esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Research Design and Methods
### FAB-BIM Competencies  
The NCS classified the competencies into 3 levels, 'Knowledge', 'Skills', and 'Attitude'. However, in the case of 'Attitude' competency as a qualitative indicator, it may present different results depending on the respondents' criteria, and as such, it is difficult to evaluate it as a quantitative indicator. Therefore, in this study, the items involving knowledge or skills among competency items of 'Attitude' were reflected in the competencies of 'Knowledge' domain and 'Skills' domain. For example, 'Attitude to understand the optimal BIM program for different design phase work' was shifted to 'Major functions of BIM software' (Knowledge), while 'Attitude to collaborate and share data derived through analysis' being changed to competency groups of 'BIM-based reports and documents extraction' (Skills) and 'BIM-based data sharing' (Skills). The competencies in this study were defined as BIM-FAB competencies redefined from the BIM competencies presented by the NCS (Knowledge, Skills, and Attitudes) to match with the characteristics of the FAB through FAB's work analysis. As can be seen in Table 2, the above FAB-BIM competencies needed for carrying out the tasks of FAB construction projects were further subdivided and grouped in hierarchical fashion into the 'Specific Competency' (level 3- minor classification), 'Competency Group' (level 2- middle classification), and 'Competency Domain' (level 1- major classification). The competency of the 'Knowledge' domain was composed of 13 specific competencies. The specific competencies were grouped into 4 competency groups, which were 'BIM-related knowledge', 'Understanding FAB', 'Construction related knowledge', and 'Standards evaluation'. For this study, the competencies of 'Principles of CR (cleanroom)', 'Utility characteristics', 'Process and Instrument Diagram (P&ID)', and 'CR certification criteria' were added to reflect the characteristics of FAB. The competency of the 'Skills' domain was composed of 19 specific competencies. The specific competencies were grouped into 5 competency groups, which were 'Generate BIM data', 'BIM-based project management', 'BIM-based analysis and review', 'BIM-based reports and documents extraction', and \"BIM-based data sharing'. For this study, the competencies of 'Equipment layout review', 'UT (Utility) matrix review', 'CR airflow review', and 'Approval for construction (AFC) drawings extraction' were added to reflect the characteristics of FAB.
# Estimation of Stability Parameters for Wide Body Aircraft Using Computational Techniques
## 2 US DATCOM
### US DATCOM Results
#### 2.3.3 Lateral Aerodynamic Coefficients  
Results of lateral aerodynamic coefficients with a variation of the angle of attack and control surface deflections were obtained and plotted in Figure 7. According to the theory, the roll moment coefficient for a stable aircraft must have a positive slope. The plot from DATCOM shows a positively increasing slope, thereby verifying that results obtained from software agree with conventional aircraft behavior. The rolling moment due to changing side-slip has a negative slope and the plot satisfies the stability condition for lateral motion.  
The plot of side force with a change in roll rate shows an increase in force as the roll rate increases. This plot is in concurrence with the theory and proves that lateral and directional motions of an aircraft are coupled. The longitudinal stability aerodynamic coefficient results obtained at low-cruise-flight conditions are shown in Table A1 of Appendix A. The results obtained from US DATCOM are very close to the analytical results; however, the reason for the large absolute error in some of the parameters, i.e., Cladot, Cmatdot, and Clq, is that DATCOM is a traditional aircraft sizing technique, and it em  
Figure 6: Analysis of longitudinal aerodynamic coefficients with deflection of the control surfaces (**a**) Variation of drag coefficient with elevator deflection; the figure shows the variation of the drag coefficient at each deflection angle from the positive side to the negative side. (**b**) Variation of drag coefficient with flap deflection; the figure shows the variation of the drag coefficient due to single slotted flap deflection.  
Figure 7: Analysis of lateral aerodynamic coefficients for different angle of attack (**a**) Variation of roll moment coefficient with silicon deflection; the figure shows an increase in roll moment coefficients with positive aileron deflection and vice versa for the other side. (**b**) Variation of roll moment coefficient with angle of attack; the figure shows the negative slope of Cl\(\beta\), satisfying the roll stability requirement for the range of the angle of attack. (**c**) Variation in the side force coefficient due to roll rate; the figure shows an increase in side force with an increase in roll rate.  
from an empirical source to approximate the stability parameters. Results obtained at low values of angle of the attack indicate a close correlation. Similarly, the lateral stability aerodynamic coefficients' results obtained at low-cruise-flight conditions are shown in Table 12 of Appendix A. Results obtained for directional and lateral coefficients are also quite close to the analytical results. Rudder control derivatives could not be estimated because there is no option for giving rudder input in DATCOM. The error can be further reduced by using more accurate geometric measurements of the airplane and by referring to the available upgraded version of the software.
