esa-sceva/satcom-chunk-collection huggingface dataset:
# Threat Modelling and Beyond-Novel Approaches to Cyber Secure the Smart Energy System
## 7 Risk Analysis Using Formal Methods
### UC3: Smart Grid and Black-Out Attack  
7.4.1. Probabilistic Model Generation  
Configuration analyzed in UC3 is presented on Figure 11.  
The system response is defined through the following service policies:  
* _PQM/PMU policy:_ PQM/PMU send regularly Grid Stability (GS) status to WAMS;
* _WAMS policy:_ Based on PQM/PMU readings WAMS sends GS value to SCADA; GS value is considered available when at least one PQM and at least on PMU readings are available;
* _PED policy:_ PED sends its status to SCADA via RTU, upon request;
* _SCADA policy:_ SCADA initiates island mode for the network segment based on GS and PED readings;
* _SwG actuator policy:_ SwG opens when island mode is initiated by SCADA.  
Figure 10: Smart home and smart meter hijacking use case results.  
The modeled attack properties are described in Table 15. Modeled attacks include four attack scenarios selected from the attack scenarios described in Section 6 as the most representative ones. One additional attack scenario, _Grid stability unavailable/jammed_, is modeled because it is a part of an other described scenarios as middle step (e.g., 3.2.1, 3.2.3), but it has final outcome and impact, completely masking GS value for the rest of the system.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Vulnerability** & **Associated Threat** & **Threat Id** & **Expl. Prob.** \\ \hline PQM1/2–SCADA link & Link jammed: denied transmission & 230/353 & 0.75 \\ PMU1/2–SCADA link & Link jammed: denied transmission & 478/593 & 0.75 \\ WAMS & Tailored context/incorrect reading & 51 & 0.59 \\ SCADA–RTU(SwG) link & Link jammed: denied transmission & 618 & 0.65 \\ RTU(PED)–SCADA link & Link jammed: denied transmission & 672 & 0.65 \\ RTU(SwG) & Tailored context/incorrect actuation & 621 & 0.59 \\ RTU(PED) & Tailored context/incorrect reading & 686 & 0.59 \\ PED & Tailored context/incorrect reading & 647 & 0.57 \\ PED sniffing & Sniffing & 1057 & 0.53 \\ PQM/PMU sniffing & Sniffing & 640 & 0.53 \\ PMU & Tailored context/incorrect reading & 1052 & 0.59 \\ PQM & Tailored context/incorrect reading & 187 & 0.59 \\ SCADA & Highjacking & 672 & 0.64 \\ \hline \hline \end{tabular}
\end{table}
Table 14: Vulnerabilities, exploitation probabilities and associated threats for UC3.  
Figure 11: Smart grid and black-out attack use case architecture.
# Estimating Time-Varying Applied Current in the Hodgkin-Huxley Model
## 1 Introduction
While particle methods like the unscented Kalman filter and EnKF can be successfully employed to estimate time-varying system components, the resulting time series estimates rely on the appropriate choice of certain algorithm-specific inputs, such as the innovation and observation error covariance matrices of the underlying state-space models [19; 20]. In particular, the success of the parameter tracking algorithm in estimating time-varying parameters depends on the a priori choice of the drift covariance in the random walk as well as the amount of data available. More specifically, the drift covariance has a direct effect on the associated uncertainty of the resulting parameter estimate, and a poor choice of this term could lead to filter divergence [21; 22; 23]. Along with estimating the time-varying applied current, we further illustrate the sensitivity of the results to the choice of the drift covariance and time-frequency of available data. In this work, we analyze the problem of estimating the time-varying applied current in the Hodgkin-Huxley model using synthetic voltage data generated by applying four different deterministic functions as the applied current--a constant current, a step function with one long pulse, a step function with multiple shorter pulses, and a sinusoidal function--each resulting in different model dynamics. We establish baseline results, demonstrating that the augmented EnKF with parameter tracking is able to estimate well the applied current and unobserved Hodgkin-Huxley model components in each of these four cases. We then further test the efficiency of the algorithm by performing numerical experiments to analyze the effects of changing the standard deviation of the drift term in the parameter tracking as well as the frequency of data available on the resulting applied current parameter estimates, including the corresponding uncertainty. The paper is organized as follows. Section 2 gives a brief review of the Hodgkin-Huxley model, summarizing the relevant equations. Section 3 reviews the parameter estimation inverse problem and outlines the ensemble Kalman filtering algorithm, with specific focus on time-varying parameter estimation using the EnKF with parameter tracking. Section 4 describes the numerical results, including the generation of synthetic data and the numerical experiments relating to estimating the time-varying applied current parameter. Section 5 features a discussion of the results and future work, while Section 6 gives a brief summary and conclusions of this work. Additional numerical experiments are included in Appendix A.
