esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 System Description
### Air Spring Modeling  
An air spring is installed between the chassis and unsprung masses to create the active force which can regulate the displacement for the active suspension system. This external force can be controlled by regulating the supply pressure and is computed by  
\[F_{a}=A_{\text{as}}P_{\text{as}} \tag{4}\]  
where \(A_{\text{as}}\) denotes the effective working area and \(P_{\text{as}}\) is defined as the working pressure inside the pneumatic spring.  
Although the pressure inside the air spring is controlled by the airflow, it is also affected by the working conditions, including unmodeled dynamics and parametric uncertainties. Hence, we can describe its nonlinear dynamic model by [11]  
\[\dot{P}_{\text{as}}=\frac{\kappa RT}{v_{\text{as}}}\bigg{(}a_{0}q_{\text{as}}- \frac{P_{\text{as}}A_{\text{as}}(x_{2}-x_{4})}{RT}\bigg{)} \tag{5}\]  
where \(\kappa\) is the polytropic index, \(R\) is the ideal air constant, \(T\) denotes the gas temperature, \(v_{\text{as}}\) represents the volume of pneumatic spring, \(a_{0}\) defines the orifice open area of the solenoid valve, \(q_{\text{as}}\) and denotes the working area of mass flow rate.  
Figure 1: Pneumatic active suspension.  
The air bellow volume can be calculated by the initial height and relative movement of the chassis and unsprung mass, we have:  
\[v_{as}=A_{as}(z_{as0}+x_{1}-x_{3}) \tag{6}\]  
where \(z_{as0}\) is the normal height of the pneumatic spring.  
**Assumption 1**.: _In this study, it is assumed that the valve spool movement is directly proportional to the voltage parameter applied to the pressure control valve. Thus, the dynamic characteristics of servo valve could be neglected in model construction while the orifice working area \(a_{0}\) of the control valve is demonstrated by_  
\[a_{0}=\sigma_{pc}u \tag{7}\]  
_where \(\sigma_{pc}\) denotes the coefficient control factor and \(u\) represents the control voltage._  
Substituting (6) and (7) into (5), we can obtain the dynamic model  
\[\dot{P}_{as}=\frac{\kappa RT}{A_{as}(z_{as0}+x_{1}-x_{3})}\bigg{(}\sigma_{pc}q _{as}u-\frac{P_{as}A_{as}(x_{2}-x_{4})}{RT}\bigg{)} \tag{8}\]  
Consider \(x_{5}=A_{as}P_{as}/m_{ch}\), the dynamic model of the pneumatic actuator is rewritten  
\[\dot{x}_{5}=\frac{\kappa RT}{m_{ch}(z_{as0}+x_{1}-x_{3})}\sigma_{pc}q_{as}u- \frac{\kappa}{(z_{as0}+x_{1}-x_{3})}x_{5}(x_{2}-x_{4}) \tag{9}\]
## 6 Conclusions  
This paper introduces a new technology for providing a fully recycled foundation support system in shallow-depth foundation pits located in soft soil areas, using steel-pipe-pile-anchored sheet piles. It investigates the impact of relevant factors on the stability of the support system through model testing.  
1. The anchoring and pulling effect of the pipe pile significantly restricts structural displacement. The larger the spacing, the smaller the horizontal displacement of the top of the sheet pile.
2. Under conditions of double pipe piles, the displacement of the sheet pile is notably reduced compared to single-pipe-pile configurations. Therefore, increasing the number of pipe piles per unit width of sheet pile effectively mitigates support system displacement.
3. The failure pattern of the model foundation is influenced by the spacing between the pipe pile and sheet pile. A closer spacing restricts the active slip failure surface by the pipe pile, causing changes in its morphology near the pipe and exposing the top surface of the pit. On the other hand, natural slip failure surfaces appear when there is sufficient spacing between the two piles.
4. The maximum horizontal displacement of the top of the pipe pile exhibits a hyperbolic relationship with excavation depth.
5. Displacements measured at both ends of the tie rods show minimal overall variation, indicating consistent deformation of the pipe pile and sheet pile. This parameter is considered crucial in design considerations.  
Figure 17: Comparison of displacement between pipe piles and sheet piles.  
