esa-sceva/satcom-chunk-collection huggingface dataset:
# Metabolomic Insights into the Potential of Chestnut Biochar as a Functional Feed Ingredient
## 2 Materials and Methods
### Evaluation of the Chestnut Agro-Residue Biochar Extract on E. coli Growth  
The effect was assessed of the CB extract on the growth of two fimbriated _E. coli_ strains, F4 (F4+) and F18 (F18+), which have adhesive fimbriae. These strains were obtained from the collection of the Department of Veterinary Medicine and Animal Science, University of Milan (Italy). Overnight cultures (200 \(\upmu\)L) of _E. coli_ were inoculated into tubes containing 15 mL of Luria-Bertani (LB) medium, supplemented with 0, 25, 50, and 100 \(\upmu\)L/mL of CB extract. Prior to inoculation, bacterial densities were normalized using spectrophotometry (UV/VIS Lambda 365, PerkinElmer, Waltham, MA, USA) at 600 nm (OD\({}_{600}\) = 0.03). The tubes were incubated aerobically at 37 \({}^{\circ}\)C with shaking at 180 rpm. Bacterial growth was monitored by measuring the optical density at 600 nm (OD\({}_{600}\)) at 60-min intervals using a spectrophotometer (UV/VIS Lambda 365, PerkinElmer, Waltham, MA, USA). Bacteria-free tubes containing equivalent concentrations of biochar extract served as blanks. Optical density data were converted to cell counts (CFU/mL) using a calibration curve. The analysis was performed in biological duplicates with three technical replicates each.
## 4 Ge Photodetector Light Coupling Schemes
### Waveguide Photodetectors  
Waveguide integrated photodetectors have been considered to be one of the most promising candidates for overcoming the bandwidth-efficiency tradeoff in normal incidence detectors. In this configuration, a light signal is delivered to the device by in-plane optical waveguide rather than top down, permitting the bandwidth and efficiency to be determined almost independently because the efficiency is specified no longer by the photoabsorption layer thickness, but rather by the waveguide length. Furthermore, large scale integration of Si optical and electrical devices requires all devices to be fabricated on the same planar wafer, which makes an optical waveguide indispensable. Thus integration of a waveguide with photodetectors seems to be a natural choice. The development of Ge-on-Si photodetectors has been going on for more than ten years. In Table 2 and Figure 5, performances reported for some typical Ge photodetectors are summarized.  
\begin{table}
\begin{tabular}{|c|c|c|c|c|c|c|c|} \hline
**Year** & **Reference** & **1 st author** & **structure** & **I\({}_{\text{data(\mu A)\#}}\)** & **Responsivity** & **Highest 3 dB** & **APD** \\  & & & **-1 V** & **@\(\lambda\) = 1.55 \(\mu\)m** & **electrical bandwidth** & **gain-bandwidth** \\  & & & **@\(\lambda\)**–1 V (A/W)** & **(G\(\lambda\)**Hz)** & **product (GHz)** \\ \hline
2000 & [4] & [PERSON]. [PERSON] & NI PIN & 12 & 0.25 & \textasci
## 1 Introduction
Furthermore, through wind tunnel experiments with box girder models, they have proposed a nonlinear aeroelastic self-excited force model, coupling bridge lift and torsion [18]. Additionally, investigations into complex nonlinear fluid-structure interaction phenomena in turbulent flow around bluff bodies have been conducted through wind tunnel tests and numerical simulations [19; 20; 21]. It has been found that the presence of a strong shear layer flow separation contributes significantly to the nonlinearity of aerodynamic self-excited forces, manifested in variations in the amplitude of the first harmonic and the appearance of higher harmonics. As for the nonlinear motion system of bridge flutter, researchers have focused on the critical bifurcation state and post-bifurcation behavior. Research has mainly centered on analyzing various mechanical and aerodynamic characteristics (such as mechanical damping ratio, natural frequency, initial angle of attack, and flutter derivatives) and their influence on the motion behavior of a given cross-section after the critical flutter state [22; 23; 24]. Moreover, the critical state between static and flutter behavior of nonlinear systems is represented by Hopf bifurcations [25]. Measures to suppress the occurrence of flutter motion require attention, primarily in terms of optimizing and controlling the placement of tuned mass dampers [26; 27]. However, previous studies have often concentrated on specific local aspects of nonlinear motion systems, such as establishing wind tunnel models corresponding to bridge structures to analyze flutter motion states, exploring the acquisition and identification of high-order flutter derivatives in nonlinear aerodynamic self-excited forces, and investigating effective energy dissipation and vibration suppression measures post flutter. There remains a relatively limited amount of research focused on establishing nonlinear motion equations for bridge flutter systems and studying critical flutter states and post-flutter motion behaviors. Based on the status of current research, it is evident that nonlinear aerodynamic self-excitation exists, and the discrete values of the nonlinear components of flutter derivatives can be obtained through wind tunnel section model tests. Therefore, this study considers the effect of nonlinear aerodynamic self-excited force on bridges, establishes nonlinear flutter equations for long-span suspension bridges, and fits the function expression of flutter derivatives with respect to reduced wind speed based on the discrete values of flutter derivatives obtained from the literature. Subsequently, the nonlinear bifurcation and limit cycle oscillation phenomena are investigated based on the motion equations, analyzing and determining the bifurcation types and studying the properties of LCO, as well as predicting the development of the relationship between LCO and wind speed. Finally, on this basis, the effects of nonlinear damping and structural nonlinear stiffness on flutter LCO are further considered.
