esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Substitute Ordinary Portland Cement (OPC) by biomass fly ash (BFA) reduce the environmental impact produced by cement-based materials, and at the same time, decreased the economic and environmental burden associated with the landfilling of this waste. This study aims to evaluate the recycling of BFA as supplementary cementitious materials (SCMs) in a commercial screed mortar formulation. Two BFA varieties, both resulting from fluidized bed combustion of forest residues, were used to replace 17, 50, and 67 wt.% of OPC. The influence of simple pre-treatment processes of the BFA, such as sieving and grinding, in the fresh and hardened state properties of the mortars, was evaluated. The BFAs were characterized in terms of chemical (XRF) and mineralogical (XRD) composition, particle size distribution (laser diffraction-COULTER) and morphology (SEM). The prepared formulations were characterized in terms of workability, mass loss upon curing, bulk density, sorptivity (by immersion and capillary), flexural and compressive strength and durability to 25 freeze-thaw cycles. Both of the BFAs are potential SCMs. Substitution of 17 wt.% OPC with BFA complied with the product technical requirements for compressive and flexural strength (10 and 3 MPa, respectively), with the ground and sieved and just sieved BFAs perform slightly better than the as-received BFA.  
biomass fly ash; green buildings; mortar; supplementary cementitious materials; sustainability; waste recycling +
Footnote †: journal: Applied Sciences
# Conservative Interference Injection to Minimize Wi-Fi Sensing Privacy Risks and Bandwidth Loss
## 4 Keystroke Recognition Using Wi-Fi Sensing
### Minimum CSI Sensing Rate for Reliable Sensing  
The result in the previous section was achieved with a CSI data rate of 1300 Hz. To illustrate the importance of this rate, we perform a subsequent experiment in which we change the transmission frequency of the Wi-Fi sensing device (Tx). We setup the devices as in Figure 4 and asked the participant to press a key 50 times. This process is repeated for transmission frequencies varying between 1300 Hz and 20 Hz. We observe what percentage of the 50 keystrokes the system was able to detect from the captured CSI. This is presented in Figure 6.  
In Figure 6, we present a result that demonstrates the effect of the CSI data rate on the keystroke detection algorithm. The x-axis represents the data rate (Hz) of the sensing system, and the y-axis represents the percentage of 50 keystrokes that were detected from the CSI. Then, each plotted point represents an empirical result. Here, we note that _detection_ refers to the ability of the system to extract a keystroke event from the CSI waveform, _not_ the classification accuracy.  
We observe that CSI data rates above 400 Hz are able to detect 100% of the keystrokes. Below this, we see a clear negative trend in the keystroke detection rate as a function of the  
Figure 5: Classification accuracy.  
Figure 6: Impact of CSI Rate.  
CSI data rate. A key point of interest is 200 Hz, below which only 47% of the keystrokes can be detected by the system. This corroborates our analytical finding in Table 1, where the critical data rate for keystroke recognition was 189 Hz. Given that we are discussing the ability to _detect_ keystrokes, these results do not reflect ML performance or the reliance of feature calculation schemes on the sampling rate. Instead, this result demonstrates the importance of dense sampling to reconstruct human movement in sampled CSI time series. This issue is akin to the Nyquist-Shannon sampling problem for sampling any time varying information. Overall, the results in this section demonstrate the importance of the underlying CSI data rate for Wi-Fi sensing systems.
