esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Recently, the lipolytic abilities of the yeast _Sporidiobolus metaroseus_ were also exploited to remove an oil-based patina from a historical painting from the XVIII Century [24]. Thus, it can be suggested that the isolated extracellular enzymes can be used for the restoration of different artworks and historical items without microbial contamination of the treated surface. White-rot fungi, considered a physiological group of fungi exhibiting the activity of lignin degradation within lignocellulosic substrates, have been investigated intensively due to their great potential to degrade a wide variety of recalcitrant organic compounds and synthetic dyes [28; 29; 30; 31; 32]. These fungi, as well as brown-rot fungi, secrete various extracellular enzymes called lignin-modifying enzymes (LMEs), which include heme-dependent lignin peroxididases (LiP), manganese peroxididases (MnP), dye-decolorizing peroxididases (DyP), and copper-dependent lacases [33; 34; 35; 36; 37]. LMEs have found their use in environmental applications, including the transformation and degradation of compounds, such as different synthetic dyes, pharmaceuticals, and pesticides [38; 39; 40; 41; 42; 43; 44; 45]. These enzymes are classified as Auxiliary Activity (AA) families in the Carbohydrate-Active enZYmes Database (CaZy database; [[http://www.cazy.org/](http://www.cazy.org/)]([http://www.cazy.org/](http://www.cazy.org/)) accessed on 22 September 2022), which provides an overview of cellulose- and lignin-degrading enzymes for biotechnical applications [46; 47]. Some other enzymes such as vanillyl-alcohol oxidases, glyoxal oxidases, cellobiose/quinone oxidoreductase, and cellobiose dehydrogenase are correlated with lignin degradation through enhancement of the activity of lacases, MnPs, and LiPs [34; 48; 49]. Therefore, it could be useful to utilize these enzymes in order to remove the stains on archival documents and books. This review will illustrate several types of fungal pigments and synthetic dyes present in historical books and paper documents and the possible removal tools which can be represented by the ligninolytic enzymes and dye-decolorizing peroxididases, moreover, their function in known and potential decolorization applications.
# Influence of Altitude on Phytochemical Composition of Hemp Inflorescence: A Metabolomic Approach
## 3 Materials and Methods
### HPLC-Q-Exactive-Orbitrap-MS Untargeted Metabolomics Approach  
Raw data from high resolution mass spectrometry were elaborated with Compound DiscovererTM (Thermo Scientific), that facilitated the peak recognition, retention times arrangement, profile assignment, and isotope pattern [43]. Metabolite identification was based on accurate mass and mass fragmentation pattern spectra against MS-MS spectra of compounds available on mzCloud database (HighChem LLC, Slovakia, [[https://www.mzcloud.org](https://www.mzcloud.org)]([https://www.mzcloud.org](https://www.mzcloud.org))) and in the literature [44]. The ChemSpider Web services ([[https://www.chemspider.com](https://www.chemspider.com)]([https://www.chemspider.com](https://www.chemspider.com))) and Human Metabolome platform ([[https://hmdb.ca/](https://hmdb.ca/)]([https://hmdb.ca/](https://hmdb.ca/))) was used as supplementary confirmation tools. If mass fragmentation pattern did not correspond to any of databases annotated by Compound DiscovererTM software, manual confirmation of their fragments using program ChemDrow was completed.
