esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Monthly Variation in GPP, ET, and WUE  
The seasonality of GPP and ET in both YP and MP was distinct, with a higher carbon uptake and evapotranspiration in April-September when spring and summer conditions favored leaf development, and generally lower during the non-growing months (i.e., October-December and January-March). During spring and summer seasons, the average GPP was 8.39 \(\pm\) 1.55 g C m\({}^{-2}\) d\({}^{-1}\) in YP and 10.46 \(\pm\) 1.47 g C m\({}^{-2}\) d\({}^{-1}\) in MP. However, during the fall and winter season, GPP was only 2.98 \(\pm\) 1.16 g C m\({}^{-2}\) d\({}^{-1}\) in YP and 4.98 \(\pm\) 1.75 g C m\({}^{-2}\) d\({}^{-1}\) in MP. In the same manner, ET during the growing season reached 2.76 \(\pm\) 0.94 kg H\({}_{2}\)O m\({}^{-2}\) d\({}^{-1}\) and 3.87 \(\pm\) 0.60 kg H\({}_{2}\)O m\({}^{-2}\) d\({}^{-1}\) for YP and MP, respectively. In contrast, during the non-growing season, ET was only 1.06 \(\pm\) 0.65 kg H\({}_{2}\)O m\({}^{-2}\) d\({}^{-1}\) in YP and 1.67 \(\pm\) 0.66 kg H\({}_{2}\)O m\({}^{-2}\) d\({}^{-1}\) at the MP site (Figure 4).  
Figure 3: Inter-annual variation in (**a**) evapotranspiration (ET), (**b**) gross primary productivity (GPP), and (**c**) water use efficiency (WUE) at different ages of the chronosequence (YP and MP). Monthly data were used in the analysis.  
However, there was no clear seasonal pattern in WUE, even though a higher variability was observed during the growing season, with higher WUE in YP (i.e., 3.22 \(\pm\) 1.05 g C kg\({}^{-1}\) H\({}_{2}\)O\({}^{-1}\)) compared to MP (i.e., 2.74 \(\pm\) 0.47 g C kg\({}^{-1}\) H\({}_{2}\)O\({}^{-1}\)). Interestingly, the WUE at YP and MP during the non-growing season did not differ significantly at 3.05 \(\pm\) 1.61 g C kg\({}^{-1}\) H\({}_{2}\)O and 3.05 \(\pm\) 0.53 g C kg\({}^{-1}\) H\({}_{2}\)O, respectively.  
Figure 4: Seasonal trend in (**a**) evapotranspiration (ET), (**b**) gross primary productivity (GPP), and (**c**) water use efficiency (WUE) across different age levels of the chronosequence sites (YP and MP) based on monthly smoothed values for each year. Each year was assigned with different color. Smooth curve is represented by colored line and colored circles represent monthly data for each year.
## 3 Results and Discussion
### Effect of Hydraulic Residence Time and Porous Media
The W5 FGZ-R unit exhibited higher average removal rates than the W3 FG-R unit for all pollutants (i.e., BOD, COD, TKN, and NH\({}_{4}\)-N). The \(t\)-test showed statistically significant differences (\(p<0.05\); Table 6) for the average removal values of BOD, COD, and NH\({}_{4}\)-N. These results suggest that the presence of zeolite in the substrate enhances the removal of both OM and nitrogen. Zeolite is a low-cost material and a very good adsorbent for cations such as ammonium ions. It improves cation exchange and ammonium adsorption because of its high surface area and ion exchange capabilities. Furthermore, it serves as a site for microbial biofilm growth, as the porosity of the material may favor and enhance the growth of microorganisms [34]. According to studies [46], zeolite enhances nitrogen removal by temporarily binding ammonium, delaying rapid leaching, and making it available for microbial decomposition. As nitriifying bacteria within the biofilm use ammonium adsorbed to the zeolite particles, the ion exchange capacity of the zeolite is bio-regenerated [58]. These properties make zeolite a popular material for use as a filler in constructed wetland units for the removal of ammonium and metal ions. It has been used in CW systems by many researchers for the removal of ammonia and metals in high-strength wastewaters, such as landfill leachate [46, 59].
