esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 An Overview of Selected Chemical Crosslinkers
### Edc-Nhs
Furthermore, a recent patent by Geistlich Pharma AG also supported the used of a low-EDC-NHS crosslinking concentration. Their collagen-based sponges (created from a wide variety of mammalian sources) for tissue regeneration in oral cavities have been shown to allow complete regeneration of gingival cells whilst withstanding the forces accompanied by the movement of the jaw and tongue during mastication and speech. This collagen-based sponge was crosslinked using 0.3 g of EDC per gram of collagen [20], which can be expressed as 26% of the standard crosslinking concentration. Similar observations of reduced cellular attachment with EDC-NHS crosslinking were reported with C2C12 mouse cardiomyocytes by [PERSON] et al., as well as platelet and HT1080 fibrosarcomas by [PERSON] et al., on crosslinked collagen films (Type I microfibrillar bovine dermal and Achilles tendon) but not on crosslinked gelatin films (bovine dermal) [15; 17]. The hypothesis emerging from these studies related the observed reduction in the cellular attachment to the ablation of the GXOGER motifs in collagen through the carbodiimide crosslinking process. Due to the availability of RGD motifs for cell binding in gelatin (which is cryptic in collagen), similar decreases in cell binding are not observed with the crosslinking of gelatin. [PERSON] et al. further investigated the effect of EDC-NHS crosslinking on integrin binding with the aim to provide a mechanistic understanding of the manner in which the crosslink modify the collagen backbone to produce the observed reduction in cell attachment [7]. [PERSON] et al. isolated the biochemical receptors which participate in binding with the crosslinked Type I bovine Achilles tendon collagen substrates by characterising the attachment of two integrin I domains (\(\alpha_{1}\) and \(\alpha_{2}\)) and four different model cell lines expressing different collagen-binding integrins: platelets, HT1080 human fibrosarcomas, Rugli rat glioma cells and C2C12 mouse fibroblasts with transfected integrin I domains. Through isolated integrin domain binding and cellular attachment experiments to collagen, the authors were able to conclude that four collagen integrins were affected by the EDC-NHS crosslinking: \(\alpha_{1}\beta_{1}\), \(\alpha_{2}\beta_{1}\), \(\alpha_{10}\beta_{1}\), and \(\alpha_{11}\beta_{1}\). As a result, the mechanism illustrated in Figure 3 was proposed to described the loss of integrin-binding due to the involvement of glutamic acids in the crosslinks formed by EDC-NHS. Since the binding of the I-domain in an integrin is dependent on its coordination with a divalent cation supported by MIDAS (metal ion dependent adhesion site) motifs, the loss of glutamates during EDC-NHS crosslinking is suggested to ablate the GXOGER motifs on collagen. At high values of EDC-NHS crosslinking (\(\geq\)10%), the extent of GXOGER ablation caused by the carbodiimide has been suggested to promote non-native cellular interactions with the substrate [7].
# A GPU-Accelerated Method for 3D Nonlinear Kelvin Ship Wake Patterns Simulation
## 3 Banded Preconditioner JFNK Algorithm  
### Jacobian-Free Newton-Krylov Method  
The JFNK method combines the inexact Newton iteration method with the Krylov subspace method. Its core content is the Generalized Minimum Residual (GMRES) algorithm, according to the matrix free idea, which uses the finite difference form to approximate the product of the coefficient matrix and vector, avoiding the Jacobian matrix calculation and storage alone. The JFNK method mainly has two processes, namely external and internal iterations. The external iteration is the inexact Newton iteration method, and the damping parameter \(\lambda_{k}\) is used to ensure that the nonlinear residual decreases significantly in each iteration for \(t=0,1,2,\dots\) as follows:  
\[\mathbf{u_{t+1}}=\lambda_{k}\mathbf{\delta u_{t}}+\mathbf{u_{t}},\lambda_{k}\in(0,1] \tag{8}\]  
Its internal iteration is the GMRES algorithm [18], which efficiently solves the correction in inexact Newton iteration; that is, it computes large-scale linear equations as follows:  
\[\mathbf{J(u_{t})}\mathbf{\delta u_{t}}=-\mathbf{F(u_{t})} \tag{9}\]  
where \(\mathbf{J(u_{t})}=\mathbf{\partial F(u_{t})/\partial u_{t}}\) is the Jacobian matrix [19].  
