esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Material and Methods
### Angular Distribution Models
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **CERES** & **Bins Supplemented** & **Min.–Max. in Angular Bin Medians of** \\ \hline \(\theta_{s}\) (\({}^{\circ}\)) & **Footprints** & **with Simulations (\%)** & **Cloud-Top \(R_{e}\) (μm)** & **Cloud-Topped WV (kg m\({}^{-2}\))** \\ \hline  
\hline \hline \end{tabular}
\end{table} 
Table 2: A list summarizing the availability and nature of CERES footprints per increment of \(\theta_{s}\). To fill angular bins (resolved by \(\phi\) and \(\theta_{v}\); here shown for \(\theta_{v}\) between 0 and 70\({}^{\circ}\)) within the upward hemisphere, CERES footprints (numbers shown in Column 2) were in part supplemented by broadband simulations (fraction of bins receiving support shown in Column 3). Collected CERES samples varied considerably in cloud-top effective radius (Column 4; showing minimum to maximum of medians for each angular bin) and cloud-topped water vapour (Column 5).
## 4 Analysis and Discussion  
PUFs are adopted in applications and cryptographic-based systems; however, PUFs fail to provide proper protection because they can be completely broken using computational models and other non-invasive methodologies [12]. Since the PUF is one of the main components of cryptography, it can achieve all goals of security protection for various companies, businesses, and other essential organizations. Some research has mentioned how PUFs are suitable for hardware security and protocol authentication. PUF entities, namely, the authentication, protocol, classification, and model, are shown in Figure 8.
# Design and Optimization of Piezoelectric-Powered Portable UV-LED Water Disinfection System
###### Abstract  
Due to the environmental pollution threatening human life, clean water accessibility is one of the major global issues. In this context, in literature, there are many portable water disinfection systems utilizing ultraviolet (UV) radiation. UV water disinfection systems employ piezoelectric-based electric power along with UV light-emitting diode (LED) sources. This paper elaborates on the detailed design and parametric optimization of a portable UV disinfection system. The proposed system aims to generate piezoelectric harvesting-based electrical power simply by shaking, and the generated power is then used to supply UV-LEDs for water disinfection. To this end, overall system parameters along with a physical-mathematical model of mechanical, electrical and biochemical aspects of the system are fully developed. Moreover, the main design parameters of the developed model are derived for optimal operation of the system by employing Genetic Algorithm (GA). Finally, optimal design parameters were identified for three different cost scenarios. The model can further be improved for practical implementation and mass production of the system.  
UV disinfection; piezoelectric energy harvesting; design optimization; genetic algorithm +
Footnote †: journal: Applied Sciences
## 6 Discussion
### Theoretical Contributions and Practical Implications
#### 6.1.2 Practical Implications  
First, to provide high-quality system support, functions such as virtual reality, gaming, and simulations can be introduced by providers to offer practical or experiential learning opportunities. Second, providers are supposed to establish collaborations with governments, large companies, and universities to increase the knowledge base of AI tools and expand the database. At the same time, attention should be paid to filtering practical information quickly and effectively, and to providing feedback to college students on time. This aims to ensure high-quality and comprehensive information. Then, AI tools can be employed in student affairs to offer personalized degree planning, supplementary counseling, and advisory functions, among others [84]. During the learning process, solutions to issues encountered by university students can be offered by these tools, prioritizing the enhancement of their perceived competence. Furthermore, providers increase the emphasis on socialized interaction and genuine feedback. Surveys and other services can be conducted by providers to obtain timely and valuable suggestions. Comment sections or learning and communication groups can also be established to foster an environment where users can share ideas and engage in meaningful exchanges. AI techniques can simulate one-on-one human tutoring by offering personalized learning activities that address a learner's cognitive needs and by delivering focused, timely feedback, all without requiring the physical presence of a human teacher [85], thereby satisfying the autonomy demand of university students.
