esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Setup and Methods  
To evaluate the potential of Mach-Zehnder interferometer (MZI) optical modulators based on a liquid-crystal-based phase shifter on a SiN\({}_{\rm x}\) waveguide platform, half of the entire structure shown in Figure 1, consisting of a liquid-crystal-based phase shifter integrated into a SiN\({}_{\rm x}\) waveguide structure, a multi-mode interferometer (MMI) splitter, and linear tapers of the liquid crystal (LC) section to accommodate optical integration between the two sections, is holistically and systematically investigated. The interplay between each parameter is subsequently discussed. Electric fields applied across the LC-filled region are also observed to determine the contact configuration that is compatible with the CMOS drivable voltage. The LC phase shifter is based on a 4-n-pentyl-4\({}^{\prime}\)-cyanobiphenyl (5 CB) liquid crystal material due to its well-known optical and electrical nematic-phase properties during room-temperature operation [22]. Finally, to reliably evaluate the extinction ratio (ER) and overall insertion loss (IL) of the LC-based MZI optical modulator, we perform a 3D-FDTD simulation of the entire structure from the SiN\({}_{\rm x}\) input to the SiN\({}_{\rm x}\) output waveguide, including two MMIs, the linear tapering of the LC section, and the two arms of the LC-based phase shifter integrated with the SiN\({}_{\rm x}\) waveguide. For a numerical calculation with high accuracy, the finite-difference time-domain (FDTD) method (Ansys-Lumerical FDTD 2023 R1) is employed [23; 24]. The smallest grid size is \(\sim\)2 nm, and transparent boundary conditions are implemented using perfectly matched layers (PMLs) to suppress reflections from the simulation region boundaries. A 3D-FDTD simulation of the entire structure is also performed to reliably evaluate the extinction ratio (ER) and overall insertion loss (IL) of the LC-based MZI optical modulator. The ER is the ratio between the optical power of the quasi-transverse-electric (TE) fundamental mode at the output SiN\({}_{\mathrm{x}}\) waveguide in the ON and OFF statuses, 10\(\mathrm{log}_{10}(I_{OUT,ON}/I_{OUT,OFF})\). The IL is the ratio between the optical power of the quasi-TE fundamental mode at the input SiN\({}_{\mathrm{x}}\) waveguide and of the quasi-TE fundamental mode at the output SiN\({}_{\mathrm{x}}\) waveguide in the ON status, 10\(\mathrm{log}_{10}(I_{IN}/I_{OUT,ON})\).
# Genome-Wide Analysis Reveals the Secondary Metabolome in _Streptomyces kanasensis_ ZX01
## 1 Introduction  
Actinomyces are an especially abundant source of secondary metabolites, contributing more than half of microbial antibiotics. Moreover, a large number of these metabolites are derived from one genus, _Streptomyces_. Since the publication of the genome of _Streptomyces ocelicolor_, researchers were encouraged to mine actinomyces as a source of novel secondary metabolites [1]. Meanwhile, approaches based on genomic or bioinformatics for discovering natural products have been well developed [2]. Genomic information is very helpful to microbial natural products studies, because secondary metabolites of _Streptomyces_ are often biosynthesized by complex gene clusters [3]. In addition, it is the genomic information that provides an opportunity for regulating the antibiotic biosynthesis at the molecular level [4]. Studies of metabolic regulation may provide a vital way for increasing production of antibiotics.  
_Streptomyces kanasensis_ ZX01 was isolated from forest soil around Kanas Lake of China [5]. Its secondary metabolites showed significant and various bioactivities, such as antiviral activity (_Tobacco mosaic virus_, _Cucumber mosaic virus_), antifungal activity (_Cercospora sorghi_, _Esserohilum turcicum_) and antibacterial activity (_Bacillus subtilis_). Glycoprotein GP-1, one metabolite from _S. kanasensis_ ZX01, exhibited powerful antiviral activity and wide application prospects [6].  
Here we reported all predicted biosynthetic gene clusters for secondary metabolites and abundant regulatory genes from the genome sequence of _S. kanasensis_ ZX01. In addition, we evaluated the effect of _nsdA_, a globle regulator, on the production of glycoprotein GP-1 and on the biomass of _S. kanasensis_ ZX01.
