esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
[25] studied wheat plants using hyperspectral imaging (400-1000 nm) for early detection of _Fusarium_ infection, and results demonstrated that _Fusarium_ infestation could not be detected by spectral analysis immediately after infection. [PERSON] et al. [26] used hyperspectral imaging with a spectral range of 1000-2498 nm to study maize kernels inoculated with _F. verticillioides_ at the incubated process from 0 to 90 h, and results showed that principal component analysis (PCA) models without pre-processing could discriminate between the images of the control, 17 h after inoculation and 20-90 h, and infection that changes the starch structure or content was noted. [PERSON] et al. [2] studied early detection of maize kernels inoculated with different toxigenic fungi using visible-near infrared (Vis/NIR) hyperspectral imaging (400-1000 nm), and results indicated that the analytical method they presented allowed early detection of fungal contaminants on the maize, starting at 48 h from inoculation and incubation at 30 \({}^{\circ}\)C for _A. flavus_ and _A. niger_. All of the studies showed the possibility of the application of hyperspectral imaging in fungi detection on cereals. Although some scientific studies were successfully carried out to detect toxin and fungi contamination on maize at an early stage [2; 19], studies on detection of fungi contamination on maize are limited, and are applied with different wavelength bands of hyperspectral imaging technologies, such as fluorescence (ultraviolet, UV), 400-1000 nm(Vis/NIR), and 1000-2500 nm (NIR), for different fungi infection detection, such as _Fusaium_ spp. and _Aspergillus_ spp. [2,26,27]. Therefore, there are limited studies on detection of _Aspergillus parasiticus_ infection in maize kernels using NIR hyperspectral imaging. The objectives of this work were to study early detection of maize kernels infected with _Aspergillus parasiticus_ using NIR hyperspectral imaging. To that end, the specific objectives were to: (1) detect fungal contamination of maize kernels before the onset of visual symptoms; to (2) discriminate contamination and/or damage levels; and to (3) determine optimal wavelengths for subsequent instrument development.
# Fault Prediction and Reconfiguration Optimization in Smart Grids: AI-Driven Approach
## 5 Evaluation
### Deep Learning Techniques
#### 5.4.2 Model Execution and Results' Evaluation  
After identifying the optimal hyperparameters for the MLP model from the _Scikit-Learn_ library, the configuration was replicated in the ANN model defined by the _Keras_ module of _TensorFlow_. The goal was to verify that the results obtained with Grid Search were consistent and that two different ANN models with the same hyperparameter values achieved similar results.  
In Figures 18 and 19, it can be observed that unlike the previous model, the _Keras_ ANN completed all 100 iterations in this case. However, it was confirmed that the loss function (0.068) and the accuracy values (97.87%) obtained in the last iteration were very similar to those of the previous model.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline _Solver_ & \multicolumn{2}{c}{_Adam_} & \multicolumn{2}{c}{_Sgd_} \\ \hline \hline \multirow{2}{*}{_Hidden Layers_} & \multicolumn{4}{c}{_Activation Function_} \\ \cline{2-5}  & _Relu_ & _Tanh_ & _Relu_ & _Tanh_ \\ \hline (5,) & 88 & 37 & 63 & 35 \\ \hline (8,) & 96 & 43 & 35 & 36 \\ \hline (10,) & 94 & 40 & 56 & 43 \\ \hline (50,) & 157 & 168 & 143 & 70 \\ \hline (100,) & 236 & 223 & 170 & 131 \\ \hline (5, 5) & 136 & 50 & 52 & 44 \\ \hline (8, 8) & 159 & 54 & 69 & 46 \\ \hline (10, 10) & 149 & 55 & 54 & 48 \\ \hline (50, 50) & 333 & 319 & 166 & 155 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Time results (s) (_mean_fit_time_) extracted from the _cv_results_ attribute of the MLP.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline _Solver_ & \multicolumn{2}{c}{_Adam_} & \multicolumn{2}{c}{_Sgd_} \\ \hline \hline \multirow{2}{*}{_Hidden Layers_} & \multicolumn{4}{c}{_Activation Function_} \\ \cline{2-5}  & _[PERSON]_ & _[PERSON]_ & _[PERSON]_ & _[PERSON]_ \\ \hline (5,) & 90.17 & 97.61 & 97.66 & 97.54 \\ \hline (8,) & 92.03 & 89.73 & 97.65 & 97.65 \\ \hline (10,) & 87.00 & 89.90 & 97.48 & 89.76 \\ \hline (50,) & 86.89 & 89.82 & 89.53 & 97.65  
Figure 16: Evolution of the accuracy value for the ANN from _Scikit-Learn_.  