**Author Contributions:** Conceptualization, P.L. and G.W.; validation, Q.L., J.Y. and P.L.; formal analysis, G.W.; data curation, Q.L.; writing--original draft preparation, P.L., J.Y. and Q.L.; funding acquisition, J.Y. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China (No. 52378380, No. 52078474, No. 51779235).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Acknowledgments:** We gratefully acknowledge the financial support of the above funds and the researchers of all reports cited in our paper.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Fast Fractional-Order Terminal Sliding Mode Control for Seven-Axis Robot Manipulator
## Appendix A  
The reason why FOSMC provides benefits in terms of fast convergence is discussed here. Considering the sliding surface of FOSMC as  
\[\mathrm{s}={}_{c}D_{0,t}^{r}e(t)-Ae(t),r\in(0,1],A\in R^{-} \tag{1}\]  
where \(e(t)\) is required to stabilize at the equilibrium point. When selecting the derivative order \(r=1\), (1) is a simple first-order LSM sliding surface. After reaching the sliding surface (i.e., \(\mathrm{s}=0\)), the solved solution in the form of the Mittag-Leffler function is [22]  
\[e(t)=E_{r,1}(t)e_{0}=e_{0}\sum_{k=0}^{\infty}\frac{A^{k}t^{rk}}{\Gamma(rk+1)} \tag{2}\]  
where \(e_{0}=e(t=0)\). When \(r=1\), the solution corresponds to the first integer-order LSM. Its solution is an exponential function as  
\[e(t)=E_{1,1}(t)e_{0}=e_{0}\sum_{k=0}^{\infty}\frac{A^{k}t^{k}}{\Gamma(k+1)}=e _{0}\sum_{k=0}^{\infty}\frac{A^{k}t^{k}}{k!}=e_{0}Exp(At) \tag{3}\]  
Figure 11 shows the result of the time response of FOSMC after reaching the sliding surface. The fractional-order one (\(0<r<1\)) has a faster decay than integer-order (\(r=1\)) in the interval at the  
beginning (transient response); however, the convergence near the steady-state becomes slow. In the beginning, fast convergence is observed. It has a more significant effect on trajectory tracking, which can reduce the relatively large error fast. It explains why the fractional-order derivative allows for a better control performance in SMC for robot manipulator trajectory tracking. However, drawbacks of FOSMC, such as a slow convergence in the terminal interval (i.e., long settling time), exist. In addition, the smaller \(r\) is associated with faster convergence in the transient response part; however, extremely small \(r\) would result in a considerable settling time. Hence, selecting the order of the derivative is a tradeoff problem.  
In order to compensate for the slow convergence in the interval of small values in FOSMC, TSM control is expected to be used because the nonlinear sliding surface in TSM affects convergence speed more efficiently in the interval of a small error. Considering a TSM sliding surface is  
\[s=\dot{e}+\lambda sign(e)|e|^{\beta} \tag{10}\]  
where \(\lambda>0\) and \(0<\beta<1\). After reaching the sliding surface, it yields  
\[\frac{\left|\dot{e}\right|}{\left|\dot{e}\right|}=\lambda|e|^{r-1} \tag{11}\]  
The \(e\) in TSM (i.e., \(\beta\in(0,1)\)) generates larger \(\left|\dot{e}\right|\) than using LSM (i.e., \(\beta=1\)). Moreover, the smaller \(e\) results in a larger gradient, as shown in Figure 14. This signifies that the TSM has fast convergence benefits, especially in the small error field. This is useful to compensate for the drawbacks of FOSMC.  
However, in the case of using TSM in FOSMC, FOSMC, an explicit solution of the sliding surface, such as FOSMC shown in (14), cannot be solved because of the nonlinear term in the TSM sliding surface. Thus, the finite time for reaching the sliding surface and the equilibrium has not been solved in this research.