# Chemo-Mechanical Model for the Expansion of Concrete due to Alkali Silica Reaction
## 2 Mathematical Model for the Chemical Reaction of ASR  
### Reaction Sequence  
The following reaction sequence for the formation of ASR products is considered in our model. The reaction initiates from the dissolution of silica in an alkaline environment, in which the (\(\equiv\) Si \(-\) O\(-\)) bonds are attacked progressively by hydroxyl ions. The released silica is consumed very quickly by calcium in the nearby pore solution to form a C-S-H layer as shown in Figure 1a. This leads to the local depletion of calcium [1; 33; 34]. Then, the released silica will bind Na\({}^{+}\)(or K\({}^{+}\)) to form alkali silicates, which is called the basic ASR gel in this paper; see Figure 1b. Note that the imbibition of water is not considered yet in this basic gel. As the calcium in the pore solution penetrates into the gel layer, some of alkalis in the basic gel will be replaced by calcium to form C-S-H gel, which is called alkali-recycling by calcium [1]; see Figure 1b. Two reaction fronts are considered in our model; the ASR reaction front, \(z_{r}\), and the alkali recycling front, \(z_{c}\), respectively.  
The gel is so hygroscopic that it imbibes nearby water to generate hydrated alkali silicate gel. This is the swelling of ASR gel. The expansive pressure induced by the swelling gel causes the deterioration of concrete. The water imbibition ability (or swelling capacity) of the basic gel is influenced by the chemical composition of the gel, for example, the concentration of calcium ions in the gel [23; 24]. This dependence on calcium in the pore solution is considered in this model.
## 6 Conclusions
### Key Contributions  
First, the **methodological co-evolution** from adaptive optimization to hybrid architectures has been quantitatively validated: Neural tangent kernel-guided weighting achieves 230% convergence acceleration in Navier-Stokes solutions, while domain decomposition enables 5\(\times\) speedup in 3D turbulence modeling. The proposed hybrid numerical-deep learning paradigm reduces computational costs by 72% compared to traditional FEM in high-dimensional spaces (\(p<0.01\), \(n=15\) benchmarks).  
Second, the **theory-practice bidirectional mapping** resolves longstanding disconnections: Operator approximation theory establishes \(L^{2}\) error bounds with explicit dependence on network width, while Bayesian-physical hybrid frameworks reduce uncertainty intervals by 68% in clinical applications. The Rademacher complexity analysis provides actionable guidelines for balancing model capacity and generalization.  
Third, **cross-domain knowledge transfer** has been systematically demonstrated: TFE-PINN achieves 5.12 \(\pm\) 0.87% error in NASA hypersonic tests, ReconPINN improves MRI reconstruction SSIM by 0.18 \(\pm\) 0.04, and SeisPINN reduces earthquake localization errors to 0.52 \(\pm\) 0.18 km. These advancements are underpinned by fundamental design principles-physics-adaptive loss weighting overcomes spectral bias in 83% of nonlinear PDE cases, while wavelet-enhanced architectures improve multiscale modeling efficiency by 40%.
###### Abstract  
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the solar resource. In this study, a simple but comprehensive methodology for characterizing the solar resource for a project is presented. It is based on the determination of the best probability distribution function (PDF) of the solar irradiation for a specific location, assuming that the knowledge of statistical techniques may be more widely extended than other more complex mathematical methods. The presented methodology was tested on 23 cities across Morocco, given the high interest in solar investments in the country. As a result, a new database for solar irradiation values depending on historical data is provided for Morocco. The results show the great existing variety of PDFs for the solar irradiation data at the different months and cities, which demonstrates the need for undertaking a proper characterization of the irradiation when the assessment of solar energy projects is involved. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Moreover, its application is not limited to solar resource assessment, but can also be easily used in other fields, such as meteorology and climate change studies.  
solar energy; irradiation; satellite data; predictive models; probability distribution function; Morocco
# Purification of Produced Water by Solvents to Enhance Oil Recovery and Reuse Separated Droplets
## 4 Discussion
### Esters  
In Figure 6, the graphical representation of the percentage of residual oil removed from produced water by various esters and additionally by acetic acid is shown. Surprisingly, decyl oleate, a molecule significantly larger than the others, is the most effective. However, in no case is the efficacy sufficient to recommend its use in the purification of produced water. Also noteworthy is the stabilizing effect of butyl acrylate as its dosage increases. This behaviour may be due to its molecule having a certain surfactant capacity.  
The acrylate group, which includes a carboxyl and a conjugated double bond, acts as the hydrophilic group of the surfactant, and the butyl acts as the lipophilic group (Figure 7).  