Figure 17: Evolution of the loss function value for the ANN from _Scikit-Learn_.  
Figure 18: Evolution of accuracy value for the ANN from _Keras_.
## 5 Conclusions  
In this paper, a scheme employing the IFOTE with iterative channel estimation is proposed. The FDTE has a lower complexity and slightly weaker performance in terms of signal recovery than that of the TDTE in UWACs. A channel estimation combined with the SZA-IPNLMS and SM SZA-DIPNLMS is adopted, to achieve more accurate channel estimation compared with other sparse channel estimations. The proposed IFOTE is adopted to obtain an accurate a posteriori probability of symbols iteratively with the EP. The bidirectional structure is exploited to accelerate the convergence of turbo equalization. The innovations are listed as follows: precise sparse adaptive channel estimating using the selective zero attracting penalty term; computational complexity reduction with minimal performance loss using the selective update strategy; and high-quality recovery of UWAC signals using the IFOTE and bidirectional equalization structure. The simulation results of the EXIT charts and BERs show that the proposed scheme achieves faster convergence and better performance than those of other traditional equalization schemes with acceptable complexity. The proposed IFOTE obtains 1.9 and 0.5 dB performance gains, when compared with those of the IPNLMS and \(l_{0}\)-IPNLMS at a BER of \(10^{-3}\). It also outperforms the traditional TDTE and FDTE in UWACs by 0.5 and 1 dB, and 0.5 and 0.4 dB at the same BER of \(10^{-3}\) in the environment of  
Figure 11: BER comparison with different equalizations in the environment of MACE’10.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Algorithm** & **FDE-FDTE** & **FDDF-FDTE** & **EPIC-FDTE** & **SDFE** & **LE** \\ \hline CPU times (s) & 0.0083 & 0.0114 & 0.0541 & 0.2963 & 0.2455 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Statistics on CPU running time for different equalizers.  
SPACE'08 and MACE'04, respectively. Therefore, the proposed scheme can be efficiently used in UWACs, such as in underwater sensor networks, underwater vehicles, and other similar applications.  
Conceptualization: [PERSON], [PERSON] and X.T.; methodology: [PERSON], [PERSON], [PERSON] and [PERSON]; software: [PERSON] and [PERSON]; formal analysis: [PERSON] and [PERSON]; investigation: [PERSON], [PERSON], [PERSON] and [PERSON]; resources: [PERSON] and [PERSON]; data curation: [PERSON] and [PERSON]; writing--original draft preparation: [PERSON]; writing--review and editing: [PERSON]; visualization: [PERSON] and [PERSON]; supervision: [PERSON]; project administration: [PERSON]; funding acquisition: [PERSON] and [PERSON]. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China under Grant U1809201, and by the Zhejiang Provincial Natural Science Foundation of China under Grant LDT23F01014F01.  
Not applicable.  
The authors would like to thank the National Natural Science Foundation of China (NSFC), the Zhejiang Provincial Natural Science Foundation of China (ZPNSFC), and the Hangzhou Dianzi University for their support of this work.  
The authors declare no conflict of interest.