## 2 Materials and Methods  
### Mechanical Test  
The experimental shoe used in this study was a men's size 42 ANTA sports shoe (Figure 1a). The shoe was treated with an adhesive remover to strip away the upper part, leaving only the sole (Figure 1b). A three-point bending test was conducted on the forefoot section of the sole using a universal testing machine (TSE104B, Wance Group, Shenzhen, China) and a three-point bending fixture. The loading head and the two support beams on the fixture (Figure 1b) were approximately 45 mm wide and 10 mm thick, with a loading head diameter of 10 mm. Based on previous studies [7; 9], the support beams were placed 80 mm apart, with the loading head positioned directly above the midpoint between the beams, aligning with the metatarsophalangeal flexion area of the sole (approximately 73% of the total sole length [25]). The sole was fixed in the fixture, and tests were conducted at loading rates of 7.5 mm/s, 10 mm/s [26], 12.5 mm/s [27], and 15 mm/s [7]. The vertical displacement of the loading head was set to 15 mm for all tests [6]. Each rate was tested ten times [6], with a 3 min interval between tests. Force-displacement curves were recorded for each trial at each rate. Based on a previous study on the FLBS of carbon-plated running shoes which used the three-point bending test, the 80% to 90% segment of the curve range was used to fit a linear equation, with the slope representing the longitudinal bending stiffness of the sole [6]. The full-range fitted curve can be found in the Supplementary Materials (Figure S1). The average stiffness value of the ten trials at each rate was calculated to represent the result at that rate. The fitting equation is shown in Equation (1), where \(F\) is the force (N), \(d\) is the displacement (mm), \(K\) is the slope representing stiffness (N/mm), and \(b\) is the y-intercept of the linear regression:  
\[F=K\cdot d+b \tag{1}\]
# An Efficient On-Chip Data Storage and Exchange Engine for Spaceborne SAR System
###### Abstract  
Advancements in remote sensing technology and very-large-scale integrated circuit (VLSI) have significantly augmented the real-time processing capabilities of spaceborne synthetic aperture radar (SAR), thereby enhancing terrestrial observational capacities. However, the inefficiency of voluminous data storage and transfer inherent in conventional methods has emerged as a technical hindrance, curtailing real-time processing within SAR imaging systems. To address the constraints of a limited storage bandwidth and inefficient data transfer, this study introduces a three-dimensional cross-mapping approach premised on the equal subdivision of sub-matrices utilizing dual-channel DDR3. This method considerably augments storage access bandwidth and achieves equilibrium in two-dimensional data access. Concurrently, an on-chip data transfer approach predicated on a superscalar pipeline buffer is proposed, mitigating pipeline resource wastage, augmenting spatial parallelism, and enhancing data transfer efficiency. Building upon these concepts, a hardware architecture is designed for the efficient storage and transfer of SAR imaging system data, based on the superscalar pipeline. Ultimately, a data storage and transfer engine featuring register addressing access, configurable granularity, and state monitoring functionalities is realized. A comprehensive imaging processing experiment is conducted via a \"CPU + FPGA\" heterogeneous SAR imaging system. The empirical results reveal that the storage access bandwidth of the proposed superscalar pipeline-based SAR imaging system's data efficient storage and transfer engine can attain up to 16.6 GB/s in the range direction and 20.0 GB/s in the azimuth direction. These findings underscore that the storage exchange engine boasts superior storage access bandwidth and heightened data storage transfer efficiency. This considerable enhancement in the processing performance of the entire \"CPU + FPGA\" heterogeneous SAR imaging system renders it suitable for application within spaceborne SAR real-time processing systems.  
s 2023 15, 2885. [[https://doi.org/10.3390/rs15112885](https://doi.org/10.3390/rs15112885)]([https://doi.org/10.3390/rs15112885](https://doi.org/10.3390/rs15112885))  
Article  
An Efficient On-Chip Data Storage and Exchange Engine for Spaceborne SAR System  
2023
## 3 Results and Discussion
### Mesh Independence Study  
The quality of the mesh greatly influences the simulation results; therefore, its assessment is essential. The in-cylinder simulation includes numerous physical models, and during a single cycle, the gradients of thermodynamic parameters can change significantly. Adaptive meshing is very helpful for handling these variations appropriately. However, to accurately model complex physical processes such as injection, an adequately dense mesh is required. During the mesh sensitivity study, three different settings were tested. The base mesh size and the maximum density of the adaptive mesh were varied, as illustrated in Figure 1.  
It can be observed that in the case of the coarsest mesh (base5-amr2), there is a difference of nearly 8 bar in the maximum cylinder pressure, and the pressure rise rate is much lower, indicating that the combustion process is modeled completely inaccurately. In the next iteration (base5-amr3), a slight improvement can be seen; however, the same conclusions as in the previous case still apply. In the third iteration (base4-amr3), a significant change occurred: since cylinder pressure data from test bench measurements was available and the simulated cylinder pressure showed a high degree of agreement with it, there was no justification for using a finer mesh. Therefore, the third iteration was selected for the meshing setup: the base mesh size was 5 mm, and the AMR maximum embedding level was set to 3.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **E10** & **E10 Sur** & **E20** & **E20 Sur** \\ \hline RON [-] & 96.5 & 97.2 & 99 & 99 \\ MON [-] & 85.1 & 88.5 & 87.8 & 88.3 \\ Density [kg/m\({}^{3}\)] & 753.6 & 756.3 & 783.1 & 764.8 \\ H/C ratio [-] & 1.906 & 1.86 & 1.89 & 1.89 \\ O/C ratio [-] & 0.0307 & 0.033 & 0.0614 & 0.0617 \\ LHV [M]/kg] & 42.04 & 41.5 & 40.34 & 40 \\ Stoichi. A/F [-] & 14.019 & 13.87 & 13.42 & 13.34 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Fuel properties.