# Steering Mirror System with Closed-Loop Feedback for Free-Space Optical Communication Terminals
###### Abstract  
Precision beam pointing plays a critical role in free-space optical communications terminals in uplink, downlink and inter-satellite link scenarios. Among the various methods of beam steering, the use of fast steering mirrors (FSM) is widely adopted, with many commercial solutions employing diverse technologies, particularly focusing on small, high-bandwidth mirrors. This paper introduces a method using lightweight, commercial off-the-shelf components to construct a custom closed-loop steering mirror platform, suitable for mirror apertures exceeding 100 mm. The approach involves integrating optical encoders into two off-the-shelf open-loop actuators. These encoders read the signal reflected on purposefully diamond-machined knurled screw knobs, providing maximum contrast between light and dark lines. The resulting steering mirror has the potential to complement or replace FSM in applications requiring a larger stroke, at the expense of motion speed. In the presented setup, the mirror tilt resolution achieved based on the encoder closed-loop signal feedback is 45 \(\upmu\)rad, with a mean skew rate of 1.5 mrad/s. Importantly, the steering assembly is self-locking, requiring no power to maintain a steady pointing angle. Using the mirror to actively correct for a constantly moving incoming beam, a 5-fold increase in concentration of the beam spot on the center of the detector was obtained compared to a fixed position mirror, demonstrating the mirrors ability to correct for satellite platform jitter and drift.  
free-space optical communication; pointing acquisition tracking; tracking; acquisition; fast steering mirror; CubeSat; position sensing detector; low-earth orbit +
Footnote †: journal:  
Article
# CSEM Optimization Using the Correspondence Principle
## 2 Methodology
### Steepest Descent and Momentum Methods  
CSEM inversion aims to obtain a subsurface conductivity model representative of the investigated region and honors the measurements of electromagnetic fields collected by receivers on the seabed. It is an iterative process that seeks to minimize the objective function defined in Equation (23) through successive steps in the parameter space, using the direction opposite to the gradient of the objective function calculated from the model obtained in each iteration. This update form is the main feature of steepest descent methods [20], which leads to the following expression:  
\[\sigma_{k+1}=\sigma_{k}+\alpha\mathbf{d}_{k}, \tag{51}\]  
where \(\alpha\) is the step size, determined by a simple backtracking line search, and the update direction, \(\mathbf{d}_{k}\), is given by the preconditioned gradient, \(\mathbf{g}_{k}\), of \(\chi(\sigma)\) relative to the model conductivity:  
\[\mathbf{d}_{k}=-\frac{\mathbf{g}_{k}}{\|\mathbf{g}_{k}\|}. \tag{52}\]  
We use the most straightforward line search strategy, starting with a step size equal to 1.0 in Equation (51). We calculate the value of the objective function using the updated model, and if there is a decrease, we proceed to the next iteration. Otherwise, we discard the update and compute a new model with a step size that is half of the previous step. This process iterates until the objective function decreases or we reach the maximum number of iterations allowed, in which case the inversion stops. In our experiments, this maximum number is 20.  
Another inversion strategy used involves updating the model with a momentum vector, \(\mathbf{s}\), defined from the gradient of the objective function and the momentum calculated in the previous iteration as follows:  
\[\sigma_{k+1}=\sigma_{k}-\alpha\hat{\mathbf{s}}_{k}, \tag{53}\] \[\hat{\mathbf{s}}=\frac{\sqrt{1-\beta_{2}^{k}}}{1-\beta_{1}^{k}} \mathbf{s}_{k};\quad\mathbf{s}_{k}=\beta_{1}\mathbf{s}_{k-1}+(1-\beta_{1}) \mathbf{d}_{k}, \tag{54}\]  
where we adopt the parameters \(\beta_{1}=0.9\) e \(\beta_{2}=0.999\), according to the usual prescription of the Adam algorithm [21; 30], formulated initially with a second momentum (which we do not use here). Indeed, our momentum update is very similar to the formulation of the Adam algorithm, where we essentially remove the term involving the second momentum from the equation. Furthermore, although it is not common practice, we combine momentum with the line search strategy already adopted in the context of steepest descent in an attempt to obtain more accurate models.