# Anomalous Beam Transport through Gabor (Plasma) Lens Prototype
## 4 Beam Test Setup  
The prototype Gabor lens was exposed to proton beams with a kinetic energy of 1.4 MeV at the Ion Beam Facility at the University of Surrey [58] in October 2017. Schematic diagrams of the two setups used in the beam tests are shown in Figure 5. The proton beam entered the lens through a section of evacuated beam pipe. The length of the drift on the first day of data taking was approximately 380 mm (Setup 1 in Figure 5). On the second day the length of the drift was extended to approximately 680 mm to exploit the divergence of the beam to illuminate a larger area at the front face of the lens (Setup 2 in Figure 5).  
Narrow \"beamlets\" were created using an aperture plate placed at the entrance to the lens (see Figure 6). The holes in the aperture plate were 2 mm in diameter and arranged in a pattern designed to minimise the overlap of the outgoing beamlets under a focusing force that is rotationally symmetric about the beam axis.  
Figure 5: Schematics of the day 1 beam test setup, Setup 1 (**top**) and the day 2 beam test setup, Setup 2 (**bottom**). The setup includes the Gabor lens, aperture, and beam pipes.  
Figure 6: Photograph of the aperture placed in the beamline upstream of the Gabor lens. 30 holes of 2 mm width are drilled in a symmetrical pattern around one further hole on the axis. The surrounding holes are pitched at an angle of 20\({}^{\circ}\).  
A further section of evacuated beam pipe of length 670 mm was attached to the downstream flange of the prototype lens. A phosphor screen was installed on the downstream flange as indicated in Figure 5. The phosphor screen used was a P43 phosphor surface on an aluminised pyrex substrate with an effective area of diameter 44.9 mm and a thickness of 10-15 um as shown in figure 7. Photographs of the image of the beam on the phosphor screen were acquired with a DSLR camera using an exposure long compared to the beam spill.
# A Method for Generation of a Sizing System and Representative Models for a Facial Mask Design
## 2 Development of a Sizing System of a Pilot Oxygen Mask for KAF Pilots
### Modification of the Oxygen Mask Sizing System  
The proposed sizing system was adjusted through a panel of discussion with stakeholders of KAF to consider the economic and managerial efficiencies in military equipment logistics while maintaining a reasonable accommodation percentage. First, the two sizing categories Small Wide and Large Narrow were eliminated from the proposed sizing system as the existing sizing system of the MBU-20/P also does not contain Small Wide and Large Narrow sizes (Figure 1c) based on anecdotal recommendations from the expert personnel in the USAF [10]. The reasons for the exclusion of those two sizing categories from the existing sizing system could include (1) low presence rates of the two sizing categories and (2) economic efficiency for mask manufacturing and logistics after cutting the two sizing categories. For the same reasons, this study excluded Small Wide (presence rate = 2%) and Large Narrow (presence rate = 15%) from the proposed sizing system (Figure 4). Second, the sizing criteria of Small Narrow and Large Wide sizes were adjusted to effectively accommodate the user population with the remaining four sizing categories. The range of SSL of Small Narrow size was set as 85 to 90 mm (initial range: 80 to 90 mm) in order to find a better RFM for the Small Narrow size. The range of LW of Large Wide size was decided to be 45 to 55 mm (initial range: 50 to 60 mm) to accommodate more pilots. The accommodation percentage of the adjusted sizing system was decreased to 90% from 99% but still acceptable to accommodate a sufficient number of Korean pilots. Additionally, the material elasticity (as silicon rubber) of the oxygen mask was considered as it can increase the accommodability [26]. Besides, the economic efficiency of the adjusted sizing system (number of sizing categories = 4) will be comparably better than that of the sizing system having six sizes. The four-category sizing system will have better practicality in terms of managerial efficiency as the sizing category names are the same as the existing ones, but the shapes of each sizing category are dualized if new oxygen masks are used in KAF.
