e}\) for evaluation, either for immediate or future use. Now, the client generates its own garbled input values for each input wire in the circuit using the unique seed values \(s_{i}\)\((1\leq i\leq n)\), and sends them to the server \(p_{e}\) for evaluation. Using these garbled inputs, the server \(p_{e}\) unlocks each gate on the first level of the circuit to obtain the corresponding garbled outputs, which, in turn, can unlock each gate on the second level of the circuit, and so on. In this manner, the server \(p_{e}\) unlocks every gate in the circuit, to obtain the garbled outputs of the circuit, and returns them to the client. To recover the result of the desired computation, the client now translates these garbled output values into plaintext bits.  
Figure 1 depicts an overview of our proposed secure cloud computing system with \((n+2)=5\) servers.
## 3 Results and Discussion
### Effect of Strain FY-07 on Degradation of Strain WJ-1  
After the degradation by WJ-1, FY-07 and the mixture of the two strains for 7 days, the relative contents of the different components of the crude oil (saturated hydrocarbons, aromatic hydrocarbons, non-hydrocarbon, and asphaltene) before and after degradation are shown in Figure 5. Luliang oil without microbial treatment consisted of 71.62% oil saturated hydrocarbons, 9.91% aromatic hydrocarbons, 13.84% non-hydrocarbons, and 4.63% asphaltene. After degradation by WJ-1, the content of the saturates decreased to 70.40%, while the proportions of aromatics, non-hydrocarbon, and asphaltene increased to 10.33%, 14.03%, and 5.23%, respectively. This indicates that WJ-1 mainly degraded the saturated hydrocarbons. After degradation by FY-07, the contents of the saturates and aromatics increased to 73.43% and 10.72%, respectively. In contrast, the proportions of the  
Figure 4: Growth curve of _E. cloace_ FY-07 without and with _Pseudomonas aeruginosa_ WJ-1.  
Figure 3: Surface tension curve under the action of different bacteria.  
non-hydrocarbon and asphaltene increased to 14.03% and 5.23%, which indicates that WJ-1 mainly degraded the saturated hydrocarbons. When crude oil passes through the combined action of WJ-1 and FY-07, the proportion of the saturates and aromatics reduced to 66.07% than WJ-1, which indicates that FY-07 improved the degradation of saturated hydrocarbons by WJ-1.  
The compositions of the saturated hydrocarbons were analyzed by GC method [19]. A relative wide range of alkanes (C8-C45) were utilized by the strains according to GC analysis (Figure 6). The degradation of FY-07 was not obvious, and the degradation of WJ-1 and complex bacteria was obvious. The degradation was mainly reflected in the decrease of C15+ content and the increase of C14- content (Figure 7). By calculating the ratio of C14- to C15+, it was found that the ratio untreated crude oil was 0.17, and for WJ, FY-07, and WJ-1 and FY-07 mixture was 0.37, 0.15, and 0.67, respectively. Obviously, FY-07 did not degrade the crude oil, but it promoted the degradation of WJ-1.  
Figure 5: Contents of different carbon numbers of crude oil before and after microbial treatment.  
Figure 6: Gas chromatography (GC) analysis of n-alkane compositions of crude oil after treatments of strains. (**A**) Control; (**B**) WJ-1; (**C**) FY-07; (**D**) WJ-1 + FY-07.