Esters, although they are readily available, low-cost, and non-hazardous materials, have the disadvantage of low efficiency in oil removal, and therefore are not recommended for industrial use.
## 5 Experimental Results
### GVNS versus Nearest Neighbor Variants
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Benchmark Name** & **Improved NN** & **Repeated NN** & **GVNS BI** & **GVNS FI** & **OV** \\ \hline a280 & 3171 & 3008 & 2779 & 2766 & 2579 \\ \hline att48 & 13,447 & 12,012 & 10,645 & 10,654 & 10,628 \\ \hline bayg29 & 1938 & 1935 & 1610 & 1610 & 1610 \\ \hline bayg29 & 2307 & 2134 & 2020 & 2020 & 2020 \\ \hline bier127 & 148,330 & 133,953 & 121,393 & 121,551 & 118,282 \\ \hline kroA100 & 28,244 & 24,698 & 21,664 & 21,774 & 21,282 \\ \hline burma14 & 4470 & 3822 & 3454 & 3454 & 3323 \\ \hline ch130 & 7342 & 7129 & 6342 & 6373 & 6110 \\ \hline \end{tabular}
\end{table} 
Table 2: The experimental results show that GVNS outperforms the improved and the repeated NN on TSP instances (1/2).
## 2 Kinematic Calculation Matrix Chain Multiplication  
Forward and inverse kinematics solutions of robotic arms mainly include the rotation and translation matrix multiplication of each joint angle position or the known end joint position and velocity to obtain inverse solutions. Reference [21] provides the calculation process of the homogeneous end pose transformation matrix. \(X_{M_{k}\times N_{k}}\) is defined as the homogeneous transformation matrix of joint \(k\), and then the terminal homogeneous pose transformation matrix \(Y_{M\times N}\) is  
\[Y_{M\times N}=\prod_{k=0}^{S-1}X_{M_{k}\times N_{k}} \tag{1}\]  
where \(S\) represents the number of joints, \(S\geq 1\) and \(S\in Z^{+}\). \(M_{k}\) and \(N_{k}\) represent the number of rows and columns of the \(k\)th matrix, \(M=M_{0}\), \(N=N_{S-1}\), and \(N_{k-1}=M_{k}\).  
It can be seen from Formula (1) that the kinematic solution process of robotic arm control is a standard matrix multiplication calculation problem, so traditional dynamic programming can be used to search for the optimal multiplication order to reduce the amount of calculation [22]. The multiplication amount of any two adjacent matrices \(X_{M_{k-1}\times N_{k-1}}\) and \(X_{M_{k}\times N_{k}}\) is \(T(k-1,k)=M_{k-1}N_{k-1}N_{k}=\prod\limits_{u=k-1}^{k+1}M_{u}\). For the multiplication chain of \(S\) matrices, the optimal order is defined as \(m(i,j)\), where \(i,j\in[0,S-1]\), and then the recursive optimal order of traditional matrix multiplication is  
\[m(i,j)=\left\{\min_{i<d<j}\{m(i,d)+m(d+1,j)+M_{i-1}M_{d}M_{j}\},i<j\right. \tag{2}\]  
The order of the homogeneous matrix \(T(k-1,k)\) is unified in the kinematic solution of the robotic arm. It is difficult to directly reduce the amount of calculation to search for optimal multiplication by matrix multiplication dynamic programming alone. Therefore, an equivalent order reduction mechanism should be established according to the sparsity of the homogeneous matrix in the settlement process of the robotic arm movement, and then the optimal multiplication order should be searched according to dynamic programming.
## 3 Results
### Biocompatibility and Pharmacological Activity
#### 3.3.2 In Vitro Cell Cultures  
The biocompatibility of the VitE/chitosan scaffolds was tested on human fibroblast cultures (Figure 7). Cells grown up to 28 days maintained the typical spindle morphology and remained close to confluence independently from the presence of VitE and from its concentration. By specifically observing images taken at day 7, it is possible to state that cells on the VitE 1 scaffolds proliferated with a certain delay with respect to the VitE 0.1 scaffolds and the control. At day 14, fluorescent clusters of cells started to be visible in all of the samples within the macro-pores. After day 21, confluence was achieved in all of the scaffold types, and the cell density was higher than previous sampling points, demonstrating high biocompatibility and excluding the hypothesis of toxic effects.
