esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 NLP-Based ECMS Algorithm  
In this paper, the NLP-based ECMS algorithm, a combination of NLP and an A-ECMS, is proposed. A conceptual diagram of the NLP-based ECMS algorithm is shown in Figure 4. Based on the reference SOC trajectory obtained by NLP, the A-ECMS operates to minimize fuel consumption of the HEV. The process of performing the NLP-based ECMS algorithm is as follows. First, the required torque demanded by ICE and EM is calculated according to the driving condition. The gear ratio must be properly considered when calculating the required torque, because the gear ratio of the P2 powertrain is a discrete variable. Secondly, the reference SOC trajectory corresponding to the required torque through NLP is calculated. NLP can cause long calculation times and infeasible solutions if the system model and constraints are poorly designed. Thirdly, the A-ECMS determines the control input so that the measured SOC can follow the reference SOC trajectory.
# A Comparative Study of Local Descriptors and Classifiers for Facial Expression Recognition
## 6 Conclusions  
This study evaluated different combinations of local descriptors and classifiers for facial expression recognition. The experiments comprehensively evaluated six descriptors and four classifiers on two famous datasets, such as CK+ and RFD. Notably, the appropriate choice of extraction parameters improved several descriptors' performances. We can single out HOG as the descriptor that achieved the most consistent performance across all the datasets. The computational costs of each classifier and descriptor were also studied, and we found that the NB and MLP classifiers provided the fastest predictions. However, MLP can be time-consuming during training compared to the other classifiers. When evaluating the classifiers' recognition efficiencies, we found that SVM and MLP achieved the best results.  
Out of the six considered descriptors, HOG and ALDP are some of the most promising, while SVM and MLP rank at the top of the considered classifiers. We also found that SVM was faster to train and required little model tuning compared to MLP. On the other hand, MLP has a notably faster prediction, which could be an advantage in real-time applications.  
Conceptualization, A.B.M. and J.-
# Multi-Means Comprehensive Forecasting Technology for Water Inrush in Long Tunnels
## 3 Comprehensive Geophysical Exploration Techniques  
### Seismoelectric Effect Technology  
The seismoelectric effect describes the generation of electromagnetic fields resulting from mechanical vibrations, such as seismic waves, propagating through porous media, where interactions occur between pore fluids and the solid matrix. This phenomenon is primarily measured through the seismoelectric method, which focuses on detecting electromagnetic fields produced by the electrokinetic effect. The electrokinetic effect arises from the relative motion between the rock matrix and pore fluids induced by acoustic waves, typically P-waves, traversing porous rock. When ions flow within capillary channels, cations (or, less frequently, anions) tend to adsorb onto the capillary walls. External pressure induces fluid flow relative to the rock matrix, creating electric dipoles within the medium. In heterogeneous media, seismic waves induce periodic fluid oscillations, generating electromagnetic fields, as illustrated in Figure 2. These electromagnetic fields can be detected using electrode antennas installed in the tunnel.  
In addition to electromagnetic waves generated by the seismoelectric effect, P-wave propagation in water-bearing solids also produces electromagnetic waves known as coseismic waves. During seismoelectric measurements, electromagnetic sensors simultaneously capture signals from both the seismoelectric effect and coseismic waves.  
The seismoelectric acquisition system shares similarities with seismic acquisition systems and primarily consists of the following components: dipole antennas (electrode pairs), preamplifiers, seismic cables, receivers, and a seismic source.  
Figure 1: Regional structural geology (red lines represent fault broken belt, while blue lines represent the stratum lithologic range).