# Advances in the Biosynthesis and Molecular Evolution of Steroidal Saponins in Plants
## 5 Distribution of Steroidal Saponins in Plants
### Dioscoreales Plants  
Dioscoreales plants are an ancient branch of monocots, among which Dioscoreaceae and Taccaceae contain steroidal saponins. Among the Dioscoreaceae plants, only _Dioscorea_ plants contain steroidal saponins. It has been reported that, among the over 600 species of _Dioscorea_, about 137 contain steroidal saponins, of which 41 species of _Dioscorea_ contain more than 1% diosogenin [95]. More than 190 steroidal saponins have been isolated and identified from _Dioscorea_ plants, including spirostandol saponins and furostandol saponins. These steroidal saponins have also been used as chemical taxonomic markers of _Dioscorea_ plants [70; 96].  
Among the nine major clades of _Dioscorea_ pants, steroidal saponins were mainly distributed in the early diverged lineage of _Dioscorea_ plants, such as _Dioscorea_ sect. _Stenophora_[20]. The common plants containing steroidal saponins in _Dioscorea_ sect. _Stenophora_ are \(D\)_. zingiberensis, \(D\). panthaica, \(D\). parriffora, \(D\). futschauensis, \(D\). septemloba, \(D\). nipponica, and \(D\). collettiti_ var. _hypoglauca_[70; 72; 97]. More than 70 steroidal saponins have been isolated from the rhizomes of _Dioscorea_ sect. _Stenophora_ plants, mainly including the following two types: spirostandol saponins and furostandol saponins, and the content of spirostandol saponins is higher than that of furostandol saponins [72]. The most common of these steroidal saponins include dioscin, gracillin, protogracillin, parvifloside, protodeltonin, trillin, methyl topogracillin, and protobioside [70; 72]. Species-specific steroidal saponins include progenin II and III and dioscoreside C/D/E in \(D\). _panthaia_[97], and spongipregnoloside A-D and spongioside A/B in \(D\). _septemloba_[98]. A few pregnane saponins have also been isolated from \(D\). _spongiosa_[5; 99] (Supplementary Table S1).  
Other clades of Dioscorea species, such as _Dioscorea_ sect. _Combilium_ and _Dioscorea_ sect. _Opsophyton_, also contain a few steroidal saponins, including \(D\). _escultenta_ and \(D\). _bulifera_[100; 101]. However, there has been little research on steroidal saponins in the _Dioscorea_ sect. _Shamiticero_, _Dioscorea_ sect. _Lasiophyton_, _Dioscorea_ sect. _Botyrosicyos_, and _Dioscorea_ sect. _Enantiopleyllum_ plants are mainly distributed in China. Among the _Dioscorea_ plants distributed outside China, \(D\). _composita_, native to Mexico, also contains a high content of steroidal saponins, which is another important steroidal drug resource plant, in addition to \(D\). _zingiberensis_[95]. It has been determined that the content of diosgenin in the tubers of \(D\). _composita_ is 3.68 \(\pm\) 0.5% (dry weight) [94]. In Taccaceae, only _Tacca chantrieri_ contains steroid saponins; about five furostandol saponins and two spirostandol saponins were identified from its rhizome [102] (Supplementary Table S1).
## 2 Materials and Methods
### P3P Problem  
We choose to follow the same outline of the existing P3P solvers, but add three extra unknown components to the intrinsic parameter matrix \(K\) as described above. As shown in Figure 1, the P3P problem is to estimate the rotation \(R\) and translation \(t\) between the world frame \(O_{w}X_{w}Y_{w}Z_{w}\) and the camera frame \(O_{c}X_{c}Y_{c}Z_{c}\), by using three 2D-3D point correspondences.  
