esa-sceva/satcom-chunk-collection huggingface dataset:
# Finding Hamiltonian and Longest \((s,t)\)-Paths of \(C\)-Shaped Supergrid Graphs in Linear Time
Note that rectangular grid graphs are not Hamiltonian connected. [PERSON] et al. [19] gave sufficient conditions for a grid graph having a Hamiltonian cycle, and proved that all grid graphs of positive width have Hamiltonian line graphs. Later, [PERSON] et al. [20] improved the Hamiltonian path algorithm of [18] on rectangular grid graphs and presented a parallel algorithm for the Hamiltonian path problem with two given endpoints in rectangular grid graphs. In addition, there is a polynomial-time algorithm for finding Hamiltonian cycles in solid grid graphs [21]. However, the Hamiltonian problems are still open for solid supergrid graphs. In [22], [PERSON] introduced alphabet grid graphs and determined classes of alphabet grid graphs which contain Hamiltonian cycles. Supergrid graphs first appeared in [16], and the authors proved that the Hamiltonian cycle and path problems on general supergrid graphs are NP-complete, and every rectangular supergrid graph always contains a Hamiltonian cycle. Recently, the Hamiltonian connectivity of \(L\)-shaped supergrid graphs has been verified in [17]. Note that \(C\)-shaped supergrid graphs contain \(L\)-shaped supergrid graphs as their subgraphs. Thus, the results of \(L\)-shaped supergrid graphs can not be directly applied to \(C\)-shaped supergrid graphs. However, the results in [17] will be used in our method. In this paper, we will consider the Hamiltonian, Hamiltonian connectivity, and longest path of \(C\)-shaped supergrid graphs. The rest of the paper is organized as follows. In Section 2, some notations, observations, known results, and one special Hamiltonian connected property of a special rectangular supergrid graph are given. In Section 3, we give the necessary and sufficient conditions for the Hamiltonian and the Hamiltonian connected \(C\)-shaped supergrid graphs. This section shows that \(C\)-shaped supergrid graphs are always Hamiltonian and Hamiltonian connected except for a few conditions. In Section 4, we present a linear-time algorithm to compute the longest path between any two distinct vertices in a \(C\)-shaped supergrid graph. Finally, a conclusion is given in Section 5.
## 5 Experiments and Evaluation
### Performance Evaluation  
Using the datasets described above, Table 4 shows the performance comparison of a linear model of a baseline model that only used a [CLS] token and the BiLSTM model that used syllable vectors. The linear model, which is most frequently used in binary classification problems, was configured with two layers of FCNN and softmax layers and only used a [CLS] token of KoCharELECTRA as an input for a linear layer. In the BiLSTM model, which is proposed in this paper, only syllable vectors were used as inputs without using a [CLS] token.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Datasets** & **Test 1-1** & **Test 1-2** & **Test 2** & **Test 3** \\ \hline \multirow{2}{*}{Training} & AI FactChecknet & +AI FactChecknet & +COVID \\  & (training data) & (test data) & (training data) \\ \hline \multirow{2}{*}{Test} & AI FactChecknet & COVID & COVID \\  & (test data) & (test data) & (test data) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Dataset configurations for transfer learning.  
Accuracy, which is most widely used in classification problems, is used as an evaluation metric. The accuracy represents the number of correctly predicted samples among all samples.  
In test 1-1 where the model was trained with large-scale fake news data and the performance was evaluated using the AI FactChecknet test data, the accuracies of the linear model and BiLSTM were 59.34% and 60.54%, respectively, in which BiLSTM slightly outperformed.  
Similarly, in test 1-2, the accuracy of the proposed model was higher when the performance was evaluated using the small amount of the collected COVID-19 dataset. In test 2, a higher accuracy was measured for both the linear and proposed models compared to test 1-2. This result indicates that performance improves when trained with a large amount of data. In addition, the performance was significantly improved when a greater amount of data was used in the BiLSTM model compared to the linear model.  
Test 3 reflected the performance when transfer learning was performed with the COVID-19 dataset for the model in test 2. The accuracies of the linear model and the BiLSTM models were 70.70% and 74.51%, respectively, thus demonstrating a significant improvement in both models.  
