esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Microbiological Analyses for Shelf-Life Determination  
Microbiological analyses along with organoleptic control of the vegetable spread took place for determination of its microbiological quality and the verification of the product's expected shelf-life. While sensory evaluation described in Section 2.4 focuses on consumer perception of attributes, like taste and odor, the organoleptic control described herein primarily aims to assess shelf-life stability of the product. Analyses for the enumeration of total viable count (TVC), aerobic and anaerobic bacterial spores, _Escherichiacoli_, coagulase-positive staphylococci, sulfite-reducing bacteria, _Clostridium perfrignens_, _Bacillus cereus_, yeasts and molds count (YMC), as well as for the detection of _Salmonella_ spp. and _Listeria monocytogenes_ and the organoleptic evaluation of the product's five sensory attributes (i.e., taste, odor, color, consistency, packaging) by a panel of 5 analysts, were performed on days 1, 5, 25, 45, 90, 120, 150, and 180 at Eurofins Athens Analysis Laboratories. Microbiological analyses were performed according to standard methods published by the International Organization for Standardization (ISO) and the American Public Health Association (APHA) in an ISO 17025-accredited microbiology laboratory [24], depending on the target microorganism for enumeration or detection in food, whereas culture media and incubation conditions were all supplied by Merck (Darmstadt, Germany) and were the same as described by [PERSON] et al. [25; 26]. Additionally, dextrose tryptone agar was utilized for the enumeration of aerobic and anaerobic bacterial spores after incubation at 35 \({}^{\circ}\)C for 48 h, tryptrose sulfite cycloserine agar for the enumeration of _C. perfrignens_ following incubation at 37 \({}^{\circ}\)C for 24 h, and mannitol egg yolk polymycin agar was used for the enumeration of _B. cereus_ after incubating at 30 \({}^{\circ}\)C for 24 h. For the enumeration methods, three serial decimal dilutions were plated onto a Petri dish with the appropriate culture medium. Microbiological counts were calculated from the weighted mean of two plates from two countable dilutions, containing 30-300 or 15-150 colonies for general purpose and selective media, respectively.
# Design of a Rotary Transformer for Installations on Large Shafts
## 4 Design of the Transformer
### Realization of the Core and Further Weight Reduction  
The attention was moved to more practical aspects related to the realization of the ferrite core after the two optimization procedures. Indeed, due to the high fragility of the ferrite, it is not simple to shape the core as desired. The winding slot should be dug on a toroid with a high risk of cracking the material. In addition, vibrations during operation may damage the bulk ferrite cores. Therefore, the possibility to realize them by placing small pieces of ferrites was investigated, as proposed in [15]. In particular, C-shaped ferrites were identified as the most interesting products available on the market. In this way, a further weight reduction was achieved due to the lack of material between adjacent ferrites. It must be noted that this operation is a trade off between the decrease in the coupling between primary and secondary (and therefore a drop in the transferred power) and weight reduction. Therefore, a filling factor around 80% was identified for both the volumes of the cores as the most suitable arrangement. Considering the outcome of the genetic algorithm reported previously as the reference design, this solution led to the placement of 75 ferrites on the innermost core and 85 on the outermost. Each piece of core had a width of 6 mm and showed the same cross section that can be obtained with the data reported