## 4 Overview of GNSSs
### BeiDou  
The BeiDou Satellite Navigation System (BDS) provides a range of services resulting from its functionality. Currently in operation, the BeiDou is the third phase of China's satellite navigation system. In addition to the positioning, navigation, and timing (PNT) service provided by all GNSS, BDS also offers regional message communication, global short message communication, global search and rescue (SAR) service, regional precision point positioning (PPP) service, built-in satellite extension service (BDS-BAS), and space environment monitoring function [78; 86; 87].
## 5 Applications of BSNs  
With the deepening and extension of research, BSN technology is gradually becoming mature and widely used in many fields, including medicine, social welfare, sports, and man-machine interfaces, as shown in Figure 4. In addition, in other fields, such as the military, entertainment, and industrial systems, applications of BSNs can also be found.
# Towards a Better Understanding of Transfer Learning for Medical Imaging: A Case Study
## 5 Methodology
### Datasets
#### 5.1.2 Pre-Train Datasets  
We collected large datasets from different sources. The first dataset (Dataset C) is in the same domain as the first target dataset (Dataset A) while the second dataset (Dataset D) is in the same domain as the second target dataset (Dataset B). The main purpose of these datasets was to pre-train our model for target datasets. Both datasets have images that look similar in features such as color, shape, and size to the target datasets. Dataset C is similar to Dataset A while Dataset D is similar to Dataset B. All images of both datasets were used for training for TL purpose.  
**Medical Dataset (Dataset C):** we collected the dataset from different sources although all images were in the same domain as the DFU dataset. The first source had 594 images that were classified into 15 wound categories including abdominal wounds, burns, epidermolysis bullosa, extravasation wounds, foot ulcers, hemangioma, leg ulcers, malignant wounds, meningitis, miscellaneous, orthopedic wounds, pillonidal sinus, pressure ulcers (a), pressure ulcers (b), and toes [68]. The second source  
Figure 1: Sample from diabetic foot ulcer (DFU) dataset (Dataset A) of normal and abnormal region with a size of \(224\times 224\). The blue color is abnormal patch (DFU) class, green color is normal class.  
Figure 2: Samples from animal dataset (Dataset B) (first row is chicken class; second row is cow class).  
had 2700 different wound images that were collected from the internet. The third source contained 1000 images of clinical skin diseases that were collected from [69]. The last source had 37,364 images of skin cancer including melanoma, melanocytic nevus, basal cell carcinoma actinic keratosis, benign keratosis, dermatofibroma, and vascular lesions [70,71]. All images were resized to \(224\times 224\). Some of the images were divided into two or three sub-images. The final total of images was 50,103. Figure 3 shows some samples of the dataset.  
**Large Animal Dataset (Dataset D):** This dataset consisted of several classes of animals that were collected from different sources. The first source had eight classes of animals including dog, cat, horse, spider, butterfly, sheep, squirrel, and elephant [69]. The total number of images was 21,215. The second source had 8000 images of cats and dogs that were added to those in the first source [72]. The third source had 2099 different types of birds [73]. The fourth source had images of animals such as chimpanzee, ox, deer, etc., [74]. The total number of images was 3000. The last source included 16,643 images of wild animals such as panda, zebra, gorilla, giraffe, camel, tiger, bear, lion, elephant, and kangaroo. All images were collected from the internet. The overall number of images in this dataset was 50,957 and they were resized to \(224\times 224\). Figure 4 shows some samples of the dataset.  
Figure 4: Samples from the large animal dataset (Dataset D).  
Figure 3: Samples from the medical dataset (Dataset C).
# A Review on Vibration Control Using Piezoelectric Shunt Circuits
## 2 Types, Applications, and Recent Advances of Piezoelectric Shunt Circuits  
Although active piezoelectric damping systems have drawn significant attention, the utilization of piezoelectric shunt circuits in vibration suppression offers important benefits in some applications. Starting with the classical approach, passive control methods provide many benefits, such as the fact that they function without the need for external power or any active control systems, which simplifies the implementation and reduces energy consumption, playing a significant role in drawing attention to it and making it preferable to active control systems.
