esa-sceva/satcom-chunk-collection huggingface dataset:
### Revival of BCG/SCG  
Since 2003, researches related to SCG/BCG technology have sprung up like mushrooms after a spring rain, with the publications of research in large quantities and high frequency, as [PERSON] [27] put it, the year 2003 was \"the starting point for the revival of the BCG/SCG research\".  
One of the highlights of BCG/SCG technology that attracts researchers is its non-invasive characteristics, i.e., the measurement can be done without direct contact with the human body [28; 29]. It can be seen from Figure 3 that this non-invasive sensing  
Figure 2: A schematic of SCG measurement device.  
technology can be mounted on a variety of carriers for measurement. Part a shows a BCG-based chair that using cuffless blood pressure measurement methods that detect the peak pressure via signals measured using photoplethysmogram (PPG) and electrocardiogram (ECG) sensors the pulse transit time (PTT) or pulse wave velocity (PWV) have been studied [30]. Part b shows a BCG-based mattress which had three accelerometers to measure the _ballistocardiogram_ (BCG) [31]. Part c shows an ECG-based weighing scale which measures using dry electrodes R-J intervals were extracted as a BP correlated parameter at every cardiac cycle [32]. Part d shows a BCG-based camera A robust HR measurement method was proposed and, a bidirectional optical flow algorithm is designed to select and track valid features in the video captured by the camera [33]. Part e shows a PPG-based wearable device using a multi-location wireless vital signs monitor and head movement PPG signal [34]. Part f shows portable device placed on sternum reading simultaneously ECG and BCG signals during the flight [35]. BCG/SCG can be used in different application scenarios, such as a ward [36], a hospital waiting room [37], a MRI room [38], or at home [39], for monitoring physical health status.  
Figure 3: Various devices for BCG/SCG measurement.  
Wearable devices can be carried easily in daily life realizing zero load measurement on human body [40]. With the gradual maturity of the technology related to measurement of BCG/SCG signals, the development and production costs have been gradually reduced [41], so as to meet the market demands, and be applied in wider fields such as medical treatment, health, and military applications [42]. The purpose of this study was to review the existing literature by means of bibliometrics, systematically discuss the development and trends of BCG/SCG technology since 2003 worldly, with the emphasis on the progress of the research of application of the technology, and exploration of the realization of the future technology, by analyzing the important research directions, to provide references for the research of BCG/SCG technology in the field of medical, health care and nursing.
## 6 Conclusions  
This study proposed a hybrid anomaly detection framework tailored for Wireless Sensor Networks (WSNs) in forest fire monitoring scenarios. By combining a Transformer-based Autoencoder with Isolation Forest and XGBoost, the model effectively captured temporal patterns and classified anomalies into sensor malfunctions and intrusions with high precision. The integration of adaptive thresholding further enhanced robustness by reducing false positives under varying sensor dynamics. The framework achieved a classification accuracy of 95%, demonstrating its capability to improve the reliability of critical environmental monitoring systems. Unlike conventional methods that focus solely on anomaly detection, our approach emphasizes fine-grained anomaly classification, which is essential for early warning systems and network resilience. Future work will focus on real-world deployment, computational optimization for edge devices, and self-adaptive learning to enable continuous improvement without retraining. Additionally, the proposed architecture has the potential to be generalized across domains such as industrial IoT, disaster prediction, and healthcare monitoring, which we plan to explore through transfer learning strategies.  
Conceptualization, H.S. and A.H.; methodology, A.H. and H.S.; software, A.H.; validation, A.H. and H.S.; formal analysis, H.S. and A.H.; investigation, A.H.; resources, A.H.; data curation, A.H.; writing--original draft preparation, A.H.; writing--review and editing, H.S.; visualization, A.H. and H.S.; supervision, H.S.; project administration, H.S.; funding acquisition, H.S. and A.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The raw data supporting the conclusions of this article will be made available by the authors upon request.  
On behalf of all authors, the corresponding author states that there are no conflicts of interest.
