esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In this study, we investigated the activities of hexamethylene-1,6-bis-(\(N\),\(N\)-dimethyl-\(N\)-dodecylammonium bromide) (C6), pentamethylene-1,5-bis-(\(N\),\(N\)-dimethyl-\(N\)-dodecylammonium bromide) (C5), and their two neutral analogues: hexamethylene-1,6-bis-(\(N\)-methyl-\(N\)-dodecylamine) (A6) and pentamethylene-1,5-bis-(\(N\)-methyl-\(N\)-dodecylamine) (A5) at concentrations of 1\(\times\) MIC, MIC, and 2 MIC (minimal inhibitory concentration) against hybrid forms of _Aspergillus brasiliensis_ ATCC 16404. Enzymatic profiles were determined using the API-ZYM system. Extracellular proteins were extracted from the mycelia and analyzed using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The ultrastructure was evaluated using a transmission electron microscope (TEM). Both groups of surfactants caused changes in the enzyme profiles. Larger changes in the number and concentration of enzymes were noted after the action of non-ionic gemini surfactants, which may have been due to the 100\(\times\) higher concentration of neutral compounds. Larger differences between the protein profiles of the control sample and the biocide samples were observed following the use of cationic compounds. On the basis of TEM analyses, we found that, with increasing concentrations of compound C6, the mycelium cells gradually degraded. After treatment at 2 MIC, only membranous structures, multiform bodies, and dense electron pellets remained. Based on these results, we concluded that cationic gemini surfactants, in comparison with their non-ionic analogues, could have a wide range of practical applications as active compounds.  
gemini surfactants; antifungal activity; _Aspergillus_; proteins profile; enzymes; ultrastructure
## 4 Discussion  
This project spanned more than one technological advancement and encompassed thorough analyses to verify and validate the efficacy of their practical implementations. All of the results show integrity in precision through intra-observer repeatability tests, which show excellent ICC and accuracy through cross-referencing established values in the literature. Importantly, the procedure using 3D-printed custom implants was compared with a conventional approach that uses bone grafts and standard off-the-shelf implants, both of which, in this study, were homogenized in terms of patient demographics and surgical procedure of the tumor resection. Given the detailed and meticulous nature of the analyses, each parameter is discussed at a high level. However, in general, it has been  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Acetabular Inclination Angle Deviation**} \\ \hline  & **3D Printed** & **Bone Graft** \\ \hline Max & 6.2 & \(-\)7.9 \\ Min & \(-\)18.1 & \(-\)38.6 \\ Median & \(-\)4.8 & \(-\)21.2 \\ Standard Deviation & 7.6 & 10.5 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Characteristic values of the acetabular inclination angle deviations. All measurements are in degrees.  
Figure 7: Acetabular inclination angles superimposed on relevant safe zones. (Note: the green zone represents the [67] safe zone, and the green + blue zones together represent the [68] safe zone).  
found that all measures of precision and accuracy were statistically comparable, except that the precision of reconstruction of the acetabular inclination angle of the 3D-printed implant group was higher. Given the fact that all 16 patients were operated on by the same experienced senior surgeon, these results are favorable for the advocacy of using 3D-printed customized implants to guarantee a consistently high standard of skeletal surgical reconstruction, especially as a preventative measure of error with less-experienced surgeons and a comforting factor for patients. While the focus of this study is on the impact that 3D-printed personalized implants have intra-operatively, the improved reconstruction can explain the reported survival rates of custom 3D-printed implants from three studies, two at approximately 3 years follow-up [22; 23] and one at 5 years follow-up [10]. The survival rates of the 3D-printed personalized implants were found to be acceptable.
# Investigating 2-D and 3-D Proximal Remote Sensing Techniques for Vineyard Yield Estimation
## 4 Discussion  
To date, most studies have employed 2-D RGB imagery for vineyard yield estimation at both bunch- and plant-level. However, only [PERSON] et al. [9] have investigated the use of 3-D RGB-D (specifically making use of a Kinect sensor) imaging for vineyard yield estimation. The research we have presented investigated 2-D and 3-D PRS techniques for vineyard yield estimation. The study was undertaken as three experiments, consisting of bunch-level and plant-level datasets, with in-situ measurements captured for the two canopy treatments (FC and LR). The following subsections discuss the results of the two PRS techniques in further detail.
