esa-sceva/satcom-chunk-collection huggingface dataset:
# Significance of Camera Pixel Error in the Calibration Process of a Robotic Vision System
## 2 Experimental Setup and Measurement Uncertainties  
The robotic vision system illustrated in Figure 1 comprises of a six degrees of freedom (DOF) robot, i.e., KUKA Agilus KR6 R900 sixx robot, a 3 CCD Jai camera that is mounted on the flange of the robot, and an calibration object in the form of 63 squares (\(7\times 9\)) checkerboard. The specifications of Jai camera are given in Table 1. The accuracy of the robotic vision system depends on the multiple factors, examples include kinematic errors, resolution of the camera, accuracy of parameters determined during camera calibration, accuracy of image processing algorithms used to detect objects etc. [16]. The types of calibrations involved in developing a robotic vision system and possible cause of uncertainties in each step are discussed below. Further, the feasible ways to overcome the effect of such uncertainties are also reported in each sub-section.
# Radiation-Induced Structural Changes of _Miscanthus_ Biomass
## 3 Results and Discussion
### Influence of Irradiation Treatment on Structural Properties of Miscanthus Biomass  
#### 3.3.1 DP, CrI, and Molecular Weight Distribution  
The effect of irradiation treatment on molecular weight distribution, _DP_, and _CrI_ of _Miscanthus_ biomass was investigated, and the results are shown in Table 3. When the biomass was irradiated from 0 to 1200 kGy, the _DP_ values decreased from 366,225 to 11,354, indicating that irradiation treatment can destroy the biomass structure. Moreover, the values for Mw(the weight average molecular mass) and Mn (the number average molecular mass) decreased with the increase in absorbed doses. Briefly, the Mw and Mn values of the untreated samples (0 kGy) were 542,342 and 45,544 Da, respectively, whereas for the irradiated samples at 1200 kGy, the values of Mw and Mn decreased to 150,821 and 30,237 Da, respectively. In comparison with the untreated sample, the value of Mw/Mn decreased after irradiation treatment. However, the value of Mw/Mn showed no absorbed dose dependence due to  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Absorbed Dose** & **SSA** & **D [3; 2]** & **D [4; 3]** & **d (0.1)** & **d (0.5)** & **d (0.9)** \\
**(kGy)** & **(m\({}^{2}\)/g)** & **(\(\upmu\)m)** & **(\(\upmu\)m)** & **(\(\upmu\)m)** & **(\(\upmu\)m)** & **(\(\upmu\)m)** \\ \hline
0 (Untreated) & 0.252 & 23.808 & 221.005 & 18.026 & 153.465 & 547.317 \\
400 & 0.256 & 23.432 & 203.056 & 14.963 & 131.620 & 496.540 \\
600 & 0.315 & 19.053 & 169.749 & 4.397 & 107.316 & 462.257 \\
800 & 0.319 & 18.806 & 169.307 & 4.641 & 105.537 & 461.163 \\
1000 & 0.642 & 9.343 & 33.060 & 2.924 & 21.181 & 90.421 \\
1200 & 0.815 & 7.357 & 20.099 & 2.772 & 18.423 & 39.082 \\ \hline \hline \end{tabular} Note: SSA, specific surface area; D [3; 2], Sauter mean diameter; D [4; 3], the volume mean particle diameter; d (0.5), median diameter; d (0.1), 10\(\%\) diameter; d (0.9), 90\(\%\) diameter.  
\end{table}
Table 2: Effect of absorbed doses on particle size and SAA of _Miscanthus_ biomass.  
the similar decrease variance in Mw and Mn values. We found that the _Miscanthus_ macromolecular structure was degraded after irradiation treatment [23]. These structural changes in biomass are helpful for enzymatic hydrolysis [24]. Table 3 shows that the _CrI_ values of irradiated samples showed a dose-dependent decreasing tendency, which also improved the enzymatic hydrolysis efficiency. The change in _CrI_ values demonstrated that irradiation treatment may damage the crystalline structure of cellulose, which was confirmed by TGA analysis in the following experiment.
# Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin
## 4 Results and Discussion
### Evaluation of Precipitation Products' Hydrological Performance using SWAT Model
#### 4.2.1 Evaluation of Model Performance
At Nong Khai station (mid-latitude region), the fitting of the simulated streamflow of the GSMaP data-forced model has relatively lower but still reasonable performance compared to the other precipitation products, with an NSE and R\({}^{2}\) of around 0.84 and 0.94, while those same values for CPC, Gauge, CMORPH, and TRMM 3B42 are around 0.93 and 0.97, respectively. In addition, the PBIAS values in this area vary from 3.65 to \(-\)8.76 for all of the GPPs' forced simulations, showing a large variability in the performances between the different GPPs. At the Mukhdan, Pakse, and Stung Treng gauges (i.e., the eastern part), the best performance is attained when using the rain gauge observation data, with the NSE being around 0.94 and the R\({}^{2}\) being 0.98 for all three of the stations. This is simply because the highest density of rainfall is collected, which better reflects the precipitation characteristics for this sub-region (Figure 6). All of the GPPs' forced data simulations exhibit satisfactory performance, with the NSE changing from 0.78 to 0.89. The lowest NSE can be seen for GSMaP. The TRMM 3B42 forced simulation exhibits an almost negligible PBIAS (\(-\)5.62% to \(-\)2.01%), suggesting its promising potential to replace in situ observations in hydrologic applications, even though it produces a slightly lower streamflow than that of the observations. The simulation of GSMaP shows large variation of the PBIAS (from \(-\)26.64% to \(-\)5.93%), which suffers from serious underestimation, especially in the eastern part of the basin (Table 5). A similar tendency as that of GSMaP is visualized during the simulation of CPC, with the highest PBIAS at the Mukhdan and Stung Treng gauges being \(-\)24.54% and \(-\)10.44%, respectively. Overall, at the daily scale, there is a large variability in hydrological performance depending on the GPP being used. In the upstream part of the basin, CPC attains the best performance, while in the mid- and low-latitude regions, the best performance can be seen by TRMM 3B42's forced simulations.
# Approximation Algorithms for Sorting \(\lambda\)-Permutations by \(\lambda\)-Operations
## 6 Experimental Results
Another observation is that, for totally random \(\lambda\)-permutations, the average approximation factor of the inversions-based algorithm and the breakpoints-based algorithm were similar (except for Sorting Signed \(\lambda\)-Permutations by \(\lambda\)-Reversals), even with the relevant difference among their theoretical approximation factors. Regarding the results for random \(\lambda\)-permutations generated from the identity, the maximum approximation factors for sorting unsigned \(\lambda\)-permutations problems were 6.08 and 18.5 for \(\lambda\)-reversals, 2.83 and 2.64 for \(\lambda\)-transpositions, and 4.33 and 3.58 for when both \(\lambda\)-operations are allowed, considering the breakpoints-based and the inversions-based algorithm, respectively. For the sorting signed \(\lambda\)-permutations problems, the maximum approximation factors were 7.13 and 22.85 for \(\lambda\)-reversals and 5.00 and 11.56 for when both  
Figure 4: Average and maximum approximation factors of the algorithms for Sorting Unsigned \(\lambda\)-Permutations by \(\lambda\)-Operations, with random \(\lambda\)-permutations generated from \(\iota\) of size 100 as inputs. Note that a logarithmic scale is used in the y-axis of each graph. \(\lambda\)-operations are allowed, considering the breakpoints-based and the inversions-based algorithm, respectively. Furthermore, for this second type of \(\lambda\)-permutations, the maximum approximation factors of the inversions-based algorithm for the sorting signed \(\lambda\)-permutations problems and for the Sorting Unsigned \(\lambda\)-Permutations by \(\lambda\)-Reversals were considerably greater when compared with their average approximation factors. Despite that, the average and maximum factors given by the inversions-based algorithm were better for the two sorting unsigned \(\lambda\)-permutations problems which allow \(\lambda\)-transpositions. For both problems which allow only \(\lambda\)-reversals, the breakpoints-based algorithm had better average and maximum approximation factors. For Sorting Signed \(\lambda\)-Permutations by \(\lambda\)-Reversals and \(\lambda\)-Transpositions, both algorithms had similar average approximation factor, but the breakpoints-based algorithm had a better and more constant maximum approximation factor. Our experiments reveal that the average approximation factor for the breakpoint-based algorithms slight increases for the interval \(\lambda\in[30..100]\), while the average approximation for the inversion-based algorithms has a greater increase in the same interval. This occurred because there are more \(\lambda\)-reversals that decreases a breakpoint, when using bigger values of \(\lambda\), since the strips tend to get smaller compared to the value of \(\lambda\), which is a crucial point in Lemmas 8 and 9. A similar relation is not so common for inversions, since extending the segment to be inverted may lead to inversions being added.