## 1 Introduction
MZI based demultiplexers can solve this problem by simultaneously filtering and delaying the optical channels with respect to their adjacent channels. In addition to this, some optical signal processing circuits require MZI based lattice filter architecture suchthat filter parameters can be tuned (electro-optically or thermo-optically) to generate tunable optical signals [12]. Therefore, MZI based thermally tunable wavelength demultiplexer is an important device which adds more functionalities or tunability in the low-loss Si\({}_{3}\)N\({}_{4}\) delay waveguide based components. For the applications where large optical time delays are required in addition to the wavelength filtering, the AWG based multiplexer and MZI filter based demultiplexer can be used together to build the complete PIC on chip [1]. In this paper, we present the analysis and experimental results of a 1 \(\times\) 4 channel MZI based wavelength demultiplexer designed using the 2.8 \(\upmu\)m \(\times\) 72 nm cross-section area Si\({}_{3}\)N\({}_{4}\) waveguide. The waveguide has a SiO\({}_{2}\) substrate and a plasma-enhanced chemical vapor deposition (PECVD) SiO\({}_{2}\) upper cladding, where the thickness of both layers is 15 \(\upmu\)m. The demultiplexer is fabricated using the TriPleX photonic platform [13] from LioniX BV. Performance result of the general interference based 2 \(\times\) 2 MMI couplers used to build the MZ interferometers shows \(-\)3.3 dB to \(-\)3.7 dB power division ratio over 50 nm wavelength range from 1530 nm to 1580 nm. We have measured 1 \(\times\) 10\({}^{-12}\) bit error rate (BER) for all of the four demultiplexed 40 Gb/s data rate channels after electrically time demultiplexing them at a 10 Gb/s rate.
# Comparison of Key Nutrient Content of Commercial Puppy Foods with Canine Dietary Requirements
## 3 Results
### Fatty Acids
The fatty acid profiles of DEPF_4 and DEPF_5 feeds exhibit  
Figure 4: Biplot based on the first two principal component axes for fatty acids composition of dog foods (**A**) and distribution of tested puppy foods based on the first two components obtained from principal component analysis (**B**). high similarity (0.657), despite their significantly different basal composition profiles (as indicated in Table 4, Figure 3A,B). PCA analysis indirectly supports these observations (as shown in Figure 4A,B). The DEPF_4 and DEPF_5 feeds have high levels of \(n-3\) and \(n-6\) acids and PUFAs, in contrast to the other feeds, and particularly the DEPF_2 feed, which has high \(n-3/n-6\) and MUFA quotient values. The quotient was 15.23, which is 2-3 times higher than that found in the other feeds, ranging from 3.35 to 6.34. The food also had a high SFA content. Based on a study of five puppy foods, PCA analysis showed a high positive correlation between the quotient of \(n-6\) and \(n-3\) fatty acids with MUFA content, as shown in Figure 4A. Additionally, it can be confirmed that there is no correlation between SFAs and the other parameters used in the analysis. Table 6 displays laboratory analysis results for fatty acids in dry extruded puppy diets and the corresponding FEDIAF recommendations per 100 g of dry matter. The DEPF_2 feed had the lowest amount of LA (0.55 g/100 g DM), and this value was 57.69% lower than the MRL for this fatty acid in puppies (early and late growth). The DEPF_3 feed had the highest amount of this fatty acid (3.37 g/100 g DM), which met the established MRL. Among the tested feeds, DEPF_1 had the lowest AA (0.01 g/100 g DM), which was 66.67% below the recommended MRL, whereas DEPF_2 had the highest level of AA at 0.06 g/100 g DM, which exceeded the MRL. DEPF_2's ALA level was the lowest (0.03 g/100 g DM) and did not meet the required MRL, being 62.50% below the MRL. The DEPF_4 diet had the highest ALA content (0.74 g/100 g DM) that met the MRL for this acid. The DEPF_2 diet had the lowest concentrations of EPA (0.01 g/100 g DM) and DHA (0.02 g/100 g DM). The total