# Hybrid Dual-Link Data Transmission Based on Internet of Vessels
## 3 Algorithm Design
### Spatial Crowdsourcing Task Allocation
#### 3.2.3 Cold Start Problem  
When new users participate in crowdsourcing, there are no historical data, making it difficult for the system to accurately assess the credibility of the new users, which can lead to the cold start problem. This may affect the fairness and efficiency of task allocation. To avoid situations where new, high-quality ship workers are not allocated tasks due to the lack of historical credibility data, this study not only considers the direct credibility of the ship workers but also takes into account the amount of participation. New users or users with less participation will have an initial credibility score \(N_{o}\). The total credibility \(Q_{i}\) is calculated by combining the direct credibility value \(C_{i}\) obtained from the above algorithm and the initial credibility value \(N_{o}\) according to their respective weights. As the amount of participation increases, the weight of the initial credibility \(N_{o}\) becomes smaller, while the weight of \(Q_{i}\) becomes larger. Once the participation count (\(n>5\)), the weight of the initial score \(N_{o}\) becomes 0, and the total credibility value \(Q_{i}\) is entirely determined by \(C_{i}\). Therefore, the final credibility value of ship \(i\), denoted as \(Q_{i}\), is calculated as follows:  
\[Q_{i}=(1-\alpha)C_{i}+N_{o}\alpha \tag{10}\]  
where \(C_{i}\) is the direct credibility value of ship \(i\), \(N_{o}\) is the participation count score, and here, \(\alpha\) is the weight coefficient. The formula for calculating the weight coefficient \(\alpha\) is as follows:  
\[\alpha=\left\{\begin{array}{ll}\frac{5-n}{10}&0\leq n\leq 5\\ 0&n>5\end{array}\right. \tag{11}\]
## 6 Conclusions  
Through a system model analysis, we were able to identify some limitations of the traditional model. In this study, a SISP multi-body dynamics model is established. Based on the new model, a composite controller is proposed to achieve high performance while suppressing the vibrations. The mathematical calculations and the experimental results verify the stability of the proposed controller. The experimental results also reveal that the proposed method can successfully suppress the vibration and improve the controller performance. Compared with the PI control methods, this newly developed method has a significant improvement in the tracking performance and the disturbance isolation. The RMSE of the relative angular velocity is reduced from 0.5165 \({}^{\circ}\)/s to 0.3610 \({}^{\circ}\)/s, and the isolation is reduced from 3.37% to 1.54%. The significant contribution of the proposed method is that the SISP model was established with a light base support and a modified feedback controller was designed according to the vibration characteristics. Combining the disturbance controller and the feedforward controller, high-precision control performance was achieved, and inertial stability of the LOS was realized. These performance improvements are significant in the fields of science and engineering.  
In future work, an advanced control method, such as SMC, adaptive control, or the \(H_{\infty}\) control, will be used to further enhance the control performance while suppressing the vibrations.  
Conceptualization, [PERSON]; methodology, [PERSON] and D.T.; validation, [PERSON] and L.S.; formal analysis: [PERSON] and D.T.; writing--original draft preparation, [PERSON]; writing--review and editing, [PERSON] and J.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Natural Science Foundation of China under Grant No. 51705496; in part by the Youth Innovation Promotion Association of Chinese Academy of Sciences under grant No. 2017257; in part by the Innovation Project of Changchun Institute of Optics, Fine Mechanics and Physics under grant No. Y4 CX1 SS145; and in part by the Foundation of Key Laboratory of Airborne Optical Imaging and Measurement under grant No. HCKF-201912 KZ02.
# Practical Application of Mesh Opportunistic Networks
## 5 Discussion
### Mesh OppNets in Group Communications  
According to our results, there is no specific problems or limitations with using mesh OppNets in group communications. It seems a good alternative for sending texts to current options. A benefit on this regard is the easy way to get the location of the rest of participants. This seems of special interest when users are in the same area or region and they want to know where the members of the group are located.