## 4 Experiment and Results
### Experimental Setup  
The objective of this research is to develop an SER model that combines both discrete and dimensional emotion representations using a joint model architecture. The experimental setup involves several key components:  
1. Parallel Feature Extraction: Mel-Frequency Cepstral Coefficients (MFCC), Short Term Features (STF), Mel-spectrogram, and raw audio Pulse Code Modulation (PCM) values are extracted from the input signals;
2. Feature Encoders * One-dimensional Convolutional Neural Networks (1 DCNNs) and Bidirectional Long Short-Term Memory (BiLSTM) encoders for MFCC and STF features; * A CNN-based feature encoder for Mel-spectrogram; * Pre-trained models (Wav2 Vec 2.0 and HuBERT) for raw audio signals;Self-Attention Mechanism: Extracted latent features pass through self-attention layers, generating attention weights for each feature;
4. Co-Attention Mechanism: Jointly attends to multiple weights from self-attention layers, learning interdependencies between them.  
To evaluate the model, a leave-one-subject-out (LOSO) cross-validation approach was employed. Unlike traditional methods where the dataset is explicitly divided into training, validation, and test subsets, LOSO eliminates the need for such a division by iteratively leaving out data from one subject for testing while using the remaining subjects' data for training. Specifically, the model is trained on data from nine speakers and tested on the remaining speaker in each iteration. This process is repeated 10 times, ensuring that every speaker serves as the test subject exactly once.  
The key advantage of the LOSO approach lies in its ability to evaluate the model's generalizability to unseen subjects, mimicking real-world scenarios where speakers in the test set are not present in the training set. Since the data for each iteration consist of distinct subjects, there is no explicit validation set; instead, model hyperparameters and optimization strategies are typically tuned through the iterative cross-validation process. This ensures a robust evaluation of the model's performance across diverse speaker-specific variations, without requiring predefined splits into training, validation, and test sets. By using LOSO, the study prioritizes subject independence in its evaluation methodology, providing a comprehensive and unbiased measure of the model's performance. However, this also means that proportions for training, validation, and test sets cannot be explicitly defined, as the division dynamically changes with each iteration based on the left-out speaker.
# NICE: Superpixel Segmentation Using Non-Iterative Clustering with Efficiency
###### Abstract  
Superpixels intuitively over-segment an image into small compact regions with homogeneity. Owing to its outstanding performance on region description, superpixels have been widely used in various computer vision tasks as the substitution for pixels. Therefore, efficient algorithms for generating superpixels are still important for advanced visual tasks. In this work, two strategies are presented on conventional simple non-iterative clustering (SNIC) framework, aiming to improve the computational efficiency as well as segmentation performance. Firstly, inter-pixel correlation is introduced to eliminate the redundant inspection of neighboring elements. In addition, it strengthens the color identity in complicated texture regions, thus providing a desirable trade-off between runtime and accuracy. As a result, superpixel centroids are evolved more efficiently and accurately. For further accelerating the framework, a recursive batch processing strategy is proposed to eliminate unnecessary sorting operations. Therefore, a large number of neighboring elements can be assigned directly. Finally, the two strategies result in a novel synergetic non-iterative clustering with efficiency (NICE) method based on SNIC. Experimental results verify that it works 40% faster than conventional framework, while generating comparable superpixels for several quantitative metrics--sometimes even better.  
superpixel segmentation; acceleration; inter-pixel correlation; recursive processing +
Footnote †: journal: Applied Sciences
## 4 Experiments and Results
### Evaluation Metrics  
The assessment of systolic and diastolic value predictions relies on two key metrics: mean absolute error (MAE) and mean square error (MSE).  