## 3 Results
### Parameters of Strong Ground Motion
Comparative observations reveal that the sixth floor experienced more significant oscillations and higher amplitudes than the basement, indicating the influence of dynamic amplification resulting from the structure's height and flexibility. The basement exhibits smoother oscillations, whereas the sixth floor displays more complex, higher-frequency vibrations, likely due to resonance. The sixth-floor decay in velocity is slower, which could indicate reduced damping efficiency at higher structural levels. Figure 6 shows amplification in the Fourier spectrum (FS\({}_{\text{sixth floor}}\) vs. FS\({}_{\text{basement}}\)) as a function of the period for different directional components. The highest amplification occurs in the FS\({}_{\text{-NS}}\) (purple) component at a period of 0.36 s, as derived from the Fourier spectrum. This period represents a dominant vibration frequency in the building's dynamic response. At this period, the building absorbs more energy, making it more vulnerable to seismic damage. The mean amplification (red) also shows significant values around this period. The dominant amplification period is 0.36 s, with noticeable peaks in FS\({}_{\text{-NS}}\), FS\({}_{\text{-EW}}\), and the mean. FS\({}_{\text{-EW}}\) (blue) shows smaller peaks around 0.3-0.4 s, while FS\({}_{\text{-UD}}\) (green) remains primarily flat. Beyond 0.5 s, amplification stabilizes, indicating a reduced dynamic response. The results highlight a strong response and potential vulnerabilities at shorter periods, particularly in the NS direction, suggesting the need for targeted mitigation measures. Figure 5: The accelerogram pulse indicator (PI) data recorded in the basement (**a**,**c**) and on the sixth floor (**b**,**d**) of the building. Grey line—original record, blue line—predominant pulse of the record.
## 5 Application of MSWOA in Fault Diagnosis of Analog Circuits
### Fault Diagnosis of Sallen-Key Bandpass Filter Circuit  
#### 5.1.1 Simulation Settings  
The Sallen-Key bandpass filter circuit is presented in Figure 15. Parameters of the circuit were set as follows: the resistor tolerance was rated to 5%, and the capacitance tolerance value was 10%. We applied a sinusoidal excitation signal to the circuit (amplitude 5 Vrms, period 10 kHz), and the voltage signals of the output node were collected.  
As mention above, the maximum fault deviation rate was 40%, and the parameter settings of different fault categories are exhibited in Table 4, where \(\uparrow\) represents the actual value was higher than the normal state, and \(\downarrow\) represents the actual value was lower than the normal state. Table 4 indicates that the Sallen-Key band pass filter circuit had nine kinds of different running states, including one normal state and eight soft fault sates.
# An Optimal Power Control Strategy for Grid-Following Inverters in a Synchronous Frame
## 4 Simulation and Experimental Results
### Experimental Results
It can be noticed that the THD of the output current did not have considerable increase under nonlinear load conditions. Despite the changes in the load conditions under nonlinear or unbalanced loads, the injected power of the LQR-ORT remains accurate without distortion. Figure 11: Experimental results evaluating the performance of the LQR-ORT controller under unbalanced and nonlinear loads. The inverter starts connected to a balanced linear load. At \(t=0.7\) s, event (1) occurs by connecting the unbalanced load. At \(t=2.5\) s, event (2) occurs by connecting the nonlinear load. (**a**) Active power. (**b**) Reactive power. (**c**) Output current showing the transition between balanced and unbalanced load (LEFT), and the transition between unbalanced and nonlinear load (RIGHT). (**d**) Load current showing the transition between balanced and unbalanced load (LEFT), and the transition between unbalanced and nonlinear load (RIGHT).
# Improved 2D Ground Target Tracking in GPS-Based Passive Radar Scenarios
## 3 Ground Target 2D Localization Scheme
### First Stage Spatial Filtering  
This stage focuses on increasing the target echo power to enable detection of small targets in the range-Doppler domain, taking advantage of the beamforming gain in a ubiquitous radar configuration with a set of two simultaneous beams. The selected digital beamforming algorithm operates in the frequency domain after applying the CAF to the  
Figure 3: Proposed two-stage frequency-domain spatial filtering scheme.  
individual surveillance channels. This approach takes advantage of the inherent clutter and target mapping in the range-Doppler domain of the coherent processing stage to isolate the energy of each contributor [20].
