esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Work
### Model Architecture Components  
#### 2.2.1 Long Sequence Processing Architectures  
The standard Transformer architecture's self-attention mechanism has quadratic complexity (\(O(n^{2})\)) [5], limiting its ability to process long sequences. This computational bottleneck has motivated extensive research into alternative architectures capable of handling extended contexts more efficiently. Researchers have explored sparse attention patterns [30], recurrence mechanisms, and sliding windows with global attention to address this limitation. However, these approaches still face efficiency-performance trade-offs with extremely long sequences.  
Novel architectures like Hyena Hierarchy [19] use implicitly parameterized long convolutions and data-controlled gating [5] to achieve sub-quadratic complexity (\(O(n\log n)\)). The Hyena architecture represents a significant departure from attention-based mechanisms, instead leveraging gated convolutions with learnable kernels to capture long-range dependencies. This approach demonstrates particular promise for processing financial documents, where maintaining complete contextual information across entire documents is crucial for accurate interpretation. These architectures effectively handle sequences far beyond traditional models' limits while maintaining or surpassing Transformer performance [19; 31]. This technological advancement enables the direct processing of lengthy central bank reports, motivating our choice of Hyena as the model's backbone.
# Wireless Energy Harvesting for Internet-of-Things Devices Using Directional Antennas
## 5 Simulation Results
### Comparative Performance Evaluation
#### 5.3.1 Different Number of Devices  
We show the charging time of different schemes for different numbers of devices in Figure 10 by setting the transmission angle to 90 degrees and the offset value to 10. The results show that the proposed greedy algorithm has the shortest charging time compared to other methods. We also observe that the charging time of the DE method is slightly worse than that of the greedy algorithm for different numbers of devices. The charging time of the Fix method increases as the number of devices increases, where the charging time is about 60 s for different number of sensor devices. The RAN method may arbitrarily select a transmission direction to result in charging some devices that have been fully charged. The RR method has a similar problem to the RAN method. Both the RAN and RR methods suffer from a high charging time regardless the number of devices mainly because of the poor charging efficiency for those distance devices.  
We show the performance of the overflow energy for different methods in Figure 11. The overflow energy is related to the charging time and the selected transmission directions. The Fix method results in the most overflow energy for 50 devices because the devices are more distant. Both RAN and RR methods lead to a higher amount of wasted energy because of redundant charging. The RR method slightly outperforms the RAN method because the RAN method repeatedly charges devices. Both the proposed greedy and DE algorithms outperform the other methods. Although the DE algorithm requires a slightly longer charging time than the proposed greedy algorithm in Figure 10, it achieves the least overflow energy. In particular, the DE algorithm improves the overflow energy of the greedy algorithm by 12.9%, 9%, and 7.8% for 30, 40, and 50 devices. The improvement decreases as the number of devices increases because having more devices in a sector may result in more devices with overflow energy. We believe that the tradeoff between a slightly longer charging time and less overflow energy is reasonable.
# UAV-Based Privacy-Preserved Trustworthy Seamless Service Agility for NextG Cellular Networks
## 4 Privacy-Preserved Trustworthy Seamless Service Agility
### UAV/Guest eNB Mutual Authentication  
Next, the UAV must authenticate itself to the guest service provider, the eNB/gNB guest network, and vice versa using the following Challenge-Response Authentication Process as follows,  
* The UAV \(D_{i}\) sends a service providing request including its proxy signature tuple \((\sigma_{i}|_{T_{2}},r_{i},w_{i},yp_{i},DID)||T_{2}\) to the eNB/gNB guest network, where \(DID\) is the UAV ID (aka, Drone ID) registered within the guest network by its \(y_{i}\).
* Then, the eNB/gNB validates the signature (i.e., the home network delegation warrant \(w_{i}\)) using \((r_{i},yp_{i},y_{i})\) and \(T_{2}\).
* Next, the eNB/gNB guest network responds with an authentication response containing an encrypted version of the released delegation warrant \(w_{ACK}\) along with the home network core token (\(TTK_{2}\)) and the eNB/gNB guest network ID (\(eNBID\)) as \(E_{y_{i}}(w_{ACK},eNBID)\).
* The UAV confirms \(TTK_{2}\), then register the \(eNBID\).
