esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Summary and Future Prospects  
Despite the highly competitive performance of all of the above literature, this area is far from saturated with research. Challenging questions continue to emerge as researchers delve deeper into the field. This paper firstly analyses complex layouts, on the basis of which a review of layout-analysis methods is presented. Secondly, the research progress in the field of image aesthetic-quality evaluation is described. Finally, the commonly used datasets for layout analysis and image aesthetic-quality evaluation are introduced and analyzed, and we will construct a dataset suitable for this study based on the existing datasets in the future. The existing research ideas and technical solutions of the researchers are summarized and analyzed, and an outlook on the future direction of this research area is drawn up.  
(1) Building a visual-communication-design-class image dataset  
Most of the current open-source complex-layout analysis datasets are for complex layout images such as documents and newspapers, and most of the image aesthetic-quality assessment datasets are also images without text, tables, and other elements; to make the aesthetic quality assessment of complex layout images more accurate and targeted, this paper proposes the establishment of visual-communication-design image datasets, such as posters, covers, brochures and other complex layout images that contain text, graphics, images and other elements.  
(2) Modular-design network-model structure  
Nowadays, there are many neural network models for complex layout analysis, all of which can achieve good results, but they are used for documents and newspapers with a single background; layout analysis models for visual-communication-design images are rarely reported, so they can also be the future development direction of layout analysis; visual-communication-design images inevitably need to be assessed for aesthetic quality, to judge the quality of the image design and the degree of aesthetics. Aesthetic quality assessment of visual-communication-design images is inevitable in judging the quality and aesthetics of the image design, so it can also be a future direction for the study of aesthetic-quality assessment of images. The modular design of the network-model structure for the two parts of the task can greatly reduce the training time, and the scope of the model can be determined by the model itself.  
Investigation, Y.P.; methodology, Y.P. and Y.Z.; supervision, D.L.; validation, D.L. and S.C.; resources Y.Z.; writing--original draft, Y.P. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Hunan Province; Project Grant No. 2021J30218.
# Simulation-Based Reliability Design Optimization Method for Industrial Robot Structural Design
## 3 Demonstrative Example
### Reliability Design Optimization Model
This will also affect the reliability of the robotic arm. The function could be obtained by the step 2 and step 3 of the proposed method, and Equation (2) was adopted as the approximation function. The ANSYS v. 18.1 and MATLAB v. R2021b software were combined to complete this process. The data transfer from MATLAB and ANSYS was performed as follows: (1) MATLAB was used to obtain the samples of the uncertainties, and then we used the \"save\" function to save the samples data as a \"txt\" file readable by ANSYS; (2) ANSYS was activated by the \"system\" statement of MATLAB; (3) ANSYS used the APDL command \"VREAD\" to read the \"txt\" file of the samples data saved by MATLAB; (4) ANSYS invoked the APDL command established by Section 3.1 to carry out the simulation for all the samples, and the results of maximum stress and deformation were also saved as a \"txt\" file using the APDL command \"MWRITE\": (5) MATLAB read the results file by the \"load\" function, and then the coefficient of the approximation function was obtained by data fitting of MATLAB. The coefficients of the approximation function are reported in Table 3.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Coefficient**} & \multicolumn{2}{c}{**Big Arm**} & \multicolumn{2}{c}{**Small Arm**} \\ \cline{2-5}  & **Stress** & **Deformation** & **Stress** & **Deformation** \\  & \(\delta_{1}(x_{1},x_{2},x_{3})\) & \(\delta_{2}(x_{1},x_{2},x_{3})\) & \(\delta_{3}(x_{4},x_{5},x_{6})\) & \(\delta_{4}(x_{4},x_{5},x_{6})\) \\ \hline \(a_{0}\) & 16.08 & 0.09 & 76.08 & 1.04 \\ \(b_{1}\) & \(-0.79\) & \(4.2\times 10^{-3}\
# Effects of the Damping Parameters on the Opening and Closing Characteristics of Vent Valves
## 3 Results
### Different Diameters of Middle Nozzle 1  
The nozzle is also an important damping component in the vent valve system. The diameter of the nozzle has an important influence on the pressure transmission and control of the system [28]. Middle nozzle 1 is the key to the first pressure control of the vent valve. Figure 14 shows the opening and closing characteristic curves of the valve under the middle nozzle diameters of different supports. From Figure 14a, with the decrease in the middle nozzle diameter, the middle pressure rising time decreased. When T\({}_{1}\) was equal to 0.5 mm, the middle pressure of the support began to increase at 0, but the mutation point of the middle pressure of the support did not change. With the increase in the diameter of T\({}_{1}\), the time for the middle pressure of the support to reach the control pressure increased because the jet flow and pressure loss in front of the nozzle changed. It can be seen from Figure 14b that with the increase in diameter of nozzle 1, the pressure in the piston chamber increased gradually when it reached the mutation point of the control pressure. According to Figure 14c,d, as the diameter of nozzle 1 decreased, the control pressure decreased when  
Figure 13: Opening and closing characteristics of valve with different diameters of rear orifice: (**a**) The variation law of middle bearing pressure with time; (**b**) Control of the change in cavity pressure with time; (**c**) The variation law of piston displacement with time; (**d**) The variation of piston displacement with pressure in control chamber.  