When the accuracies of test 1-2 and test 3 were compared, pre-training with large-scale data and then performing transfer learning with a small amount of data can contribute significantly to performance improvement. Furthermore, performance was more outstanding in the BiLSTM model, which only used syllable vectors, compared to the linear model, which used only a [CLS] token of KoCharELECTRA.
## 3 Results and Discussion
### Partial Correlation Matrix among PMs of Gangneung (G) and PMs of Beijing (B)

Table 1: Multiple correlation coefficients and predictive regression equations among PMs of Gangneung city (G) with PMs of Beijing city (B) under the influence of meteorological parameters. T, W and RH denote air temperature (\({}^{\circ}\)C), wind speed (m/s) and relative humidity (\(\%\)). In particular, the air quality of Gangneung city during the dust period becomes seriously worse due to the huge amounts of transported dusts (mainly composed of coarse particles larger than 2.5 \(\upmu\)m in diameter) from the Gobi Desert passing through Beijing city, as shown in Figure 2. Correlation coefficients of PM\({}_{10}\) between PM\({}_{2.5}\) and PM\({}_{1}\) at Gangneung city are high with 0.913 and 0.854 (before the dust period), 0.725 and 0.689 (during the dust period), 0.732 and 0.709 (after the dust period), and 0.767 and 0.685 (all periods). PM\({}_{10}\), PM\({}_{2.5}\) and PM\({}_{1}\) at Gangneung during the dust period are highly correlated with PM\({}_{10}\) at Beijing with 0.407, 0.567 and 0.574, in contrast to other periods. It means that when PM\({}_{10}\) of Beijing increased, those concentrations of Gangneung also increased. As a result, the effect of PM\({}_{10}\) of Beijing city exists, when the PMs of Gangneung increases. However, both PM\({}_{2.5}\) and PM\({}_{1}\) concentrations of Gangneung were still positively influenced by PM\({}_{2.5}\) of Beijing, except for PM\({}_{10}\), having a negative sign. From the above statement, the long-distance transport of dust particles from Beijing, China to Gangneung, Korea is very significant to the variation in the air quality of Gangneung.
## 3 Results and Discussion
### Radiation Patterns  
Figure 10 illustrates the simulated and measured radiation patterns of the proposed antenna at resonating frequencies for various switching states. For all resonating frequencies, the antenna exhibits an omnidirectional radiation pattern in principle H-plane (\(\theta=90^{\circ}\)). On the other hand, for all resonating frequencies, the antenna exhibits a monopole like bi-directional radiation pattern in principle E-Plane (\(\theta=0^{\circ}\)). Moreover, it is observed for all switching states that the proposed antenna shows good agreement between simulated and measured results.  
Figure 10: Simulated and measured radiation patterns for case-00: (**a**) 2.24 GHz (**b**) 2.74 GHz (**c**) 3.71 GHz.  
Figure 9: Simulated and measured results of S\({}_{11}\): (**a**) case-11 (**b**) case-01 (**c**) case-10 (**d**) case-00.
## 2 Related Work
### Network Slicing and Machine Learning for Resource Management  
SDN-enabled solutions for enhancing network flexibility and scalability in next-generation IoT and VANETs include Machine Learning (ML) frameworks, that utilise the SDN Controller API for centralised resource management. The comprehensive survey conducted in [17] effectively captured the various applications of Artificial Intelligence (AI) and ML in next-generation networks, including techniques for traffic and load prediction, congestion control, traffic flow, QoS, and resource management. Network slicing is the key SDN principle driving innovation for SDN and AI-based solutions, enabling the deployment of Virtualised Network Functions (VNFs) for enhanced network scalability and flexibility. A network slice is a customised portion of a network, deployed to fulfil the specific requirements of a particular use case. This provides an avenue to deploy several logical segments that may be isolated on a shared infrastructure.  
Flow-prioritisation techniques were applied in [18] to classify traffic flows, via the SDN controller, into bandwidth-intensive and priority queues to enable dynamic resource allocation, achieving an accuracy of approximately 93%, 95%, and 99% for the deep learning models Deep Neural Network (DNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), respectively. LSTM and Q-Learning algorithms were also applied in [19] to address the resource allocation decision problem in VANETs, with a maximum accuracy of approximately 88%. Similarly, a Multi-Layer Perception (MLP) neural network was applied in [7] to predict offloading success across a Wireless Local Network (WLAN) 802.11 p, and RSU (Road-Side Unit) and cellular Long-Term Evolution (LTE) networks. The MLP classifier achieved an accuracy of 81% for edge offloading due to the overutilisation of edge servers.
