esa-sceva/satcom-chunk-collection huggingface dataset:
# A Performance Evaluation Approach for Satellite Attitude Control System in Tracking Mode
## 4 Establishment of Performance Indicator Evaluation Model
### Improved Principal Component Weight Determination Method Based on Generalized Grey Numbers
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Indicators** & **Pointing** & **Relative** & **Stability** & **Response** & **Angular** & **Energy** \\
**Accuracy** & **Accuracy** & **Time** & **Velocity** & **Consumption** \\ \hline Sum of correlation coefficients & 1.8834 & 1.8378 & 1.9274 & 1.9425 & 2.1987 & 1.5909 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Sum of correlation coefficients for evaluation indicators. In Equation (21), \(\omega_{j}^{0}\) represents the weight of the \(j\) indicator. In Equation (22), \(\max\lvert Cov(j)\rvert\) represents the maximum value of the first row of the covariance matrix. The improved method uses \(F(j,i)\) instead of the correlation coefficient \(Cov(j,i)\) used in the traditional principal component method; according to the definition of \(F(j,i)\), when the correlation coefficient \(Cov(j,i)\) is larger, the value of \(F(j,i)\) will be smaller, so the improvement in principal components to a certain extent eliminates the influence of the correlation of the indicators on the weights of the indicators. In order to ensure that the sum of the indicator weights is 1, the weights should be processed according to Equation (23):  
\[\omega_{j}^{\otimes}=\frac{\omega_{j}^{0}}{\sum\limits_{i=1}^{n}\omega_{j}^{0}} \tag{23}\]  
The traditional principal component analysis and the improved principal component method proposed in this paper were used to calculate the weights of the assessment indicators under the day-to-day pointing mode, respectively, and the results of the weight determination are accurate to four decimal places, as shown in Table 2:  
In the weighting results of the principal component analysis method, the weights of the two indicators of attitude control response time and maneuvering angular speed are 0.5072 and 0.3382, respectively, while the weights of other indicators are not more than 0.1. As shown in Table 2, the correlation coefficients between these two indicators and other indicators are the largest. Based on the analysis in the previous section, it can be seen that larger correlation coefficients will amplify the results of the calculation of the weights of these two indicators, while in the calculation results of the improved principal component method proposed in this paper, the weights of attitude control response time and maneuvering angular velocity are 0.1837 and 0.1249, respectively, and the weight values are reduced, effectively weakening the influence of the indicator correlation on the weights of the indicators. Compared with the traditional principal component analysis method, the weight determination method proposed in this paper is more reasonable.
## 1 Introduction
Sun-induced chlorophyll fluorescence (SIF) provides a more direct measurement of plant carbon fixation through photosynthesis [25] and a new perspective for studying vegetation growth and its response mechanisms to environmental stresses at both global and regional scales [26]. [PERSON] Xet al. [27] investigated the impact of extreme drought and heat waves on terrestrial ecosystems in southern China and found that the SIF effectively captured the spatiotemporal dynamics of drought and heat wave development in the early stages. Compared with NDVI and EVI, SIF is more sensitive to heat stress. Additionally, physiological signals derived from SIF, such as \(\Phi\)F, have been used to quantify the response of U.S. corn crops to environmental stresses, demonstrating higher stress sensitivity and spatial scalability [28]. Although SIF has the potential for drought monitoring and assessment, its acquisition and processing remain challenging. Therefore, combining other vegetation indices to comprehensively analyze the response of vegetation to climate change is a new approach to monitoring and describing the impact of drought on vegetation growth. This study employed the SPEI to quantify climatic droughts by calculating the deviation in the difference between precipitation and potential evapotranspiration from the average state, thus evaluating the severity of water deficiency. The multi-timescale SPEI was used to represent the cumulative water balance over recent months to reflect the lag in the response of vegetation to drought. Simultaneously, SIF and NDVI were used to quantify the physiological and structural responses of vegetation to climate change. Correlation analysis of the SPEI at different timescales was performed to explore the sensitivity of vegetation in different ecological regions and vegetation types in Xinjiang to various drought types. This has significant scientific value for understanding the mechanisms of vegetation responses to specific environmental conditions in Xinjiang and for assessing the impacts of wet-dry variations on vegetation. These findings are practically important for formulating effective vegetation protection and management measures as well as for mitigating the impacts of drought disasters caused by climate change, thereby safeguarding ecosystem stability.