# Proteomics in Forensic Analysis: Applications for Human Samples
## 3 Applications of Forensic Proteomics for Human Samples
### Other Applications of Forensic Proteomics for Human Samples
#### 3.4.7. Fingermark  
In forensic science, fingermarks are valuable evidence for identifying the perpetrator of crime. The ridge pattern of the fingermarks could also contain additional chemical and biological evidence. Proteomics can be used to identify body fluids present in the fingerprints. In particular, matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) IMS allows the direct mapping of foreign body fluids in fingerprints. [PERSON] et al. applied MALDI-TOF IMS to discover traces of body fluids, such as blood and vaginal fluid [35]. Proteolysis of body fluids deposited in fingerprints can be implemented in approximately 12 h (conventional proteolysis) or 2 h using RapiGest-SF surfactant. Vaginal fluid deposited in fingermarks could be identified by spectra and maps related to the peptides of comulin (_m/z_ 1501 and 994) in MALDI-TOF IMS (Figure 6c). The ion intensity maps of _m/z_ 1501 and 994 formed some ridges in the fingermarks, thus confirming the presence of vaginal fluid on the finger. The MS/MS spectrum of the precursor ion [M + H] 1501.91 matched the peptide EQGQTQTQPGSGQR of comulin with the identified ion fragments of 'b' and 'y' and loss of NH3 (Figure 6c). Similarly, fingermarks containing blood showed ion intensity maps of _m/z_ 1529 matched to the hemoglobin alpha-subunit, while _m/z_ 1274 and 1314 matched to peptides of _b_-hemoglobin.  
[PERSON] et al. performed proteomic profiling of fingermarks and identified 52 proteins [51]. Analysis of covariance (ANCOVA) was conducted for 31 proteins that were found in all sample pools to determine the effects of aging on protein abundance. The normalized abundances of 5 proteins were found to increase with age of the finger marks, including keratin, type II cytoskeletal 1 (K2C1), Keratin, type II cytoskeletal 2 epidermal (K22E), Keratin, type I cytoskeletal 9 (K1C9), keratin, type I cytoskeletal 10 (K1C10), and dermcidin (DCD). The authors also investigated the effects of fingers contaminated with saliva, urine, and vaginal fluid on the proteome of finger marks, which showed the presence of approximately 53%, 29%, and 44% of the proteome, respectively. Notably, all potential age-marker keratins were positively identified in the contaminated samples. In addition, unique proteins for the contaminated body fluids could be identified, such as mucin-5B and alpha-amylase-1, salivary acidic proline-rich phosphoprotein 1, carbonic anhydrase 6, cystatin-D for saliva, and uromodulin for urine, whereas no unique protein for vaginal fluid was found. The study, although in the preliminary stage, paves the way for the application of proteomics in determining age-markers of fingermarks.
# An Interleaved DC/DC Converter with Soft-switching Characteristic and high Step-up Ratio
###### Abstract  
This study presents a dc/dc converter featuring soft-switching characteristic, high conversion efficiency, and high step-up ratio. The proposed circuit is composed of two parallel-connected boost converters. Only one coupled inductor is used to replace inductors of the boost converters which are interleaved operated at discontinuous-conduction mode (DCM). The current ripples at the input and the output terminals are reduced due to the interleaved operation. By freewheeling the current of the coupled inductor to discharge the stored electric charges in the parasitic capacitors of the active switches, both active switches can fulfill zero-voltage switching on (ZVS). Owing to DCM operation, the freewheeling diodes can fulfill zero-current switching off (ZCS). Therefore, the power conversion efficiency is improved. The operation principle for each operation mode is analyzed in detail and design equations for the component parameters are provided in this report. Finally, a prototype 200 W 48-400 V converter was implemented and measured to demonstrate the effectiveness of the proposed circuit.  