# Motion Deblurring for Single-Pixel Spatial Frequency Domain Imaging
## 2 Materials and Methods  
The motion degradation model for single-pixel SFDI is first introduced in this section. The motion estimation approach is then described that obtains the required target displacements. In addition, a circular sampling strategy that can maximize the sampling efficiency and a dynamic reconstruction scheme that can accelerate the frame rate of single-pixel SFDI are adopted, respectively.
## 4 Conclusions  
An approach to assess the insulator string condition level in case of flashover due to contamination at the 500 kV substations was developed. This approach produced a logarithmic regression-based model (y = 0.11424 ln(x) + 3.2598 with R\({}^{2}\) = 0.7164) for classifying the insulator string condition levels. The input data for the model was the UV emission area value extracted by applying the image processing to the UV image (frames from video). The UV emission area value was an average value involving the UV pixels of each cup-and-pin insulator in the observed string, where the UV emissions due to partial discharge and partial arc were also calculated, so the assessment result was fair. In other words, the model was able to bring a visual assessment (manually observing the UV pattern of each frame) into a quantitative assessment that made it easier for the operator. In simple terms, there were three levels of classification: level one was the condition without partial discharge and arc, level two was the condition with partial discharge, and level three was the condition with partial discharge and arc. The field test showed that most strings had category level two, while most strings with level three were of the suspension type. The use of the UV emission area was better at representing the sporadic nature of the discharge phenomenon since the facular area curve was much more volatile and the UV count curve was delayed relative to the facular area curve. With an error rate based on the MAE value = 0.182, this model was quite effective for application in the field. However, the implementation of the model must be followed by the same procedures as described in this paper, except for the insulator string condition level criteria which could be generally accepted.  
Conceptualization, T. and M.W.; methodology, F.A.D., A.M.K., T. and M.W.; software, F.A.D. and N.A.S.; validation, F.A.D., A.M.K., T., M.W. and N.A.S.; formal analysis F.A.D., A.M.K., T., M.W. and N.A.S.; investigation, F.A.D., A.M.K., T. and M.W.; resources, D.S.; data curation, F.A.D. and D.S.; writing--original draft preparation, T. and M.W.; writing--review and editing, T. and M.W.; visualization, F.A.D. and A.M.K.; supervision, T.; project administration, T.; funding acquisition, T. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
# Multi-Source Data Fusion-Based Grid-Level Load Forecasting
## 3 Results
### Relationship Between Evaluation Indicators and Forecasting Performance
#### 3.5.1 Comparative Analysis of Regional Evaluation Indicators  
Figure 17 outlines the evaluation indicators for peak and non-peak periods, revealing distinct characteristics that influence weighting decisions in our fusion methodology. During peak periods, forecast reliability scores remain consistent with non-peak periods, indicating that while challenging, peak period forecasting maintains comparable reliability within our evaluation framework. However, provincial impact scores are noticeably lower during peak periods, reflecting the more complex interaction patterns between regional grids during high-demand periods.  
The most significant differentiation appears in forecasting complexity, where peak periods substantiate substantially higher complexity scores. This increased complexity during peak periods is expected due to the greater volatility and sensitivity to external factors (e.g., temperature extremes, industrial production schedules) during high-demand periods. Despite these higher complexity scores, the final composite scores show only a moderate reduction during peak periods, demonstrating the balanced nature of our evaluation framework.  
Figure 18 extends this analysis to a comparison between two representative regions with differing forecasting characteristics. Region 1 exhibits higher forecasting complexity but lower provincial impact as opposed to Region 2. Despite comparable forecast reliability scores, Region 2 achieves a significantly higher final score (0.58 vs. 0.52), primarily due to its substantially greater provincial impact on the overall grid. This underscores how our evaluation framework appropriately balances intrinsic forecasting quality with the practical significance of each region's contribution to the integrated grid forecast.