## 5 Investigation of the MIMO-Antenna Diversity Performance
### Mean Effective Gain (MEG)  
The MEG, which describes the antenna effect in the link budget, is a measure of how much better a MIMO antenna performs than an isotropic antenna. This helps to measure how well the antenna performs in a real environment. It takes into account both the antenna's gain and the environmental factors that can affect the signal. For a better performance, this ratio must be less than 3 dB [36; 37]. It can be calculated using the following two expressions [42]:  
\[MEG_{1}=0.5\;\eta_{1,rad}=0.5\Big{[}1-\left|S_{11}\right|^{2}-\left|S_{12} \right|^{2}\Big{]} \tag{9}\]  
\[MEG_{2}=0.5\;\eta_{2,rad}=0.5\Big{[}1-\left|S_{21}\right|^{2}-\left|S_{22} \right|^{2}\Big{]} \tag{10}\]  
According to Figure 17, the simulated MEG remains at a constant level of 3 dB over the frequency band. This obtained result falls within the standard range expected for MIMO systems.  
A performance comparison was performed between the proposed UWB-MIMO antenna and other two-element MIMO structures, and the results are reported in Table 2. Various aspects, such as the antenna size, bandwidth, isolation, gain, radiation efficiency, and diversity performance parameters namely: ECC, DG, CCL, TARC, and MEG, were considered. The proposed antenna offers several advantages, including its compact size, innovative structure, excellent isolation, good radiation efficiency, and good diversity performance parameters, compared to the designs reported in the literature.  
Figure 16: Simulated and measured channel capacity losses of proposed antenna.
## 5 Performance Evaluation
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number of Sectors** & **omni + RR** & **SAS + RR** & **ABT-RRMAC** \\ \hline
3 & 52.96 & 42.79 & 20.55 \\
4 & 47.02 & 39.6 & 19.03 \\
6 & 19.04 & 20.69 & 3.03 \\
8 & 18.71 & 18.15 & 2.62 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Energy consumption: standard deviation vs. the number of sectors. Figure 10: Packet delivery ratio (PDR) comparison. (**a**) Average PDR vs. number of sectors. (**b**) Average PDR vs. queue size. directional high-gain beamforming are quite straightforward; in particular, by considering the best and worst cases, the energy saving amount in the case of RR-MAC is from 23 to 29 J, compared to the omnidirectional case. Nevertheless, ABT-RRMAC, thanks to dynamic sector time assignment, improves the performance of the RR-MAC, extending battery life of nodes byabout 21% (on average) compared to the latter. This effect seems to remain uniform as the mobility speed of nodes increases. Note that, when ABT-RRMAC curves related to the best and worst case are almost overlapped, indeed, the effect of queue size is mitigated compared to other considered cases.
# Credit Card Fraud Detection in Card-Not-Present Transactions: Where to Invest?
## 4 Experiment
### Dataset and Experiment Setup  
Our industrial partner's real-world dataset consisted of 197,471 transactions that took place over three months. Each row contains 377 features, of which:  
* 66 are transaction features;
* 305 are aggregated features computed from the card's previous transactions. For instance, one variable is \"the number of ATM transactions in the past 30 days\". Current models use only eight aggregated features, and we have aggressively expanded the feature set to evaluate the aggregated features' impact on the model quality. It should be noted that aggregated features are not free of cost--they incur significant resource costs: to calculate them in near real-time, one must have transaction history at their disposal for fast computation of features. Keeping that in mind, the transaction rate of credit card processing can be quite a technological challenge;
* Depending on the model position, fraud_score and rule_count features are available to models B and C; and
* Target variable: whether a transaction is a fraud or not.
* For the model training purposes, the dataset was divided into training and test datasets:
* Training dataset: 70% of transactions, roughly first two months.
* Test dataset: 30% of transactions, roughly the third month.  
We decided to divide the transactions chronologically (instead of sampling) to achieve a realistic scenario where the models need to predict future events based on historical data. The test dataset was used strictly for testing, and model scores in the testing phase were in no way used to improve the models (cross-validation on the training dataset was used for that purpose).  
This dataset was already under-sampled to include all fraudulent transactions, having a fraud rate of 5%.  