## 1 Introduction
Although these studies demonstrate that altering the dielectric medium can effectively enhance shock wave intensity and improve rock breaking efficiency, current work still exhibits two main deficiencies. Firstly, most enhancement methods rely on energetic materials such as sensitive explosives and strong oxidizers [21; 22]. While these significantly boost performance, they easily introduce safety hazards and create new environmental pollution issues, contradicting current green and sustainable development requirements. Secondly, there is a lack of systematic and comparative research on multiple environmentally friendly dielectric media. Specifically, there is an absence of performance evaluations and principle analyses of diverse green dielectric media under equivalent experimental conditions, which fails to provide systematic guidance for practical engineering applications. To address these issues and research gaps, this study selected seven dielectric media that meet green and environmental protection requirements, with tap water as a control group, for metal wire electrical explosion experiments in concrete blocks. Through electrical signal and high-precision strain acquisition devices, we comparatively analyzed the effects and differences of various media on electrical explosion discharge characteristics and shock wave intensity. The research aims to elucidate the enhancement mechanisms of electrical explosions in different media and identify dielectric media that can significantly improve rock-breaking effects while remaining safe and environmentally friendly. This study provides a scientific basis and theoretical support for the application of electrical explosion rock-breaking technology in engineering practices.
# Skin Cancer Disease Detection Using Transfer Learning Technique
## 5 Conclusions and Future Work  
Melanoma is the worst type of skin cancer, but if caught in a timely enough manner, it can be a non-life-threatening disease. As a result, it is critical to employ supportive imaging modalities that have been proved to help with diagnosis. These methods are based on procedures devised by doctors to detect melanoma before it spreads to nearby lymph nodes. In this research, we provide a transfer learning model for melanoma and benign skin lesions diagnosis based on MobileNetV2, which can be used to investigate any suspicious lesion. The suggested method is applied to an ISIC2020 challenge dataset of skin cancer disorder images to determine if a disease is malignant or benign. Data augmentation techniques were used to increase the dataset's size and improve the accuracy of MobileNetV2. This architecture works effectively and has a diagnostic accuracy of 98.2 percent. Finally, the accuracy of various state-of-the-art models is compared to the proposed framework. The suggested architecture was found to provide outstanding classification accuracy without needing model training from scratch to improve model efficiency. After a sufficient number of high-resolution photographs is acquired, this study will be carried out on a series of skin cancer images for patients from Pakistan in the future.  
The research conception, technique, and programming were proposed by [PERSON], [PERSON], [PERSON] and [PERSON] are in charge of the technical and theoretical framework. [PERSON], [PERSON] and others created the datasets. [PERSON], [PERSON] and [PERSON] were in charge of the technical review and improvement. [PERSON] and [PERSON] provide comprehensive technical assistance, direction, and supervision. [PERSON] and [PERSON].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref.** & **Methodology** & **Diseases** & **Dataset** & **Accuracy** \\ \hline
[58] & CNN based & Melanoma, & Dermofit, & Dermofit (90.58\%), \\  & CMLD model & Benign & MED-NODE & MED-NODE (90.14\%) \\ \hline
[8] & ANN & Melanoma, & Self Contained & \\  & & Benign & 172 Images & 93.6\% \\ \hline
[48] & FSM \& SVM & Melanoma, & \\  & & Benign & Ph2 & 91.90\% \\ \hline
[7] & Ensemble Model & Melanoma, & Xanthous Race (XR), & XR (94.14\%), \\  & & Benign & Caucasian Race (CR) & CR (91.11\%) \\ \hline
[75] & InceptionV3, ResNet, & Melanoma, & ISIC archive between & \\  & and VGG19 & Benign & 2019 and 2020 & 86.90\% \\ \hline  & Proposed Method & Melanoma, & \\  & & Benign & ISIC2020 & 98.20\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison with state-of-the-art models.  
are in charge of editing and proofreading. All authors have read and agreed to the published version of the manuscript.  
The researchers would like to thank the Deanship of Scientific Research, Qassim University for funding the publication of this project. This research received no external funding. Not applicable. Not applicable. Not applicable. Not applicable.  
Data Availability Statement Not applicable. Not applicable.  
The authors declare no conflict of interest.
# Distributed Joint Source-Channel Coding Using Quasi-Uniform Systematic Polar Codes
## 5 Simulation Results
### Complexity  
For each distributed source, the encoding complexities of both two referenced schemes are \(O(N\log N)\). The encoding complexity of the proposed scheme is slightly larger, which is \(O(N+N\log N)\). Due to low encoding complexity, these schemes are well-suited for WSNs.  