The MAE gauges the linear disparity between desired and predicted values, as calculated by Equation (3):  
\[MAE=\frac{1}{n}\sum_{i=1}^{n}|x_{i}-y_{i}| \tag{3}\]  
In contrast, the MSE introduces a squared penalty for deviations between target and predicted values, as defined by Equation (4):  
\[MSE=\frac{1}{n}\sum_{i=1}^{n}(x_{i}-y_{i})^{2} \tag{4}\]
# The Bivariate Empirical Mode Decomposition and Its Contribution to Grinding Chatter Detection
## 5 Conclusions  
In this paper, bivariate empirical mode decomposition (BEMD) and Hilbert transform were demonstrated as reliable methods for processing simulated and experimental chatter signals. Moreover, the extraction criterion of intrinsic mode functions (IMFs) based on correlation coefficients successfully distinguished true IMFs from spurious components. The method of selecting the ideal number of projection directions was investigated. Additionally, real-time variance and instantaneous energy were recognized as effective predictors of chatter. Accordingly, the following conclusions can be made:  
* The BEMD and Hilbert transform methods were combined to decompose a simulated chatter signal derived from a grinding vibration signal generator. This was validated with experimental data collected from a CNC guideway grinder (KD4020X16). The results illustrate the good behavior of BEMD in terms of processing nonstationary and nonlinear signals, and providing good indicators of signal phase shifting and synchronization information. Meanwhile, Hilbert and marginal spectra accurately revealed the actual characteristics of signals.
* The extraction criterion of true IMFs based on correlation coefficients is a reliable technique that successfully identifies and estimates the spurious components and reserves the main frequency bands of great import for extracting the actual vibration mode and corresponding features of the time and frequency domains.  
Figure 15: **(a)** Experimental chatter signal; **(b)** Superposed and normalized real-time variance and instantaneous energy.  
* The most ideal number of projection directions was investigated by assessing the indicators of computational time and stability degree (SD) which change along with direction number. According to the results, the ideal number of projection directions is 16.
* Real-time variance and instantaneous energy were proposed as appropriate feature vectors for chatter detection and identification. These can be applied as predictors of chatter in order for chatter suppression to be applied in a timely manner.  
The work described in this paper was supported by the National Natural Science Foundation of China (Grant No. 51475432), the Zhejiang Provincial National Natural Science Foundation of China (Grant No. LZ13E050003), and the State Key Program of National Natural Science of China (Grant No. U1234207).  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON] analyzed the data; [PERSON] contributed reagents/materials/analysis tools; [PERSON] wrote the paper.  
The authors declare no conflict of interest.
## 4 Agro-Food Substrates for Anaerobic Digestion
### Livestock Manure
#### 4.1.5 Inhibitory Substances in Livestock Manure  
In the AD process, acetogenic and methanogenic bacteria are different in many traits such as physiology, nutritional needs, growth kinetics, and sensitivity to environmental conditions. A modification in the balance between these two groups of microorganisms may cause reactor instability and this problem is often caused by the presence of a large quantity of inhibitory substances. Among the residues in manure showing inhibitory effects on the AD processes, antibiotics are the more problematic and widespread as they are often used for therapeutic in and sub-therapeutic purposes in confined animals [88], although the European Union (EU) has definitely banned the use of antibiotics for growth promotion in animal feed since 2006 (Regulation EC No 1831/2003) [89], as antibiotic residues in animal manure are of considerable concern for the potential development of antibiotic resistant bacteria in the environment.  
Contrasting results were obtained on the effect of antibiotic residues on methane yield. For example, [PERSON] et al. (2000) [90] found that penicillin and tetracycline could decrease methane production, whereas other studies found that oxytetracycline (OTC) had a minor inhibitory effect on methane production during the anaerobic digestion of dairy manure [91]. Low levels of antibiotics, such as tylosin, limomycin, sulfamethazine, and carbodox did not significantly affect methane production from swine manure, whereas significant effects were observed at high antibiotic concentration [92; 93]. Diary manure and waste milk from cows treated with cefazolin for mastitis problems were conveniently used as substrates for biogas production with significantly higher methane yield as compared with dairy manure alone. [PERSON] et al. [94] found that added cefazolin (10 mg\(\cdot\)L\({}^{-1}\)) did not affect the total and methane gas yields. [PERSON] et al. [95] studied the effect of four common cattle husbandry antibiotics (ampicillin, florfenicol, sulfamethazine, and tylosin) on AD biogas production and antibiotic degradation resulting from the AD process. These authors found that the four antibiotics affected the AD process differently. Although sulfonamides had no inhibitory impact, ampicillin did alter the biogas production rate even if the total biogas production was not affected. However, the antibiotic concentrations tested in that study were higher than those normally detected in mixed feedlot manure.  