In our experiment, we varied the following properties:  
* Model position: A, B, or C.
* Fraud percentage: 5% or 50%. The latter is obtained in two ways: \(\bigcirc\) Undersampling of the majority class while preserving all fraud transactions--the resulting dataset has ~14 k transactions and is referred to as \"small\". \(\bigcirc\) Combination of undersampling and oversampling--the resulting dataset has ~120 k transactions and is referred to as \"balanced\".
* Basic (transactional) set of 66 features and the full set of features. The former is here referred to as \"trans\".  
Table 1 shows the abbreviations for the properties above-mentioned that are used to present results in the following text:  
Figure 4: Diagram of the baseline (production) system and possible inclusion positions of a newly developed model.  
For instance, label _RF.50.A.sm.trans_ means: random forest model trained on the undersampled dataset with a 50% fraud rate positioned parallel to the production system (position A) having used only transactional features.
###### Abstract  
_E. rutacarpa_ var. _officialis_ is a traditional Chinese medicinal plant known for its therapeutic effects, which encompass the promotion of digestion, the dispelling of cold, the alleviation of pain, and the exhibition of anti-inflammatory and antibacterial properties. The principal active component of this plant, limonin, is a potent triterpene compound with notable pharmacological activities. Despite its significance, the complete biosynthesis pathway of limonin in _E. rutacarpa_ var. _officialis_ remains incompletely understood, and the underlying molecular mechanisms remain unexplored. The main purpose of this study was to screen the reference genes suitable for expression analysis in _E. rutacarpa_ var. _officialis_, calculate the expression patterns of the genes in the limonin biosynthesis pathway, and identify the relevant enzyme genes related to limonin biosynthesis. The reference genes play a pivotal role in establishing reliable reference standards for normalizing the gene expression data, thereby ensuring precision and credibility in the biological research outcomes. In order to identify the optimal reference genes and gene expression patterns across the diverse tissues (e.g., roots, stems, leaves, and flower buds) and developmental stages (i.e., 17 July, 24 August, 1 September, and 24 October) of _E. rutacarpa_ var. _officialis_, LC-MS was used to analyze the limonin contents in distinct tissue samples and developmental stages, and qRT-PCR technology was employed to investigate the expression patterns of the ten reference genes and eighteen genes involved in limonin biosynthesis. Utilizing a comprehensive analysis that integrated three software tools (GeNorm ver. 3.5, NormFinder ver. 0.953 and BestKeeper ver. 1.0) and Delta Ct method alongside the RefFinder website, the best reference genes were selected. Through the research, we determined that _Act1_ and _UBQ_ served as the preferred reference genes for normalizing gene expression during various fruit developmental stages, while _Act1_ and _His3_ were optimal for different tissues. Using _Act1_ and _UBQ_ as the reference genes, and based on the different fruit developmental stages, qRT-PCR analysis was performed on the pathway genes selected from the \"full-length transcriptome + expression profile + metabolome\" data in the limonin biosynthesis pathway of _E. rutacarpa_ var. _officialis_. The findings indicated that there were consistent expression patterns of _HMGCR_, _SQE_, and _CYP450_ with fluctuations in the limonin contents, suggesting their potential involvement in the limonin biosynthesis of _E. rutacarpa_ var. _officialis_. This study lays the foundation for further research on the metabolic pathway of limonin in _E. rutacarpa_ var. _officialis_ and provides reliable reference genes for other researchers to use for conducting expression analyses.  