###### Abstract  
Successful liver cancer resection requires a comprehensive pre- and intraoperative understanding of the spatial relationships between a patient's cancer and intrahepatic anatomy. The recent literature has highlighted that patient-specific 3D-printed liver models (3 DPLMs) reconstructed from medical imaging data may enhance the comprehension of patients' liver anatomy and thereby provide a useful preoperative planning and intraoperative guidance tool for liver cancer resection (LCR). The purpose of this systematic review was to critically examine the utility and feasibility of 3 DPLMs for LCR surgical planning and intraoperative guidance and explore whether these applications improve patient outcomes. Articles were retrieved from four electronic databases (Scopus, Embase, PubMed, and Curtin University Database) according to predetermined eligibility criteria. In total, 22 eligible articles were identified, including 11 original research articles and 11 case reports. Key concepts were synthesised using an inductive content analysis approach suitable for this heterogeneous body of literature. There is significant descriptive and case-report evidence that 3 DPLMs strengthen pre- and intraoperative comprehension of patient liver and liver tumour anatomy and can enhance pre- and intraoperative surgical decision making for LCR. The analysis of these studies presents large variances in the times and costs necessary to produce 3 DPLMs, as studies did not provide the full expenses of materials, software, and equipment. Production times were focused on different aspects of the 3D printing process and were not comparable. The review nonetheless demonstrates the potential value of 3 DPLMs as preoperative planning and intraoperative guidance tools for LCR. Future studies should detail these economic data points to ensure 3 DPLMs' viability. Further experimental research and randomised controlled trials are also necessary to examine the relationship between 3 DPLMs and patient's intra- and postoperative outcomes.  
three-dimensional printing; hepatic tumour; liver cancer resection; model; surgical planning; intraoperative guidance
# A Multi-Machine and Multi-Modal Drift Detection (M2D2) Framework for Semiconductor Manufacturing
## 2 M2D2 System Framework
### Short- and Long-Term Drift Detection  
1. Short-Term Detection:  
Industrial processes often exhibit acute, short-term anomalies--such as sudden pressure spikes or momentary disruptions in gas flow--that can rapidly degrade product yield or threaten equipment safety. To capture these events, M2D2's short-term drift detection module compares each incoming data point's reconstruction error or latent distance against an adaptive (e.g., Bayesian) threshold. If the error exceeds this threshold, the system flags a potential drift within seconds or minutes. Unlike rigid fixed-threshold methods, M2D2's dynamically updated threshold accommodates normal fluctuations in process parameters, ultimately minimizing false alarms and enhancing responsiveness.
2. Long-Term Detection:  
In addition to acute anomalies, many manufacturing processes undergo gradual performance erosion or chronic changes--for instance, due to mechanical wear or contamination accumulation--that may span days, weeks, or months. Such drifts rarely surpass short-term thresholds but can substantially impair operational efficiency and reliability. Consequently, M2D2 employs periodic batch analysis: at fixed intervals (e.g., weekly or monthly), it gathers recent data and quantifies how their distribution differs from an established baseline or historical reference using metrics like KL divergence or the Wasserstein distance. Once this distance crosses a threshold or displays a sustained upward trajectory, the system designates a long-term drift. If coupled with multi-scale attention, M2D2 can simultaneously capture both immediate irregularities and gradual, low-frequency shifts.