# Buckwheat Seeds: Impact of Milling Fractions and Addition Level on Wheat Bread Dough Rheology
## 3 Results
### Fitting Models  
The investigation was conducted following the experimental design for determining the effects of the particle size and buckwheat milling fractions level added in wheat flour on falling number (FN) value and thermo-mechanical parameters. Mixolab rheological properties during the mixing stage in terms of water absorption (WA), dough stability (ST), dough development time (DT), minimum C2 torque, the difference between torques C1 and C2 (C1-2), and in the starch behaviour process as maximum C3 torque (C3), the difference between torques C3 and C2 (C3-2), minimum C4 torque (C4), the difference between torques C3 and C4, (C3-C4), maximum C5 torque (C5) and the difference between torques C5 and C4 (C5-4) [32] were assessed. The most fitting models were highly significant for almost all responses and were used for studying the influence of factors on the responses. These adequate models represented the experimental data well, showing high values (0.66-0.92) for coefficients of determination (\(R^{2}\)) (Table 3). The ANOVA results, which comprise significant regression coefficients (\(p<0.05\)), expressed in terms of coded value, quadratic determination coefficients (\(R^{2}\)), and adjusted-\(R^{2}\) (\(Adj\)-\(R^{2}\)), were calculated to assess the adequacy of quadratic models and are shown in Table 3.  
Falling Number Index Estimation as Influenced by Buckwheat Milling Fractions and the Addition Level in Wheat Flour  
The Falling Number (FN) index values as the parameter used for estimation of amyloid activity of grain enzymatic complex in the buckwheat-wheat composite flours formulated ranged from 299 to 369.5 s. The model can be adequate to predict the FN index, with a high level of significance (\(p<0.001\)), defining the amylolytic activity of the buckwheat-wheat flour through the FN index. As in data showed in Table 3, the milling fractions caused a significant negative influence (\(p<0.001\)) on FN, while the amount of buckwheat flour (BF) added was not-significant (\(p>0.05\)). The negative effect of buckwheat milling fractions addition showed that the FN index of buckwheat-wheat flour increased with decreasing particle size of BF. This consequence can be probably associated to the phenolic compounds from the lowest fractions that bind to \(\alpha\)-amylase and changing its conformation, and thus led to a rise in the FN index. A significant negative correlation was observed between FN and the interaction effect between the factors, while the quadratic
# Taylor Bird Swarm Algorithm Based on Deep Belief Network for Heart Disease Diagnosis
## 3 Proposed Taylor-BSA-DBN for Medical Data Classification  
The accessibility of a large amount of medical data led to the requirement of strong data analysis tools for extracting valuable knowledge. Researchers are adapting data mining and statistical tools for improving the analysis of data on huge datasets. The diagnosis of a disease is the foremost application in which data mining tools are offering triumphant results. Medical data tend to be rich in information, but poor in knowledge. Thus, there is a deficiency of effectual analysis tools for discovering hidden relation and trends from medical data generated from clinical records. The processing of medical data brings a manifestation if it has some powerful methods. Thus, the proposed Taylor-BSA-DBN is devised to process medical data for attaining effective heart disease diagnosis. Figure 1 portrays the schematic view of the proposed Taylor-BSA-DBN for heart disease diagnosis. The complete process of the proposed model is pre-processing feature selection, and detection. At first, the medical data is fed as an input to the pre-processing phase, wherein log transformation is applied to pre-process the data. Log transformation is applied for minimizing skew, and to normalize the data. Once the pre-processed data are obtained, then it is further subjected to the feature selection phase. In the feature selection phase, the imperative features are selected with Sparse FCM. After obtaining imperative features, the detection is performed with DBN, wherein the training of DBN is carried out using Taylor-BSA. The proposed Taylor-BSA is devised by combining the Taylor series and BSA. The output produced from the classifier is the classified medical data.  
Consider an input medical data be given as \(A\), with various attributes, and is expressed as  
\[A=\left\{A_{G,H}\right\};(1\leq G\leq B);(1\leq H\leq C) \tag{1}\]  
where \(A_{G,H}\) denotes \(H^{th}\) attribute in \(G^{th}\) data, \(B\) specifies a total number of data, and \(C\) specifies total attributes in each data. The dimension of the database is represented as \([B\times C]\).