## 3 Modeling Method Validation through a Test Rotor  
In order to verify the modeling method proposed in this paper, a rotor with both conical and cylindrical structures was designed, as shown in Figure 5. The dynamic model of the test rotor is established with 10 main elements, as shown in Figure 5a. The  
Figure 4: Assembly process for the total matrices after Guyan DOF reduction.  
frequency response function of the test rotor is obtained by hammering method under approximately free boundary conditions (see Figure 5b). A comparison between the tested and the calculated results for the first three natural frequencies is shown in Table 1. The first three modes are cylindrical mode, conical mode, and bending mode, respectively. It can be seen from Table 1 that the calculated results agree well with those of the tested, and the maximum relative error is within 3.2%, which shows that the modeling method is correct and reliable.  
To further verify the effectiveness of the proposed modeling method for complex rotors, response simulation and corresponding vibration tests were carried out. As shown in Figure 6, the test rotor is driven by a three-phase AC motor controlled by a frequency converter, with rolling bearings at both ends (Model: UCP205). The vibration signal of the bearing seat was collected by a piezoelectric acceleration sensor (sensitivity: 98.1 mV/g), and the rotor rotation pulse signal was collected by the combination of a non-contact photoelectric sensor and reflector. In order to simulate the unbalance force caused by blade loss, a screw was added to the hole corresponding to node 4. Within the speed range of 1000-3000 r/min, the vibration response was measured at an interval of 100 r/min, and the amplitude of the steady-state response at every speed was taken to obtain the amplitude-frequency response curve, which is compared with the simulation result, as shown in Figure 7. It can be seen from the comparison of the response curves that the simulation and test results show the same trend of vibration with rotation speed, and the difference between them is small. The amplitude difference between simulation and test results is because the test rotor has a certain residual imbalance caused by machining  
\begin{table}
\begin{tabular}{c c c c} \hline
**No.** & **Simulation Result (Hz)** & **Experimental Value (Hz)** & **Relative Error (\%)** \\ \hline
1 st order & 413 & 402 & 2.74 \\
2 nd order & 1164 & 1146 & 1.57 \\
3 rd order & 5839 & 5768 & 1.23 \\ \hline \end{tabular}
\end{table}
Table 1: The first three natural frequencies.  
Figure 5: The test rotor for the modal test. (**a**) Rotor model. (**b**) Rotor test bench.  
and assembling in addition to the unbalance screw applied, which is only applied on the simulated model.
## 3 Results
### Relationship Between NDVI (800, 1200) and AGB  
We used linear and nonlinear regression analysis to investigate NDVI (800, 1200) with AGB. Table 6 indicated that the nonlinear regression models that are based on NDVI (800, 1200) performed well at four different growth stages; NDVI (800, 1200) had a good correlation with the AGB of WOR. The determination coefficients \(\mathrm{R^{2}_{cal}}\) and \(\mathrm{R^{2}_{val}}\) were greater than 0.60, the values of RMSEC and RMSEV varied from 622.82 to 2944.28 kg/hm\({}^{2}\), and the ratio of prediction to deviation (RPD) are distributed between 1.45 and 1.99. Most red and near-infrared-based spectral VIs (NDVI, SAVI) had a low correlation with AGB at the flowering and pod stages. However, NDVI (800, 1200) was highly correlated with AGB at the flowering and pod stages, and the two effective wavelengths (800 nm and 1200 nm) proved to have good fitting characteristics in estimating AGB.
## 4 Evolution of Cadmium Transporters and Their Functions in Cadmium Accumulation
### Function of Cd Transporters
#### 4.2.6 ABCCs  
The family of ABC proteins is one of the largest in organisms [139] and has various substrates, including carbohydrates, lipids, xenobiotics, antibiotics, drugs, and heavy metals [140]. Unlike NRAMP3/4, HMA3, and CAX2/4, which transport free Cd\({}^{2+}\) ions, ABCCs transport Cd-PC complexes [141]. In Arabidopsis plants, AtABCC1 and AtABCC2 are responsible for the transport of Cd-PCs into the vacuoles [82]. Likewise, AtABCC3 has been suggested to mediate the transport of Cd-PC complexes [142; 143]. Apart from ABCCs, other ABC transporters also confer Cd tolerance. AtABCG36/AtPDR8, a member of the pleiotropic drug resistance (PDR) subfamily of ABC transporters in Arabidopsis plants, has been suggested to play a role in Cd tolerance by pumping Cd\({}^{2+}\) or Cd complexes out of root epidermal cells [144]. AtATM3, which belongs to the mitochondria subfamily of Arabidopsis ABC proteins, contributes to Cd tolerance by mediating the transport of glutamine synthetase-conjugated Cd across the mitochondrial membrane [145]. In rice, OsABCG36/OsPDR9 has been recently demonstrated to be involved in Cd tolerance through exporting Cd\({}^{2+}\) or Cd conjugates from the root cells [146].