# Wideband Eight-Antenna Array Designs for 5G Smartphone Applications
###### Abstract  
This paper proposes a broadband eight-antenna array design suitable for Fifth Generation New Radio (5G NR) smartphone applications. To cover the 5G NR bands n77/n78/n79 (3300-5000 MHz) and 5G NR-U m46 band (5150-5925 MHz), the single antenna array unit applied is a modified loop antenna element (MLAE) that can generate three different loop modes. To yield good multi-input multi-output (MIMO) performances, the designed MLAE is further arranged as an eight-antenna array, and the experimental results show that the overlapping 6 dB bandwidth can cover the bands-of-interest (3300-5925 MHz) with good isolation and total efficiency of >10 dB and 51-84%, respectively. Finally, good MIMO performances, such as an envelope correlation coefficient (ECC) of lower than 0.1 and desirable channel capacity (CC) of 37-40 bps/Hz, were calculated across the bands-of-interest.  
antenna array; 5G smartphone; 5G NR band Article
# Enhancement of EPR Effect for Passive Tumor Targeting: Current Status and Future Perspectives
## 5 Enhancing the EPR Effect
### Pharmacological Strategies  
#### 5.3.1 Vascular Normalization  
In the realm of cancer treatment, one classical approach involves the use of antiangiogenic agents to disrupt the blood supply to tumors, thereby cutting off oxygen and nutrients. While this strategy aims to starve tumors, its effectiveness as a standalone treatment has been limited in clinical practice. Recent studies have explored the concept of vascular normalization, which seeks to restore the structure and function of tumor vasculature, thereby improving drug delivery and therapeutic outcomes.  
[PERSON] et al. demonstrated that vascular normalization could be achieved using moderate doses of anti-VEGF receptor antibodies. This approach reduced necrotic and hypoxic areas within tumors, leading to a more uniform distribution of therapeutic agents. By normalizing the tumor vasculature, the study highlighted the potential for improved drug penetration and efficacy [187].  
Another promising strategy involves the use of tyrosine kinase inhibitors (TKIs), a class of small molecules that target specific signaling pathways involved in angiogenesis. For instance, erlotinib, a TKI targeting the epidermal growth factor receptor (EGFR), has been shown to enhance the accumulation of human serum albumin-bound paclitaxel in various tumor models. This improvement in drug delivery is attributed to the normalization of tumor vasculature, which facilitates the enhanced permeability and retention (EPR) effect [188].  
Imatinib, another TKI that inhibits VEGF-independent angiogenesis, has also been investigated for its ability to promote vascular normalization. In studies involving A549 lung carcinoma, imatinib was found to increase the accumulation of nanomedicine within tumors, further underscoring the potential of TKIs in enhancing EPR-mediated drug delivery and improving therapeutic outcomes [188].
# 3D Stress Analysis of Multilayered Functionally Graded Plates and Shells under Moisture Conditions
## 5 Conclusions  
The authors proposed a closed-form 3D shell solution that handles the hygro-elastic stress analysis of plates, cylinders, cylindrical shells, and spherical shells while embedding Functionally Graded Material (FGM) layers. First, the author imposed the external moisture content on the top and the bottom surfaces. The moisture conditions act in steady state as an external load; calculating the moisture content profile is a prerequisite. The authors showed that three approaches might be used to determine the moisture content profile along the thickness direction and coupled them with a consolidated elastic solution. The results demonstrated the importance of a correct moisture content profile evaluation in the thickness direction. The 3D Fick's law of diffusion is the only way to obtain exact results when the structures embed FG layers; it is also necessary when the structures are sufficiently thick. On the other hand, the 1D Fick's law of diffusion comes closer to it only when structures are thin; as a rule of thumb, the results of the two models are almost coinciding only from a thickness ratio of 50. The problem relies on a set of differential equations in the thickness direction. The authors demonstrated that the exponential matrix method is a reliable way to solve it, provided that the structures are divided into a sufficiently high number of mathematical layers. This layer-wise approach is critical to get a reliable description of the material properties grading; as a rule of thumb, 300 mathematical layers always deliver the correct results. This achievement is general and does not depend on the geometry, FGM law, and lamination sequence/scheme.