## 6 Conclusions
A general observation is that the implementation of SARAL/AltiKa data into **operational systems** has been extremely easy both into operational oceanography centres for the SSH signal and into meteorological centres for the SWH in particular. It has also been the case for building databases of various levels of sophistication, for example for AVISO that integrates SARAL/AltiKa data as well as other altimeter data. SARAL/AltiKa is in many respects a prototype of the altimetry of the future. SARAL/AltiKa represents the beginning of a new class of altimeters operating at Ka-band frequency with a small footprint and high pulse rate. The Ka-band is envisioned for several new altimetric satellite projects (i.e. AltiCryo from CNES, CryoSat-3 and SKIM from ESA) and the chosen band for the upcoming SWOT. It even opens more than previously the doors of interdisciplinarity. Indeed, the extended capabilities that are offered by the Ka-band allow to open even more widely some new frontiers of altimetry such as coastal oceanography, cryosphere, hydrology, beyond the traditional scope of the open ocean investigations. Ka-band altimetry, with SARAL/AltiKa as the today's most emblematic declination, can be seen also as a step towards improved resolution altimetry and a preparation for the NASA-CNES SWOT mission project and the Ka-RIN instrument (Ka-band Radar INterferometer). **Acknowledgments:** The SARAL/AltiKa mission is an achievement of a very fruitful cooperation between ISRO and CNES. The contribution of EUMETSAT to data distribution is also strongly appreciated. We acknowledge the support of all the Investigators, Pls and Co-Is, of the SARAL/AltiKa Mission. Most of the studies performed by the French authors have been conducted and financed thanks to Centre National d'Etudes Spatiales (CNES), Centre National de la Recherche Scientifique (CNRS), and French Ministry of Research. The manuscript contents are solely the opinions of the authors and do not constitute a statement of policy, decision, or position on behalf of NOAA or the U. S. Government. **Author Contributions**: [PERSON] and [PERSON] coordinated the whole paper. For the ocean, [PERSON], [PERSON], [PERSON] and [PERSON] brought their contribution to Section 2.1; [PERSON], [PERSON] and [PERSON] to Section 2.2; [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] to Section 2.3; and [PERSON] and [PERSON] to Section 2.4. On inland waters, [PERSON], [PERSON], [PERSON] and [PERSON] brought their contribution to Section 3.1.1; and [PERSON] to Section 3.2. On ice, [PERSON] brought hercontribution to Section 4.1; [PERSON] to Section 4.2 ;and [PERSON] to Section 4.3. On geodesy, [PERSON] contributed to Section 5. The authors declare no conflict of interest.
## 6 Experimental Validation of the Calculation Result
### Measurement of Air Film Thickness  
Generally, to ensure the static performance of the aerostatic bearing and the motion accuracy of a spindle, a serial of stringent machining accuracy requirements (including flatness, parallelism, and perpendicularity, etc.) are proposed for each part of the spindle system (the shaft, sleeve, and thrust plates). Nevertheless, the real air film thickness may deviate from the design value due to unavoidable machining errors and assembly errors.  
Figure 9a presents the experimental setup for air film thickness measuring. By measuring the displacement of the thrust plate under the condition of the air supply valve closing and opening, the actual air film thickness can be acquired. A capacitive displacement sensor (Micro-Epsilon capaNCDT6500) with a resolution of 1 nm and a measurement range of 50 \(\upmu\)m is employed in this research to record the displacement of the thrust plate. The experimental setup is mounted on a vibration isolation worktable to avoid the impact of external vibration.  
Figure 9b shows the displacement curve of the thrust plate before and after the opening of the air supply valve. It can be seen that the thrust plate moves upward due to the support of pressurized air film. The above measuring process is implemented at eight points. These points are equally spaced along the circumferential direction of the  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Office Number** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline
**Office diameter (mm)** & 0.148 & 0.147 & 0.154 & 0.148 & 0.153 & 0.152 & 0.151 & 0.151 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Experimental result of the orifice diameter.  
Figure 8: Experimental setup for orifice diameter measuring. **(a)** The Experimental apparatus for orifice diameter test and **(b)** the tested image of an orifice.  
thrust plate, and the tested data is detailed in Table 3. It can be inferred that the measured average air film thickness is about 12.84 \(\upmu\)m, which is slightly less than the design value of 13 \(\upmu\)m. It may result from the machining error of the shaft, sleeve, and thrust plate.