the valve was opened and closed. When T\({}_{1}\) was equal to 0.5 mm, the pressure of the piston chamber was small when the valve was fully opened, which is not conducive to the opening and closing of the valve. Combined with Figure 14a,b, it can be seen that in the opening and closing process when T\({}_{1}\) was 0.5 mm, the middle pressure of the support did not reach the mutation point, so there would be a large energy loss at T\({}_{1}\). It can be seen from Figure 14d that the opening and closing process of the valve was most stable when T\({}_{1}\) was 2.8 mm, so the recommended diameter of middle nozzle 1 is 2.8 mm, and the control performance within 1.0-5.0 mm is also acceptable.
## 3 Results and Discussions
### Capital Cost  
With the cost breakdown from Table 1, the total capital cost of the project is calculated. Figure 3 depicts the waterfall chart showing the capital cost requirement for two different scenarios. The total initial investment for solar panel and its accessories is found to be USD 4.3 million including AC/DC inverter. With the battery management cost included, the capital cost of the battery system is calculated as USD 3.8 million. Considering the decrease in electrochemical performance during charging and discharging cycles of the lithium-ion battery, battery replacement is required every 10 years or after 3600 cycles [53]. Therefore, for the battery-based system, an additional cost is needed at the end of each 10-year operational period. This is shown as 'battery replacement' cost in Figure 3b. The price of lithium-ion batteries after 10 years is projected based on the available published resources [54; 55; 56], and accounting the time value of money. The capital cost of a single refrigeration plant is USD 910k including installation and commission charge. The storage cost of ice is USD 32 per kWh and the total cost of the required storage system is USD 350k [38]. For ITES, a small amount of battery is required to supply sufficient voltage and current for the refrigerator. This number at least should be equal to the number of batteries in series given by Equation (15). However, to be on the safe side, the battery system is designed to supply continuous energy demand for half an hour. Corresponding total cost of such a designed battery system is USD 100k.  
Clearly, the investment cost of BS is higher than that of ITES. Although both systems shown here share the same solar PV cost, the difference can be attributed to the battery cost. Another important point that should be noted is the cost of a refrigerator in an ITES. The refrigeration cost for this option is four times the BS. As mentioned earlier, both systems are designed to generate an equal amount of ice each day, and ITES does not have a battery bank to operate during non-sun hours. Hence, to ensure the required amount of ice generation, multiple refrigerators should be used. This analysis assumes  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**S.N.** & **Variable** & **Value** & **Unit** \\ \hline
1 & Solar PV capacity & 2.5 & MW \\
2 & Energy storage capacity & 10.6 & MWh/day \\
3 & Levelized Cost of Energy from PV & 0.06 & USD/kWh \\
4 & Energy savings from Diesel & 3.9 & GWh/year \\
5 & Diesel savings & 1180 & Kilo liter/year \\
6 & Total cost of diesel per liter & 0.81 & USD \\
7 & Diesel energy cost per MWh & 246 & USD \\
8 & Carbon emission savings & 3103 & Tonne/year \\
9 & Operating expenses savings & 1.1 & million (USD)/year \\ \hline \hline \end{tabular}
\end{table}
Table 2: Key technical findings.  