## 2 Materials and Methods
### Signal Enhancement  
We can easily segment PCG signals based on the cardiac cycle, because the distance between S2 of the n-th beat and S1 of the (n + 1)-th beat is clear. SCG signals, however, may be another matter, when the amplitudes of S1\({}^{\prime}\) and S2\({}^{\prime}\) are close to each other and a high HR makes the S1\({}^{\prime}\) of the next beat move closer to the S2\({}^{\prime}\) of the current one. For this reason, signal enhancement is essential.  
We used an empirical mode decomposition (EMD)-based method for signal enhancement [23]. Unfortunately, this method was not suitable for real-time application, although it resulted in good, enhanced signals with clear separation for each cardiac cycle. For this reason, we left out this method and used a 5 th-order Butterworth bandpass filter at 20-50 Hz to remove high frequency noise, possible baseline wandering, and other low frequency oscillations. Figure 3 compares raw and enhanced signals using the two methods.  
Figure 2: Measurement setup for small children and infants [20]. The accelerometer was placed on the chest of the subjects after they fell asleep. As some subjects moved in their sleep, they induced motion artefacts to the recorded signals.
## 2 Materials and Methods
### Statistical Analysis  
All six TA descriptors for CR and SR (appropriate and distorted images) were measured in each of the different imaging locations and compared in the same descriptors respectively. For CR, TA descriptors of CR images yielding the lowest difference in contrast between holes and background were compared within all CT scanners using a one-way analysis of variance (no adjustments were made for multiple comparisons). Afterwards, CR TA descriptors were also compared between different scanner models of the same manufacturers, using either a two-tailed, independent two-sample \(t\)-test (comparing two models) or a one-way analysis of variance (comparing three models; no adjustments were made for multiple comparisons). SR TA descriptors were compared between appropriate and distorted images using a two-tailed, paired \(t\)-test, and between different scanner models of the same manufacturers, using either a two-tailed, independent two-sample \(t\)-test or a one-way analysis of variance.  
Principal component analysis was used to determine the texture descriptors with the most utility for CR and SR evaluation. First, Kaiser-Meyer-Olkin and Bartlett's test of sphericity was used to evaluate the case-to-variable ratio. Thereafter, the rotated component matrix was obtained and simplified using varimax rotation [34]. A \(p\)-value \(<\) 0.05 was considered statistically significant.
## 2 Millimetre-Wave Network Applications
### Satellite  
The rising demands for device connectivity and enhanced mobile broadband have led to somewhat of a resurgence in satellite communications. With the continued deployment of high throughput satellites (HTS), and the pursuit of terabit-scale network capacities [22], the potential for satellite technology to complement, and augment, terrestrial mobile networks (by providing robust 5G service delivery) has been widely recognised [23; 24]. Indeed, the term 'Non Terrestrial Networks' (NTN) is now used to refer to 5G communications, including satellites, unmanned aerial systems (UAVs) and high altitude platforms (HAPs), with ongoing standardization seeking to seamlessly integrate these facilities with the 5G eco-system [25; 26]. In rural areas where fibre penetration may be low, mm-wave satellite links may be used to provide 5G data transport--effectively acting as a 5G RAN node in a hybrid satellite-terrestrial network [24], with the potential to provide front-haul and back-haul services. The convenient overlap between 5G NR's FR2 and the Ka band strengthens the case for mm-wave service delivery through such a hybrid networking scheme [27].  
With photonic technologies offering reduced size, weight and power consumption, and robustness to RF interference compared to conventional electronic components, it is no surprise that hybrid photonic/mm-wave systems have also been proposed for deployment in satellite communications systems [28].
## 3 Results and Discussion  
### Enzyme Hydrolysis  
Discovering functional, nutraceutical, and therapeutic agents requires systematic scientific research of the biological effects of dietary elements. One of the crucial factors for this is food protein. It has been demonstrated in the literature that the nutritional value of proteins generated through enzymatic hydrolysis can lead to improved functional and therapeutic properties [60].  