# The Cybersecurity Focus Area Maturity (CYSFAM) Model
As a result of the attention given to cybersecurity, there has been an abundance of scientific research with increasing intensity in this decade. However, little research has been performed in developing a standard-based process improvement framework. The small number of frameworks available are mostly based on the Capability Maturity Model (CMM) [11; 12], but they received some critical remarks; mainly related to implementation costs, applicability, and reliability [13]. Previous scientific work has shown that focus area maturity models (FAMs) have several advantages as improvement frameworks [14]. Furthermore, focus area maturity modelling has been shown to be suitable for developing a valid maturity model ISFAM (Information Security Focus Area Maturity) model [15]. ISFAM focuses on information security capabilities. In this paper, the authors provide a holistic view of all security domains--information security, cybersecurity, network security, application security, etc.--and their relationships. The aim is to propose a comprehensive cybersecurity capability coverage to accompany information security capabilities. The present research aims to answer the following research question: \"How can cybersecurity capabilities for generic organisations be modelled in a focus area maturity model?\" This paper presents the CyberSecurity Focus Area Maturity (CYSFAM) model that was developed using the method presented by [14]. Amongst several existing cybersecurity maturity models, CYSFAM has distinctive characteristics; it is mainly based on international standards and frameworks, it is intended for generic organisations and it is structured as a focus area maturity model--the only cybersecurity focus area maturity model. The present paper contributes to the cybersecurity maturity modeling body of knowledge as a mainly standard-based focus area maturity model for generic organizations. Using CYSFAM, practitioners can assess and improve their cybersecurity capabilities with the help of 144 assessment questions/capabilities categorized into 11 focus areas. The paper presents an overarching approach to cybersecurity that can enable organizations to see the broad view on cybersecurity domain. The analysis and the visual presentation of the dependencies between the capabilities facilitate capability improvement planning. The rest of the paper is organized as follows: first, the related work on security domains, existing information security and cybersecurity maturity models, the concept and design of FAMs, and the ISFAM are introduced. Second, the design science research framework and methodology applied for artifact development are described. Third, CYSFAM is presented. Fourth, the evaluation of the model and its results are presented. Fifth, the findings are discussed. Lastly, conclusions are drawn and the areas for future research are given.
# Design and Fabrication of a MEMS Bandpass Filter with Different Center Frequency of 8.5-12 GHz
###### Abstract  
The design simulation and fabrication results of a bandpass filter based on micro-electro-mechanical system (MEMS) switches are presented in this paper. The MEMS filter element consists of a MEMS capacitance switch and two resonant rings that are fixed onto coplanar waveguide lines through anchor points. The micromachine characteristics of the filter could be optimized to change the center frequency from 8.5 to 12 GHz by improving the geometrical parameters; other electrical parameters of the filter, such as stopband rejection, insertion loss, and return loss at each center frequency, were simulated and calculated. In order to evaluate the MEMS filter design methodology, a filter working at 10.5 GHz fabricated with an aluminum top electrode was used, and it displayed a low insertion loss of 1.12 dB and a high stopband rejection of 28.3 dB. Compared with the simulation results, these proposed filter showed better electrical performance. Our results demonstrated that the filter with the integrated RF MEMS switch not only provides the benefit of reduced size compared with a traditional filter, but also improves stopband rejection, insertion loss, and return loss.  
RF MEMS switch; filter +
Footnote †: journal:  
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## 3 Experiment and Results
### Experiment
#### 3.1.2 Evaluation Metrics  
In order to quantitatively assess the performance of the proposed joint deep learning framework for metal artifact reduction in industrial CT images, two widely recognized image quality metrics were employed: Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) [26]. The PSNR is an estimation of the reconstruction quality relative to the maximum possible pixel values. It is calculated in the log scale of the Mean Squared Error (MSE) between the reconstructed and the original image, and is typically expressed in decibels (dB). The PSNR is defined as:  
\[PSNR=10\cdot log_{10}(\frac{MAXValue^{2}}{MSE})\]  
where \(MAXValue\) represents the maximum possible pixel value of the image (for instance, 255 for an 8-bit grayscale image), and the MSE is the mean of the squares of the pixel-wise differences between the original and the reconstructed image.  
The SSIM index is a more sophisticated metric that measures the similarity between two images, addressing structural information, luminance, and contrast. SSIM has been described in Section 2 and will not be described here.
# Explainable MRI-Based Ensemble Learnable Architecture for Alzheimer's Disease Detection
## 4 Results and Discussion
### Comparative Analysis of Ensemble Explainability Techniques
#### 4.6.2 Saliency Map Results Comparison  
_Finally, the Saliency maps_ in Figure 16 provide an additional perspective on feature importance in our ensemble classification approaches.  
* **Brightness Intensity and Diagnostic Focus:** Saliency maps visualize feature importance through brightness intensity bright red indicates high importance, while darker areas represent low importance. Both ensembles show similar patterns, though stacking exhibits marginally more concentrated bright spots in the hippocampal and temporal regions, correlating with its slightly superior precision (98.0%).
* **Diagnostic-Specific Brightness Patterns:** Each diagnostic category shows characteristic brightness distributions across both methods: AD cases with concentrated bright spots in temporal structures, MCI with distributed patterns across broader regions, and CN with fewer, less intense bright spots, validating neuroanatomical progression patterns.  