# A Division Algorithm in a Redundant Residue Number System Using Fractions
## 4 Conclusions  
The new algorithm described in this paper speeds up the modular division procedure in the RNS representation in comparison with the well-known analogs. This fact can be explained by the rather simple structure of the algorithm containing uncomplicated operations, namely, addition and shift (for quotient approximation), as well as shift and subtraction (for quotient refinement). Owing to CRT usage with fractions, the new algorithm does not include such operations as modular remainder calculation and number conversion into the mixed radix number system (MRNS) representation. The simulation of the algorithm on FPGA Kintex-7 has demonstrated a considerable reduction in hardware costs and an appreciable gain in speed as against the algorithms based on the CRT and MRNS representations.  
Currently, this is the best hardware implementation of the general modular division. In comparison with the well-known algorithms, the suggested algorithm guarantees smaller hardware and time costs by a close connection between architectural calculations and hardware implementation. As a result, the computational complexity of modular division has been essentially decreased. The new algorithm is remarkable for easy implementation, thereby requiring fewer calculations than its well-known analogs.  
A promising direction of further research is to find fast algorithms for several problem-causing operations in the RNS, namely, RNS-MRNS conversion and the optimal choice of RNS moduli within different ranges for specific applications. Each of the directions would promote the development of this field of computational mathematics owing to new RNS applications.  
Conceptualization, D.K., P.L., and N.C.; data curation, M.B. and I.L.; formal analysis, M.D.; funding acquisition, D.K.; investigation, A.L., A.N., M.V., and A.V.; methodology, P.L.; project administration, N.C.; resources, M.B. and I.L.; software, A.N., M.V., and A.V.; supervision, D.K. and P.L.; validation, M.D. and A.L.; visualization, A.V., M.V., and A.N.; writing--original draft preparation, N.C., P.L., and M.B.; writing--review and editing, D.K. and P.L. All authors have read and agreed to the published version of the manuscript.  
Figure 5: Frequency as a function of dynamic range bit count.  
**Funding:** This research was funded by the grant of the Russian Science Foundation (Project N19-19-00566).  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Numerical Performance Investigation of a Hybrid eCVT Specialized Agricultural Tractor
## 4 Numerical Investigation
### Slope Test  
Another important test to evaluate the HeCVT tractor performance in terms of peak power capabilities is the slope test. In this case, different work scenarios were considered to explore different critical work conditions for the powertrain:  
* Maximum approachable slope at 40 km/h with no trailer.
* Maximum approachable slope at 5 and 15 km/h with 10,000 and 5000 kg of payload, respectively.
* Maximum reachable speed with no trailer and 45% of slope.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline  & **HeCVT** & **HeCVT** & **Conventional** \\ \hline  & **with GS** & **High Speed** & \\ \hline
0–15 km/h & & & \\ \hline No trailer & 1.2 s & 2.1 s & 2.2 s \\
6000 kg trailer & 2.5 s & 6.7 s & 3.4 s \\
10,000 kg trailer & 3.6 s & 11.3 s & 4.3 s \\ \hline
0–40 km/h & & & \\ \hline No trailer & 4.8 s & 4.9 s & 5.6 s \\
6000 kg trailer & 14.5 s & 17.8 s & 14.7 s \\
10,000 kg trailer & 23.1 s & 30.3 s & 24.4 s \\ \hline \hline \end{tabular}
\end{table}
Table 5: HeCVT acceleration performance with different trailer payloads.  
These tests aimed to verify the capability to provide full power at those different speed conditions under the constant load of the road slope. Moreover, each test was performed with a standing start at the prescribed slope to test the tractor capability to also start moving on the proposed slope condition (Italian traffic laws prescribe that the tractor should at least be able to stand start at 14% with the prescribed trailer load). Results are reported in Table 6. In almost all the work conditions, the HeCVT tractor slightly outperformed the conventional one except for the 5 km/h and 10,000 kg trailer test. In that case, the greater number of possible gear configurations given by a traditional gearbox configuration allowed for greater tractive effort at that specific speed, enabling the conventional ICE to work closer to its max power condition. Only in this special work scenario, the HeCVT system required the use of the boost function of the electric system in order to achieve the prescribed slope. The HeCVT tractor recorded good results at 40 and 15 km/h since its two speed regimes were dimensioned for those vehicle speeds.  