# Design and Optimization of Piezoelectric-Powered Portable UV-LED Water Disinfection System
## 6 Conclusions  
In this study, the design and optimization of a piezoelectric-powered portable UV-LED water disinfection system were presented. Operation of the proposed system was described based on the filed patent of the first named author. Physical-mathematical models of mechanical, electrical and biochemical components of the system were fully developed from the design point of view. Then, the models were used in optimization of the design parameters. The results of single and multi-objective optimization employing Genetic Algorithm (GA) were presented. Finally, the design parameters were derived for three different cost scenarios. The cost of the system and the shake duration were taken as critical design parameters. For the three cost scenarios, optimal shake duration was quite diverse, ranging from 5040 s to 15.4 s. However, it should be noted that the impact of some other parameters both on the cost and the shake duration might also be considered. This paper elaborates on the full theoretical design and modeling of the system, and the realization of the system might require further engineering work.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Parameter**} & \multicolumn{4}{c}{**Cost Scenario**} \\ \cline{2-4}  & **Low** & **Moderate** & **High** \\ \hline \(C\) (S) & 5.82 & 34.39 & 87.32 \\ \(T_{S}\) (s) & \(5040\) & 100.6 & 15.4 \\ \(P_{d}\) (W) & \(1.5\) & 1.5 & 1.5 \\ \(N\) & 1 & 4 & 10 \\ \(\phi\) (W) & 0.0025 & 0.034 & 0.08 \\ \(f_{s}\) (Hz) & 5.49 & 5.49 & 5.5 \\ \(\alpha\) (m/s\({}^{2}\)) & 34.98 & 34.99 & 35.0 \\ \(h_{1}\) (m) & 0.099 & 0.1 & 0.1 \\ \(h_{3}\) (m) & 0.003 & 0.003 & 0.003 \\ \(r_{2}\) (m) & 0.031 & 0.031 & 0.031 \\ \(R_{PZT}\) (m) & 0.01 & 0.01 & 0.01 \\ \(T_{d}\) (s) & 895.7 & 65.9 & 27.9 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Optimal System Parameters for Three Cost Scenarios.  
Figure 7: Multi-objective GA optimization for the shake duration and the cost.  
**Author Contributions:** Conceptualization, methodology, D.E.S., Y.D., A.K. and M.D.; investigation, visualization, writing--original draft preparation, D.E.S. and Y.D.; validation, writing--review and editing, A.K. and M.D.; supervision, A.K. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data available on request from the authors.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Method
### Improvements Based on Shield Tunneling Characteristics
#### 2.3.3 Special Factor Handling  
During shield tunneling, special construction factors such as abnormal stoppages and secondary grouting significantly affect surface settlement [35]. To further increase the prediction accuracy, these two factors were encoded as special feature inputs into the dataset. This encoding effectively marks anomalous points in the shield tunneling process, integrates these special influences into the dataset comprehensively, and allows more complete consideration of their effects on surface settlement.  
Unlike prior Informer adaptations for tunneling [23, 27], which relied on standard convolutions and static soil inputs, the improved algorithm uniquely integrates dilated causal convolutions with tunable dilation rates (d = 1, 2, 4) and kernel sizes (k = 5). This design exponentially expands the temporal receptive field while enforcing causality, addressing settlement lag effects more effectively. Additionally, the self-attention distillation combines ELU-activated convolutions and max-pooling (Equation (1)), reducing redundant computations by 30.64% (Section 3.5.3). Furthermore, dynamic input features (e.g., moving windows and event markers) enable real-time adaptation to abrupt construction disturbances, a capability absent in earlier implementations.
## 2 Materials and Methods
### Enzyme-Linked Immunosorbent Assay (ELISA)  
The human 8-isoprostane F2-\(\alpha\) level (catalogue no. E4805 Hu) was determined using sandwiched enzyme-linked immunoassay (ELISA) kit from Bioassay Technology Laboratory (Shanghai, China). Briefly, 40 \(\mu\)L of cell lysates (1 mg/mL; in duplicate) were mixed with 10 \(\mu\)L of free biotinylated human 8-isoprostane F2-\(\alpha\) antibody in the 96-well plate pre-coated with human 8-isoprostane F2-\(\alpha\) antibody. The standard solutions (50 \(\mu\)L; in serial concentration) were added separately into another 2 rows of wells. Subsequently, all the sample and standard wells (except the blank) were added to with 50 \(\mu\)L of streptavidin-linked horseradish peroxidase (HRP) reagent and the 96-well plate was then incubated at 37 \({}^{\circ}\)C for 1 h. Subsequently, the plate was washed 5 times with wash buffer solution and blot-dried with paper towels. Immediately, 100 \(\mu\)L of pre-mixed substrate Solution A and B was added to each well and the plate was further incubated at 37 \({}^{\circ}\)C for 10 min. Lastly, 50 \(\mu\)L of stop solution was added to stop the colourimetric reaction and the absorbance was measured using Multiskan GO microplate reader (Thermo Fisher Scientific, Vantaa, Finland) at the wavelength of 450 nm. The absolute levels of 8-isoprostane F2-\(\alpha\) were determined based on the standard curve derived from the standard solutions with known concentration.  