Keywords:boost converter; discontinuous-conduction mode (DCM); interleaved operation; voltage gain; zero-current switching off (ZCS); zero-voltage switching on (ZVS) +
Footnote †: journal: Applied
# The Effect of the Chemical Composition on Mechanical Properties of CMAS Diopside Glass Ceramics
## 3 Results and Discussion
### Effect of the Al in Glass Composition  
Although no Al ions exist in the diopside crystal, the glass region may contain a small amount of Al. Since the addition of Al\({}_{2}\)O\({}_{3}\) would significantly compromise the bioactivity, as mentioned before, the CMAS diopside GCs samples in this study contained only 2% Al ions (relative to the Ca or Mg ions). Three samples were prepared by replacing 1% of Ca ions and 1% of Mg ions with Al ions. Since the charge for Al is different, the corresponding O ions were added to make the charge balance. The comparison of the average stress-strain curves between the Al-containing sample and original sample is shown in Figure 6a. Note that the sample with the Al ion demonstrates a decreasing flow stress after 0.15 strain. Previous experimental results showed that the addition of Al\({}_{2}\)O\({}_{3}\) to glass would increase the strength [27], so the finding in this study is surprising. To find out the reason, atomistic structures for samples were examined. Notice that voids appeared at larger strains in all three samples. A larger void and a smaller one were found in Figure 6b,c, respectively. It is obvious that the void formation reduces the flow stress. The strength enhancement effect of Al\({}_{2}\)O\({}_{3}\) was not found before 0.15 strain in this simulation, which may be due to the small addition of Al ions. Since the total number of Al ions in these samples is very small, we can directly observe their role in deformation by enlarging their representation in the atomistic structure using the visualization tool OVITO. Figure 6d demonstrates the enlarged Al ions in Figure 6b. We can see there are several Al ions coincidently close to the void in the glass region. Considering the fact that Al tetrahedra are not easily formed by linking the O ions,  
Figure 5: Atomistic structure for CMS diopside GCs with Mg/Ca ion ratios equal to 1.2:0.8 (**a**,**c**) and 0.8:1.2 (**b**,**d**). Ions in (**a**,**b**) are colored according to their shear strain. Ions in (**c**,**d**) are colored according to their displacement vector magnitude.  
it seems to be reasonable that the Al ions aggregating near the crystal-glass interface would tend to promote void or fracture formation. The result shows the fact that the Al ions in CMAS diopside GCs samples are harmful to the materials' ductility.
# Estimating the Observation Area of a Stripmap SAR via an ISAR Image Sequence
## 3 ISAR Imaging and Method for Estimating the Stripmap SAR Observation Area
### ISAR Imaging Principle and Model  
#### 3.2.1 ISAR Imaging Principle  
The 2D ISAR image of the space target in range and Doppler dimension is essentially the projection of the 3D scatterers of the space target on the ISAR imaging plane [23]. As shown in Figure 4, \(r_{l}\) is the radar line-of-sight, \(\zeta\) is the angle between the space target rotation vector \(\mathbf{\omega}\) and the radar line-of-sight direction, and \(\mathbf{r}_{P}\) is the position vector of the scatterer \(P\) on the space target relative to the rotation center.  
The range value of scatterer \(P\) in the ISAR image is expressed as  
\[\mathbf{x}_{P}=\mathbf{e}_{l}\mathbf{r}_{P} \tag{8}\]  
where \(\mathbf{e}_{l}=\mathbf{r}_{l}/|\mathbf{r}_{l}|\).  
The Doppler frequency shift caused by the rotation of the scatterer \(P\) is  
\[f_{dP}=-\frac{2\mathbf{\omega}\times\mathbf{r}_{P}}{\lambda}\mathbf{e}_{l}=-\frac{2\mathbf{e}_ {l}\times\mathbf{\omega}_{eff}}{\lambda}\mathbf{r}_{P} \tag{9}\]  
where \(\mathbf{\omega}_{eff}=\mathbf{\omega}\sin\zeta=(\eta\times\hat{\eta})/|\mathbf{\eta}|^{2}\) is the effective rotation vector of the space target.  
The tangential velocity \(\mathbf{v}_{c}\) corresponding to the effective rotation vector is  
\[\mathbf{v}_{c}=\frac{\mathbf{r}_{l}\times\mathbf{r}_{l}}{\left|\mathbf{r}_{l}\right|^{2}} \times\mathbf{r}_{l}. \tag{10}\]  
From (9) and (10), the projection of the scatterer \(P\) in the direction of \(\mathbf{v}_{c}\), that is, the Doppler value of the ISAR image, is  
\[\mathbf{y}_{P}=-\frac{\lambda f_{dP}}{2\left|\mathbf{\omega}_{eff}\right|}. \tag{11}\]  
After cross-range scaling, the Doppler value of scatterer \(P\) in the ISAR image is  
\[\mathbf{y}_{P}=\mathbf{e}_{d}\mathbf{r}_{P} \tag{12}\]  
where \(\mathbf{e}_{d}=\mathbf{v}_{c}/|\mathbf{v}_{c}|\).  