## 8 Conclusions  
This study introduced an enhanced Hybrid Genetic Algorithm (HGA) for optimizing sales routes, integrating Adaptive Mutation, Tabu Search, and an LSTM-based travel time prediction model. The experimental results demonstrated that the proposed approach significantly improves route efficiency while maintaining adaptability to real-time conditions. The GAAM-TS variant consistently outperformed the Standard GA and GA-AM, reducing total travel distance and delivery time while preserving higher population diversity and achieving superior convergence. The LSTM-based component enabled the dynamic adjustment of routes based on real-time traffic conditions, making the approach suitable for realistic, time-sensitive logistics scenarios.  
Although GAAM-TS exhibited the best optimization performance, it incurred a significantly higher computational cost. In contrast, GA-AM provided a favorable balance between computational efficiency and solution quality, making it more suitable for applications with time or resource constraints.  
From a practical standpoint, the proposed algorithm can be deployed in a variety of logistics contexts, including last-mile delivery optimization, fleet dispatch management, and territory planning for field sales representatives. Its adaptability makes it applicable to industries such as e-commerce logistics, urban courier services, and retail distribution networks where route efficiency and traffic responsiveness are essential.  
Future research should focus on enhancing the computational scalability of the algorithm through parallel processing techniques, including GPU-accelerated batch evaluations and distributed population management. Another promising direction is the integration of reinforcement learning or graph-based neural models to guide mutation or crossover decisions adaptively. Additionally, future work should investigate multi-objective optimization strategies to simultaneously minimize operational costs, emissions, and time, aligning with the broader goals of sustainable logistics systems.  
All authors contributed equally to this work. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Data Availability Statement:** The datasets and source code used in this study are publicly available at [[https://github.com/cristianzambrano/HGA-SalesRouteOptimization](https://github.com/cristianzambrano/HGA-SalesRouteOptimization)]([https://github.com/cristianzambrano/HGA-SalesRouteOptimization](https://github.com/cristianzambrano/HGA-SalesRouteOptimization)) (accessed on 25 April 2025).  
**Acknowledgments:** The authors would like to express their gratitude to the State Technical University of Quevedo for the support provided throughout this research. Their continuous encouragement and resources have been invaluable in the development of this study.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 3 Results and Discussion  
### Analysis of Tocopherol Isoforms by NP-HPLC-UV-Vis  
The chromatographic method based on HPLC-UV-Vis with a normal-phase column provided a suitable separation and resolution of the four locopherol isoforms with retention times of 5.04, 6.38, 6.73, and 8.70 min for \(\alpha\)-, \(\beta\)-, \(\gamma\)-, and \(\delta\)-tocopherols, respectively (Figure 2), showing a better performance than reversed-phase columns where \(\beta\)- and \(\gamma\)-tocopherols usually coelute and cannot be identified separately [25; 26]. The assessment of linearity in the range of 10 to 375 \(\upmu\)g/mL, LOD, and LOQ, as well as the intra-day and inter-day precision, are shown in Table 1.  
Figure 2: HPLC–UV–Vis chromatogram of standards of the four locopherol isoforms (600 ppm each) measured at \(\lambda\) = 292 nm.  
All tocopherol isoforms exhibited an excellent linear response in the assayed range according to the R\({}^{2}\) values. LOD and LOQ were in the ranges 0.32-0.63 and 1.08-2.11 ppm, respectively, for the four tocopherol isoforms, which are close to the values reported in previous works using HPLC-DAD as a chromatographic method for tocopherol analysis. [PERSON] et al. reported an LOD between 0.50 and 0.60 ppm and an LOQ between 1.5 and 2.0 ppm for different tocopherol isoforms (detection wavelength of 290 nm) [27], and [PERSON] et al. found an LOD between 0.20 and 0.35 ppm and an LOQ between 1.00 and 1.75 ppm (detection wavelength of 296 nm) [28]. Other studies have reported lower LOD and LOQ values for tocopherol isoforms when using fluorescence detection (FLD), such as [PERSON] and [PERSON] (LOD of 0.006-0.007 ppm, LOQ of 0.019-0.023 ppm) [29], and [PERSON] et al. (LOD of 0.014-0.039 ppm and LOQ of 0.019-0.099 ppm) [30], due to the higher sensitivity of FLD compared to DAD or UV-Vis detectors. However, DAD and UV-Vis detectors are much more common in HPLC instrumentation than FLD due to their high versatility and applicability to the analysis of bioactive compounds such as sterols, carotenoids, organic acids, and vitamins in food matrices, in addition to their reliability and cost-effectiveness. Therefore, DAD and UV-Vis detectors are commonly used in many laboratories for tocopherol analysis [31].  