Figure 3: (a) Capital cost breakdown for ITES and (b) Capital cost breakdown for BS.  
the number of sun-peak sours to be six, hence four such refrigerators are needed which increases the capital cost of refrigerators in ITES.
## 3 Results and Discussion
### Nature of the Antimicrobial Compounds Contained in CFS
#### 3.5.1 The Synthesis of Organic Acids and Their Contribution to Antimicrobial Activity  
In a first step, the concentration of organic acids was measured by HPLC. Lactic acid and acetic acid stand out as the two most prevalent organic acids generated by LAB (S  
The maximum production of acetic acid was observed by strain _L. brevis_ CNTA 1374 amounting up to 3.78 \(\pm\) 0.07 g/L, surpassing the levels reported by some authors [72]. Notably, _B. subtilis_ CNTA 517 did not exhibit detectable levels. Lastly, _P. acidilactici_ CNTA 1059 demonstrated a high production capacity, yielding 119.13 \(\pm\) 1.17 mg/L, which was aligned with the production described by [PERSON] et al. [70] of 117.7 \(\pm\) 1.25 mg/L.  
Secondly, the pH of the CFSs was modified to elucidate whether the measured organic acids were partially responsible for the antimicrobial activity. Table 3 shows the native pHs of the tested CFS, alongside the antimicrobial activity of the CFS of the four microorganisms selected under pH 3.50 and 7.00. Acidifying or neutralizing the CFS of strain _P. acidilactici_ CNTA 1059 did not affect the native antimicrobial activity (24.53 mm). This aligned with the results of [PERSON] et al. [73] regarding the stability of the antimicrobial activity of another _P. acidilactici_ strain. Similarly, the CFS of _L. brevis_ CNTA 1374 also showed stable antimicrobial activity (compared to the original 32.20 mm of halo size) when its pH was modified, consistent with findings by [PERSON] et al. [74]. In contrast, a significant decrease in antimicrobial activity (from 22.35 mm of original halo size) was observed when acidifying or neutralizing the CFS of _L. plantarum_ CNTA 600. This agrees with the results reported by [PERSON] and [PERSON] [54] for a _L. plantarum_ strain isolated from yogurt. The CFS from _B. subtilis_ significantly decreased its native antimicrobial activity (28.52 mm) under acidic conditions, similar to what was previously observed by [PERSON] et al. [75]. From these results, it could be inferred that the antimicrobial activity of CFSs is not exclusively due to the production of organic acids, and further research is needed.
# Research on Stagger Coupling Mode of Pulse Duration and Tool Vibration in Electrochemical Machining
## 3 Experimental Procedures  
Figure 8 shows a schematic diagram of the experimental setup. The different coupling modes of pulse duration and tool vibration were carried out by the equipment, and the results were researched independently. The electrical signals created by the pulse current and tool motion were recorded using a Memory HiCorder (Model 8861-50, Hioki, Japan). During the PVECM process, the workpiece did not move, and the tool cathode moved toward the workpiece at a special feed rate and at a single vibration frequency. At the same time, electrolyte was pumped at a high velocity into the inter-electrode gap between the cathode and the workpiece to remove electrolysis products and Joule heat [13]. The cathode and the workpiece were made of stainless steel 304 and the nickel-based alloy GH4169, respectively. The ECM fixture and important components of the experimental apparatus are shown in Figure 9. The main part of fixture was made of epoxy materials, which had small rates of deformation and good size stability.  
Figure 8: Schematic diagram of the experimental setup.  
Figure 7: Schematic diagram showing tool motion and pulse duration.  
As shown in Figure 8, the initial inter-electrode gap was 0.1 mm, and the workpiece machining surface had a height difference of 1 mm. Based on previous experiments involving tool vibration [14], the machining conditions were chosen as listed in Table 2.  