in Table 1. The geometry of the winding was not affected by this operation. Figure 9 shows top and perspective views of the new cores. Despite the removal of ferromagnetic material, the coupling between the two sides of the transformer was still high, and this arrangement allowed us to transfer even more power \(P_{2}\) on the secondary than in the solid core solution, with a weight reduction of 17.6%. The explanation of this result is that the power transfer strongly depends on the particular arrangement of the values \(L_{1}\), \(L_{2}\) and \(M\), keeping the resistive parameters constant. Indeed:  
\[\begin{split} P_{1}=R_{\rm in}\,l_{1}^{2}=R_{\rm in}\bigg{(} \frac{V}{Z_{\rm in}}\bigg{)}^{2}=\Bigg{(}R_{1}+\frac{\omega^{2}M^{2}(R_{2}+R_{ \rm L})}{\left(R_{2}+R_{\rm L}\right)^{2}+\omega^{2}L_{2}^{2}}\Bigg{)}\cdot\\ \cdot\frac{V^{2}}{\Bigg{(}R_{1}+\frac{\omega^{2}M^{2}(R_{2}+R_{ \rm L})}{\left(R_{2}+R_{\rm L}\right)^{2}+\omega^{2}L_{2}^{2}}\Bigg{)}^{2}+ \Bigg{(}\omega L_{1}-\frac{\omega^{3}M^{2}L_{2}}{\left(R_{2}+R_{\rm L}\right) ^{2}+\omega^{2}L_{2}^{2}}\Bigg{)}^{2}}\end{split} \tag{18}\]  
where \(P_{1}\
eq P_{2}\) due to the ohmic losses on \(R_{1}\) and \(R_{2}\) only. In this operation, the power transfer was not brought to its global maximum point, but it was ensured that the goal of about 3.6 kW was still satisfied. The main data that refer to this new configuration are reported in Table 1. It can be noted that, this time, the inductance parameters were intended as average values. Indeed, they depended on the particular alignment between primary and secondary ferrite cores.
## 3 Problem Formulation
### Optimization Problem Formulation
#### 3.1.2 Minimization of Energy Consumption  
It is crucial to minimize the energy consumption of the UAV BS for it to stay in the air for a longer time so that the service that the ground users get is prolonged. Put it another way, the optimization objective elaborated in Section 3.1.1 focuses on maximizing the number f connected users, \(n_{\mathrm{c}}\), however, such objective is instantaneous (i.e., for a duration of a single time slot, \(T_{\mathrm{d}}\)) and does not aim to maximize \(n_{\mathrm{c}}\) for a period of time. The total number of connected users over a period of time considered can be calculated by  
\[n_{\mathrm{c,f}}=\sum_{i=1}^{n_{\mathrm{bs}}}n_{\mathrm{c,i}}, \tag{21}\]  
where \(n_{\mathrm{c,i}}\) indicated the number of served users by the UAV BS during time slot \(i\) from \(\vec{T}\). In (21), \(n_{\mathrm{bs}}\) is a function of \(T_{\mathrm{s}}\), such that \(n_{\mathrm{bs}}=f(T_{\mathrm{s}})\), thereby although \(T_{\mathrm{s}}\) is assumed to be fixed here, normally it is dependent on the energy stored in the UAV battery (i.e., battery capacity) as well as the energy consumption of the UAV BS. Since the battery capacity is fixed (We acknowledge that different UAVs have different battery capacities, but here we mean that once a UAV is selected out of various options, the battery capacity becomes something that cannot be changed/controlled), the only way left to prolong the UAV flight time is reducing the energy consumption. Therefore, the second objective of our problem formulation becomes the minimization of the total energy consumption of the UAV BS (\(E_{\mathrm{T}}\)), and that can be modeled as follows:  
\[\begin{array}{rl}\min_{\vec{C}_{\mathrm{M}}\in\mathbb{R}^{3}}&g(\vec{C})\\ \mathrm{s.~{}t.}&\mathrm{C_{1}}\mathbf{:}&h_{\min}\leq h_{\mathrm{d}}\leq h_{\max},\\ &\mathrm{C_{2}}\mathbf{:}&\angle A_{1}+\angle A_{2}+\angle A_{3}+\angle A_{4}<2\pi, \\ &\mathrm{C_{3}}\mathbf{:}&\theta<\pi,\\ &\mathrm{C_{4}}\mathbf{:}&P_{\mathrm{t}}\leq P_{\max},\end{array} \tag{22}\]  
where \(g:\mathbb{R}^{3}\rightarrow\mathbb{R}\) is the objective function, and \(g(\vec{C})=E_{\mathrm{T}}\) in this case.