To investigate decoding complexity, we consider adaptive CA-SCL decoders [23] where the list size is expanded if decoding error is detected by CRC. These kinds of decoders have \(O(\bar{L}N\log N)\) complexity, where \(\bar{L}\) is average list size. In the simulations, the allowable maximum list size is set as \(L_{\text{max}}=32\) and the average list size \(\bar{L}\) for decoding both two sources is recorded. The complexity (per source-symbol) can be approximated as \(O(\frac{1}{MK}\cdot LN\log N)\) for the proposed scheme and DJSCC scheme with classic SPCs, and \(O(\frac{1}{N_{\text{s}}}\cdot LN\log N)\) for DSSCC schemes. As shown in Figure 9, for the high SNR region and the low SNR region, the DSSCC1 has lower decoding complexity while the proposed scheme has lower decoding complexity for the middle SNR region. In general, three schemes have similar decoding complexity under adaptive CA-SCL decoders.  
Figure 8: The BER performance under the CRC-aid SC list (CA-SCL) decoder.
## 3 Finite Element Analysis  
### Finite Element Modeling of Arc-Shaped Incisions  
The ABAQUS (6.14) software (Changsha University of Science and Technology, Changsha, China) was used to establish the finite element model of the steel box girder segment, and a section of the steel box girder between two pairs of slings was intercepted for the local force analysis. The boundary conditions were approximated by restraining the vertical displacement of the two ends of the segment box girder, restraining the angular displacement of the two ends of the segment box girder around the transverse direction, and the horizontal displacements of the box girder at one end of the restrained section in both the cis- and trans-bridge directions. Further, the self-weight of the steel box girder, the deck pavement and the load effect of the main cable on the steel box girder were not considered. As shown in Figure 4, the stress gradient in the curved cutout area of the cross-sectional plate is relatively large and fatigue-sensitive, so the grid is encrypted in this area. The box girder section model after grid encryption contains about 640,000 plate cells (S4R) in total. The following assumptions were used in the finite element calculation: 1 the structural members are in the elastic range, and the material nonlinearity and geometric nonlinearity are not considered; 2 the support of the sling to the steel box girder is rigid support; 3 the reinforcing plate and the diaphragm are in good contact and no slippage under the action of high-strength bolts; 4 the crack can be compressed but not pulled.  
In this work, the Chinese specification \"Design Code for Highway Steel Bridges\" (JTG D64) standard vehicle is used for loading, and the loading vehicle is shown in Figure 5. Wheel load acts directly on the steel bridge panel, according to the thickness of the bridge  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Name**} & **Thickness** & **Yield** & **Tensile** & **Modulus of** & **Maximum** \\  & **(mm)** & **Strength** & **Strength** & **Elasticity** & **Elongation** \\  & **(MPa)** & **(MPa)** & **(MPa)** & **(GPa)** & **(\%)** \\ \hline Q345 qD & 10 & 345 & 510 & 206 & 21.5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Materials parameters of steel plates.  
Figure 4: Finite Element Model of Steel Box Girder.  
Figure 3: Schematic representation of the optimized reinforcement scheme for arc-shaped cuts: (**a**) Optimized plan when 0 \(<\) L1(L2) \(\leq\) 25 mm, (**b**) reinforcement plan when L1(L2) \(>\) 25 mm.  
deck pavement and tire landing area, the wheel load area of action is spread by 45\({}^{\circ}\) angle, and the axle weight of the fatigue car refers to the axle weight of the actual loaded vehicle, the uniform load area is 0.3 m (length) \(\times\) 0.7 m (width) rectangle, the uniform load set of the rear wheel is 0.33 Mpa.
# DynseNet: A Dynamic Dense-Connection Neural Network for Land-Sea Classification of Radar Targets
## 2 The Proposed Methodology
### Training Loss  
The fused features are input into the average pooling and fully connected layers to obtain the prediction results. During the entire network training process, we calculate the classification loss using cross-entropy as follows:  
\[Loss=-\frac{1}{N}\sum_{i=1}^{N}y_{i}log(\widehat{y}_{i}) \tag{11}\]  
where \(y_{i}\) represents the true label, \(\widehat{y}_{i}\) represents the output result of the model inference, and \(N\) represents the current batch size.
# Simulation of Electromagnetic Generator as Biomechanical Energy Harvester
## 2 Electromagnetic Generator Modelling
### Geometry of Electromagnetic Generator  
In this study, an 8-slot/8-pole surface-mounted permanent magnet generator will be evaluated. The electromagnetic generator's assembly is shown in Figure 3.  