* To form the first set of simultaneous beams, digital beamforming techniques were selected under the requirement of sidelobe level control to generate orthogonal beams along with the azimuth sector of the single radiating element. An iterative process was followed to define the \(N\) orthogonal beam steering angles, \(\Phi_{SLL}=\{\phi_{SL,1,}\phi_{SL,2},\ldots,\phi_{SL,N}\}\). The process starts with the first lobe steered to the broad-side, then the steering direction of the adjacent lobes is adjusted to the first null of the initial beam. The process continues with the following adjacent lobes until the entire azimuthal sector of a single radiating element is covered.
* The orthogonal beams design procedure reduces the contribution to signal power in the current beam of targets whose DoAs are the steering directions of adjacent beams. However, the decrease in gain with respect to the maximum at the intersection points of the beams can be greater than 3 dB, negatively affecting the echoes of the targets in those directions (Figure 4). As the main objective of this first stage of spatial filtering is to improve target echoes SNR to allow their detection, beamforming gain losses should be minimized along the whole coverage area. Therefore, a second set of \(N-1\) steering angles, \(\Phi_{LI}=\{\phi_{LL,1},\phi_{LL,2},\ldots,\phi_{LL,N-1}\}\), was defined according to the crossing points of the previous orthogonal beams. Both steering angle sets are merged together in a steering vector to continue the design process, \(\Phi_{D}=[\Phi_{SLL},\Phi_{LI}]\).
* The optimization problem was solved for each steering direction and Doppler shift pair (\(\phi_{D,i},p\)) to compute the weight vector \(\mathbf{w}_{D}(p,\phi_{D,i})\). Applying the weight vectors to the corresponding snapshots in the transformed domain (6), a three dimensional matrix, \(\mathbf{S_{CAF}}[m,p,\phi_{D,i}]\) is obtained. \[\mathbf{S_{CAF}}[m,p,\phi_{D,i}] =\mathbf{w}_{D}(p,\phi_{D,i})^{H}\cdot\mathbf{s}_{z}[m,p]\] \[i =1,\cdots,2N-1\] (6)
# Robust and Secure Data Transmission Using Artificial Intelligence Techniques in Ad-Hoc Networks
## 5 Experiments and Analysis
### Discussion  
As most of the work performed by researchers to detect black hole attacks is performed using DT and RF techniques, we considered DT and RF techniques to compare our proposed hybrid classification SVM with the ANN approach to show the efficacy of the work. From the abovementioned work, it was observed that an improvement of 1.96% in PDR was obtained against DT and 2.99% against RF approach. Similarly, improvement in terms of throughput of 1.05% and 1.27% were observed against DT and RF approaches. An improvement of 13.04% and 16.67% occurred while evaluating delay using the proposed approach in comparison to DT and RF approaches, respectively.
## 4 Data Analysis in Maritime IoT Applications
### Benefits and Limitations
#### 4.3.6 Innovation and Continuous Improvement  
Data analysis can lead to profound insights, revealing new opportunities for improvement and innovation. These insights can drive the development of innovative solutions for challenges in the maritime industry, from energy conservation to automation. Additionally, continuous analysis of data allows for the constant refinement of processes, contributing to the ongoing improvement of maritime operations. It enables organizations to adapt and evolve with changing industry trends, market demands, and technological advancements, ensuring they remain competitive in the long term [90].