## 2 Theoretical Background
### Fuzzy Theory
#### 2.1.6 Processing the Evaluation Indices  
After the evaluation indices \(b_{j}\) (\(j=1,\ 2,\ \ldots,\ n\)) are determined, the results of the evaluation target can be determined by the methods of maximum degree of membership and weighted average, as follows.  
(a) Maximum degree of membership  
Based on the principle of maximum degree of membership, the evaluation element \(v_{i}\) corresponding to the maximum evaluation index \(b_{j}\) is selected. This approach considers only the contribution of the maximum evaluation index; information supplied by other indices is neglected. Moreover, when there are more than one maximum evaluation indices, it will be difficult for maximum degree of membership to determine a concrete result. In this case, weighted average is usually used.  
(b) Weighted average  
By taking \(b_{j}\) as the weight, the weighted average of each evaluation element \(v_{j}\) is determined to obtain the evaluation result; that is,  
\[D=\frac{\sum\limits_{j=1}^{n}b_{j}v_{j}}{\sum\limits_{j=1}^{n}b_{j}}. \tag{14}\]When the evaluation index \(b_{j}\) is normalized, then  
\[D=\sum_{j=1}^{n}b_{j}r_{j}. \tag{15}\]  
If the evaluation target is quantitative, Equation (14) can be used to determine the \(D\) value, which is the result of the fuzzy comprehensive evaluation for the evaluation target. If the target is not quantitative and the evaluation set is {superior, good, neither good nor bad, bad}, quantification of the nonquantitative targets of superior, good, neither good nor bad, and bad should be carried out. Otherwise, maximum degree of membership should be used. Based on these evaluation criteria, the distribution of various characteristics of the evaluation target can be determined. This method provides a deeper understanding of the evaluation target in order to determine the most appropriate processing approach to evaluate the data.
## 3 Monitoring and Detection Technology of SF\({}_{6}\) and Its Decomposition Components
### Photoacoustic Spectroscopy (PAS)
#### 3.2.3 Cantilever-Enhanced Photoacoustic Spectroscopy (CEPAS) Method  
Studies have shown that cantilever-enhanced photoacoustic spectroscopy has the potential for research in the sensitivity and selectivity of trace gas analyzers, and the detection sensitivity of trace gases can reach the ppt level [34; 35]. [PERSON] et al. [36] used a cantilever to enhance the photoacoustic spectrum of benzene to reach a detection limit of less than 1 ppb. The detection limit of trace acetylene was 80 ppt [37]. The noise equivalent detection limit of HCN and CH\({}_{4}\) was able to reach 190 ppt and 65 ppt [38].  
[PERSON] et al. [39] proposed a cantilever-enhanced optical fiber photoacoustic microprobe, using UV multi-mode fiber and single-mode fiber to transmit excitation light and detection light from UV led, respectively, for SO\({}_{2}\) detection. Allen-Werle deviation analysis was used to evaluate the long-term stability of the system, with white noise as the system noise, and SO\({}_{2}\) detection limits of 35 ppb and 5 ppb in the SF\({}_{6}\) and N\({}_{2}\) background, respectively.  
[PERSON] et al. [40] designed a C\({}_{2}\)H\({}_{2}\) and CO detection system based on a microcantilever and single-channel photoacoustic unit. The minimum detection limits for C\({}_{2}\)H\({}_{2}\) and CO were 0.27 ppmv and 23.42 ppmv, respectively. This system simultaneously detected these multi-component gases. [PERSON] et al. [41] used the distributed feedback semiconductor laser (DFBLD) as the light source to build a cantilever-enhanced photoacoustic spectroscopy detection system and then studied the photoacoustic spectrum of carbon-monoxide at 4291.5 cm\({}^{-1}\). The high stability of the photoacoustic signal had a good linear relationship with the gas concentration, and the detection limit of carbon monoxide was able to reach 5.1 ppmv. [PERSON] et al. [42] studied the relationship between PA signal and CO concentration under SF\({}_{6}\) and N\({}_{2}\) backgrounds, which was based on a cantilever-enhanced PA detector (Figure 3c). The infrared absorption wavenumber at 6380.318 cm\({}^{-1}\) was selected, and the central wavelength was 1567 nm infrared laser. Finally, the minimum detection limit was 3.63 ppmv in the N\({}_{2}\) background and 9.88 ppmv in the SF\({}_{6}\) background.