In this study, the factor \(\psi\), which represents the ratio of the depth of material removed at the low surface on the workpiece to that removed at the high surface on the workpiece, was introduced to evaluate the machining localization of PVECM, and is defined as  
\[\psi=\frac{h}{H} \tag{11}\]  
where \(h\) is the depth of material removed at the low surface and \(H\) is the depth of material removed at the high surface. In ECM, different inter-electrode gaps lead to different corrosion abilities. A higher feed rate could lead to a smaller inter-electrode gap. The smaller \(h\) and the larger \(H\) express the higher concentrated corrosion ability and the better machining localization. Thus, a smaller \(\Psi\) is better. Figure 10 shows a schematic diagram of the machining layout.  
\begin{table}
\begin{tabular}{c c} \hline
**Conditions** & **Value** \\ \hline Electrolyte & NaNO\({}_{3}\) \\ Electrolyte conductivity & 16.1 S/m at 30 \({}^{\circ}\)C \\ Voltage (V) & 20 \\ Electrolyte inlet pressure (MPa) & 0.6 \\ Electrolyte outlet pressure (MPa) & 0.1 \\ Electrolyte temperature (\({}^{\circ}\)C) & 30 \(\pm\) 1 \\ Initial gap (mm) & 0.1 \\ Amount of feed (mm) & 1 \\ Vibration frequency (Hz) & 10 \\ Vibration amplitude (mm) & 0.3 \\ Duty cycle & 25\% \\ \hline \end{tabular}
\end{table}
Table 2: Machining conditions.  
Figure 10: Schematic diagram showing the dimensions involved in the calculation of \(\psi\).  
Figure 9: Photograph of the ECM fixture and important components of experimental apparatus.
# Stability Prediction of Soil Slopes Based on Digital Twinning and Deep Learning
## 4 Results
### Optimization of Non-Circular Slip Surface
#### 4.2.3 Prediction Results  
In this paper, a six-layer 2D CNN model is built. The network structure is shown in Model 4 in Table 7. The network solver adopts Adam, the initial learning rate is 0.001, and 300 (10%) verification sets are taken as the test set. The prediction performance of the model is shown in Figure 20.  
Figure 19: RMSE of CNN models with different depths.  
Figure 20: Model prediction results.  
Figure 18: Residual network structure.  
In order to verify the generalization ability of the model, this paper collects a typical landslide case from the existing literature. The landslide is located in Qingning Township, Daxian County, Sichuan Province. The slope shape is shown in the figure, and the physical parameters of the soil are listed in Table 11. The coordinate information and the physical and mechanical parameters of the soil layer are arranged as shown in Table 3 and input into the trained network model. The actual slope safety factor is 1.0197, the model prediction result is 1.0229, and the absolute error is 0.0032, which verifies the applicability of the model.
# Improving the Energy Efficiency of the Modular Buildings
## 4 Results and Discussion
### Drying Room Setup in Wincham
#### 4.3.3 Effect of Relative Humidity on Drying Time  
There is a direct correlation between relative humidity and moisture content in wet garments such that the relative humidity decreases at the same time, and the moisture content reduces, as shown in Figure 21. In fact, [19] showed in their study that relative humidity can be reduced in three possible ways: increasing operational drying temperature, removing moisture in the air, and combining these two, which was realised through these four tests. These results showed that combining a high temperature and removing moisture using a dehumidifier with a further enhancement of air circulation using an air mover gives the best results in terms of drying time, which is similar to [20]'s findings that revealed that adjusting air temperature, humidity, air velocity, and direction energy utilisation can be improved.  
These findings demonstrate the objectives of this study by analysing the impact of environmental factors (temperature, humidity, and air speed) on garment drying and concluding that adding a dehumidifier and air mover to the drying process helps reduce the drying time, which provides valuable insights for future design and optimisation.
# Uncertainty Analysis and Improvement of Propellant Gauging System Applied in Space
## 5 Conclusions  
The effect of each factor on the final measuring uncertainty of the Propellant Gauging System Method was analyzed by applying the Monte Carlo Method. From the analyzed results, the temperature and pressure in the tank have a great effect on the measuring uncertainty. Using the suggested pressure sensor and temperature sensor with an uncertainty of 0.04% FS and 0.4% FS, the final measuring uncertainty of the Propellant Gauging System Method can reach 0.4% FS. By building a ground experimental setup, the adjusted PGS method was tested, and the inspired measurement uncertainty came to 0.4% FS, which is very high compared to the commonly used method in space.  