## 5 Background Noise Elimination Method
### Background Elimination and Comparative Analysis
However, the amplitude of the fault frequencies shown in ALO-VMD are larger than shown in other methods. To further evaluate the effectiveness of the five methods, two quantitative indexes, namely, the signal-noise-ratio (SNR) and the root-mean-square error (RMSE), are used [53], and described as follows. \[SNR=10\log\left(\frac{\sum_{i=1}^{N}x^{2}(i)}{\sum_{i=1}^{N}\left(x(i)-\hat{x }(i)\right)^{2}}\right) \tag{39}\]  
\[RMSE=\sqrt{\frac{1}{N}\sum_{i=1}^{N}\left(x(i)-\hat{x}(i)\right)^{2}} \tag{40}\]  
where \(x(i)\) is the original signal, \(\hat{x}(i)\) is the mean value of \(x(i)\), and \(N\) denotes the length of signal \(x(i)\). As shown in Table 5, the signal-noise-ratio (SNR) of the reconstructed signal processed by ALO-VMD is larger than other methods, and the root-mean-square error (RMSE) of the reconstructed signal processed by ALO-VMD is smaller than other methods. It is concluded that the proposed ALO-VMD method has better performance in noise reduction for the double-teeth spalling fault than other methods.
# Blockchain-Embedded Strategic Options for Satellite Operators: Sell, SataS, or Dual?
## 4 Models Including Blockchain Technology
### BR Model: Sell Channel with Blockchain  
By setting Equation (9) equal to zero, we can derive the marginal customers who are indifferent to the choice between the sell channel and SataaS channel. One of the economic aspects that warrants examination is the customization cost associated with integrating blockchain into satellites. This customization cost, denoted as \(c_{b}\), encompasses the expenses incurred when adapting the satellite infrastructure to accommodate blockchain technology. It includes the development of custom smart contracts for secure data transmission, the integration of cryptographic security measures, and the modification of existing satellite systems to align with the principles of decentralization and data immutability that underpin blockchain [43]. Due to the presence of blockchain-related satellite customization costs \(c_{b}\) and unit satellite costs \(c_{r}\), to ensure a non-negative demand, we assume that \(0\leq c_{b}\leq b*e-c_{r}\). Since the upper limit of the launch success probability is 100%, to be consistent with reality, we assume that \(b\in[1,\frac{1}{e}]\). Then, the sell channel demand and the SO's payoff function can be measured as follows:  
\[\begin{split} D_{r}^{B}&=1-\frac{p_{r}^{B}}{be}\\ \pi_{r}^{B}&=(p_{r}^{B}-c_{r}-c_{b})\times(1-\frac{p _{r}^{B}}{be})\end{split} \tag{11}\]  
After the derivation, we arrive at the optimal sell price and profit for the SO in the sell channel, that is, \({p_{r}^{B}}^{*}=\frac{b+c_{r}+c_{b}}{2}\) and \({\pi_{r}^{B}}^{*}=\frac{(c-c_{r}-c_{b})^{2}}{4e}\), respectively.  
Similar to the NR model, both the price and profit increase with the launch success rate and decrease with the unit satellite cost. The difference is that the price and profit in the BR model also increase with \(b\) as well as \(c_{b}\) due to the participation of BCT, and the price in the BR model is higher than that in the NR model because of the added blockchain-related customization costs. The comparison of the returns is not easy to visualize, and we will analyze them in detail in Section 5.