# Enhanced Efficient EMT-Type Model of the MMCs Based on Arm Equivalence
###### Abstract  
The large number of switching elements in modular multilevel converters (MMCs) contribute a tremendous computational burden for electromagnetic transient (EMT) simulation programs. Detailed equivalent models (DEMs) and average value model (AVMs) are currently two major types of accurate and efficient model. However, the DEMs are still computationally inefficient for the simulation scenarios in large-scale MMC based high-voltage direct current (MMC-HVDC) grids, as the models represent all submodule (SMs) switching events, and memorize all individual capacitor voltages. Though the AVMs provide a faster simulation speed by using a single equivalent capacitor on the DC side, they have a relatively low simulation accuracy compared to DEMs, especially under blocked mode. This paper proposes an enhanced computationally efficient model based on arm equivalence (AEM), which can accurately represent the dynamic behaviors in both de-blocked and blocked modes. Compared to the DEMs, the proposed AEM is more efficient, with no loss of accuracy, and the simulation speed is irrespective of the SM number. The accuracy and computational efficiency of the proposed model were validated against the DEM and AVM through several simulation scenarios in a two-terminal MMC-HVDC system on the power systems computer aided design/electromagnetic transient in DC system (PSCAD/EMTDC) program.  
Keywords:modular multilevel converter (MMC); electromagnetic transient (EMT) simulation; detailed equivalent model (DEM); average value model (AVM); arm equivalence +
Footnote †: journal: Applied Sciences
## 4 Conclusions  
Recently, exosomes are considered as significant mediators in intercellular communication. The exosomes' ability to transport DNA, proteins, non-coding RNAs, and mRNA, makes them an attractive target of research on the pathogenesis of several illnesses, including cardiovascular and autoimmune disease, cancer, obesity, etc. MSC and other cell type-derived exosomes play an important role in intercellular communication by using several neurotrophic factors, protein, and genetic materials to axons, and they can inhibit the issues resulting from stem cell transplantation. The involvement of exosomes in both biological and pathobiological functions makes them an interesting organelle, and hence it is interesting to study their potential biological applications in the treatment of diverse diseases and offer new possibilities in the amelioration and possible cure of some infectious and non-infectious diseases. Furthermore, results from both clinical and experimental studies on MSC-derived exosomes have shown their potential in the treatment of diverse diseases. However, future research must concentrate on improving the methods for the isolation of exosomes and other EVs to distinguish them appropriately, as well as their mechanism of action, before they are used in clinical studies. Success in this regard will promote their prompt application in the diagnosis, prevention, and treatment of diseases.  
Conceptualization, A.M.B., G.E.-S.B., and T.E.O.; methodology, A.M.B., G.E.-S.B., N.R.-P., and A.Z.-B.; software, A.M.B., and G.-E.-S.B.; validation, A.M.B., G.E.-S.B., T.E.O., N.R.-P., H.F.H., M.Z., S.A., and A.Z.-B.; formal analysis G.E.-S.B., and T.E.O.; investigation, A.M.B., G.E.-S.B., T.E.O., N.R.-P., H.F.H., M.Z., S.A., and A.Z.-B.; data curation, A.M.B., G.E.-S.B., M.A.G., and A.K.M.; writing--original draft preparation, A.M.B., T.E.O., and G.-E.-S.B., writing--review and editing, A.M.B., T.E.O., G.E.-S.B., N.R.-P., and A.Z.-B.; visualization, A.M.B., G.E.-S.B., N.R.-P., A.Z.-B., M.A.E.-E.; supervision, A.M.B., G.E.-S.B., and H.F.H.; funding acquisition, S.A., H.F.H., and M.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Graphical abstract and Figure 1 were made using biorender.com.  
The authors declare no conflict of interest.
# Real-Time, Content-Based Communication Load Reduction in the Internet of Multimedia Things
## 3 Methodology
### System Composition
#### 3.2.3 Load Reduction  
To further reduce the data quantity, JPEG compression [33] is applied on a ROM, whereas an integer-valued indicator (rather than a ROM) is sent to a receiver in the case of little to no change identified across the difference image.  