Figure 8: HeCVT 0–40 km/h acceleration test with 10,000 kg trailer and 0% of slope.
## 3 Results and Discussion
### Quantitative Risk Assessment  
Based on the available experimental data, the systemic exposure (SE) for a whole working day (assuming application to 1 ha) has been estimated to be lower than the respective health-based guidance value for both bupirimate (pesticides A) and tebufenozide (pesticide B) (Table 8). Regarding the combined exposure of mixer/loaders and applicators to both pesticides, the hazard index calculated was lower than 1, indicating that there is no risk anticipated under the specific conditions examined.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Pesticide A (Bupirimate)**} \\ \cline{2-7}  & **ML1/AP1** & **ML2/AP2** & **ML3/AP3** & **ML4/AP4** & **ML5/AP5** & **ML6/AP6** \\ \hline SE* (mg a.s./kg bw/day)—AP & 0.00055 & 0.0013 & 0.00066 & 0.00036 & 0.00016 & 0.00075 \\ SE (mg a.s./kg bw/day)—ML & 0 & 0.00046 & \(5.01\times 10^{-5}\) & \(8.76\times 10^{-6}\) & \(8.773\times 10^{-7}\) & \(8.26\times 10^{-6}\) \\ TOTAL SE (mg a.s./kg bw/day) & 0.00055 & 0.0018 & 0.00071 & 0.00037 & 0.00016 & 0.00076 \\
**Estimated exposure as \% AOEL** & **1.09** & **3.53** & **1.42** & **0.73** & **0.33** & **1.52** \\
**H/Q** & **0.011** & **0.035** & **0.014** & **0.0073** & **0.0033** & **0.015** \\ \hline  & \multicolumn{6}{c}{**Pesticide B (Tebufenozide)**} \\ \cline{2-7}  & **n/a** & **n/a** & **n/a** & **4** & **5** & **6** \\ \hline SE (mg a.s./kg bw/day)—AP & - & - & - & \(3.06\times 10^{-5}\) & \(0.00011\) & \(8.95\times 10^{-5}\) \\ SE (mg a.s./kg bw/day)—ML & - & - & - & \(2.63\times 10^{-6}\) & \(6.13\times 10^{-5}\) & \(2.51\times 10^{-5}\) \\ TOTAL SE (mg a.s./kg bw/day) & - & - & - & \(3.30\times 10^{-5}\) & \(0.00017\) & \(0.00011\) \\
**Estimated exposure as \% AOEL** & - & - & - & **0.41** & **2.15** & **1.43** \\
**H/Q** & - & - & - & **0.0041** & **0.021** & **0.014** \\ \hline  & \multicolumn{6}{c}{**Combined exposure to Pesticide A and B**} \\ \cline{2-7}  & **n/a** & **n/a** & **n/a** & **4** & **5** & **6** \\ \hline
**HI*** & - & - & - & **0.011** & **0.025** & **0.029** \\ \hline \hline \end{tabular}  
* SE: Systemic Exposure, AOEL: Acceptable Operator Exposure Level, H/Q: Hazard Quotient, HI: Hazard Index, **Mixer loader/Applicators (1), (2) and (3) handled pesticide A (morming), while Mixer loader/Applicators (4), (5) and (6) handled pesticide B (afternoon), and thus have been exposed to pesticide A existing deposits.  
\end{table}
Table 8: Systemic exposure to bupirimate (pesticide A) and tebufenozide (pesticide B): operator risk assessment.  
For the calculation of the systemic exposure (SE), the dermal penetration factors (Pf) concluded following the EFSA peer review for each a.s. (concentrate and spray dilution) have been considered: (a) Bupirimate: 1.3 and 12% for the concentrate and the dilution, respectively [28]; (b) Tebufenzoide: 0.2 and 2.1% for the concentrate and the dilution, respectively [29]. The AOEL value for bupirimate has been set at 0.05 mg/kg b.w./day [30], while for tebufenoxide, the respective value is 0.008 mg/kg b.w./day [31].