E. rutacarpa_ var. _officialis_; limonin; biosynthesis pathway; reference genes; expression patterns; qRT-PCR
# Research Progress on Curved Plates in China: Applications in Architecture
## 6 Conclusions  
This review investigated the application of curved plates in the three aspects of image expression, acoustic characteristics, and optical characteristics with a focus on the Chinese architectural cases. The specific research results are as follows:  
1. From the perspective of architectural image expression, a fresh classification system for curved plates has been established in two dimensions of the design concept source and their role as building elements. This systematic classification method can be used to guide the design of curved plates in buildings;
2. Based on the introduction to the principle of curved surface acoustic design, it focuses on the evolution of theater design form. Moreover, combined with the curved surface design cases of typical theaters in China, the curved surface acoustic characteristics in theaters are discussed;3. The optical characteristics of the building are explained around the natural lighting design of the curved plates applied to the main structure of the building (side daylighting, top daylighting, and top-side combined daylighting) and auxiliary elements (curved-plate reflector and light duct lighting system). Furthermore, on this basis, to develop curved plates and their applications in engineering more effectively and accurately, the following main future development directions are proposed: (1) In terms of architectural image expression, harsh climate conditions have increased in recent years. Future research will provide a better performance of curved surface building shapes on the basis of fully considering the coupling effect of structure and material. (2) In terms of architectural acoustics, research on the mechanism and numerical calculation of curved diffuser systems with different sizes and curvatures is the focus of future research. (3) In terms of architectural optics, experimental research on various and complex curved plates and conditions and exploring their optimal optical characteristics will be an important development direction. Curved plates have a wide range of applications in Chinese architecture, and their applicability is expected to be broadened and optimized. This research has carefully summarized the applications of curved plates in image expression, acoustic characteristics, and optical characteristics using methods such as the establishment of a new classification and case analysis. Moreover, the development directions described in this paper will also attract researchers engaged in curved plates research and engineering applications.  
Conceptualization, Y.S. and J.C. ([PERSON]); methodology, Y.S. and J.C. ([PERSON]); investigation, J.C. ([PERSON]) and Z.W.; resources, J.C. ([PERSON]); writing-review and editing, Z.W.; visualization, Y.S.; supervision, J.C. ([PERSON]); funding acquisition, J.C. ([PERSON]). All authors have read and agreed to the published version of the manuscript. This study was financially supported by the National Natural Science Foundation of China (Grant No. 51875102).  
Not applicable.  
The authors declare no conflict of interest.
# Research on Bandwidth Improvement of Fine Tracking Control System in Space Laser Communication
## 3 Results  
### Identification and Testing of Hysteresis Model  
Based on the test results, when the input signal frequency is lower than 5 Hz, the hysteresis curve of the PZT FSM experiences minimal changes, approximately resembling a static hysteresis system. Therefore, the parameters of the P-I model are identified as low-frequency. In this paper, 10 play operators are employed to fit hysteresis curves. The resulting fitting values for the weight coefficient \(\omega\) and the threshold coefficient \(r\) are as follows:  
\[\omega=[0.3695,0.1983,0.1232,\ldots,0.0369]^{\mathrm{T}}\]  
\[r=[0,210,420,\ldots,1890]^{\mathrm{T}}\]  
Figure 12 shows the hysteresis curve of the P-I model and the measured hysteresis curve of the PZT FSM when the input signal is 1 Hz. It can be observed that the hysteresis curve of the P-I model is particularly similar to the measured curve of the PZT FSM, thereby confirming the high accuracy of the modeling.  
Figure 11: Comparison of error suppression bandwidth.  
Figure 12: Hysteresis curves of model and measured at 1 Hz.  
Next, the sinusoidal signals with a wide frequency range are inputted into both the P-I model and the PZT FSM. The output data from these two parts are used as the inputs and outputs to identify the parameters of the dynamic linear model. The results are as follows:  
\[G_{0}(z)=\frac{1.004z+0.002338}{z^{2}+0.001714z+0.0000006143} \tag{11}\]  
Figure 13 shows the hysteresis curve of the P-I rate-dependent model and the measured hysteresis curve of PZT FSM, when the input signals are in the middle- and high-frequency ranges. It can be observed that the modeling has a high accuracy. So far, the hysteresis model of the PZT FSM has been established, and the feedforward controller will be designed using its inverse model.
## 3 Results and Analysis  
### Sensitivity Analysis of Anchored Sand Slope  
Case 1 for the sensitivity analysis condition is a sand slope with a height of 20 m and a groundwater level of 2 m away from the crown level of the slope. Meanwhile, the surface water level is 3 m higher than the bottom of the slope, and the slope inclination is 30\({}^{\circ}\) (Figure 2). In other words, the height of the slope \(H\) is 20 m; \(L_{1}\) is 17 m; \(L_{2}\) is 2 m; \(\beta\) is 30\({}^{\circ}\); and the internal friction angle \(\varphi\) is 35\({}^{\circ}\). Figure 2. Sand slope model: (**a**) sand slope section; (**b**) sand slope model with umbrella anchors.  