Thus, in many cases the video frame compression rate, will be the ratio of the original frame size to that of one integer. On the other hand, if there is maximal content change in the video frame (caused by many moving objects) then the compression rate will be equal to that achievable by JPEG compression of the whole frame. In general, however, the compression rate will be proportional to the size of the ROM. In addition, the compression rate within a ROM is also content dependent, according to factors such as the extent of exploitable spatial frequencies present in the ROM for the purpose of JPEG compression. Section 4.2.4 indicates the bit-rates achieved after compression (and before encryption) for varying content. From that Section it will be apparent that the overall compression rate is highly variable according to the content, so that there is no simple descriptor of the compression rate.
# Advancements in Glucose Monitoring: From Traditional Methods to Wearable Sensors
## 4 Non-Invasive Methods
### Reverse iontophoresis
In a notable study by [PERSON] et al., an innovative biofuel cell-based sensor has been presented that combines flexible enzymatic biofuel cells (EBFCs) with a power management system (PMS) circuit, for glucose detection in urine and serves as an alarm device for diabetic patients [91]. While reverse iontophoresis shows great potential for non-invasive glucose monitoring, several challenges need to be addressed for its practical application in clinical settings, particularly sensors and algorithms. Since the concentration of target substances extracted through reverse iontophoresis is typically lower than that in the bloodstream, more sensitive sensors with lower detection limits are required to detect these low concentrations. Additionally, reverse iontophoresis often requires adhesion to the skin for extraction. Given that human skin is a curved surface, rigid devices face challenges due to deformation, which can lead to significant measurement errors. Therefore, flexible sensors need to be more advanced, in order to adapt the skin deformation. Moreover, the concentration of target substances in the extracted interstitial fluid (ISF) does not match that in the blood, making it essential to understand and establish a relationship model between these concentrations [92]. This will enable the conversion of ISF measurements into accurate blood glucose levels [93]. However, this conversion is complicated by microcirculation variability, and the exact quantitative relationship remains unclear. Thus, suitable algorithms need to incorporate both advancements in computational science and a better understanding of human physiology. Furthermore, environmental factors such as temperature can influence reverse iontophoresis performance, necessitating further research to refine the extraction process and improve the algorithms used to adjust for these variations.
## 3 Results and Discussions
### Model Validation  
To assess the reliability of the results of geometric parameter optimization and validation of the numerical model, a series of additional CFD calculations were performed for the configuration that showed the best aerodynamic characteristics according to the Taguchi method: rotor diameter D = 3 m, chord length c = 0.4 m, number of blades N = 4. Verification modeling was carried out at different values of the speed coefficient \(\lambda\) in the range from 0.2 to 2.8, with a step of 0.2. This range was chosen by analogy with the work of [PERSON] et al. [22], where similar calculations were performed for a three-bladed wind turbine with a chord length of c = 0.3 m. Despite the difference in the number of blades, the use of a comparable range of \(\lambda\) allows an objective comparison of the nature of the change in the power coefficient Cp and a qualitative validation of the model.  
Based on the values of the torque coefficient Cm obtained because of CFD modeling for the steady-state last revolution, using Equation (3), the dependence \(C_{\mathrm{p}}=f(\lambda)\) was constructed, reflecting the efficiency of converting the kinetic energy of the flow into mechanical energy under different rotor rotation modes.  
Figure 17 shows a comparison of the dependence of the power coefficient \(C_{\mathrm{p}}\) on the speed coefficient \(\lambda\) for an optimized configuration of a vertical-axis wind turbine with four blades (rotor diameter D = 3 m, chord length c = 0.4 m) and a numerical model from the work of [PERSON] et al. [22] for a three-bladed wind turbine with a similar diameter and chord length c = 0.3 m. Both curves demonstrate a characteristic dependence: with an increase in the speed coefficient, an increase in \(C_{\mathrm{p}}\) is observed, reaching a maximum in the region of \(\lambda\) = 2.0-2.2, after which the efficiency decreases. The \(C_{\mathrm{p}}\) values obtained in this work are lower by \(\sim\)10% compared to the model by [PERSON] et al. [22], which is due to the increase in total resistance with a four-blade layout. At the same time, the behavior of the curve as a whole remains consistent with the literature data, which confirms the physical correctness and realism of the performed CFD modeling.  
Figure 16: S/N analysis using Taguchi method for 20 wind turbine configurations.