Figure 15: LIME explanation for (**a**) hard voting and (**b**) stacking ensemble classifiers.  
* **Early Detection Enhancement:** For early-stage MCI, stacking shows slightly more nuanced brightness variations in the cortical and subcortical regions, potentially capturing subtle structural changes indicative of early neurodegeneration, contributing to enhanced sensitivity to early biomarkers (Table 9).
## 3 Experimental Section
### COD Analysis  
Initially, the immobilized TiO\({}_{2}\)/PEG DSAT (TP2) film was immersed in 20 mL of distilled water inside a glass cell under the irradiation of a 55-W compact fluorescent lamp. After 1 h of irradiation, the water sample was withdrawn and replaced with another set of distilled water using the same immobilized TiO\({}_{2}\)/PEG film until 8 h of irradiation. The withdrawn water samples were then subjected to the COD test. It can be observed that MB dye and its generated by-products had undergone almost 100% complete mineralization after 8 h of irradiation using an immobilized TiO\({}_{2}\)/PEG film.
# Editorial for Special Issue: Underwater Acoustics, Communications, and Information Processing
## 3 Underwater Acoustic Communication Systems
The proposed fractional Fourier transform-based orthogonal frequency division multiplexing (FrFT-OFDM) system employs the amplitude shift keying (ASK) modulation technique (hence, the name FrFT-ASK-OFDM). Specifically, ASK achieves a good bandwidth efficiency, and the data rate of the proposed system is approximately double the values of the corresponding conventional OFDM systems with the same resource parameters. Once the hardware or physical system configurations are fixed, upper layers or resource management issues remain, which include an efficient and fair medium access, scheduling of resource management, cognitive management of communication resources, etc. [14; 15; 16]. In [14], \"Message Collision Avoidance Protocols for Detecting Stray Nodes in a Scuba Diving Group Using Ultrasonic Multi-Hop Message Communication\", [PERSON] et al. investigated the medium access for recreational scuba divers not to make critical message collision during slow underwater acoustic communications. The proposed protocol, over an ad hoc mesh network between divers to detect a stray diver, suggests that messages are relayed in multiple hops with a message collision avoidance method, which reduces the packet loss rate caused by message propagation delay. They implemented the proposed methods in a network simulator, and compared them with existing communication methods. [PERSON] et al. proposed a resource management protocol for the backhaul of underwater cellular networks in [15]. They consider an underwater base station-initiating (UBSI) resource allocation problem, which is a new approach to determine the backhaul capacity of underwater base stations (UBSs), in the sense that a UBS initiates to redetermine its backhaul capacity according to its queue status. The protocol is simulated to be appropriate and efficient to the underwater backhaul link, especially when the transmission rate is quite low and the latency is unneglectable. In [16], [PERSON] et al. proposed a cognitive routing in software-defined underwater acoustic networks. Cognitive networks presume two different types of primary users, one natural acoustic and the other artificial acoustic, and there is a long propagation delay for acoustic links in underwater cognitive acoustic networks. Thus, the selection of a stable route in the underwater acoustic networks is a key design factor to improve the overall network stability, thereby reducing end-to-end delay. Under the software-defined or software-configurable networking, they proposed a novel routing protocol that two nodes can only communicate when they have a consensus about a common idle channel, to find a stable route between source and destination.
## 4 Conclusions  
This study investigated the fabrication and multi-parameter evaluation of electrospun PLA membranes functionalized with magnesium oxide (MgO) and gold nanoparticles (AuNPs) for potential use in guided bone regeneration (GBR). Through a combination of surface, structural, and biological analyses, dual functionalization was associated with improved scaffold performance compared to unmodified PLA. Key in vitro findings included enhanced surface wettability, increased swelling capacity, and improved buffering ability. SEM/EDS and FT-IR analyses confirmed the uniform incorporation of MgO and AuNPs into the PLA matrix. Biodegradation studies indicated that MgO helped stabilize acidic byproducts via pH buffering, while dual modification enabled a more controlled degradation profile. Biological assays demonstrated that all tested membranes maintained cell viability above 80%, with dual-modified samples showing the most favorable osteoblast adhesion and proliferation. Alizarin Red S staining revealed significantly increased calcium deposition in the MgO/AuNP co-modified membranes, particularly in the formulation containing 0.25 g MgO and 1 mL AuNPs (sample 9), suggesting a synergistic effect. Based on these statistically significant results, the null hypothesis was rejected. The study further suggests that MgO contributes to osteogenic stimulation through ionic release and pH modulation, while AuNPs may support mineralization and angiogenic activity. However, as the presented data are based exclusively on in vitro experiments, further in vivo validation is necessary to confirm the clinical relevance of these findings. Additionally, a random forest machine learning model was implemented to predict biological performance from material parameters, yielding high predictive accuracy and identifying MgO content and pH as key determinants of cytocompatibility. This data-driven approach supports the future application of machine learning in biomaterial optimization. In summary, this study provides promising in vitro evidence that PLA membranes functionalized with MgO and AuNPs may serve as an effective platform for GBR applications. Nonetheless, further in vivo testing and functionalization strategies, such as peptide conjugation or antimicrobial enhancement, are required to confirm their translational potential in dental and orthopedic regenerative medicine.  