The future work of this research should lie in the ultrahigh real gas law, which can help to calculate the exact amount of gas in each vessel. Another suggestion for further research is an applied construction for high pressure that is equal to the real working conditions in space for engine tanks.  
Conceptualization, Y.Y. and Y.H.; methodology, Y.Y., W.H. and Y.H.; software, Y.Y. and X.Z.; validation, Y.Y. and H.H.; formal analysis, Y.Y., Y.H. and H.H.; investigation, Y.Y. and W.H.; resources, W.H. and X.Z.; data curation, Y.Y.; writing--original draft preparation, Y.Y. and Y.H.; writing--review and editing, Y.Y. and W.H.; visualization, Y.Y.; supervision, Y.H.; project administration, W.H.; funding acquisition, Y.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No.** & **Injection Bottle Pressure (kPa)** & **Tank Pressure (kPa)** & **Uncertainty (\% FS)** \\ \hline
1 & 374.326 & 102.536 & \(-\)0.383 \\
2 & 377.676 & 101.296 & \(-\)0.270 \\
3 & 390.306 & 101.976 & 0.120 \\
4 & 399.426 & 98.900 & \(-\)0.360 \\
5 & 402.406 & 103.986 & 0.210 \\
6 & 487.956 & 108.896 & 0.163 \\
7 & 488.506 & 108.616 & 0.024 \\
8 & 506.286 & 109.976 & \(-\)0.199 \\
9 & 503.276 & 105.176 & \(-\)0.305 \\
10 & 519.114 & 100.386 & \(-\)0.014 \\
11 & 608.356 & 112.156 & \(-\)0.110 \\
12 & 617.566 & 116.446 & \(-\)0.220 \\
13 & 603.996 & 114.396 & 0.120 \\
14 & 611.216 & 115.656 & \(-\)0.167 \\
15 & 595.316 & 114.986 & 0.204 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Measured mass uncertainties.  
**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Advanced Biological Imaging for Intracellular Micromanipulation: Methods and Applications
## 3 Intracellular Micromanipulation with Computational Image Information
### Planar Localization  
#### 3.1.1 Segmentation  
Segmentation is a preliminary process to obtain clear planar contours of targets or detect small particles inside cells. Normally, cells or other biological targets are covered by other devices and similar objects. The localization of such targets requires specific segmentation algorithms. Thresholding is a simple approach for eliminating unnecessary information. Sampled images can be binarized into two categories by setting a constant or adaptive threshold value: a bright target and an unnecessary background. A simple process using the Otsu adaptive thresholding was proposed for detecting the position of an oocyte. The area and roundness of the segmented object were calculated as an identification factor to remove unnecessary objects [123]. In many intracellular micromanipulation tasks, microfluidic chips are utilized to immobilize floating cells. Trapped cell contours can be extracted with a Canny edge detector [124] and a Sobel edge detector [125] and then fitted with a Hough circle transform, as shown in Figure 5a. With the use of fluorescent dye, stained organelles exhibit a higher pixel density than that of the others. Figure 5b illustrates the intracellular localization of JC-1 stained mitochondria. The mitochondrion contour was extracted by setting a threshold defined as Hue, Saturation and Value (HSV) range value [126]. Although Gauss [124], and Median filters [126] or morphological operations [123] was adopted to smoothen the sampled images in the aforementioned methods, most out-of-focus blurs and imaging noises were difficult to eliminate. Direct segmentation with a threshold value or edge detectors on original sampled images is only suitable for the manipulations of large-sized objects, because it may erase useful information near real object boundaries and produce inaccurate contours and localization of targeted specimens. WFFM-sampled images should be subjected to a deconvolution process to de-blur and de-noise, the deconvoluted images can then be processed through segmentation. Other sampling methods with out-of-focus blurs rejection capability should be considered. A nucleus laser ablation system was proposed based on LSFM. The region of interaction between laser and the targeted nucleus was segmented in different shapes on the acquired high-contrast images for subsequent ablation [127], as shown in Figure 5c. Compared with WFFM and CFM which can observe the fluorescence structure after laser manipulation, LSFM can record the target quickly and persistently before and after operations.