The precision values were less than 15% for all of the assayed concentrations, which fits the acceptable limit for precision set by the Food and Drug Administration (FDA) [32]. This demonstrates that the method tested in this work is reliable for identifying and quantifying the four tocopherol isoforms.
# Benchmarking Anomaly Detection Methods for Extacardiac Findings in Cardiac MRI
## 3 Materials and Methods
### Dataset Pre-Processing  
Since the CMR dataset comprises multiple anatomical sequences, images were first organized by view. Subsequently, all images were min-max normalized and saved in PNG format, accompanied by their respective foreground and ground truth (GT) masks. The foreground mask was generated by applying a thresholding operation to roughly identify the body, followed by a morphological closing operation to fill inner holes and keeping only the largest connected component. Regarding the GT mask, since classifying the specific type of ECF was not a focus of this study, all segmentation maps were merged into a single binarized mask. Images containing at least one abnormal pixel were labeled as abnormal.  
Since AD methods are often designed for datasets with low-resolution images, such as MvTec-AD [29; 25; 27; 28; 29; 30; 31; 33] or MNIST [30], an image size of 128 \(\times\) 128 pixels was adopted to streamline architecture and hyperparameter tuning. This resolution also improves computational efficiency and ensures compatibility across all benchmarked methods while preserving most image details, including small abnormalities. Most images originally had a resolution of 256 \(\times\) 256 pixels and were resized using Lanczos interpolation, followed by center cropping when necessary. Foreground and GT masks were resized using nearest-neighbor interpolation.  
To ensure robust evaluation, each view subdataset was randomly split five times into training, validation, and test subsets in a patient-disjoint manner. Since the benchmark includes supervised, semi-supervised, and unsupervised methods, both normal and abnormal images were included in all subsets. Balanced evaluation subsets were created by sampling an equal number of normal and abnormal images for both validation and test subsets (100 and 500 each in the validation and test subsets, respectively). The remaining available images from unsampled patients were assigned to the training subset. Additionally, the distribution of samples across subsets was qualitatively assessed, and the sampling process repeated until similar abnormality class prevalence was achieved across subsets. Importantly, normal images from abnormal sequences were excluded from all subsets to prevent the unintentional inclusion of subtle abnormal patterns in otherwise visually normal images. Consequently, normal images were only sampled from sequences entirely free of abnormalities.  
Figure 2: Frequency of each ECF subtype relative to the total number of images in each subdataset.
# Practical Performance Analysis of Interference in DSS System
## 2 Motivation and Contribution  
Facing the long-term coexistence of 4G and 5G, DSS technology can dynamically share the spectrum between 4G and 5G as an effective transition solution, offering the possibility of stable evolution from 4G to 5G. However, DSS will introduce intra-frequency interference between inter-systems in the network, which seriously affects the user experience.  
The main contributions of this paper are summarized as follows:  
* The interference between 4G and 5G DSS was not addressed, and they have not been tested and validated in commercial networks.
* We have innovatively proposed two interference solutions: buffer setting and rate matching, and performed a theoretical analysis and field validation for the first time ina real commercial 4G/5G coexistence network built based on mainstream equipment vendors.
* The analysis and evaluation of the interference situation and the performance improvement after taking the proposed scheme are provided based on the real-time network performance and the target user experience. This is also the first study in the world to share the 4G/5G DSS interference solution, which is analyzed and verified from both theoretical and experimental perspectives.