From (8) and (12), the 2D ISAR imaging projection matrix is expressed as  
\[\mathbf{H}=\left[\begin{array}{c}\mathbf{e}_{l}\\ \mathbf{e}_{d}\end{array}\right]. \tag{13}\]
## 4 Simulation Results
### Case 7: Fuel cost and voltage deviation  
Voltage profile management is essential to ensure system security. Voltage profile improvement reduces the deviation of load bus voltage. A multiobjective function is presented in Equation (21) to reduce the voltage deviations and fuel cost simultaneously. Simulation results show that the fuel cost and voltage deviations using the proposed approach are 802.45 ($/h) and 0.10 (p.u), respectively. Compared with MSA, MDE, MPSO, FPA, and MFO approaches in Table 12, HIC-GWA has significantly reduced the fuel cost and voltage deviations.
# Eigenmode Wavefront Decoupling Algorithm for LC-DM Adaptive Optics Systems
###### Abstract
To achieve simultaneous working of dual correctors, researchers have proposed many decoupling control methods, including the two-step [16], Zernike limited term [17], control signal reset [18], Fourier mode [19], Lagrangian damped least square [20], and the wavelet mode decoupling [21] method. According to the results of reference [22], only two-step, Zernike limited term, and control signal reset methods are effective to suppress coupling aberrations. Other methods cannot make the system work stably for a long duration, due to the large amount of calculation and the accumulation of calculation errors. The two-step method is not suitable for dynamic correction. The Zernike limited items and control signal reset method can provide good results through closed-loop correction in the dual DM system. However, for LC-DM AO systems, LC works in the open loop to improve the energy utilization ratio [12]. The residual cannot be measured using a WFS, and the double DM decoupling method cannot be employed. A study used the Zernike mode to correct wavefront decomposition and proved the feasibility of LC-DM AO systems [13]. However, the fitting accuracy of the DM decreased with an increase in the number of Zernike modes [23]. Cross coupling is serious, and the correction effect must be improved. In this paper, we proposed a wavefront decoupling method based on DM eigenmodes, which used the DM response matrix to construct the eigenmodes, thereby preventing the fitting error of the DM with the Zernike modes. Then, we discussed the wavefront decomposition method based on eigenmodes, and the aberrations in the infrared waveband were decomposed and corrected using the DM. The DM was controlled with eigenmodes to improve the compensation accuracy. The aberration in the visible waveband was compensated by the DM and LC. In order to ensure the aberration generated by LC does not include the aberration that has been corrected by the DM, the decoupling control method of LC and the DM must be studied. The reason for cross coupling between the two correctors was analyzed, and we calculated the projection of the LC response matrix on the DM eigenmode response matrix to obtain the coupling term of the two matrices when correcting the same wavefront. Then, the control signal of LC was reset with the coupling term to realize aberration decoupling between the two correctors, thereby achieving high-precision correction in the visible waveband. Finally, a setup of the LC-DM AO system was developed for a 2 m telescope. The experimental results showed that the proposed method can effectively realize dual corrector decoupling. Compared with the correction accuracy of the traditional Zernike decomposition method, the correction accuracy of the proposed method was considerably improved.
# Satellite Edge Computing for the Internet of Things in Aerospace
## 3 The Architecture and Application Scenarios of Satellite Edge Computing
### Application Scenarios  
According to [22], the typical satellite constellation-based IoT application scenarios are divided into two groups: delay-tolerant applications (DTAs) and delay-sensitive applications (DSAs). We will describe the capabilities of iSat in these two application scenarios.  