In Figure 1, let \(O_{C}\) be the center of perspective, \(X_{i}(i=1,2,3)\) be the 3D control points and \(x_{i}(i=1,2,3)\) be their image projections. The 3D points are known in the world frame and let \(|X_{1}X_{2}|=a\), \(|X_{2}X_{3}|=b\), \(|X_{3}X_{1}|=c\). In the existing P3P solvers, the camera is fully calibrated and then \(\angle P_{w2}CP_{w3}\), \(\angle P_{w3}CP_{w1}\), \(\angle P_{w1}CP_{w2}\) can be computed as \(\alpha\), \(\beta\), \(\gamma\) with the camera intrinsic parameters (focal length, principal point) and image projections \(x_{i}\). We assume \(|O_{c}X_{1}|=d_{1}\), \(|O_{c}X_{2}|=d_{2}\), \(|O_{c}X_{3}|=d_{3}\) and from triangles \(O_{c}X_{1}X_{2}\), \(O_{c}X_{2}X_{3}\), \(O_{c}X_{3}X_{1}\), we obtain the P3P equation system:  
\[\begin{array}{l}d_{2}^{2}+d_{3}^{2}-2d_{2}d_{3}\cos\alpha=a^{2}\\ d_{3}^{2}+d_{1}^{2}-2d_{3}d_{1}\cos\beta=b^{2}\\ d_{1}^{2}+d_{2}^{2}-2d_{1}d_{2}\cos\gamma=c^{2}\end{array} \tag{5}\]  
The P3P problem is to obtain a set of solutions for \(d_{1}\), \(d_{2}\), \(d_{3}\) and this problem is known to provide up to four possible solutions that can then be disambiguated using a fourth point.
# Multigap Resistive Plate Chambers for Time of Flight Applications
## 3 Applications in Large Experiments
### STAR Experiment in RHIC
#### 3.1.2 The STAR-ToF System  
The cylindrical ToF consists of 120 trays, each of 32 MRPCs. Tsinghua University is in charge of a majority of the MRPC production. To assure the quality of MRPC modules, a rigid set of manufacturing criteria and quality assurance (QA) procedures [29] are set up. Specifications of the dimensions and materials have been controlled strictly, and the characteristics such as dark current, noise rate, efficiency and time resolution have been validated. Moreover, the avalanche ratio, the ratio of avalanche to streamers, is found to be related to the amplitude and time resolution. A high fraction of streamers will worsen the time resolution, as shown in Figure 3. Therefore, the avalanche ratio is specified to be larger than 80% to maintain the detector's performance and save the QA time. Beam tests [28] at CERN showed that the overall time resolution after time slewing correction could reach 60 ps, and an efficiency of 97% was achieved.  
The R&D and production of STAR-ToF were started in 2000 and completed in 2009. The final trays [55] ran stably in different physics runs. The overall start and stop time resolutions are reported in Table 1. The pseudo vertex position detector (pVPD) [56] records the event start time, while the ToF system provides the stop times. Earlier runs 3-5 are the initial tests of the MRPC prototypes, while run 8 and run 9 are for the final system trays. From run 5, the rising and falling times of a signal are recorded by HPTDC and the time slewing effects are corrected according to the time over threshold (ToT) values instead of the signal amplitude for earlier runs. The time resolutions of the final system trays are below 80 ps, which meets the physics requirement.  
Figure 3: The amplitude (**a**) and time resolution (**b**) versus the avalanche ratio. Reproduced with permission from [PERSON] et al., Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment; published by Elsevier B.V., 2009 [29].  
Figure 2: The structure of the STAR MRPC detector. (**a**) shows the long side view, while (**b**) shows the short side.
## 2 Materials and Methods
### Methodology
#### 2.1.3 Analysis Process
After identifying and eliminating outliers, inconsistencies, and missing data in the historical records, we aimed to develop initial prediction or classification models using Machine Learning (ML) techniques with the cleaned data. The models were then evaluated using certain metrics to select the model with the best predictive performance and to adjust the selected classification and regression models, optimizing their parameters and adjusting their complexity to improve their performance.
# Opportunities and Challenges for Error Control Schemes for Wireless Sensor Networks: A Review
## 2 Error Control Scheme (ECS)
### Forward Error Correction (FEC)
#### 2.2.2 Convolutional Codes  
Convolutional code is another large family of a linear code. However, convolutional codes differ from block codes in many ways. In convolutional code, there is no division of information bits into smaller blocks. In this code, the whole data stream is converted into a single codeword during the encoding operation. Mathematically, a convolutional code is represented by the triple \((n,k,L)\) where the \(n\) output bits from the convolutional encoder at any given time not only depends on \(k\) information bits, but also on \(L\) previous information bits (called constraint length of convolutional code). Convolutional codes can be classified into systematic and non-systematic. Figure 4 shows an example of an encoder with \(1/2\) code rate and constraints length of three. Even the encoding operation of convolutional codes is different from block codes; there is no difference while defining the code rate for these codes.  
The concept of code concatenation is introduced by [PERSON] in 1965 [25]. The code concatenation is obtained by combining an inner code and an outer code either in series or parallel. These codes are widely used in space communications. Some examples of concatenated codes are Serial Concatenated Convolutional Code (SCCC), Parallel-Concatenated Convolutional Code (PCCC) [26], turbo code [27], and RA code [22].  