Heavy metal from mineral supplementation, such as Cu and Zn, may remain in manure and affect methane production potential. In particular, Cu at about 2-6 mg/L had a positive effect on methane yield, whereas concentrations over 8 mg/L reduced gas production [96]. According to [PERSON] et al. [51], the critical concentrations of Cu and Zn are much higher (57.9 mg/L and 53.3 mg/L, respectively) and similar to the values (48-96 mg/L) reported from other authors [97].
## 2 Material and Algorithm
### Embedded OS Support for Energy Harvesting  
Power-saving mode is used in LTE devices by controlling the devices' power in states when it is not communicating data in either connected or idle states, known as discontinuous reception (DRX) [55]. If a period of data inactivity of 6 \(s\) occurs in an LTE smartphone, then a low-power interval can occur [55]. Many applications are available that can turn off hardware functions, stop running applications, and turn off features for lower battery consumption.  
A special mode, 'Energy Harvesting Mode' needs to be created in the operating system (OS) of the smartphone, when smartphone power-ON in this mode only allows basic functions to be performed, such as calling and text messages. This allows for start-up with minimal power consumption.
## 4 Discussion
Compound **2** with kinase domain of EGFR kinase formed hydrogen bond. Among the hydrogen bonds, Asp855 and Phe856 involved in the ATP binding site and DFG motif, thus, Compound **2** can act as type I inhibitor by active against EGFR kinase. The interactions of both compounds (**1** and **2**) with EGFR kinase showed ATP competitive inhibition and thus support previous experiments [71; 72]. Compound **1** with VEGFR-2 kinase domain revealed two hydrogen bond interactions with Cys919 and Glu917, \(\pi\)-\(\pi\) T shaped interactions with many residues, as well as van der Walls interaction, therefore, it was clear from the analysis that, Compound  
**1** can interact with the DFG motif residue Phe1047 of the ATP binding site Cys9919 of the hinge region which also act as a gate keeper residue. Compound **2** similarly made two hydrogen bond interactions with the gate keeper residue, and additionally, it formed several \(\pi\)-alkyl interactions as Compound **1** with the similar residues except Lys868. The interactions of Compounds **1** and **2** with the kinase domain is consistent with the previous docking results which showed similar interaction of the synthesized compounds [73; 74]. Therefore, the docking result of Compounds **1** and **2** with the kinase domain of VEGFR showed similar fashion of interactions involving both DFG motif and hinge region (which comprise the ATP binding site) interaction could possibly make them type I ATP competitive inhibitor (DFG motif interaction implies active state of kinase) against VEGFR kinase. The interactions of Compound 1 and Flt-3 kinase domain involve hydrogen bond. Previously published co-crystal structure of FLT-3 with Quizartinib showed that, interactions with Phe830 in the DFG motif and Phe691 in the hinge region would be crucial for inhibition of the active kinase [75]. However, Compound **1** lacked these interactions. The interactions between Compound 2 and Flt-3 kinase domain lack active state kinase residues. However, it showed several hydrogen and ionic bond interactions similar to Compound **1** except Glu692. It lacked interaction with Tyr693 compared to Compound **1**. Finally, from the docking result of Compounds **1** and **2** with FLT-3 kinase domain it can be concluded that both compounds lacked active state kinase domain interactions and lacked interactions with hinge region of the ATP binding site and can be considered as type II inhibitor in case of FLT-3 kinase but not as ATP competitive inhibitor.
###### Abstract  
Based on the extended Huygens-Fresnel (eHF) principle, approximate analytical expressions for the spectral density of nonuniformly correlated (NUC) beams are derived with the help of discrete model decompositions. The beams are propagating along horizontal paths through an anisotropic turbulent medium. Based on the derived formula, the influence of the anisotropic turbulence (anisotropy factors, structure parameters) on the evolution of the average intensity, the shift of the intensity maxima and the power-in-the-bucket (PIB) are investigated in detail through numerical examples. It is found that the lateral shifting of the intensity maxima is closely related to the anisotropy factors and the strength of turbulence. Our results also reveal that, in the case of weak turbulence, the beam profile can retain the feature of local intensity sharpness, but this feature degenerates quickly if the strength of the turbulence increases. The value of _PIB_ of the NUC beams can be even higher than that of Gaussian beams by appropriately controlling the coherence parameter in the weak turbulence regime. This feature makes the NUC beams useful for free-space communication.  
n pacs: 8