# Enhancing User Experience in Virtual Museums: Impact of Finger Vibrotactile Feedback
## 1 Introduction  
Virtual reality (VR) has revolutionized how we experience digital environments, offering immersive visual and auditory experiences that transport users to alternate realities. Despite these advancements, the tactile dimension remains significantly underexplored, particularly in educational and museum settings where touch is crucial in interaction and learning. Current VR systems rely heavily on visual and auditory cues while lacking realistic haptic feedback, resulting in limited immersive experiences [1]. To address this gap, introducing a vibrotactile glove represents a pioneering step toward enhancing tactile interactions in virtual environments [2]. This technology aims to enhance the users' experience by simulating the feel and textures of different materials, thereby making virtual interactions more realistic and engaging [3]. Several studies have explored various forms of haptic feedback in VR; however, few have focused on the detailed and nuanced feedback necessary for applications such as virtual museums.  
Virtual museums offer a unique platform for education and cultural engagement, allowing users to explore artifacts and exhibits worldwide. However, the inability to touch and feel these virtual objects limits the depth of interaction and the overall immersive experience. We can bridge this sensory gap by integrating FSVF, potentially transforming how users interact with and perceive virtual artifacts [4]. This study presents a novel approach to enhancing user interaction in virtual museum environments by developing and applying an FSVF glove. Unlike previous research that has primarily focused on general haptic feedback in VR, this study introduces a highly detailed and nuanced form oftactile feedback specifically tailored for virtual museums. The unique contribution of this research lies in its mixed-methods evaluation of user performance, efficiency, immersion, and satisfaction when interacting with virtual artifacts using the FSVF glove compared to traditional methods. The findings demonstrate significant improvements in task accuracy, reduction in errors, and enhanced user engagement, thereby offering new insights into the design and application of advanced haptic technologies in educational and cultural VR settings. This study not only bridges the sensory gap in VR interactions but also provides a foundational framework for future innovations in haptic feedback, paving the way for more immersive and realistic virtual experiences.  
We hope to demonstrate the transformative potential of vibrotactile feedback in enhancing virtual museum visits and contribute valuable insights to the design and application of haptic technology in virtual environments. Our findings provide a foundation for future innovations in virtual reality, ultimately enriching the immersive experiences offered by interactive digital environments.
###### Abstract  
Various material processing techniques have been proposed for fabrication of smart surfaces that can modulate cellular behavior and address specific clinical issues. Among them, laser-based technologies have attracted growing interest due to processing versatility. Latest development of ultrashort pulse lasers with pulse widths from several tens of femtoseconds (fs) to several picoseconds (ps) allows clean microfabrication of a variety of materials at micro- and nanoscale both at surface and in volume. In this study, we addressed the possibility of 3D microfabrication of photosensitive glass (PG) by high repetition rate ps laser-assisted etching (PLAE) to improve the fabrication efficiency for the development of useful tools to be used for specific biological applications. Microfluidic structures fabricated by PLAE should provide the flow aspects, 3D characteristics, and possibility of producing functional structures to achieve the biologically relevant microenvironments. Specifically, the microfluidic structures could induce cellular chemotaxis over extended periods in diffusion-based gradient media. More importantly, the 3D characteristics could reproduce capillaries for in vitro testing of relevant organ models. Single cell trapping and analysis by using the fabricated microfluidic structures are also essential for understanding individual cell behavior within the same population. To this end, this paper demonstrates: (1) generation of 3D structures in glass volume or on surface for fabrication of microfluidic channels, (2) subtractive 3D surface patterning to create patterned molds in a controlled manor for casting polydimethylsiloxane (PDMS) structures and developing single cell microchambers, and (3) designing glass photo-masks to be used for sequel additive patterning of biocompatible nanomaterials with controlled shapes, sizes, and periodicity. Mesenchymal stem cells grown on laser-processed glass surfaces revealed no sign of cytotoxicity, while a collagen thin coating improved cellular adhesion.  
picosecond laser-assisted etching; photosensitive glass; 3D microfluidics; PDMS; microchambers; photo-masks; biomimetics +
Footnote †: journal: Applied Physics Letters
## 4 Discussion
### Hyperspectral Imaging for Spectral Characterization of Kidney Tissue in the VIS/NIR Region  
HSI enables fast and non-invasive measurement of tissue properties in, e.g., medical applications. Using this technique, information about physiological and pathological tissue characteristics can be obtained [20; 21; 22; 23; 24; 25]. Water-specific tissue features of the kidney were assessed using HSI in the wavelength range between 500 and 995 nm. By predicting the TWC, tissue-related damage during ex vivo preservation could be detected in the future.  