In this study, enzymatic hydrolysis was carried out to produce lupin protein hydrolysates. The percentage of cleaved peptide bonds in a protein hydrolysate is referred to as the degree of hydrolysis (DH). The results are presented in Table 2. All the results were statistically different (\(p<0.05\)) between samples as analysed by one-way ANOVA ad Tukey test. Accordingly, the DH increased with the E:S ratio and the duration of hydrolysis. The highest degree of hydrolysis was calculated for sample P9--27.97 \(\pm\) 0.37%. The solo and combined effects of E:S ratio and duration of hydrolysis were analyzed by two-way ANOVA (results in Supplementary file). Both factors and combination influenced the DH (\(p<0.05\)). [PERSON] et al. [61] also studied the degree of hydrolysis of lupin proteins by papain. In their study, only a 0.2% E:S ratio for 2 h was used and the temperature was set to 80\({}^{\circ}\)C instead of 65 \({}^{\circ}\)C that was used in this study. The authors reported a DH of 2.61 \(\pm\) 0.66%, which is much lower than the one we obtained.  
Papain, being a cysteine endopeptidase, possesses broad specificity for peptide bonds; however, it prefers an amino acid bearing a large hydrophobic side chain at the P2 position. The resulting lupin hydrolysates were subjected to SDS-PAGE analysis. The electrophoretic pattern of protein molecular weight distribution of each sample is given in Supplementary file. Presented in Table 3 are the corresponding molecular weights (in Daltons) of each identified fraction. Overall, in all the samples, the resulting polypeptide fragments possessed molecular weight below 16 kDa. Four to five fractions are identified in all the samples. We might also consider that the bands' intensity decreased as the hydrolysis progressed. Similar electrophoretic profile was reported by [PERSON] et al. [61] for papain lupin hydrolysates after 120 min of reaction. In a study by [PERSON], it was demonstrated that lupin protein fractions possess IgE-reactivity in the range 40-26 kDa [62]. In this regard, the treatment with papain most likely resulted in breaking down the allergen fractions. Papain was demonstrated to remarkably hydrolyze all soy protein proteins into small peptides and amino acids not visible in the electrophoretic pattern [63]. LPH were demonstrated to crosses the human intestinal Caco-2 monolayer, as well as to exert remarkable reduction in nitric oxide and ROS in the cell-based system [33].  
Considering our results, we may conclude that enzymatic hydrolysis with papain led to the release of low molecular weight peptides which exhibit certain biological activities described below.
# A Two-Stage Registration Strategy for Thermal-Visible Images in Substations
## 2 Proposed Methodology
### Initial Registration  
In order to minimize the impact of the difference in scale between the thermally visible image pairs on image registration, this paper adopts an improved algorithm based on FAST to perform an initial coordinate transformation based on the image pairs of the input device. The process of this method is shown in Figure 2.  
Figure 1: Data flow of the thermal–visible substation image registration.  
Figure 2: Process of the initial registration.  
Firstly, the OTSU threshold [43] is calculated for the original thermal visible image, and is converted into the corresponding binary image. Taking the visible image in Figure 1 as an example, its original size is (359 \(\times\) 269) 96,571 pixels, and the binarized image contains about 5400 pixels of edge information, but fewer than 6% of the pixels contain most of the key corner features and significant edge line features in the image. This improves the calculation speed of the subsequent image processing at the expense of information density. Then, FAST is selected to detect the key points of the generated binary image. In order to further improve the operation speed, we chose FAST-9 (where the radius from the detection center point to the ring pixel is 9) as the feature point detector. Because FAST cannot detect angle feature information and is very sensitive to edge contour feature information, The Harris corner measure was chosen as the method to filter and rank the keypoints detected by the FAST algorithm. To pursue a good scale invariance, the FAST keypoints filtered by Harris corner measurements in each layer of the image pyramid are calculated according to the scale space theory to achieve multi-scale FAST. Finally, the intensity centroid [44] proposed by [PERSON] is used to locate the diagonal direction. Usually the intensity centroid of an image block deviates from its physical center, so this deviation can be used to calculate a direction. [PERSON] defines the moments as:  
\[mpq=\sum_{x,y}x^{p}y^{q}I(x,y) \tag{1}\]  
Here, \(I(x,y)\) denotes the intensity value of the image at this point; \(p\) and \(q\) denote the order of \(x\) and \(y\), respectively.  