_Applied_  
_sciences_  
_Article_  
**Comparison of Dynamic Characteristics between Small and Super-Large Diameter Cross-River Twin Tunnels under Train Vibration**  
[PERSON] \({}^{1}\)\({}^{\copyright}\), [PERSON] \({}^{1}\), [PERSON] \({}^{1,*}\)\({}^{\copyright}\), [PERSON] \({}^{1}\) and [PERSON] \({}^{2}\)\({}^{\copyright}\)  
\({}^{1}\) School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China; [EMAIL_ADDRESS] (L.W.); [EMAIL_ADDRESS] (X.Z.); [EMAIL_ADDRESS] (X.M.)  
\({}^{2}\) School of Civil Engineering and Architecture, Shaamxi University of Technology, Hanzhong 723001, China; [EMAIL_ADDRESS]  
\({}^{*}\) Correspondence: [EMAIL_ADDRESS]; Tel.: +86-187-1133-2003  
**Featured Application: The quantitative comparison of the dynamic characteristics between super-large and small diameter twin tunnels under train vibration is helpful to the design and construction of super-large diameter twin tunnels.**  
**Abstract:** Train vibration from closely aligned adjacent tunnels could cause safety concerns, especially given the soaring size of the tunnel diameter. This paper established a two-dimensional discrete element model (DEM) of small (\(d=6.2\) m) and super-large (\(D=15.2\) m) diameter cross-river twin tunnels and discussed the dynamic characteristics of adjacent tunnels during the vibration of a train that runs through the tunnel at a speed of \(120\) km/h. Results in the D tunnel showed that the horizontal walls have the same horizontal displacement (\(D_{\rm H}\)) and the vertical walls have the same vertical displacement (\(D_{\rm V}\)). The stress state of the surroundings of the \(D\) tunnel is the decisive factor for \(D_{\rm H}\), and the distance from the vibration point to the measurement point is the decisive factor for \(D_{\rm V}\). Results in the comparison of the \(d\) and \(D\) tunnels showed that the \(D\) tunnel is more stable than the \(d\) tunnel with respect to two aspects: the time the tunnel reaches the equilibrium state and the vibration amplitude of the structure's dynamic and static responses. The dynamic characteristic of the \(d\) and \(D\) tunnel is significantly different. This research is expected to guide the design and construction of large diameter twin tunnels.  
**Keywords:** twin tunnels; super-large diameter tunnel; train vibration load; dynamic characteristics; discrete element method (DEM)
## 3 Overview of OCC
### Decoding Principle  
An image sensor is built with pixel arrays and a built-in read-out circuit. Each pixel of an image sensor acts as a photodetector. Depending upon the type of camera, these arrays are activated either at once or one by one; this is the basic working principle of the global shutter and rolling shutter. The pixels are activated together in the global shutter, whereas pixels are activated in succession in the rolling shutter. Rolling shutter enables capturing of LED states at different pixels resulting in a series of stripes as shown in Figure 4.  
The transmitted bits are decoded using image-processing techniques as shown in Figure 5. The first step is detecting and tracking the transmitter from video frames using computer vision algorithms to identify the Region of Interest (RoI). The RoI from the image is cropped and resized to obtain an image containing stripes. The cropped RoI further undergoes pre-processing to obtain a 2D signal using thresholding and decoding techniques. The decoded binary bits are used to reconstruct sent data. Details on this process are discussed in Section 4.  
Figure 4: Rolling Shutter Effect.  
Figure 3: Modulation Patterns.