## 3 Results and Discussion
### Characterization of the Parylene C Coating on Cylindrical Zn Stents
#### 3.2.2 Morphology of the Parylene C Coating.  
Atomic Force Microscopy (AFM), performing in a tapping mode, was used to evaluate the surface roughness and the phase differences in the polymeric coating on the Zn stents. The polymer coating morphology was further investigated using both secondary and backscattered electrons at a low beam current and voltage of 10 kV. As shown in Figure 11a, the AFM \"height image\" of the coating suggests relatively even morphology and roughness R\({}_{\text{q}}\), R\({}_{\text{q}}\), and R\({}_{\text{max}}\) of 33.9, 26.8 and 231 nm respectively. The AFM \"phase image\" in Figure 11b reveals good uniformity of the polymer coating over the surface of the Zn stent.  
SEM studies of the coating morphology were conducted after the coated stents had been expanded. Conventional stents are usually deployed by dilating at the site of interest in the arteries using a balloon catheter as a delivery system. When such a stent is dilated, it undergoes a mechanical alteration known as elastoplastic deformation. During this process, the polymeric coating on the stent also undergoes mechanical deformation, forming small crevices (openings) on the surface. These crevices provide potential sites for the corrosion process to begin and then propagate after the sample is exposed to a physiological environment. Figure 12 displays both secondary and backscattered electron SEM images from the surface of an expanded, Parylene C-coated Zn stent. Crevices in the coating, which exposed the uncoated Zn metal, were visible with secondary electron imaging (Figure 12a and Figures S2-S4. EDS analyses of stent surfaces are provided in the Supplementary Information, S5-S8), however, the contrast was greatly improved using backscattered electron imaging, as shown in Figure 12b. Figure 12c displays a backscattered electron image of the uniform polymeric coating before stent expansion, obtained in a dark contrast mode where no crevices were observed.  
Figure 11: AFM images obtained from the surface of Parylene C-coated Zn stents. (**a**) Surface morphology of the coating in a “height” mode. (**b**) Surface image of the polymer in a “phase” mode.
## 3 MRCIF Algorithm
### Code Injection Covert Page Identification Sub-Algorithm  
Hidden page identification aims to detect the virtual page set \(V_{h}\) of the hidden code module in the user space and find the set \(V_{e}\) containing the memory pages where the DLL code module is located in the virtual memory.  
The user-space address range of a process in a 32-bit system is 0-0x7 ffffffff, and in a 64-bit system, it is 0-0x7 ffffffff. According to the address range, the user space page set of the smss process is obtained as \(V_{smss\_u}=\{v_{smss\_addr}|addr<0x7 ffffff\}\). The user space of other processes is obtained in a similar way. The set of user-space memory pages of all processes is represented as \(V_{u}=\cup_{proc}V_{proc_{u}}\).  
To reduce physical memory usage by the operating system, when the same module is used by multiple processes, multiple virtual memory pages are mapped to the same physical memory page \(p\). So, there is no inverse mapping for \(t(v):V\to P\). Therefore, to find the preimage of the physical memory page \(p\), we can only traverse all the virtual memory pages \(v\) and perform the mapping \(t(v)\) to convert the pages. In this way, the preimage set \(V_{e}\) of \(P_{e}\), \(V_{e}=\{v|t(v)\in P_{e}\}\) can be obtained.  
The set \(P_{e}\) contains a part of the driver code module because the header characteristics of the driver module file are the same as that of the DLL file. However, the driver modules are loaded in the kernel space of virtual memory, and they do not appear in the LDR linked list. These pages where these driver modules are located need to be excluded from the detection, so the set of user-space code module virtual memory pages \(V_{u}\cap V_{e}\) is obtained. Finally, whether each virtual page appears in the set \(V_{l}\) is judged, and if a virtual page is not in \(V_{l}\), the virtual page is a covertly injected page. The whole covert page detection process is shown in Algorithm 2.  