Therefore, the centroid can be expressed as:  
\[c=\left(\frac{m_{10}}{m_{00}},\frac{m_{01}}{m_{00}}\right) \tag{2}\]  
Taking the center O of the corner as the origin of the coordinate system, the vector \(\overset{\rightarrow}{OC}\) from the point O to the centroid C represents the direction of the angle. The angle of this direction can be expressed as:  
\[\theta=\tan^{-1}\frac{m_{01}}{m_{10}} \tag{3}\]  
After using the multi-scale FAST descriptor to detect and match the feature points of the image pair, the affine matrix is calculated and the coordinate transformation parameters are transmitted back to the system side, together with the image pair.
## 3 Discussion
Interestingly, the authors reported that the toxicity of the original Bt strains that contained the _cry1B_ gene was higher, suggesting that other virulence factors were causing the toxicity of these strains on _A. grandis_. The Cry7 group is known to be poisonous to different Coleopteran insect species [10; 14]. Here, we showed that the mortality of _A. grandis_ caused by Cry7 Ab was not high (40% as a mean in response to 100 \(\upmu\)g\({}^{-1}\)), suggesting that this protein is not active against this insect pest. Similarly, _Anomala corpulenta_ and _Pyrrhalta aenescens_ larvae were not affected after ingestion of protein Cry7 Ab3, and low susceptibility to Cry7 Ab was observed in _Acanthoseclides obtetus_[30; 31]. However, Cry7 Ab was highly toxic to _Xylotrechus arvicola_ and _Henosepilachna vigitioctomaculata_ larvae, respectively [31; 32]. On the other hand, Mpp23 Aa/Xpp37 Aa were extremely active against _A. grandis_ larvae, with an estimated LC\({}_{50}\) = 0.18 \(\upmu\)g\(\cdot\)g\({}^{-1}\) (Table 1). These two proteins were described as toxic to _A. grandis_ in a previous work [33], although this is the first study that establishes LC\({}_{50}\) values. The toxic effect of Mpp23 Aa/Xpp37 Aa was also observed on larvae of _Tribolium castaneum_[34], _Cylas_ spp. [35], and _Xylotrechus arvicola_[32], suggesting that these proteins are able to control different Coleopteran pests. The Mpp23 Aa/Xpp37 Aa proteins were first described as a binary toxin based on the fact that both genes were located in the same operon. However, recently, it was shown that these proteins were toxic for C. _puncticollis_ larvae when tested individually [36]. In our study, we have tested the toxicity against _A. grandis_ larvae by using a _B. thuringiensis_ strain that expresses both proteins; thus, we cannot determine whether both proteins are required to exert their toxic effect. Further research will be required to test whether both proteins are required for the toxic effect against _A. grandis_ larvae. Concentrations of some Cry proteins considered viable for introgression in cotton range up to about 20 \(\upmu\)g\(\cdot\)g\({}^{-1}\), since the levels of protein expression in plants differ between flower buds and leaf tissues, ranging from approximately 3.0 to 19.0 \(\upmu\)g\(\cdot\)g\({}^{-1}\) of fresh tissue [10; 13]. Thus, according to our results, the potentially possible control of _A. grandis_ by Mpp23 Aa/Xpp37 Aa toxins can be satisfactory. More experiments will be conducted to deepen the understanding of the toxicity and mode of action of this protein complex on _A. grandis_; however, the results presented here may be useful to outline several lines of research.