The human collagen type I \(\alpha\)1 (COL1\(\alpha\)1; catalogue no. E-EL-H0869), collagen type II \(\alpha\)1 (COL2\(\alpha\)1; catalogue no. E-EL-H0777), sex-determining region Y box protein 9 (SOX9; catalogue no. E-EL-H1349), a disintegrin and metalloproteinase with thrombospondin type 1 Motif 4 (ADAMTS4; catalogue no. E-EL-H0266) and aggrecan (catalogue no. E-EL-H0294) levels were determined by using the sandwiched ELISA kits from Elabscience (Houston, Texas, USA) according to the manufacturer's protocol. Briefly, 100 \(\mu\)L of standard solution (in serial concentration) and lysates were added (1 mg/mL) in duplicate into the 96-well plates pre-coated with respective specific antibodies. The plates were then sealed and incubated at 37 \({}^{\circ}\)C for 90 min. After that, the entire content of the wells was removed and replaced with 100 \(\mu\)L of respective biotinylated detection antibody working solution. Next, the plates were incubated at 37 \({}^{\circ}\)C for another 1 h and followed by 3 times of washing with wash buffer solution. Subsequently, 100 \(\mu\)L of HRP conjugate working solution was added, and the plates were incubated again at 37 \({}^{\circ}\)C for 30 min. The plates were then washed 5 times with wash buffer solution, followed by the addition of 90 \(\mu\)L of substrate reagent solution and incubated at 37 \({}^{\circ}\)C for another 15 min. A 50 \(\mu\)L of stop solution was then added into the wells, and the absorbance was measured using Multiskan GO microplate reader (Thermo Fisher Scientific, Vantaa, Finland) at 450 nm. The levels of proteins of interest were determined based on the respective standard curves.
## 3 Security Attacks in Smart Healthcare Systems
### Side-Channel (Information Gathering, Reconnaissance) Attacks  
Before any cybersecurity attack, an attacker must scan and extract sensitive information from the victim's infrastructure, such as encryption methods, open service ports, software version numbers, and network information. In a smart healthcare system, the attackers have a wide opportunity to propagate their attacks due to the many heterogeneous devices involved in an ongoing task. Here, attackers first discover how the medical device's circuit works, how data are exchanged between devices, their communication protocols, and much more. For example, attackers can exploit the electromagnetic interference that intercepts or jams the communication to infer/extract the patient's sensitive information. In addition, the attackers can manoeuvre the medical devices that show forged sensor readings to trick the medical staff and practitioners. Also, an attacker alters the physical resources (network) to passively disrupt the performance of medical devices (e.g., sensor spoofing). By means of this attack, an adversary can easily find the cryptography keys and digital certificates that are essentially as protection from cyber-attacks. The authors of [77] show the impact of side-channel attacks in the smart healthcare sector, where an attacker can compromise the smartphone-based personal health records consisting of patient medical reports, family medical history, mental health data, fitness data, physical activity data, and other information. Furthermore, attackers can use more sophisticated side-channel attacks, such as statistical and differential power analysis attacks. These are statistical attacks that measure the power consumption of two samples to analyse the correlations between them [78]. For instance, an adversary can analyse the RSA keys by averaging the two samples, where '1' is displayed as a taller bump, and '0' has a shorter bump.