```
Input: Virtual memory page set \(V\), Code module page set \(V_{l}\) in LDR linked list, Code module physical memory page set \(P_{e}\) Output: Covert code module virtual page set \(V_{h}\)  Init: \(V_{h}\leftarrow\varnothing\) for each \(V_{proc}\subset V\) do: for each \(v\in V_{proc}\) do: if\(t(v)\in P_{e}\) and \(v\in V_{proc\_u}\) and \(v\
ot\in V_{proc\_l}\) then: \(V_{proc\_h}\gets V_{proc\_h}\cup\{v\}\) end end \(V_{h}=\cup_{proc}V_{proc_{h}}\)
```  
**Algorithm 2**Covert page detection sub-algorithm
# Remote Sensing for International Peace and Security: Its Role and Implications
## 3 Results
### Remote Sensing in Armed Conflicts
[72] used a high-frequency mixed-mode surface wave radar to detect ships for international peace and security purposes. Unmanned Aerial vehicles (UAVs) equipped with a camera and a ground-based sensor has been used for landmine surveying during humanitarian demining [73]. The recommendations based on an extensive review of global peace, security, and development have been made in [PERSON] et al. studies [74]. Another potential utilization of satellite remote sensing in border armed conflicts is tracking compliance with peacekeeping processes. Due to the recent incidents of violence across the international border of South Sudan and Sudan, the UN security council enacted a significant resolution (Resolution-2046). This resolution requires the governments of these two countries to meet several conditions to ensure peaceful settlements of international disputes, including an outright withdrawal of the respective armed forces from their sides of the border or consequences of sanctions under U.N. Charter's Article 41. However, the satellite-based tracking of border areas shows that both nations did not comply with the UN resolution even after the deadline, thus, allowing for the implementation of strict sanctions against both countries [75]. Furthermore, high-resolution satellite images showing aircraft, tanks, trucks, and troops in strategic locations indicate compelling evidence of soon-to-occur attacks. If monitored in near-real-time, such activities can be recognized as an early warning system for preparations and alert civilians about the danger of the attack. A classic example is from Sudan, where satellite-based tracking of artillery troops in a striking distance of Kurmuk area averted a potential disaster by issuing a human security warning that enables civilian people to flee away before the massive bombs strike [76]. On a similar note, in the peace talks between China and India after the conflict in Galwan valley (in 2020), the tensions cease to end after multiple negotiations from both sides about an agreement to withdraw troops from border areas. The data from satellite and aerial images confirmed the disengagement of troops from the border zones, which helped prevent a war-like situation amid COVID-19 peaks [77].
## 6 Conclusions  
This study classifies the current signals of normal, bearing damage, broken rotor bar and short circuits in stator windings of AC induction motors. Among them, we used the signal extractor to capture the current signal of the motor and use HHT to extract its maximum, minimum, average, root mean square and standard deviation features. In addition, we propose feature-selection methods for comparison, including ReliefF that gives feature weights, calculation of SU value indicating the degree of feature influence and FCBF to delete redundant features. Finally, we combined the PSO to optimize the weight of important features and tested the system's noise immunity by adding white noise. We repeated results calculations 200 times to obtain an average accuracy and performed the feature-selection method multiple times. The results showed stable numbers in both features and accuracy. Moreover, using FCBF-PSO to optimize feature weights to identify fault types had better results. The following are the main research results of this study:  
1. In this study, through the comparison of feature-selection methods, ReliefF, SU value and FCBF were used to improve the invalid or poor features on the classifier. Under normal circumstances, the number of features decreased by 72.5%, 76.25% and 87.5%, respectively. In terms of accuracy of classification, only the SU method values decreased slightly by 1.16%. The other two feature screening methods were optimized. When adding severe noise (SNR = 20 dB), the number of features of the three screening feature methods improved. As far as accuracy was concerned, in addition to the obvious improvement of FCBF, the other two methods still could achieve more than 70% classification ability.
2. This study also used a PSO optimization model to optimize the feature weights of the three-phase induction motor signals obtained by the FCBF feature-selection method. This method also preserved all the features of FCBF. Under normal circumstances, its classification accuracy through BPNN could reach 92.85%, which was superior to other feature-selection methods. It also improved the accuracy of 4.59% higher than that of HHT. Then doping it with different noise SNR = 40 dB, SNR = 30 dB and SNR = 20 dB white noise, its accuracy also increased by 4.51%, 3.12% and 3.02%. Therefore, it was shown that this method could obtain a higher classification accuracy.  
Conceptualization, C.-Y.L. and W.-C.L.; Methodology, C.-Y.L. and W.-C.L.; Software, C.-Y.L. and W.-C.L.; Validation, C.-Y.L. and W.-C.L.; Formal Analysis, C.-Y.L. and W.-C.L.; Investigation, C.-Y.L. and W.-C.L.; Resources, C.-Y.L. and W.-C.L.; Data Curation, C.-Y.L. and W.-C.L.; Writing-Original Draft Preparation, C.-Y.L. and W.-C.L.; Writing-Review & Editing, C.-Y.L. and W.-C.L.; Visualization, C.-Y.L. and W.-C.L.; Supervision, C.-Y.L.; Project Administration, C.-Y.L.; Funding Acquisition, C.-Y.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
# Pore Solution Chemistry of Calcium Sulfoaluminate Cement and Its Effects on Steel Passivation
## 3 Results and Discussion
### Pore Solution Analysis
#### 3.1.2 Determination of Aluminate Ion  
Al(OH)\({}_{4}\)\({}^{-}\) was identified in a CSA pore solution for the first time. In this study, this ion was not detected together with the concentration measurement due to the lack of effective techniques. Alternatively, all the ions containing aluminum were converted to Al\({}^{3+}\) in the dilution process and its content was then tested by ICP-MS. To uncover the ion-containing aluminum, a simulation was carried out in PHREEQC using the information from the ion concentration measurement, which found that Al(OH)\({}_{4}\)\({}^{-}\) was the main ion corresponding to aluminum. The species distributions produced by PHREEQC are partly demonstrated in Table 6. [PERSON] [23] also mentioned the existence of Al(OH)\({}_{4}\)\({}^{-}\), but no evidence was provided.  