# The Potential Therapeutic Role of Bruton Tyrosine Kinase Inhibition in Neurodegenerative Diseases
## 3 Bruton Tyrosine Kinase's Inhibitors in Neurodegenerative Disease
### Parkinson's Disease  
PD is the second most common neurodegenerative disorder, affecting 2-3% of the population over 65 years, and is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta, resulting in the hallmark motor symptoms of bradykinesia, rigidity, resting tremor, and postural instability. In addition to motor dysfunction, PD involves a wide array of non-motor symptoms, including cognitive decline, depression, autonomic dysfunction, and sleep disturbances. Pathologically, PD is defined by the accumulation of misfolded \(\alpha\)-synuclein in Lewy bodies and Lewy neurites, as well as widespread neuroinflammation [53; 54]. Microglial activation is observed early in PD progression and is exacerbated in the presence of \(\alpha\)-synuclein aggregates, leading to the release of pro-inflammatory mediators such as IL-1\(\beta\), TNF-\(\alpha\), and prostaglandandins and contributing to neuronal injury by promoting a self-perpetuating cycle of inflammation and neurodegeneration [55]. BTK, which is expressed in microglia and peripheral monocytes, could be involved in mediating TLR4 and Fcy receptor signaling in response to aggregated \(\alpha\)-synuclein [56]. A recent bioinformatic analysis of PD's gene datasets revealed upregulation of BTK [57]. In particular, B lymphocyte populations are altered in PD, with reduced proliferation, decreased regulatory B cells, and increased pro-inflammatory subsets [58]. Experimental models link B-cell depletion and impaired meningeal drainage to worsened \(\alpha\)-synuclein pathology. BTK expression has been proposed as a PD biomarker, supporting the rationale for B-cell-targeted therapies, which may modulate broader immune networks and offer new treatment avenues. Even though BTK is pivotal in B-cell maturation, BTK signaling enhances NF-\(\kappa\)B activation and promotes the assembly of the NLRP3 inflammatory, leading to caspase-1 activation and IL-1\(\beta\) secretion, hallmarks of PD-associated neuroinflammation[59]. The NLRP3 inflammasome is expressed in microglia, astrocytes, and neurons; in PD, \(\alpha\)-synuclein and dopaminergic neuron damage activates NLRP3 in microglia, while Parkin normally suppresses NLRP3 in neurons via ubiquitination [50]. BTK's role in PD suggests that its inhibition could modulate peripheral immune responses implicated in PD progression, as well as detrimental central events: BTK inhibition may limit peripheral immune cell trafficking into the CNS and reduce peripheral cytokine production, providing a dual mechanism of action. Although BTKi evaluations in the PD context show relevant gaps, these preclinical findings provide a strong rationale for their investigation. Given the need for disease-modifying therapies in PD and the role of inflammation in its pathogenesis, BTK inhibition may offer a novel therapeutic avenue with both neuroprotective and immunomodulatory properties.
###### Abstract  
The study aimed to investigate exopolysaccharides (EPSs) produced by two Antarctic yeasts isolated from Livingston Island. The species were identified as _Vishniacozyma victoriae_ (V) and _Tremellomycetes_ sp. (T) based on a molecular genetic analysis of ITS1-5.8S-ITS4 regions of the 18S rRNA gene. The EPS production was investigated under stress conditions in culture flasks and a bioreactor. Different chromatographic (HPLC-RID, HPSEC-RID) and spectral (FT-IR) analyses were employed to characterize EPSs. _Tremellomycetes_ sp. accumulated 7 g/L biomass and 4.5 g/L EPS after 120 h of cultivation. The total carbohydrate content of V-EPS and T-EPS was 75.4% and 79.0%, respectively. The EPSs mainly consisted of mannose (30-32%), which was followed by glucose, xylose, galactose, and small amounts of uronic acids (6.3-7.0%). EPSs had appreciable amounts of proteins (11-12%). The FT-IR spectra contained absorption bands typical for hetero-mannans and \(\beta\)-glucans (979-1033 cm\({}^{-1}\)). EPSs were heterogeneous with a broad molecular weight distribution range (\(47\times 10^{4}\)-68 \(\times 10^{4}\) g/mol). In conclusion, both yeasts synthesized high-molecular-weight heteromannans, and _Tremellomycetes_ sp. stood out as being a better producer than _V. victoriae_. The current study also formed a basis for a better assessment of the potential for practical application of EPSs and yeasts in biochemical engineering and biotechnology.  