The generator geometry represents a single-phase permanent magnet generator and the geometrical parameters are the inner radius of rotor R\({}_{1}\), radius of the permanent magnet surface R\({}_{2}\), overall diameter of generator \(\O\), the permanent magnet sector angle \(\alpha\), slot pitch angle \(\delta\), slot opening angle \(\beta\), and the air gap thickness dm. The arrow on the permanent magnet indicates the inbound and outbound arrangement of the magnets. The dot and cross symbol on the coil represents the current flow direction in the coil. Figure 4 shows the 3D geometry view for one sector of the generator.  
Figure 3: 2D cross-section of generator assembly.  
Figure 2: Electromagnetic generator design flowchart.  
The complete design of electromagnetic generator assembly will consist of 8 sectors. The assembly portion which accommodates the coil will act as a stator and the assembly holding up the magnets will act as a rotor. The permanent magnets are arranged in a sequence where it has an opposite pole from the magnets on both sides. The generator has been designed such that for every rotation of 22.5 degrees, it will change the magnetic field of the electromagnetic generators simultaneously and generate the needed electrical power. All the parameters associated with the generator are tabulated in Table 1.
## 4 Discussion
### Topics for Future Research
#### 4.2.2 Can Maritime Data Be Protected under Copyright Law?  
This question pertains to whether maritime data are included in databases in accordance with Article 2(19) of the Copyright Act of the Republic of Korea. The Copyright Act states that the term \"database\" implies a \"compilation whose materials are systematically arranged or composed, so that they may be individually accessed or retrieved\" [53]. Therefore, copyright protection would require that maritime data satisfy the following definition. In other words, if the data defined in Section 3 are based on modern concepts, including \"raw material \(\rightarrow\) information \(\rightarrow\) knowledge \(\rightarrow\) content that is fused,\" the database function occurs when a data broker uses the \"digital platform for marine data trading.\" Therefore, we believe that maritime data could be protected under the Copyright Act, under the assumption that all elements in the database definition are met, and significant expenditures of human and physical resources have been made on databases [45; 46]. However, since the data produced by AI algorithms in autonomous vessels are not explicitly mentioned in Article 91 (\"Protected Databases\") of the Copyright Act, there is an issue of the existence of rights to their AI algorithms, under the current law [47]. However, in practice, works reproduced by AI algorithms cannot be judged as copyrighted work, because they are not a representation of a person's thoughts or emotions under Article 2 (\"Definitions\") of the Copyright Act. Nevertheless, because a computer program's work is included as an example of work under Article 4(9) of the Copyright Act, various interpretations are possible. Therefore, we need to consider practical alternatives while specifying the regulations to identify the \"author\" of work produced by AI algorithms or similar rights in the contract to data brokers that operate the \"digital platform for maritime data transactions (tentative name)\" [47].
## 5 Incipient Fault Model
### Incipient Fault Model for Periodic Disturbance  
Unlike sub-cycle disturbance, when the periodic disturbance occurs, the fault conductance persists and varies periodically. The typical periodic voltage/current and the corresponding conductance variation are shown in Figure 19.  
It can be observed that the variation of conductance exhibits a wave-like pattern, with similar maximum and minimum values in each cycle. Within half a cycle, conductance remains nearly constant for a short period after the voltage crosses zero, during which voltage and current rise synchronously. Around the voltage peak, conductance first decreases and then increases. To simulate the conductance variation within half a cycle, the conductance control function is divided into three segments: (1) conductance is set as a constant to represent its short-term invariance after the voltage crosses zero; (2) conductance decreases and then increases following a trigonometric function to model its variation near the voltage peak; (3) conductance remains constant again to simulate its short-term invariance after the final increase. Based on this conductance variation pattern and the piecewise modeling approach, the function describing conductance variation within half a cycle is constructed as follows:  
\[g_{f}=\left\{\begin{matrix}g_{\text{max}}&t<t_{\text{st}}\\ g_{\text{max}}-g_{\text{min}}\cdot\sin(\pi\cdot\frac{t_{-\text{fat}}}{t_{0}})&t _{\text{st}}<t<t_{\text{st}}+t_{0}\\ g_{\text{max}}&t_{\text{st}}+t_{0}<t<0.01\end{matrix}\right. \tag{2}\]  
In the equation, \(g_{\text{max}}\) is determined based on the voltage and current values at the current peak, while \(g_{\text{min}}\) is obtained from the voltage and current values corresponding to the minimum point within the transient current drop region. The starting time \(t_{\text{st}}\) of the transient current drop is defined relative to the zero-crossing point of the current. The duration of the transient current drop, \(t_{0}\), corresponds to the interval between the two peak values on either side of the current depression. The roles and distribution ranges of the model control parameters are listed in Table 2.  
\begin{table}
\begin{tabular}{c c c} \hline
**Parameter** & **Control Function** & **Value Range** \\ \hline \(g_{\text{max}}/\text{mS}\) & Maximum conductance & 50–148 \\ \(f/\text{Hz}\) & Conductance decrease process & 86–166 \\ \(\theta/^{\circ}\) & Conductance increase process & 33–57 \\ \(t_{\text{st}}/\text{ms}\) & Arc ignition moment & 3.5–6.3 \\ \(t_{0}/\text{ms}\) & Duration & 3.2–5.4 \\ \hline \end{tabular}
\end{table}
Table 1: Model parameters for sub-cycle disturbance.  