To verify the existence of Al(OH)\({}_{4}\)\({}^{-}\), Raman spectra was conducted for the leaching solution (CSA-5 min) and a standard solution consisting of 0.1 M NaOH and 0.15 M NaAlO\({}_{2}\) were measured to justify this deduction. The results of this are shown in Figure 2. The Raman spectra of alkaline aluminate solution is well established with the main signals in the range of 500-700 cm\({}^{-1}\)[29]. Thus, the scanning range in this study was set as 500-750 cm\({}^{-1}\). For the standard solution, Figure 2a illustrates that it has a classic Raman spectrum showing only one significant band, centered at approximately 620 cm\({}^{-1}\). This band is considered as the symmetric \(v_{1}\)-AlO\({}_{4}\) stretching of Al(OH)\({}_{4}\)\({}^{-}\) when the concentration of aluminate ion is lower than 0.5 M [30; 31; 32]. As for the leaching solution, since the concentration is much lower, the signal intensity recedes and the noise becomes stronger. However, the shape of the band, as the curve indicates, which also centered at approximately 620 cm\({}^{-1}\), is distinct in Figure 2b. No other prominent bands are found, which means that the ions containing aluminum that exist in the CSA pore solution are mainly in the form of Al(OH)\({}_{4}\)\({}^{-}\), and their concentration can be considered equal to that of Al\({}^{3+}\).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Age**} & \multicolumn{4}{c}{**Species Distribution (mmol/L)**} \\ \cline{2-6}  & **Al** & **Al(OH)\({}_{4}\)\({}^{-}\)** & **Al(OH)\({}_{3}\)** & **Al(OH)\({}^{2+}\)** & **Al\({}^{3+}\)** \\ \hline
1 d & 207.1 & 207.1 & 2.3 \(\times\) 10\({}^{-5}\) & 8.0 \(\times\) 10\({}^{-11}\) & 8.3 \(\times\) 10\({}^{-25}\) \\
3 d & 214.5 & 214.5 & 2.1 \(\times\) 10\({}^{-5}\) & 6.5 \(\times\) 10\({}^{-18}\) & 5.2 \(\times\) 10\({}^{-25}\) \\
7 d & 193.7 & 193.7 & 2.1 \(\times\) 10\({}^{-5}\) & 7.5 \(\times\) 10\({}^{-18}\) & 7.6 \(\times\) 10\({}^{-25}\) \\
28 d & 178.1 & 178.1 & 1.6 \(\times\) 10\({}^{-5}\) & 4.8 \(\times\) 10\({}^{-18}\) & 3.4 \(\times\) 10\({}^{-25}\) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Species distribution of aluminum in CSA pore solution simulated by PHREEQC.
# Abstract  
Virtual reality is considered to be useful in improving procedural skills in dental education, but systems using wearable devices such as head-mounted displays (HMDs) have many problems in terms of long-term use and hygiene, and the accuracy of stereoscopic viewing at close ranges is inadequate. We developed an abutum tooth formation simulator that utilizes a display (spatial reality display--SRD) to precisely reproduce 3D space with naked-eye stereoscopic viewing at close range. The purpose of this was to develop and validate the usefulness of an abutum tooth formation simulator using an SRD. A 3D-CG (three-dimensional computer graphics) dental model that can be cut in real time was output to the SRD, and an automatic quantitative scoring function was also implemented by comparing the cutting results with exemplars. Dentists in the department of fixed prosthodontics performed cutting operations on both a 2D display-based simulator and an SRD-based simulator and conducted a 5-point rating feedback survey. Compared to the simulator that used a 2D display, the measurements of the simulator using an SRD were significantly more accurate. The SRD-based abutum tooth formation simulator received a positive technical evaluation and high dentist satisfaction (4.37), suggesting its usefulness and raising expectations regarding its future application in dental education.  
Subject:subment tooth formation simulator; naked-eye stereoscopy; virtual reality; dental education; 3D tooth model; spatial reality display; head-mounted display; 3D-CG; dentistry; prosthodontics