## 1 Introduction
[PERSON]'s study concluded that in some cases, the concentrations of particles were 10-100 times lower than the necessary parameters and that the rooms were of a higher purity class entirely [7]. According to [PERSON] et al. [2], the control of internal contaminants in cleanrooms with overpowered and oversized ventilation systems comes about because the designs and ACH values of these systems are based on principles published in a standard or code, such as the Federal Standard FS-209 [27], IEST Best Practices RP-12.1 [28], or ISO Std. 14644-4: 2004 [29]. The study by [PERSON], et al. shows a direct connection between the reduction in the concentration of particles in a cleanroom, the increase in the ACH, and the share of the floor area for the extraction of polluted air. These results were obtained at 60-146 h\({}^{-1}\) ACH, which are typical for high purity classes [2]. [PERSON] et al. [30] stated that increasing the ventilation rate is the easiest way to improve air quality and cleanliness. However, studies on pollutant reduction have shown that high ACH values may not always guarantee a higher purity class, as shown by the studies of [PERSON] and [PERSON] [31]. They performed numerical and experimental investigations of the effects of ACH on airflow distribution and CO\({}_{2}\) concentration in a clean room with unidirectional airflow. The results illustrated that the recommended ACH should be based on room characteristics rather than empirical formulas. The increase of ACH from 15 h\({}^{-1}\) to 20 h\({}^{-1}\) did not significantly affect the pollutant removal efficiency in the occupied zone of a Class 10,000 cleanroom model. On the other hand, increasing the ACH from 20 h\({}^{-1}\) to 25 h\({}^{-1}\) showed a visible reduction in room residence time from 32% to 21% [32]. In contrast to the study by [PERSON] et al. the study focused on the higher ACH range, 20-40 h\({}^{-1}\), typical of purity classes ISO EN 7-8, where most operating theaters are included. Various mathematical models have been proposed to represent the relationship between particle concentration in clean rooms and ACH, but some factors that could affect the accuracy of the model have not been considered to simplify them. Continuous generation of particles or their removal due to the operation of the ventilation system and settling of particles on the surface of the equipment and internal structures were not considered [33; 34; 35; 36]. From the presented studies, one may conclude that there is a relationship between ACH and the value of the concentration of particles in the cleanroom. This assumption was verified in this study by using numerical simulations and experimental measurements to display the air velocity profile. The aim of this work was to determine the optimal airflow rate through the supply distribution element in the operating room. The main criteria for the optimal setting of air velocity and flow were to maintain a low concentration of particles in the patient area and amongst the instruments, a low energy consumption ventilation system, and to ensure the required temperature and humidity of the room.
## 4 Simulation Experiments and Discussion
### Experiment 1: Validation of the MO-Based ABP Determination Model
Finally, it must be pointed out that since the QOF system described in Section 2.1 can allow the electrical boresights of different frequency bands to be coaxially aligned on a common boresight, the experimental results presented herein are the same for different frequency bands, except for the computational time consumed by the GRASP software in calculating the 3-D far field antenna pattern. In other words, while the experimental results were generated for particular operating frequencies, they were representative of any operating frequency to be used for the future GEO microwave radiometer. In conclusion, the MO-based ABP determination model could achieve a comparable ABP determination accuracy to that of the PO approximation with a significant improvement in computation time. Therefore, the MO-based model could completely replace the PO approximation for real-time ABP determination on the GEO satellite.
# A Flexible FPGA-Based Stochastic Decoder for 5G LDPC Codes
## 4 Proposed Architecture
### Stochastic Variable Node Processing Unit (SVNPU)  
In this stochastic architecture, the chance of SVNPU output being in the hold state increases as inputs to SVNPU increase [24]. The SVNPU forces the current output to continuously repeat the previous output over a certain period when the two input bits of the SVNPU are not equal, known as the hold state of the SVNPU [25]. Due to this state, the decoder is unable to make correct decisions. It interrupts the decoder convergence, and its bit error rate (BER) performance degrades. Hence, the architecture of high-column-weight SVNPU is built using low-weight sub-nodes with memory blocks; typically, \(w_{v}\leq 4\) sub-nodes are employed.  
As shown in Figure 6[24], the column-weight \(w_{v}=6\) SVNPU is constructed using two column-weight \(w_{v}=3\) and one \(w_{v}=2\) sub-nodes. The memory blocks are internal memory (IM), which has a length of \(I=2\) bits for each sub-node, and edge memory (EM), which has a length of \(E=64\) bits at the output edge. The critical role of EM and IM is to minimize the correlation produced by the hold state in a stochastic sequence and disrupt the correlation of the stochastic sequence by randomizing stochastic bits [29]. We used a dual-tree design [27] to build a high-column-weight SVNPU that would be flexible enough to handle any active inputs and outputs up to the maximum \(\lambda=W_{v}+1\), which is a power of two. For instance, column weight \(W_{v}=30\) of SVNPU has \(\lambda=32\) inputs and outputs. As a result, the adopted SVNPU dual-tree design requires a total of \(S=3\times\lambda-6=90\) sub-nodes. Two significant components, summing and combining, each with \(t=\log_{2}(\lambda)-1=4\) stages, make up the dual-tree structure.