## 3 System Model and Problem Formulation
### Incentive Mechanism and Optimization Objective  
Let \(r_{i}^{t}\) denote the incentive allocated by the server to client \(c_{i}\) in round \(t\), subject to the following budget constraint:  
\[\sum_{i\in\mathcal{S}_{i}}r_{i}^{t}\leq R_{t},\quad r_{i}^{t}\geq 0, \tag{3}\]  
Each client responds by investing local resources \(x_{i}\) to complete the training. The client's utility function is defined as follows:  
\[U_{i}(x_{i})=\eta\cdot\tau_{i}^{t}\cdot\frac{x_{i}}{\sum_{j}x_{j}}-(a_{i}x_{i }^{2}+b_{i}x_{i}), \tag{4}\]  
where the first term represents the trust-weighted share of incentives, and the second term captures the cost of resource consumption.  
The server's objective is to design \(\{r_{i}^{t}\}\) and aggregation weights \(\{a_{i}^{t}\}\) to ensure model quality while promoting high-trust participation and suppressing malicious updates.
## 4 Experimental Setup
### Metrics  
Frame-level accuracyis calculated as the percentage of correct predictions. Intuitively, frame-wise metrics ignore temporal patterns and occurrence orders in the sequential inputs. It is possible to achieve high frame measures but at the same time generate considerable over-segmentation errors, as visualized later, raising the need to introduce segmental metrics to penalize predictions that are out of order or over-segmented.  
Segment-level edit distanceis also known as the Levenshtein distance, and only measures the temporal order of occurrence, without considering durations. It is therefore useful for procedural tasks in this work, where the order is the most essential.  
It is calculated as segment insertions, deletions, and substitutions between predicted order and the ground-truth sequence, then normalized to range [0\(\sim\)100] in Table 4 such that higher is better:  
\[Edit=\frac{|insertions|+|deletions|+|substitutions|}{|Ground\ truth|} \tag{10}\]  
**Segment-level mean average precision (_mAP@k_)**With an intersection over union (IoU) threshold \(k\), calculated as dividing the intersection between each pair of predicted segments \(I\) and the ground-truth segment of the same action category \(I^{*}\) by their union:  
\[IoU(I)=\frac{|I\cap I^{*}|}{|I\cup I^{*}|} \tag{11}\]  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**Datasets**} & \multicolumn{2}{c}{\begin{tabular}{c} **YouTube** \\ **Salads**[18] \\ **(2013)** \\ \end{tabular} } & \multicolumn{2}{c}{\
\begin{tabular}{c} **Breakfast**[18] \\ **(2016)** \\ \end{tabular} } & \multicolumn{2}{c}{**YouCook2**[25]} \\  & \multicolumn{2}{c}{
\begin{tabular}{c} **YouCook2**[25] \\ **(2018)** \\ \end{tabular} } \\ \hline Size (hour) & 4.5 h & 5 h & 77 h & 176 h \\
#Samples & 50 & 150 & 2k & 2k/14\(k\) \\
#Classes/\#Sub-actions & 2/17 & 5\(-\) & 10/62 & 90/_open_ \\ Sample Length & 4\(\sim\)5 min & 2 min & 0.5\(\sim\)5 min & 5 min \\ Label Length & 37\(\sim\)72 & steps & 7\(\sim\)10 steps & 3\(\sim\)10 steps & 3\(\sim\)15 steps \\ Recording (_vidth_\(\times\)_height_\(\times\)_fps_) & \(640\times 480\times 30\) & YouTube & \(320\times 240\times 15\) & YouTube \\ Recording (_Cameras/Background_) & \(Fixed/Stable\) & \(Dynamic/Open\) & \(Fixed/Stable\) & \(Dynamic/Open\) \\ \hline \multirow{6}{*}{\begin{tabular}{l} 1. CNN + \\ BLSTM [11] \\ (2016) \\ \end{tabular} } & \begin{tabular}{c} _Frame Acc._ \\ _mAP @ 0.25_ \\ _Edit_ \\ \end{tabular} & \
\begin{tabular}{c} _Fuzzy Acc._ \\ _mAP @ 0.25_ \\ _Edit_ \\ \end{tabular} &
\begin{tabular}{c} _Fuzzy Acc.  