# An Integrated Photorefractive Analog Matrix-Vector Multiplier for Machine Learning +
## 2 Materials and Methods
### Photorefractive Effect
#### 2.1.2 Crossbar Array Architecture
In order to realize a practical device, the photorefractive crossbar array processor is designed as an integrated photonic chip (Figure 4d). The photorefractive coupling requires an angular degree of freedom, which is provided by a 2D slab waveguide interaction area. Collimating mirrors are realized by a curved waveguide sidewall. The input vector is set by an electronically controlled optical input stage that maps a source beam to the input channels. A detector stage converts the optical output back to electrical signals. Input and detection stages are included for both the source and destination branch. The photorefractive crossbar array can accelerate both ANN inference and training via back propagation (Figure 5). As discussed in the introduction, the latter requires the transposed matrix and output product operation (Figure 2b). Since the gratings couple reciprocally, the transposed matrix is simply accessed by swapping the input and output branch (Figure 5a,b). Figure 4: (**a–c**) A photorefractive scheme for realizing an analog crossbar array in hardware. Photorefractive index gratings constitute synaptic coupling elements, and the full synaptic interconnect layer is realized by superimposing them. (**d**) An integrated photonic circuit offers performance benefits in terms of stability, power, and write times. All coefficients are complex, and phase stability is of importance. The weight update by the outer product is performed by applying the respective vector signals simultaneously via the input stages (Figure 5c). The grating write behavior yields the desired operation precisely (Figure 4b). Physically, decreasing a weight value is possible because a phase-shifted write-beam interference pattern may act as an erasing force on an existing grating.
## 5 Experimental Measurement  
All state variables are easily measurable as voltages at the outputs of the inverting integrators. Supply voltage is symmetrical \(\pm 15\) V, total power dissipation is about 1.35 W. Few selected measurement results for the third-order chaotic oscillator are provided by means of Figure 17. Experimental validation, especially visual validation of the prescribed strange attractors turns to be rather difficult because of the riddled basin of attraction. For the second set of internal parameters Equation (8) entire neighborhood of origin does not belong to the attraction set leading to chaotic attractor. Hand-made injection of the specific initial conditions into proper circuit nodes was tricky and often pushes trajectory to infinity. During measurement, desired strange attractors were affected even by small perturbations of the supply voltage. Observed strange attractors are also very sensitive to precision adjustment of variable resistors. Despite mentioned difficulties, very good agreement with geometrical shapes of numerically integrated trajectories can be pronounced, at least for both groups of internal system parameters Equations (7) and (8). Note that chaotic orbits simulated/calculated by Orcad Pspice and provided in Figure 11c,f can be matched with captured oscilloscope screenshots visualized within Figure 17. Moreover, for the real-valued passive components mentioned above, frequency spectrum of generated chaotic signals is in audio band and bifurcation phenomena can be heard.  
Evolution of chaos can be smoothly traced via continuous change of several resistors, for example \(R_{1}\), \(R_{2}\), \(R_{3}\), \(R_{5}\) or \(R_{6}\) (in the case of third-order oscillator) and \(R_{1}\), \(R_{2}\), \(R_{3}\), \(R_{5}\), \(R_{8}\), \(R_{12}\) (for fourth-order chaotic system). One example of circuit-oriented bifurcation scenario is provided by means of Figure 18. Besides chaotic dynamics designed analog oscillator exhibit periodic and quasiperiodic orbits, multi-stability and large limit cycle defined by the saturation levels of the active elements.  
In addition to expected chaotic attractors, several interesting geometrical structures of the strange attractors were discovered during experimental investigation and left unnoticed during numerical analysis.  
Figure 17: Experimental confirmation of strange attractors in oscillator defined by Equation (13).