# Graphene-Based Materials for the Separator Functionalization of Lithium-Ion/Metal/Sulfur Batteries
## 2 Preparation Methods of Graphene-Based Materials
### Others
#### 2.3.5 Vacuum Filtration and Liquid-Air Interface Self-Assembly
Applications of Graphene-Based Materials for the Separator Functionalization in Lithium-Ion/Metal/Sulfur Batteries  
Recently, considerable attention has been given to modification of the separator, exploring solutions for (1) inadequate chemical/mechanical stability, which causes a short cycle life, poor rate performance, shortcuts, and other unwanted consequences for lithium-ion/metal/sulfur batteries; (2) low thermal stability, which leads to unstable electrochemical performance in varying temperatures, melting, and even combustion under high temperatures; (3) poor wettability to the electrolyte, derived from low polarity and the unsuitable pore size of traditional polyolefin separators, which leads to inferior ion transfer kinetics [98; 99]; and (4) nonuniform structure distribution, which may bring about a concentration of current, promoting lithium dendrite growth [100]. Due to excellent conductivity, superb thermostability, outstanding mechanical strength, large specific surface area, and abundant active sites for high electrocatalytic activity, graphene-based material is regarded as one of the most promising candidates for separator modification. Here, we introduce the applications of graphene-based materials for the separator in lithium-ion batteries, lithium-metal batteries, and lithium-sulfur batteries.
## 6 Conclusions  
Based on the sensor-observed signals just above the sea surface, the OOB response was evaluated for the three visible bands (i.e., blue, green, and red) of the two CZI sensors onboard the HY-1C satellite, which will be launched in September 2018. The evaluation in the Case 1 (clear) and Case 2 (turbid) waters shows that the OOB response of the two sensors was consistent. For the phytoplankton-dominated (Case 1) water, the significant (>2%) OOB effect was found in the green band over the oligotrophic waters (Chla \(\leq\) ~0.1 mg/m\({}^{3}\)), which is far from the coast which is the hotspot of CZI observation. The OOB effect can be corrected by a proposed model based on the CZI blue-green band ratio of spectral remote sensing reflectance. For the turbid coastal (Case 2) waters dominated by suspended sediment and colored dissolved organic material, the OOB effect can be neglected (\(\leq\)-2%) for the three visible bands. This research highlights the importance of comprehensive pre-launch radiometric characterization and the OOB evaluation for the space-borne sensor designed for coastal zone monitoring, especially for quantitative ocean information retrieval.  
Conceptualization, T.C., J.D., J.L., and J.Z.; Data Curation and Analysis, T.C., J.D., F.J., B.M., R.L., and P.X.; Writing, T.C., J.D., and J.Z.  
This research was funded by National Natural Science Foundation of China [41476159, 41876206, 41506203, and 41506204], the National Key Research and Development Program of China [2016 YFA0600102], the China-Korea Joint Ocean Research Center [PI-2017-3], and Dragon-4 program [32405].  
NASA (National Aeronautics and Space Administration, USA), ESA European Space Agency (ESA), and NSMC (National Satellite Meteorological Centre of China) are acknowledged for providing AQUA MODIS, ENVISAT MERIS, and FY-3 MERSI data, respectively. [PERSON] and [PERSON] are acknowledged for comments on the manuscript, respectively.  
The authors declare no conflicts of interest.
## 2 Related Work
### Uncertainty Analysis  
Uncertainty analysis is vital for all measurements and, as reported by the National Physical Laboratory, measurements are only complete with a complete reference to the uncertainty in the measurand [9]. In common with [5; 6], we consider the uncertainty that derives from measuring QoS parameters using sampling. Since QoE can be represented as a mathematical expression in terms of QoS parameters using the uncertainty propagation techniques presented in [10], the uncertainty in QoE is investigated. The evaluation of the propagated uncertainty is commonly used in different fields of biochemistry [8], physics [9] and psychology [10].  
In this paper, the propagation of the uncertainty depends upon the mathematical model that relates QoE to QoS metrics, and whether the QoS parameters under observation are considered to be independent of each other or correlated. Our analysis of real network measured data has shown that they are in fact correlated. A viable uncertainty analysis for correlated variables requires the distribution of the uncertainty in each variable.
# Upgrading of the L-P Band Cryogenic Receiver of the Sardinia Radio Telescope: A Feasibility Study
## 3 Study of the Receiver Criticalities and Workflow for the Upgrading Feasibility Study
### Mitigation of the Self-Produced RFIs
#### 3.2.2 Mitigation of RFIs Generated by the Feeding Process of the Active Microwave Components  
Regarding the unwanted signals generated by the feeding process of the active microwave components of the receiver, presuming that they are chosen from the state of the art with a low unwanted signals generation, most of them cannot be eliminated. In any case, considering the use and performances of the receiver in its period of service and the future GAIA electronic board installation, some active components can be removed. One type of them is the commercial cryogenic coaxial mechanical switch (model Agilent 8761B [35]), highlighted in Figure 12a and in the photo of the Dewar block (Figure 12b). The receiver was equipped with these switches in order to isolate the LNAs in case of high unwanted or self-produced high signals (i.e., SRT should be equipped in the future with a transmitter for deep space and near-earth applications [29]). The role of these switches of Figure 12 can be executed directly by the new GAIA control board. It can remotely power off the LNA implementations, guaranteeing a high protection from high power levels of self-generated RFIs, making useless the presence of these switches.  