\(I\) is considered as a 'true positive' (\(TP\)) if \(IoU(I)\geq k\), otherwise it is a 'false positive' (\(FP\)). Average precision is accumulated across all categories. \(mAP@k\) is more invariant to small temporal shifts as compared to the above metric.  
**Segment-level F1-score (F1@\(k\))** With an intersection over union (IoU) threshold \(k\), where true positives are judged by \(IoU(I)\geq k\) with labels same as the ground truth:  
\[Precision=\frac{TP}{TP+FP} \tag{12}\] \[Recall=\frac{TP}{TP+FN}\] \[F1=2*\frac{Recall\cdot Precision}{Recall+Precision}\]
# Damage Identification Based on Adding Mass for Liquid-Solid Coupling Structures
## 6 Conclusions  
In this work, the adding mass method for damage identification was studied by considering the influence of liquid. By performing experimental measurements on a submerged cantilever beam and liquid storage tank, the effects of immersion depths and mass positions on the natural frequencies of structures were analyzed. The main conclusions of the study can be summarized as follows:  
(1) For the submerged structures tested in this study, by adding mass at different positions, the difficulty of underwater sensor placement is overcome, and the amount of experimental data is effectively increased. These ensure the accuracy of damage identification.  
(2) The proposed approach allows damage position to be quickly located according to its characteristics. This makes the calculated results very suitable for practical engineering applications.  
(3)The structural damage usually decreases the frequencies of the structure. Many groups of experimental data are obtained by adding mass blocks to the structure, and the local damage sensitivity is improved, which makes the proposed method have high accuracy for the damage identification of the liquid-solid coupling structures.  
(4) Due to the long-term complex environment, liquid-solid coupling structures, such as offshore platforms, liquid storage tanks, and dams, are prone to be damaged, so it is difficult to monitor them sometimes. The method proposed in this paper can provide a scheme for such structures.  
Conceptualization, [PERSON]; methodology, [PERSON] and L.J.; software, H.W. and P.W.; validation, P.W., H.W. and D.X.; writing--original draft preparation, H.W. and D.X.; writing--review and editing, J.H., and L.J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Key Research and Development Program of China (2018 YFC0705604), National Natural Science Foundation of China (NSFC) (51878118), the Fundamental Research Funds for the Central Universities (DUT19 LK11), the National Science Centre, Poland (project 2018/31/B/ST8/03152) and the project DEC- 2017/25/B/ST8/01800 of the National Science Centre, Poland.  
The authors declare no conflict of interest.
## 5 Simulation Validation and Discussion
### Analysis of Simulation Results
#### 5.2.2 Analysis and Consideration of GPT Zero-Phase Voltage Results
Grid operators will need to select an inductor-capacitor device capable of having an appropriate voltage size at steady state while having increased ground fault sensitivity in a fault situation, considering the characteristics of the existing system. Figure 14: GPT zero-phase voltage (according to capacitor capacity). \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{2}{c}{**Simulation Conditions**} & \multicolumn{2}{c}{**\(V_{CLR}\) [V]**} \\ \multicolumn{2}{c}{**(Capacity of L and C)**} & & **Zero-Phase Voltage at** & **Zero-Phase Voltage at** \\
**L [mH]** & **C [uF]** & **Normal Condition** & **Fault Condition** \\ \hline
0 & 0 & 85–95 & 193–196 \\
3 & 10 & 56–66 & 178–181 \\
5 & 10 & 46–55 & 178–182 \\
10 & 10 & 31–37 & 179–182 \\
20 & 10 & 19–22 & 179–182 \\
10 & 3 & 31–36 & 108–110 \\
10 & 5 & 31–37 & 145-148 \\
10 & 10 & 32–37 & 179–181 \\
10 & 20 & 32–37 & 191–196 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation result of GPT zero-phase voltage (according to inductor and capacitor capacity).