For DTA, the satellites provide automatic store-and-forward data communication services in networks [26]. In general, these applications have a characteristic feature of frequent and prolonged temporary disconnections and long propagation delays. A typical application is the ARGO program for global ocean observations using buoys. Considering that the terrestrial system cannot cope with ocean monitoring, the use of satellites could be irreplaceable. Due to the constraints of the orbit, satellites can only provide services in some arcs. Additionally, traditional satellites mainly provide store-and-forward data communication services, which are insufficient for data processing. iSat can load applications in orbit, provide other services, such as data processing in idle arcs, or share its idle resources with other satellites. Thus, as an intelligent node of space edge computing, iSat can provide services for user-ends of different locations, different communication protocols, and different processing algorithms. It improves the resource utilization and service efficiency of the entire space system.  
DSA is an entirely different scenario with strict requirements for low latency and high reliability. In such scenarios, satellite missions are usually initiated by ground control stations. All kinds of information obtained by the satellites are forwarded to the ground for unified processing. This leads to a significant increase in link latency. iSats constitute a space edge computing system, which realizes inter-satellite data interconnection and resource sharing through inter-satellite links. The tasks can be offloaded to other iSats for collaborative processing. This will reduce the amount of data transmission between satellites and ground stations and provide more efficient services.
# Chaotic Pulse-Shaping Filter Based on Root-Raised-Cosine Division
## 3 RRC-Divided Chaotic Filter
### Hybrid Dynamical System
#### 3.2.1 Topological Conjugation  
For a communication system, the information symbols can be recovered from the received signal only if the encoding baseband waveform and the symbol sequence are topologically conjugated [9; 24]. By defining \(\phi_{m}(t)=s(m)\cdot p(t-m)\), we have:  
\[x(t)=\sum_{m=-\infty}^{\infty}s(m)\cdot p(t-m)=\sum_{m=-\infty}^{\infty}\phi_{ m}(t). \tag{13}\]  
The sufficient conditions for the topological conjugation between the chaotic waveform \(x(t)\) and driving symbols \(s(m)(m=-\infty,\ldots,+\infty)\) are [9]:  
_Conditions_: For all \(a,b\in A\), fixed constants \(G,H>0\), and \(\alpha,\gamma>1\):  
1. \(|\phi_{a}(t)|<H\alpha^{-|t|}\);
2. \(\phi_{a}(t)\
eq\phi_{b}(t)\) almost everywhere for \(a\
eq b\);
3. \(max_{a,b}|\phi_{a}(t)-\phi_{b}(t)|<G\cdot\gamma^{-|t|}\), where \(G\in\mathbb  
Because of topological conjugation, we can not only construct a chaotic waveform from a symbol sequence, but we can also reversely recover a symbol sequence from a chaotic waveform.
# A Survey on Underwater Acoustic Sensor Network Routing Protocols
## 4 The Non-Cross Layer Design Method  
In this section, we briefly introduce the traditional non-cross-layer design UASN routing protocols. In recent years, cross-layer design UASN routing protocols have been widely used and investigated. The traditional non-cross-layer design UASN routing protocols are the basis of cross-layer design UASN routing protocols. The cross-layer design routing protocols are mainly modifications or improvements based on non-cross-layer protocols. Therefore, a review of traditional non-cross-layer routing protocols is necessary for the development of UASN routing protocols.  
The underwater acoustic sensor network routing protocols are devoted to providing effective and reliable routing from the source node to the destination node. As discussed in Section 3, in the underwater environment, the propagation speed of sound waves is much slower than RF waves, _i.e._, the propagation delay in UASNs is serious. In addition, in the underwater environment, sound wave attenuation is much more serious than that of RF waves. These problems will become more serious in underwater acoustic sensor networks which are sparse networks (the distances between two nodes are always long). Moreover, underwater sensor nodes are usually powered by batteries and their energy is limited, so how to reduce the energy consumption in underwater acoustic sensor networksis the first important issue for routing protocol design. Almost all routing protocols take the energy consumption into account. In addition, due to the mobility of underwater sensor nodes, the frequently changing network topology will decrease the routing reliability. This mobility therefore should also be considered in routing protocol design to increase the routing reliability. In the following of this section, we will review these routing protocols based on three factors: energy consumption, propagation delay, and node mobility.