yield of EPA + DHA was 0.03 g/100 g DM, which is 40% lower than the MRL. The DEPF_5 diet had the highest EPA content (0.07 g/100 g DM of EPA and 0.09 g/100 g DM of DHA). When combined, the total EPA + DHA content was 0.16 g/100 g DM. This value is compliant with the MRL for the combined sum of eicosapentaenoic acid and docosahexaenoicenoic acid. According to the analysis of EPA and DHA levels in the diets, their actual levels were lower than the levels claimed on the label (Table 6). The DEPF_1 feed showed the smallest difference between the label and actual values at 40%. However, in the DEPF_3 feed, the actual levels of EPA and DHA were 96.71% lower than the label data. All analyzed samples contained elaidic acid C18:1, trans. The DEPF_2 diet exhibited the highest content of elaidic acid (0.93 g/100 g DM). In the other samples, the amount of C18:1 trans was
###### Abstract  
Perinatal bisphenol A (BPA) exposure promotes the risk of cardiovascular diseases in adulthood. Currently, there is a dire need to develop new therapeutic strategies and options to treat the adverse fetal programming consequences of this exposure. The present study explored the protective effects of perinatal resveratrol (Rsv) administration on BPA exposure-induced adverse cardiovascular changes and hepatic steatosis in adult offspring mice. Pregnant apolipoprotein E-deficient mice were exposed to BPA in drinking water (I \(\upmu\)g/mL) or to both BPA (1 \(\upmu\)g/mL) and Rsv (oral; 20 mg kg\({}^{-1}\) day\({}^{-1}\)) during the gestation and lactation periods. Tissues from the heart, liver, left kidney, and brachiocephalic artery from adult offspring (20 weeks old) were processed for staining with H and E, Masson's trichrome, and Verhoeff-van Gieson and subsequent histology analysis. In both female and male mice who received Rsv supplementation, the following changes were observed in the brachiocephalic arterial wall: (a) a reduction in the BPA exposure-induced increased thickness ratio of the tunica intima to tunica media from 1.3 \(\pm\) 1.1 \(\upmu\)m to 0.5 \(\pm\) 0.37 \(\upmu\)m (\(p\) = 0.027) and 0.72 \(\pm\) 0.58 \(\upmu\)m to 0.29 \(\pm\) 0.25 \(\upmu\)m (\(p\) = 0.038), respectively, (b) a reduction in the number of elastic lamina breaks (\(p\) < 0.05), and (c) the prevention of the BPA exposure-induced progression of atherosclerotic lesions. Further, it also reduced the BPA exposure-induced increased left ventricular thickness by 135 \(\upmu\)m and 131 \(\upmu\)m in female and male offspring, respectively. The BPA exposure-induced hepatic steatosis score was also significantly reduced with Rsv treatment in female offspring mice (\(p\) = 0.02). Renal cortical cytoplasmic vacuolation was identified in both BPA and/or Rsv-treated groups. Our findings suggest that Rsv could be a potential protective candidate against perinatal BPA exposure-induced cardiovascular changes and hepatic steatosis.  
bisphenol A; resveratrol; cardiovascular disease; heart; hepatic steatosis
# Injury Patterns and Frequency in Swimming: A Systematic Review
## 4 Discussion
### Injury Prevalence and Measurement  
Injury prevalence was reported inconsistently across the analyzed studies, employing diverse metrics such as injuries per 1000 h of exposure or the percentage of athletes injured over a 12-month period. This inconsistency aligns with findings from previous systematic reviews [17], where the lack of standardized reporting frameworks complicates direct comparisons across studies. This variability underscores the need for standardized injury surveillance methods to improve data comparability in swimming research.  
Injury rates were consistently reported to be higher during competitions than training, likely due to the increased intensity, physical demands, and cumulative overload associated with competitive events [36, 37]. These findings emphasize the need for load management strategies during competitive periods to mitigate the heightened injury risk.  