An RFIs measurement campaign is performed in order to establish the amount of signals generated by these components. In particular, the receiver feed is covered with a metal cap and an electric field probe connected to a spectrum analyzer (model FSV40 from Rohde and Schwarz) is used for performing the measurement. The instrument is setup in average mode, with a span of 130 MHz (start frequency at 300 MHz and stop frequency at 430 MHz) and a resolution bandwidth of 50 Hz. The results of these measurements are reported in Figure 13. The plot shows a high number of unwanted signals in the frequency range 300-350 MHz, when the switches are powered on (blue curve), with respect to the situation when the switches are powered off (red curve). Consequently, in order to reduce the self-produced RFIs, these switches can be eliminated from the Dewar block and the GAIA board can be exploited to execute the functions of LNA protection, which were provided by these switches in the original design of the receiver.  
Figure 11: Results of the measurement campaign for surveying the signals generated by the GAIA electronic board [53]: (**a**) frequency range between 0 and 1 GHz [53]; (**b**) frequency range between 1 and 2 GHz [53].
## 4 Discussion
### Future Directions  
An abundance of literature has found that rapid maxillary expansion, both surgical and non-surgical, is associated with decreased alveolar bone dimensions and increased buccal dental tipping, necessitating a healthy supporting periodontium [18; 27; 30; 31; 32; 34; 38; 39; 42; 44]. Fortunately, the amount of bone resorption is generally well tolerated in a healthy dentition, although mild and severe complications do occur [19]. Therefore, periodontally compromised patients might benefit from reducing the physiological burden placed upon the dentition through the use of SARME and/or bone-borne appliances in place of NSRME or tooth-borne devices. [PERSON] et al. recommended that PMD be performed in periodontally compromised patients receiving SARME due to the reduction in alveolar bone caused by SARME without PMD [38]. The increased cost, invasive nature, and morbidity associated with SARME should be weighed against the potential periodontal and skeletal benefits of SARME [19]. As such, the authors highly encourage clinicians to perform a comprehensive periodontal exam prior to maxillary expansion procedures. Clear interdisciplinary communication between orthodontists and periodontitis will help prevent avoidable complications. Pre-operative soft tissue augmentation procedures (e.g., sub-epithelial connective tissue grafts, free gingival grafts) are intended to prevent the onset of hard and soft tissue deficiencies discussed in the present review. Yet, available scientific evidence remains scarce to provide solid conclusions [59].  
Ultimately, the results of the present review should be interpreted carefully as more RCTs evaluating SARME, NSRME, and tooth- as well as bone-borne appliances are necessary to control a large variety of confounding factors (e.g., age, magnitude of maxillary expansion needed, history of periodontal disease, tissue phenotype (thin/thick), KTW, and smoking status, among others). On the other hand, the qualitative analysis suggested that the onset of hard and soft tissue deficiencies is relatively higher among patients undergoing NSRME procedures when compared to SARME.
# Early Results on GNSS Receiver Antenna Calibration System Development +
## 1 Introduction  
For high-accuracy global positioning applications on the centimeter and millimeter level, global navigation satellite system (GNSS) receivers are essential sensors. To obtain the required accuracy level, all influential factors and error sources must be understood and, in an appropriate manner, accounted for. One such important influence is the phase center correction (PCC) of GNSS receiver antennas.  
Because of the antenna's design characteristics and electromagnetic properties [1], the geometric location of the GNSS signal reception, i.e., the antenna phase center (PC), changes with respect to the incoming signal's direction and frequency [2; 3; 4]. Such variations cause advances and delays in carrier phase observations and corresponding range errors. Therefore, receiver antenna calibration is needed.  
Today, _absolute filed calibration_ is the state of the art when it comes to GNSS receiver antenna calibration. Only a few calibration systems utilizing a precise robot are operational or under development worldwide [5; 6; 7; 8; 9; 10; 11; 12], and even fewer are accredited by the International GNSS Service (IGS) to provide antenna calibration results [13]. Since this topic is of high interest to the scientific antenna community, and a new calibration system is highly desirable, at the Laboratory for Measurements and Measuring Technique (LMMT) of the Faculty of Geodesy of the University of Zagreb in Croatia, a new antenna calibration system has been developed [14].  
In this article, preliminary antenna calibration results for the Global Positioning System (GPS) L1 frequency (G01) are presented and elaborated. Furthermore, the results on LMMT calibration validation with Geo++ GmbH are presented and discussed.