In literature, there are different versions of turbo codes using different component inner and outer codes, interleavers and other parameters. In classical turbo encoder, there are two identical recursive systematic convolutional coders separated by interleaver as shown in Figure 5. These encoders are connected to each other using parallel concatenation. Details of encoding and decoding operations of turbo codes can be found at [28].  
Figure 3: Factor graph of the Low-Density Parity Check (LDPC) code.
# Artificial Intelligence-Based Discontinuous Reception for Energy Saving in 5G Networks
## 2 Related Work  
### DRX in LTE  
LTE networks use DRX mechanism to minimize the power consumption of UE. The energy expenditure of UE can be reduced by switching off radio components during the unavailability of incoming data packets [17]. LTE-DRX is configured and controlled by evolved node B (eNB). The eNB informs the UE to turn off its radio components in case of no data in the buffer. The LTE-DRX can be regulated by radio resource control (RRC) layer at eNB. RRC sends the packets' information to UE via a physical downlink control channel (PDCCH). RRC operates in two modes: \((1)\) RRC_connected mode; \((2)\) RRC_idle mode, after a UE is turned on [18]. The RRC_idle mode is only responsible for paging operations, UE neither receives nor transmits the data, but only monitors the paging signals during the paging occasion. Whereas, all the data exchange between UE and eNB takes place during RRC_connected mode. Since all transmissions take place during the RRC_connected mode and this mode is responsible for more energy consumption of UE, our work focuses on the DRX in RRC_connected mode. Figure 1 shows the LTE-DRX in RRC_connected mode that works on two types of states. These states are:  
* Active State
* Sleep State  
Based on the above two states, different DRX parameters are configured in RRC_connected mode while considering various services' delay requirements.  
Figure 1: LTE-DRX in RRC_connected mode.
# Development of Jasmine Rice Flour Properties as a Safe and Efficient Ingredient for Compact Powder
###### Abstract  
Natural flour is usually not used directly in compact powder since there are some drawbacks, such as roughness and poor skin adhesion. The purpose of this research was to investigate the extraction and modification of jasmine rice flour using polyethylene glycol (PEG)-50 shea butter. The physical properties in terms of flowability and water resistance of the modified rice flour were investigated and compared with talcum. The modified rice flour was used as the ingredient to develop the compact powder by replacing talcum, which is the main ingredient in compact powder that provides the slipperiness and spread properties, but it is quite harmful. The results of this research revealed that the physical properties of the modified powder changed in terms of flowability and water-resistance by PEG-50 shea butter. The modified rice flour provided better physical properties compared to non-modified rice powder. The modified rice powder, a safe ingredient, could replace 100% talcum in the developed compact powder. Furthermore, the developed compact powder provided Sun Protection Factor (SPF) greater than 15, or 93%, UVB protection, good coverage with a natural appearance, smoothness, diffusion, softness of the skin, and a higher satisfaction level compared with the commercial product.  
jasmine rice flour; compact powder; PEG-50 shea butter Article Development of Jasmine Rice Flour Properties as a Safe and Efficient Ingredient for Compact Powder. _Applid_  
11 November 202019  
a small amount (<5%) of fat and ash found in rice. Flour presents different chemical compositions because of differences in species growth conditions (such as soil and weather) and rice flour processing [6]. Carbohydrates from rice consist of flour, cellulose, hemicellulose, as well as sugar (sucrose) [7; 8; 9; 10]. The main components found in flour are amylose and amylopectin. Rice protein consists of glutelins (80%), albumins (5%), globulins (10%), and prolamins (5%) [11]. Jasmine rice panicle extract, having high levels of phenolics, shows cutaneous benefits as the basis for skin ageing treatments, as indicated through in vitro cytotoxicity assessments and skin testing in human subjects [12; 13].  
Thus, jasmine rice flour would be a suitable ingredient for developing a compact powder. However, natural flour has some drawbacks in terms of roughness [14], poor skin adhesion, and poor water resistance. Therefore, rice flour needs some modification before application to compact powder. Polyethylene glycol (PEG)-50 shea butter is a polyethylene glycol derivative with an average of 50 moles of ethylene oxide. It is water-soluble whole shea butter made by a patented process [15]. This process maintains the well-known attributes of shea butter. It could be easily formulated into water-based products, such as shampoos, conditioners, creams, lotions, and other products.  
The ultimate goals of this research were to develop a safe compact powder from modified rice flour using PEG-50 shea butter.