###### Abstract  
This paper reports a novel micro-fluxgate sensor based on a double-layer magnetic core of a Fe-Co-B-based amorphous ribbon. The melt-spinning technique was carried out to obtain a Fe-Co-B-based amorphous ribbon composite of Fe\({}_{8.1}\)Co\({}_{24.9}\)Bi\({}_{6}\)Si\({}_{1}\), and the obtained amorphous ribbon was then annealed at 595 K for 1 h to benefit soft magnetic properties. The prepared ribbon showed excellent soft magnetic behavior with a high saturated magnetic intensity (\(B_{\mathrm{s}}\)) of 1.74 T and a coercivity (\(H_{\mathrm{c}}\)) of less than 0.2 Oe. Afterward, a micro-fluxgate sensor based on the prepared amorphous ribbon was fabricated via microelectromechanical systems (MEMS) technology combined with chemical wet etching. The resulting sensor exhibited a sensitivity of 1985 V/T, a wide linearity range of \(\pm\)1.05 mT, and a perming error below 0.4 uT under optimal operating conditions with an excitation current amplitude of 70 mA at 500 kHz frequency. The minimum magnetic field noise was about 36 pT/Hz\({}^{1/2}\) at 1 Hz under the same excitation conditions; a superior resolution of 5 nT was also achieved in the fabricated sensor. To the best of our knowledge, a compact micro-fluxgate sensor with such a high-resolution capability has not been reported elsewhere. The microsensor presented here with such improved characteristics may considerably enhance the development of micro-fluxgate sensors.  
magnetic sensor; micro-fluxgate sensor; MEMS; Fe-Co-B amorphous ribbon +
Footnote †: journal: Micro-fluxgate Sensors
_applied_  
_sciences_  
_Article_  
**Non-Destructive Assessment of the Functional Diameter**  
**and Hydrodynamic Roughness of Additively**  
**Manufactured Channels**  
**[PERSON] 1,*, [PERSON] 2, [PERSON] 1, [PERSON] 1, [PERSON] 1, [PERSON] 1 and [PERSON] 2**  
1 Baker Hughes, Via [PERSON] 2, 50127 Florence, Italy; [EMAIL_ADDRESS] (R.M.); [EMAIL_ADDRESS] (M.P.); [EMAIL_ADDRESS] (L.A.); [PERSON]E.D.P.)  
2 Department of Management and Engineering, University of Padova, Stradella S. Nicola 3, 36100 Vicenza, Italy; [EMAIL_ADDRESS] (M.B.); [PERSON]S.C.)
* Correspondence: [EMAIL_ADDRESS]; Tel.: +39-3510535522  
**Abstract:** Metal additive manufacturing, particularly laser powder bed fusion, is increasingly used in the gas turbine industry for the fabrication of channels with small diameters for conformal cooling and flow passage applications. A critical challenge in this context lies in evaluating aspects such as the geometrical and hydraulic diameters, the effective area and the roughness on the internal surface of the channel that affects the flow functionality. This paper proposes a new method to evaluate the geometrical and functional equivalent diameters, i.e., the hydraulic diameter of cylindrical channels and the mean surface topography height on the internal channel surface, using X-ray computed tomography. The developed methods were validated with experimental flow tests, considering the mean surface topography height to be equivalent to the hydrodynamic sand grain roughness, thereby determining the hydraulic diameter and the associated effective area. The method is a much faster approach to determining the available hydraulic diameter compared to flow tests and offers the possibility of evaluating the internal surface characteristics, with discrepancies between the two approaches being less than \(\pm 3\%\).  
**Keywords:** laser powder bed fusion process; X-ray computed tomography; geometrical and hydraulic diameter; effective area; mean surface topography height
### Advancements in Sliding Mode Control  
In recent years, numerous scholars have combined observers with SMC to further enhance the performance of sliding mode controllers by observing disturbances [17; 18]. For instance, some scholars have proposed methods to enhance the robustness of sliding mode controllers applied to permanent magnet linear synchronous motor servo systems [19]. [PERSON] et al. designed an adaptive backstepping complementary sliding mode controller based on a disturbance observer to reduce the impact of parameter or load variations on system control performance [20]. [PERSON] et al. used internal model control to achieve a fast and overshoot-free step velocity response for linear motors and combined a disturbance observer with a sliding mode controller to improve system robustness, though this method was structurally complex [21]. [PERSON] et al. employed adaptive control to estimate the upper bound of uncertain system parameters, designing an adaptive non-singular fast terminal sliding mode to enhance system robustness, with a step position response able to quickly follow the set value in an overshoot-free manner [22].  