The Establishment and Application of Models for Recommending Formula Fertilization for Different Maturing Genotypes of Broccoli  
Guangqing Li  
are relatively important differences in the demand for N, P, K, and other fertilizers [1,8]. N, P and K are vital factors in soil testing and fertilization recommendation, significantly influencing both the yield and quality of broccoli [9, 10, 11]. Developing fertilization function is the basis of formula fertilization via soil testing for the production of crops and vegetables. Some formulated fertilization models have been presented for various field crops, such as wheat and corn [12,13], while no significant application of model for recommend formula fertilization has been proposed for vegetables, including broccoli and cauliflower. [PERSON] et al. studied the effects of application of N, P, and K fertilizers on cauliflower yield [14,15].  
In the integrated technological process of \"soil testing-formulation-fertilic\" supplying\", the precise formulation is the core of formula fertilization [16,17], and soil testing is an important part of formula fertilization. The fertilizer response functions in domestic and foreign models of broccoli and cauliflower have been investigated [18, 19, 20], while few studies have concentrated on how to apply the optimal results of fertilizer response functions to the formula fertilization recommendation. In some cases, the optimal fertilization recommendation was directly used in recommended plots [10,18, 19, 20], which is obviously inconsistent with the principle of formula fertilization via soil testing and cannot reach the expected results. Therefore, combining the determination of soil nutrient content with fertilizer effect function, the application of models for recommend formula fertilization could be better extended.  
Nonetheless, there were few reports on the recommendation of N, P, and K fertilizers based on the response function of the yield of broccoli to fertilization. In our previous study, the fertilizer response functions reflecting the relationships between fertilizer rate and yield were presented for cauliflower and broccoli in field experiments using the 311-A optimization regression design [11,18,20].  
To date, the functions of N, P, and K fertilizers in broccoli production have not been deeply studied. In addition to response functions of N, P, and K fertilizers, the fertilization recommendation based on the soil testing is a successful tool for crop fertilization management, requiring a reasonable recommendation model for predicting fertility.  
With this aim, based on the established effect functions of N-, P-, and K-balanced fertilization for different genotypes, especially early-maturing and late-maturing varieties, the purpose of this study is to establish the models for recommending formula fertilization and to apply the recommended fertilization according to the different results of soil testing in different field plots from the main producing areas of broccoli, allowing the possibility of improving the yield and quality of broccoli and reducing pollution.
# Stents in Congenital Heart Disease: State of the Art and Future Scenarios
## 2 Stent Design
### Materials and Deployment Strategy  
An ideal stent should have good flexibility and deliverability, low thrombogenicity, strong radial force, good radio-opacity under fluoroscopy, and good biocompatibility to ensure low rates of neointimal hyperplasia and stent thrombosis during long-term follow-up [12]. The first types of devices were proposed for the treatment of coronary arteries and were called bare-metal stents, which were developed with conventional alloys that can be plastically deformed, like stainless steel, cobalt-chromium, or platinum-chromium [13; 14; 15]. Later they evolved into drug-eluting stents (DES), which are metal devices coated with an antiproliferative drug to limit the reoccurrence of stenosis. In the last years, bioresorbable vascular scaffolds have been proposed, made of degradable materials designed to support the vessel wall only temporarily and be reabsorbed when their function is no longer required; however, their long-term performance is still under evaluation [16]. Coronary stents belong to the family of the so-called balloon-expandable stents since they are positioned by the inflation of a balloon mounted on the catheter tip; the lesion is reached percutaneously and crossed by a guide wire, then the balloon catheter with the crimped stent is advanced over the wire across the lesion, and finally, the balloon allows the stent expansion to restore the artery lumen. After the balloon is deflated, the stent remains in its expanded shape, except for a slight recoil caused by the elastic portion of the deformation.  
On the contrary, stents introduced in peripheral arteries (like femoral, popliteal, or carotid) have to withstand large cyclic loads due to leg/head movements [17; 18; 19], and for this reason are usually made by shape memory alloys, such as nickel-titanium (Ni-Ti), which can recover elastic strains up to 10% [20; 21]. They are manufactured in the expanded configuration and then crimped and loaded on the tip of the catheter, maintained closed by a sheath; for this reason, Ni-Ti stents are named self-expandable stents since the retraction of the sheath allows their spontaneous expansion to the predetermined diameter due to a material property exploited at body temperature, called superelasticity [22].