## 4 Conclusions  
A sequentially coupled UV/H\({}_{2}\)O\({}_{2}\)-CW was successfully used for the treatment of synthetic cropland wastewater containing malathion. Based on the results, the following points are concluded:  
* In the first stage, the UV/H\({}_{2}\)O\({}_{2}\) system optimization resulted in the removal of most malathion content in a shorter time of period than the reported for other AOP, including those using catalysts. The TOC remaining after this stage was mainly attributed to the formation of byproducts.
* The UV/H\({}_{2}\)O\({}_{2}\)-CW system removed an average of 65% TOC during the first 17 operation days without significant difference (\(p>0.05\)) among the HRTs used in constructed wetlands related to biosorption processes. Nevertheless, the system with the lower HRT value did not increase its efficiency or reach stability over time.
* The UV/H\({}_{2}\)O\({}_{2}\)-CW system operated with 2 and 3 d HRT in CW, reached \(80\pm 6.9\%\) TOC removal, which is equivalent to value achieved by novelty prototypes based on the combination of two or more AOP.
* The overall results demonstrated that CWs planted with native vegetation from cropland and coupled in continuous flow to UV/H\({}_{2}\)O\({}_{2}\) pretreatment is a technically feasible option to treat CropWW containing malathion.
* Future research efforts regarding toxicity, degradation pathways and quantification of other recalcitrant compounds, even at trace levels, are needed to better understand the treatment process.
* Long term evaluation of in situ pilot-scale systems treating real wastewater would be necessary to evaluate the economic feasibility of the large-scale system. An economic comparison between the proposed hybrid system and the conventional advanced oxidation will help to confirm if the one proposed in this research is less costly as is expected.  
C.I.G.C.-H.: Data curation and writing original draft. A.R.-S.: Data curation and conceptualization. A.M.P.-E.: Writing, review and editing. K.R.: Writing, review and editing. J.R.-M.: Data curation and methodology. L.E.A.-S.: Conceptualization, methodology, writing-original draft and project administration. All authors have read and agreed to the published version of the manuscript.  
This research was financially supported by CONACYT projects Problemas Nacionales 2017-1 ID 5020 and is part of Catedras CONACYT Ref. 2572.  
The first and second authors acknowledge the technical facilities provided through to Proyecto interno de la Universidad Tecnologica de Culiacan 2019-2020. Likewise, all authors are grateful for the support given by Asociacion de Usuarios Productores Agricolas El Grande Modulo II-3.  
The authors declare no conflict of interest.
# Vitamin D Regulation of a SOD1-to-SOD2 Antioxidative Switch to Prevent Bone Cancer
## 1 Introduction
There are three forms of SODs, and the localization of the SODs reflect their antioxidative roles within cells. SOD1 is mostly sequestered in the cytosol but can also localize to the mitochondria, SOD2 in the matrix of mitochondria [34], and SOD3 is in the extracellular space [32]. Several regulators of SODs have been characterized. For example, SOD2 is regulated by SIRT3-mediated deacetylation that can attenuate excessive production of mitochondrial ROS under disease conditions [35]. Vitamin D exerts its anti-cancer effects by a variety of mechanisms [7; 10; 36; 37; 38]. However, only a few studies have looked at the role of vitamin D on ROS production and detoxification. For example, a recent paper has shown that supraphysiological levels of calcitriol exerts its anti-tumor effects in a mouse cell model of osteosarcoma via induction of the endoplasmic reticulum stress response with a concomitant increase in intracellular ROS [39]. In addition, cDNA microarray analysis using human prostate epithelial cells revealed that calcitriol (50 nM) can promote SOD2 expression (2.01-fold increase, 24 h) [40], as well as the early expression of the antioxidant thioredoxinin reductase 1 (TXNRD1; 2.8-fold increase, 6 h) [41]. Another cDNA microarray study using androgen-sensitive prostate cancer cells identified a 2.6-fold increase in SOD1 at 10 nM of 1,25D\({}_{3}\) treatment for 24 h [41]. Calcitriol was also found to induce glucose-6-phosphate dehydrogenase (G6 PD) transcription in a VDR-dependent manner within non-malignant prostate cancer cells to maintain NADPH levels for the production the ROS scavenger glutathione [42]. To compliment these studies, the aim of this research was to analyze the potential vitamin D-mediated regulation of the \"SOD1-to-SOD2 switch\" within the MG-63 osteosarcoma model that was recently characterized between non-tumorigenic and tumorigenic breast cancer cells [43]. This work provides insights into mechanisms that govern the anti-neoplastic actions of vitamin D.