Conceptualization, L.J., J.R.-P. and A.R.-P; methodology, J.R.-P., A.R.-P., and L.J.; validation, A.S.-B., J.R.-P., and L.J.; investigation, A.K., A.S.-B., P.R. and J.R.-P.; data curation, L.J., A.K., J.R.-P., and A.R.-P.; writing--original draft preparation, A.K., J.R.-P., and [PERSON]; resources, L.J. and [PERSON]; supervision, [PERSON]. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ministry of Education and Science, TRL 4.0 Grant number MNiSW/2020/344/DIR. 537.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
# Feasibility Analysis of Online Uncertainty Metrics for PMU-Based State Estimation
## 3 Online Performance Assessment
Based on the PMU estimates, it is possible to recover the time-domain trend of the fundamental component as:  
\[\hat{x}[n]=\hat{A}\cdot\cos\left(2\pi\hat{f}nT_{s}+\hat{\varphi}+\pi\hat{R}_{f }(nT_{s})^{2}\right) \tag{4}\]  
and define its discrepancy with respect to the corresponding acquired sample series in terms of two similar metrics:  
\[nRMSE=\sqrt{\frac{\sum(\hat{x}[n]-x[n])^{2}}{N_{s}}} \tag{5}\] \[GoF=\frac{\hat{A}}{\sqrt{\frac{\sum(\hat{x}[n]-x[n])^{2}}{N_{s}- d}}} \tag{6}\]  
where \(d\) is the model degrees of freedom (typically equal to 3, as \(\hat{R}_{f}\) is derived as a finite difference of consecutive frequency estimates). If we consider the PMU estimation as a nonlinear fit process, both the metrics quantify the residuals' energy, which can be interpreted as an assessment of the signal energy (and thus signal information content) that has been neglected or misrepresented due to the inconsistency between phasor model and acquired sample series. For the sake of brevity, the analysis considers the nRMSE metric only as its definition is slightly more general, not requiring the knowledge a priori of the model degrees of freedom. Nevertheless, similar considerations also hold for the GoF metric. In the following, we consider PMU-based measurements of voltage and current phasors as they are easily referable to a well-defined signal model, but similar approaches might be applied also to other types of measurements in a SCADA system.
## 11 Exploring Hybrid Approaches: Integrating Diverse Techniques
### Hybrid Approaches for External Artifact Removal: Case Study Analysis  
In [137], an innovative solution for the removal of external artifacts through the combined use of EMD and CCA is introduced, which demonstrates exceptional effectiveness in eliminating motion artifacts without compromising neural information in the EEG. Its computational efficiency, combined with improved signal cleaning accuracy, positions this approach as a promising method to address one of the most pressing challenges in EEG signal analysis: the reliable elimination of external artifacts.  
Ref. [138] introduces an innovative method for external artifact removal and signal classification, which is combining DWT and ANN. This hybrid approach led to an average increase of 15-16% in classification accuracy, demonstrating the effectiveness of the proposed methodology in improving both the quality of the EEG signal and the reliability of BCI systems. Through the integration of advanced signal processing and machine learning techniques, the work opens up new perspectives for optimizing BCI systems, promising significant improvements in usability and performance, and making them more accessible and reliable for users.  
The paper [139] analyzes and proposes methods based on blind source separation (BSS) to eliminate motion artifacts from EEG signals, using combinations of Independent Component Analysis (ICA), canonical correlation analysis (CCA), transform discrete wavelet (DWT), and stationary wavelet transform (SWT). Through testing on both pure and simulated EEG signals to emulate motion artifacts, the authors demonstrate that the CCA algorithm surpasses ICA in efficiency and speed in removing artifacts, while preserving important neural information. This significantly contributes to improving the accuracy and reliability of EEG-based diagnoses and signals promising directions for future research. Table 9 summarizes the SWOT analysis.