## 4 Conclusions  
In summary, with NH\({}_{4}\)HF\({}_{4}\) etchant, intercalation and ultrasonic separation were conducted to synthesize 2D MXene (Ti\({}_{3}\)C\({}_{2}\)) and mix them with a binary solution of [EMIM][OSO\({}_{4}\)] and diethylene glycol to formulate highly efficient nanofluid for light absorbance. The impact of MXene concentration on ionic liquid-based DG/MXene nanofluid optical properties was examined through UV-Vis Spectroscopy. Through visual inspection and absorbance analysis over time, the dispersion stability of the prepared ionanofluids was evaluated. Based on the analysis of UV-Vis spectroscopy, the following points are concluded:  
* The concentration of 2D MXene nanoparticles impacted a significant effect on the absorbance spectra
* With the increase in the nanoparticle loading, the absorbance capacity of the ionanofluid increased
* High extinction coefficient was obtained for fluid containing less concentration of MXene
* High absorption peaks were found on both days, which meant that the light absorbance potential over the measured wavelengths showed great stability.  
The results of the stability evaluation are summarised as follows:  
* Slight aggregation of nanoparticles was observed from day 5, which was monitored via a visual inspection method
* Stability analysis through absorbance spectra illustrated that the prepared ionanofluids were stable for 0.1 to 0.4 wt% MXene nanoparticle concentration
* Electrical conductivity improved with the addition of MXene nanoparticles, resulting in a maximum electrical conductivity of 571 \(\upmu\)S/cm at 0.4 wt%.  
Figure 14: Absorbance analysis with respect to MXene concentration.  
**Author Contributions**: Conceptualisation, B.B.; methodology, B.B.; formal analysis, R.S.; investigation, B.B.; resources, N.A.; data curation, B.B.; writing--original draft preparation, B.B.; writing--review and editing, R.S.; supervision, K.H.; project administration, R.S.; funding acquisition, K.H. and A.R.; extinction coefficient analysis, A.R.; grammar checking, A.R. All authors have read and agreed to the published version of the manuscript.  
**Funding**: The APC was funded by Charles Darwin University, Australia.  
**Acknowledgments**: The authors wish to recognize Universiti Teknologi PETRONAS for their research support through YUTP FRG grant (Grant No. 015 LC0-118).  
**Conflicts of Interest**: The authors declare no conflict of interest.
# Robust Image Watermarking in Spatial Domain Utilizing Features Equivalent to SVD Transform
###### Abstract  
In recent years, digital image watermarking has gained a significant amount of popularity and developed into a crucial and essential tool for copyright protection, security, and the identification of multimedia content. Despite its high computational complexity, singular value decomposition (SVD) is an extensively utilized transformation in digital image watermarking. This research presents a robust and blind image watermarking scheme that directly alters the image pixels in the spatial domain to incorporate the watermark by quantizing the block-wise invariant maximum singular value. Using a distribution rule, pixels from the cover image are redistributed to obtain a new image that is divided into square and non-overlapping blocks to obtain invariant maximum singular values by using the matrix 2-norm in the spatial domain without performing an SVD transform. This modifies the pixels of the cover image such that the outcome is equivalent to the difference between the maximum singular values of the corresponding blocks in covers and watermarked images. The strengths of the proposed approach are highlighted by a comparison of experimental results with the most recent and comparable watermarking approaches.  
singular value decomposition; image watermarking invariant singular value; quantization; matrix 2-norm +
Footnote †: journal: Applied Physics Letters  
**Citation:** [PERSON] Robust Image Watermarking in Spatial Domain Utilizing Features Equivalent to SVD Transform. _Appl. Sci._**2023, 13**, 6105. [[https://doi.org/10.3390/app13106105](https://doi.org/10.3390/app13106105)]([https://doi.org/10.3390/app13106105](https://doi.org/10.3390/app13106105))