The primary tools for injury measurement across the reviewed studies were questionnaires, which, although widely used for their feasibility and standardization, may not capture the multifactorial nature of injuries or subclinical issues effectively [25, 38]. For example, while the LEAF-Q offers a targeted approach to assessing risks related to the FAT [29], it lacks sensitivity for identifying broader biomechanical or overuse injuries. Conversely, technological tools such as SIMS-Med Sport Systems provide a more dynamic approach, enabling real-time injury monitoring and the longitudinal tracking of athletes' health [23]. Despite their potential, such tools remain underutilized in swimming research.  
Future studies should focus on integrating wearable sensors, digital tracking systems, and validated questionnaires for a more accurate injury assessment. These innovations can significantly enhance the accuracy, comparability, and depth of injury data, facilitating the development of tailored preventive strategies and contributing to evidence-based interventions.
## Appendix A Derivation of the Precision Measurement Optimization Model
### Derivation of Equation (3)  
To determine the optimal number of survey lines, as shown in Figure 7, set parameters \(a\) and \(b\), which are the acute angles between the leftmost and rightmost multibeam survey lines and the seabed slope, respectively. First, determine the length \(x\). According to the tangent theorem, we have:  
\[\tan\frac{\theta}{2}=\frac{x}{D_{x}}\]  
Next, determine the length \(D_{1}\). According to the tangent theorem, we have:  
\[\tan\alpha=\frac{D_{x}-D_{1}}{x}\]  
Subsequently, determine the expression for \(d_{i}\). Since the actual measurement must meet an overlap rate of 10-20%, and when the overlap rate is minimized, the multibeam coverage area is maximized, resulting in the shortest survey line length and the most efficient measurement. Therefore, we set the overlap rate at 10%:  
\[1-\frac{d_{i}}{W_{i}}=0.1\]  
Since the beams need to cover the entire plane, i.e., the coverage area must be greater than or equal to the area of the sea region, it must satisfy:  
\[W_{1}+\sum_{i=1}^{n}d_{i}^{\prime}\geq\frac{h}{\cos\alpha}\]  
Following this, we determine the expression for the coverage width \(W_{i}\). According to the sine rule, we have:  
\[W_{i}=D_{i}\cdot\sin\frac{\theta}{2}\left(\frac{1}{\sin a}+\frac{1}{\sin b}\right)\]  
Finally, determine the expression for \(d_{i}^{\prime}\). According to the angle relationships in Figure 7, we have:  
\[d_{i}^{\prime}=\frac{d_{i}}{\sin\left[180^{\circ}-\left(\frac{180^{\circ}- \theta}{2}\right)-\alpha\right]}\cdot\sin\left(\frac{180^{\circ}-\theta}{2}\right)\]  
Thus, Equation (3) is proved, which allows us to determine the optimal number of survey lines under the given conditions of the marine area.
# Ore Rock Fragmentation Calculation Based on Multi-Modal Fusion of Point Clouds and Images
## 2 Related Works
### Analysis  
The current methods for computing rock fragmentation primarily rely on image modalities. However, accurately estimating rock fragmentation becomes challenging due to the limited availability of spatial and geometric information in rock images, which mainly provide color and texture information. To overcome this challenge, researchers have explored alternative approaches, such as using specific markers for image pixel calibration.  
However, these marker-based techniques are cumbersome and impractical in real-world applications of intelligent mining. In recent years, the increasing use of laser scanning technology has opened up new possibilities for analyzing rock fragmentation by leveraging 3D point cloud modalities. By utilizing the inherent spatial and geometric information present in rock point clouds, this innovative approach enables the direct computation of rock fragmentation. However, it is important to note that point clouds generally have lower resolution compared with images and lack fine-grained data, which can potentially impact the accuracy of edge detection and rock segmentation.