Depending on the medical application, the analyzed HSI spectral range varies between 400 and 2500 nm. However, tissue characterization is preferably performed in the optical window between 600 and 1000 nm. In this wavelength range, the amount of VIS/NIR light absorbed by the tissue is limited, which allows a high penetration depth of the light into the tissue [19]. In the optical window, the main absorbers are melanin, hemoglobin, lipids, and water [37; 39; 50]. Since the organic samples' composition is complex, the absorption bands tend to be broad and generally overlap in different parts of the NIR range [51]. Two water absorption peaks were observed at 760 and 970 nm [37]. Therefore, the quantification of the TWC in medical applications or food analysis was successfully performed by using the wavelength range of 400-1000 nm [27; 37; 38; 47; 52; 53].  
The application of HSI is limited by the low penetration depth of the propagating light into the tissue. Depending on the wavelength, the illumination has a penetration depth of only a few millimeters [54]. In the kidney, the main metabolic activity is concentrated in the cortex region [55; 56]. An impairment of the kidney quality caused by IRI, for example, could have a decisive influence on this external organ region and would, therefore, have a considerable impact on the physiological condition and composition of the kidney. Consequently, metabolic-related kidney injury could be detected with HSI.
###### Abstract  
In view of the future of the Internet of Things (IoT), the number of edge devices and the amount of sensing data and communication data are expected to increase exponentially. With the emergence of new computing-intensive tasks and delay-sensitive application scenarios, terminal devices need to offload new business computing tasks to the cloud for processing. This paper proposes a joint transmission and offloading task scheduling strategy for the edge computing-enabled low Earth orbit satellite networks, aiming to minimize system costs. The proposed system model incorporates both data service transmission and computational task scheduling, which is framed as a long-term cost function minimization problem with constraints. The simulation results demonstrate that the proposed strategy can significantly reduce the average system cost, queue length, energy consumption, and task completion rate, compared to baseline strategies, thus highlighting the strategy's effectiveness and efficiency.  
low Earth orbit satellite networks; edge computing; task offloading; resource scheduling; deep Q-network Article
# A Full-Coverage Path-Planning Algorithm for a Glass-Curtain-Wall-Cleaning Robot Driven by Ropes
## 4 Full-Coverage Path Planning
### Conventional Obstacle Avoidance Strategy  
On a wall surface with conventional obstacles, when \(L\leq H\), the robot's overall motion scheme is longitudinal reciprocating motion. When \(L>H\), the robot's overall motion scheme is transverse reciprocating motion. The specific rules are as follows:  
(1) When \(L\leq H\), the first rule is that the horizontal and vertical robot motions have higher priority than oblique motions. The second rule is that if the robot starts to perform a coverage task from the subregion left (right) side, the priority of left (right) motion is set as the highest, the priority of up and down motion is second, and the priority of right (left) motion is lower than those of up and down motion. The third rule is calculating the number of uncovered grids in the upper and lower directions from the robot's current grid to the obstacle or covered grid, which are set as \(N_{n}\) and \(N_{s}\), respectively. If \(N_{n}<N_{s}\), the robot's upward motion has higher priority than the downward motion. Otherwise, the downward motion has higher priority than the upward motion. This rule ensures that the robot preferentially covers the side with a low number of uncovered grids to reduce the path repetition rate of the robot.  
Figure 7: Region decomposition.  
(2) When L > H, based on the transverse reciprocating motion, three priority rules were formulated for the robot to select the next grid position. The first rule follows that in (1). The second rule is that if the robot starts to perform the coverage task from the subarea's upper (lower) side, the upward (downward) motion priority is set as the highest, the left and right lower motion priority as the second-highest, and the downward (upward) motion priority is lower than that of left and right motion. The third rule is to calculate the number of uncovered grids in the left and right directions from the robot's current grid to the obstacle or covered grid, which are \(N_{w}\) and \(N_{e}\), respectively. If \(N_{w}<N_{e}\), the robot's left movement has higher priority than right movement. Otherwise, the right movement has higher priority than left movement.  
This overall obstacle avoidance strategy is shown in Figure 8.