Table 1 lists the parameters of the umbrella anchor.  
According to Equations (7) and (8) for the pull-out bearing capacity of umbrella anchors, when the objective conditions are determined, the main factor affecting the pull-out bearing capacity is the buried depth of the umbrella anchor \(h\). Therefore, \(h\) can be regarded as the average of multiple anchors to simplify the calculation. The anchoring force \(T\) is \(xA\sigma\), and \(x\) is the total number of umbrella anchors. The arrangement of umbrella anchors is temporarily ignored. Assuming that the sliding surface angle \(\theta\) is 25\({}^{\circ}\), \(T\approx 0.1755W\), and \(x\) is adjusted according to the weight of the sliding mass.  
Equations (4), (5), (7), and (8) are the stability equations of umbrella-anchored sand slopes under water level fluctuations. The parameters involved in the formulas are determined as follows in combination with practical experience and reference values of the engineering survey. The weight of sand soil is generally 18-20 kN/m\({}^{3}\), with a reference value of 19 kN/m\({}^{3}\). The internal friction angle of sand soil is generally 20-40\({}^{\circ}\), with a reference value of 35\({}^{\circ}\). The related parameters of the umbrella anchor involved in this sensitivity analysis are the normal angle between the umbrella anchor and the normal line of slope surface, as well as the average buried depth of the umbrella anchor. The anchorage  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Symbol** & **Value** \\ \hline The area of the umbrella anchor projected along the direction of the force & \(A\) & 375 cm\({}^{2}\) \\ Static earth pressure coefficient of the soil before the anchoring section & \(K_{0}\) & 0.25 \\ [PERSON]’s passive earth pressure coefficient & \(K_{\rm p}\) & 3.7 \\ The cohesion of soil & \(c\) & 0 kPa \\ The density of soil & \(\rho\) & 1.9 g/cm\({}^{3}\) \\ Coefficient of lateral pressure & \(\xi\) & 0.22 \\ \hline \hline \end{tabular} \(\xi\), is equivalent to [PERSON]’s active earth pressure coefficient Ka, \(\xi\), = (0.5–0.95) \(K_{\rm a}\)  
\end{table}
Table 1: Parameters of the umbrella anchor.  
Figure 2: Sand slope model: (**a**) sand slope section; (**b**) sand slope model with umbrella anchors.  
angle \(\alpha\) is generally 15-35\({}^{\circ}\), with a reference value of 25\({}^{\circ}\). The average buried depth \(h\) is 4 m. The factor of safety is 1.05.
# Exploring Image Decolorization: Methods, Implementations, and Performance Assessment
## 4 Evaluation Methods
### Grr  
GRR (gradient recall ratio) is a measure of recent origin, which evaluates the image quality based on the details in the image. More specifically, the measure uses gradients along the vertical and horizontal axes. The gradient refers to the frequency of changes in the intensity of a pixel or a group of pixels, and is widely used in the field of computer vision, feature extraction, edge detection, and image enhancement. The concrete value of this measure is calculated according to Expression (16), where \(Y_{x}[x,y]\) denotes the gradient of the gray image along the \(x\)-axis, and \(Y_{y}[x,y]\) denotes the gradient of the gray image along the \(y\)-axis. Analogously, \(I_{x}^{c}[x,y]\) and \(I_{y}^{c}[x,y]\) represent gradients along a single axis for each of the three channels in the original image (for red, green, and blue) [9].  
\[GRR=\frac{\sum_{x,y}\sqrt{Y_{x}[x,y]^{2}+Y_{y}[x,y]^{2}}}{\sum_{c}\sum_{x,y} \sqrt{I_{x}^{c}[x,y]^{2}+I_{y}^{c}[x,y]^{2}}} \tag{16}\]  
This method determines how much detail is transferred during image decolorization. The results are within the interval \([0,1]\), and a higher value indicates a greater amount of transferred detail, which is ultimately interpreted as a better image quality. As with the previous two measures, this conclusion is not necessarily valid either, which can lead to difficulties in determining the reliability of the measure. Another problem with this measure is that in practice, most results fall within a very small interval, so it is difficult to determine which gray image is really better.