In PMSM control systems, step-type or sinusoidal speed commands, or sinusoidal position commands, are typically used to verify control performance [23]. Numerous scholars have extensively studied enhancing the robustness of SMC under such conditions [24; 25]. However, there is less research on step-type position response, and most studies have not verified the robustness of SMC against changes in rotational inertia [26]. For example, one study [27] used the disturbance estimates observed by a state observer as a feedforward compensation term to correct the output of SMC, improving the sliding mode control's robustness against internal parameter perturbations. This enabled the PMSM servo system's position response to better follow sinusoidal command signals even when rotational inertia varied, but there was often overshoot when following step command signals [28]. Another study employed the real-time adjustment of SMC's output based on observed load torque values to enhance its robustness [29]. This method achieved good results in suppressing speed step response overshoot and speeding up response time, but it did not specify whether control performance would be affected by changes in rotational inertia [30; 31].
## 3 Overview of the Inhibitors Targeting the OxPhos Pathway
### NADH Dehydrogenase
Bioenergetic analyses conducted in cells in which the membrane potential was uncoupled from ATP production revealed a decrease in oxygen consumption rates (OCR) in response to the inhibitor, while IMVs showed mercapto-quinazoline-dependent inhibition of ATP production when NADH was the primary electron donor of the respiratory chain. Enzyme kinetic studies further demonstrated non-competitive inhibition of recombinant _M. tb_ Ndh protein [30]. Resistance to the compounds in _M. tb_ was conferred by promoter mutations in ndhA. Interestingly, hypersusceptibility to this class of compounds was observed when ndhA was deleted, suggesting that NDH-1 and other electron donors cannot compensate for the inhibition of NDH-2 by 2-mercaptoethanol-quinazolineones [30]. Chemical optimisation is required to improve the pharmacokinetics (PK) properties of this interesting series [30]. Quinolinequinones (QQ) exert mycobacteriaid activity through NDH-2 inhibition. Interestingly, QQ prevent the emergence of persistent cells in a time- and dose-dependant manner in _Mycobacterium bovis_ BCG in vitro [107]. This scaffold is known for its anti-cancer and anti-inflammatory properties, and can be modified to give rise to derivatives with anti-mycobacterial activity [108; 109; 110]. [PERSON] et al. synthesised a range of 6,7-substituted-5,8-quinolinequinones, and their anti-mycobacterial activities were assessed against _M. bovis_ BCG, in addition to their anti-tumour and anti-inflammatoryproperties [111]. Several compounds containing amine and halogen functionality exhibited tuberculostatic activity in the range 3-12.5 \(\upmu\)g/mL [111]. The derivative QQ8c stimulated NADH oxidation in _M. tb_ and _M. smeg_ IMVs. Ndh overexpression enhanced the stimulation of NADH oxidation [107]. This increase in NDH-2 catalytic activity has been associated with the production of lethal concentrations of ROS. Recently, [PERSON] et al. synthesised a library of 32 new QQ derivatives, with one derivative (16b) showing enhanced in vitro activity against _M. tb_[112]. Activation of NADH-dependent oxygen consumption in _M. smeg_ IMVs in the presence of 16b suggests that this new inhibitor has the same anti-mycobacterial mechanism of action than QQ8c [112]. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Chemical Class** & **Represented by** & **Structure** & **References** \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Structures of the NADH dehydrogenase inhibitors discussed in this review.