Figure 19: A typical periodic disturbance waveform: (**a**) voltage and current; (**b**) corresponding incipient fault conductance.
# Bond Characteristics of a Deformed Steel Bar Embedded in Donut-Type Voided Slab
## 3 Experimental Results and Analysis
### Crack Pattern of the Donut-Type Voided Slab  
Figure 7 shows the crack pattern of specimens according to the bond regions and inner cover thickness. As shown in Figure 7c, the GB-50-26 series specimen, which ensured sufficient inner cover thickness (2.5 \(d_{b}\)), did not show any crack regardless of the location of bond regions. However, the GB-50-10 and GB-50-0 series, whose clear inner cover thickness was insufficient (lower than 26 mm), showed a splitting crack that occurred along the rebar direction in the B-type and C-type specimens. Interestingly, A-type specimens of the GB-50-10 and GB-50-0 series did not show splitting cracks; nevertheless, it had insufficient inner cover thickness like C-type specimen. The difference between A-type and C-type specimens resulted from the direction of force at the rib of deformed steel bar. As shown in Figure 8, the bond force between the rib of deformed steel bar and concrete formed an angle of 45\({}^{\circ}\). The A-type specimen had efficient concrete shape in order to resist 45\({}^{\circ}\) bond force, but the C-type specimen had inefficient concrete shape in order to resist 45\({}^{\circ}\) bond force. Moreover, the C-type specimens had thinnest inner cover thickness at the loaded end where high bond stress occurs. Thus, as shown in Figure 9, a splitting crack was generated at the transition region of the free end, and the concrete became spall due to the vertical component force that occurred at the rib of the deformed steel bar. These results indicate that when the inner cover thickness was insufficient, the bond stress-slip relationship varied according to the bond regions. Thus, the bond strength of the donut-type voided slab should be calculated by region considering the bond characteristics according to the inner cover thickness.  
Figure 7: Crack patterns. (**a**) Inner cover thickness: 0 mm; (**b**) Inner cover thickness: 10 mm; (**c**) Inner cover thickness: 26 mm.
###### Abstract  
Swirling impinging jet (SI) is considered as an effective means to achieve uniform cooling at high heat transfer rates, and the complex flow structure and its mechanism of enhancing heat transfer have attracted much attention in recent years. The large eddy simulation (LES) technique is employed to analyze the flow fields of swirling and non-swirling impinging jet emanating from a hole with four spiral and straight grooves, respectively, at a relatively high Reynolds number (Re) of 16,000 and a small jet spacing of H/D = 2 on a concave surface with uniform heat flux. Firstly, this work analyzes two different sub-grid stress models, and LES with the wall-adapting local eddy-viscosity model (WALEM) is established for accurately predicting flow and heat transfer performance of SIJ on a flat surface. The complex flow field structures, spectral characteristics, time-averaged flow characteristics and heat transfer on the target surface for the swirling and non-swirling impinging jets are compared in detail using the established method. The results show that small-scale recirculation vortices near the wall change the nearby flow into an unstable microwave state, resulting in small-scale fluctuation of the local Nusselt number (Nu) of the wall. There is a stable recirculation vortex at the stagnation point of the target surface, and the axial and radial fluctuating speeds are consistent with the fluctuating wall temperature. With the increase in the radial radius away from the stagnation point, the main frequency of the fluctuation of wall temperature coincides with the main frequency of the fluctuation of radial fluctuating velocity at x/D = 0.5. Compared with \(0^{\circ}\) straight hole, \(45^{\circ}\) spiral hole has a larger fluctuating speed because of speed deflection, resulting in a larger turbulence intensity and a stronger air transport capacity. The heat transfer intensity of the \(45^{\circ}\) spiral hole on the target surface is slightly improved within 5-10%.  
swirling impinging jet; flow structures; heat transfer; large eddy simulation +
Footnote †: journal: Applied Sciences