Keywords:Antarctic yeasts; polysaccharides; biotechnology; chromatography; spectroscopy +
Footnote †: journal: Applied Sciences
## 3 Methods
### Data Preprocessing
#### 3.1.2 Spectral Data Preprocessing  
In the process of spectral acquisition, due to differences in acquisition time and light, as well as issues with the instrument itself, the original spectrum often contains a great deal of irrelevant information and noise; therefore, the original spectrum must be appropriately preprocessed after acquisition [23]. Common spectral preprocessing methods include baseline calibration methods represented by first-order derivative (D1) and second-order derivative method (D2), smooth denoising methods represented by Savitzky-Golay (SG) convolution smoothing, and Wavelet Transform (WT) to remove high-frequency noise, scattering correction methods represented by Standard Normal Variables (SNV) and Multiplicative Scattering Correction (MSC) to reduce the effect of solid particles. The centering method represented by mean centering, normalization, and Vector Normalization (VN) reduces the error caused by the mathematical operation of matrix inverse. In this study, a large number of combined pretreatment methods were compared, and it was determined that neither the baseline calibration method nor the normalization method played a positive correction role. In this experiment, WT adopts db4 as the wavelet base and uses soft threshold method for noise filtering. Finally, the combination of WT and MSC was selected as the spectral pretreatment method.  
Figure 2: Technology Roadmap.
# Electroless Copper Patterning on TiO\({}_{2}\)-Functionalized Mica for Flexible Electronics
## 2 Materials and Methods
### Copper Patterning and Device Fabrication on TiO\({}_{2}\)-Cated Mica Substrates  
The prepared TiO\({}_{2}\)-coated mica substrates were used for Cu electroless deposition (Cu-ELD), as shown schematically in Figure 1.  
To activate the substrates for Cu-ELD, Ag was photodeposited as a catalyst by exposing the substrate to UV light in an aqueous 0.5 M AgNO\({}_{3}\) solution. A volume of 0.15 mL of the Ag\({}^{+}\) solution was spread onto the surface of a Petri dish, with the TiO\({}_{2}\)-coated mica substrate placed on top. The UV illumination was provided from beneath using a UV LED (LTPL-C034 UVH365, \(\lambda\) = 365 \(\pm\) 5 nm, LiteOn Optoelectronics, Taipei, Taiwan). The UV irradiation intensity at the TiO\({}_{2}\) surface was measured at 16.7 mW cm\({}^{-2}\) using a calibrated optical power meter (Thorlabs PM400 with S175C thermopile detector, Thorlabs, Newton, NJ, USA). Samples were exposed for 2.5 min to achieve a total UV dose (DUV) of 2.5 cm\({}^{-2}\). After photodeposition, the Ag-activated TiO\({}_{2}\)/Mica substrates were rinsed with distilled water, dried with hot air, and immersed into the Cu-ELD bath.  
Figure 1: Schematic of the TiO\({}_{2}\)-functionalization, Ag photodeposition activation patterning, and Cu electroless deposition procedure.  
The Cu-ELD bath comprised 18 g L\({}^{-1}\) CuSO\({}_{4}\cdot\)5H\({}_{2}\)O, 48 g L\({}^{-1}\) EDTA, 57 mg L\({}^{-1}\) concentrated HCl, and 48 mL L\({}^{-1}\) 37% aqueous formaldehyde (HCHO). The pH of the solution was adjusted to 12.3 using 5 M NaOH. Cu-ELD was performed for 1-2 min on Ag-activated TiO\({}_{2}\)/Mica substrates, resulting in the immediate darkening of the Ag-activated areas and the formation of pink Cu layers. Depositions longer than 3 min caused the bubbling and delamination of the copper layer, while those shorter than 1 min resulted in non-conductive layers.  
This method was further applied to study the feasibility of using the Cu-ELD layers in resistance temperature detectors (RTDs). RTD devices were fabricated using selective Ag activation to create a serpentine pattern on the TiO\({}_{2}\)/Mica surface. The serpentine design consisted of a 300 \(\upmu\)m wide copper track with six loops, 1 mm pitch, 8 mm lateral width, and a total length of 55 mm, which is shown in Figure 2a. A 40 \(\upmu\)m thick dry-film negative photoresist was laminated on the substrate and exposed through a photomask at a UV dose of 0.25 J cm\({}^{-2}\). The photoresist was developed in 2 wt.% Na\({}_{2}\)CO\({}_{2}\), followed by Ag activation and Cu-ELD, as described earlier. Prior to the Cu deposition, the photoresist was stripped using acetone. Figure 2b presents a photographic image of a finished Cu-ELD serpentine pattern, deposited on mica.