## 3 Model Development
### Hybrid RVM-GM Prediction Method
```
1:Input: train dataset \(R_{RVM}\) and \(X_{gray}^{(0)}\), RVM model, regeneration amplitude dataset \(\left\{DH_{k}^{p}\right\}_{k=1}^{M}\), regeneration number dataset \(\left\{NUM_{k}^{p}\right\}_{k=1}^{M}\), SOH threshold \(H_{th}\)
2:while\(i<n-1\)
3:if\(H_{i-1}^{p}>H_{th}\) and \(H_{i-2}^{p}<H_{th}\)
4: set \(\beta^{p}=i-1\)
5:end
6:if the \(s\) cycle regeneration and \(s\in[i-p-q,i-1]\)
7: set \(i=s+1\)
8: set \(H_{j}^{p}=H_{p}^{p}\)
9: set \(H_{i}^{p}=H_{j}^{p}+DH_{j}^{p}-a\cdot\exp(b\cdot k)\)
10: set \(i=i+1\)
11:end
12: set \(j=j+1\)
13: Remove \(H_{i-NUM_{j}^{p}}^{p}\) to \(H_{i}^{p}\) from dataset \(X_{gray}^{(0)}\)
14:else
15:for\(k=1 top\)
16: set \(H_{i-1}^{p}\) as the input of the RVM model
17: predict \(H_{i}^{p}\) by RVM model
18: put \(H_{i}^{p}\) into the dataset \(X_{gray}^{(0)}\)
19: set \(i=i+1\)
20:end
21: predict \(H_{i}^{p}\) to \(H_{i+q}^{p}\) by GRAY model
22: put \(H_{i}^{p}\) to \(H_{i+q}^{p}\) in to set \(X_{gray}^{(0)}\)
23: set \(i=i+q\)
24: set new dataset \(R_{RVM}^{\text{new}}=\left\{R_{RVM_{i}^{p}}\left(H_{i-1}^{p},H_{i}^{p}\right)\right\}\)
25: retrain the RVM model by new \(R_{RVM}^{\text{new}}\)
26: set \(i=i+1\)
27:end
28:end
29: output: end life cycle number \(\beta^{p}\), SOH prediction results \(\left[H_{k}^{p}\right]_{k=a+1}^{n}\)
```  
**Algorithm 1**During the prediction process, all the new prediction results are added to the original sequence to update the GM. However, in contrast to the iterative updating strategy proposed by [15], which adds all the prediction results to the training dataset of the RVM, all we need is the original dataset and the latest prediction results. Because the GM cannot carry out an accurate local prediction, adding all the GM prediction results in the training set of the RVM will reduce the prediction accuracy.
# Onsite Testing for Nonlinear Analysis of an Earthquake Damaged Historical Church in Italy
## 5 Nonlinear Analysis
### Material Modeling  
The used model describes the irreversible damage that occurs during the fracturing process considering the different reductions of the elastic stiffness when unloading for tension and compression and the stiffness recovery effects during cyclic load reversals. The model accounts for the damage variable, which assumes value equal to zero in absence of damage (elastic domain) and equal to one in case of total loss of strength.  
The properties of the materials are considered differently according to the available experimental data. The Young's modulus, the mass density and the Poisson's ratios were already defined by the onsite testing and the model updating reported in Tables 1 and 3. The nonlinear compressive behavior was described through the parabolic model given by [PERSON] [33] in which both softening and limit strain depend on compressive fracture energy (\(G_{c}\)). Then, the material model was calibrated to match the envelop of the loading cycle resulting from the corresponding double flat jack test (DFJ in Figure 18), the results from the test M3 have been applied to both the interior masonry on the south and north sides. The tensile behavior was described according to [PERSON] [34] assuming tensile strengths equal to 6.7% of the corresponding compressive strength (\(f_{t}=f_{c}/15\)), the softening behavior is related to tensile fracture energy (\(G_{t}\)) through an equivalent crack length. The damage functions are derived from the stress-strain relationships of the materials. In Figure 18, the constitutive laws of the tested materials used in the numerical model are represented.  
Regarding the materials without any specific on-site testing results, the stress-strain curves (Figure 19) were obtained from the average experimental values and considering the moduli of elasticity returned from the model updating, the compressive strength is assumed as the average compressive strength from all the double flat jack tests and the other mechanical parameters (\(f_{t}\), \(G_{c}\), \(G_{t}\), Damage) with the same criteria used for the tested materials.