Firstly, the approximate solution of \(\mathbf{\delta u_{t}}\) is found by projecting obliquely onto the Krylov subspace  
\[K_{n}(\mathbf{J_{t}}\mathbf{P^{-1}},\mathbf{F_{t}})=\text{span}\{\mathbf{F_{t}},\mathbf{J_{t}}\mathbf{ P^{-1}}\mathbf{F_{t}},\dots,(\mathbf{J_{t}}\mathbf{P^{-1}})^{m-1}\mathbf{F_{t}}\} \tag{10}\]  
where \(m\) is the value of the subspace dimension.  
An initial linear residual \(\mathbf{r_{0}}\) is defined, given an initial guess \(\mathbf{u_{0}}\), for the Newton correction,  
\[\mathbf{r_{0}}=-\mathbf{F(u_{0})}-\mathbf{J_{0}}\mathbf{P^{-1}}\mathbf{\delta u_{0}} \tag{11}\]  
Subsequently, \(\|\mathbf{r_{t}}\|\) is minimized to a suitable value by the GMRES iteration wherein Jacobian-vector products are approximated with finite difference:  
\[\mathbf{J_{t}}\mathbf{P^{-1}}\mathbf{v}\approx\frac{\mathbf{F(u_{t}+h\mathbf{P^{-1}}\mathbf{v})-\mathbf{F( u_{t})}}}{h} \tag{12}\]  
where \(v\) represents an arbitrary vector used in building the Krylov subspace [20], and \(h\) is a small perturbation  
\[h=\frac{\sqrt{(1+\|\mathbf{u_{t}}\|)h_{mach}}}{\|\mathbf{v}\|} \tag{13}\]  
Finally, the initial guess \(\mathbf{u_{0}}\) can be defined as shown below:  
\[\zeta_{1,1}=0,(\zeta_{x})_{k,1}=0,\phi_{1,1}=x_{0},(\phi_{x})_{k,1}=1. \tag{14}\]  
The nonlinear equations are solved according to the calculation flow of a banded preconditioner JFNK method, as shown in Figure 2. Note that \(\mathbf{v}\) in the figure is a unit orthogonal vector in the orthonormal basis of Krylov subspace.
## 2 Results and Discussion
### Discrimination with Interaction Energy
The above results show clearly that in many cases it is possible to select the correct binder from a set of putative interaction partners. This is the case for Barnase where the interaction with the natural interaction partner Barstar shows the lowest (best) average interaction energy of -913.2 kJ/mol. The same is true for the interaction of \(\alpha\)-Chymotrypsin where also the native complex with Eglin C possesses the lowest average interaction energy of -552.8 kJ/mol. For the third test case shown, the correct interaction of _Bovine_ trypsin with the CMTI-1 squash inhibitor is only the second best solution with an average interaction energy of -588.4 kJ/mol, whereas here the lowest interaction energy of -761.3 kJ/mol was obtained for the non-native interaction with the glycosylase inhibitor. These results demonstrate the potential of our approach. However, it is also apparent that further improvements in the scoring of the possible solutions in addition to the use of these simple interaction energies are required. For example simple scoring functions that neglect factors such as entropic contributions often reward large binding interfaces and therefore tend to favor larger binding partners.
## 4 Results and Discussion
### Test of the Combined Ag/AgCl and Zn Pseudo-Membranes
#### 4.3.2 RED Test  
RED with Maximum Power Point Tracking  
Test were done with two feed water flow rates: 60 mL/ min (Figure 9) and 120 mL/min (Figure 10).  
Figure 8: Anodizing potential of four silver plates; regression lines of 3 and 4 coincide.  
Figure 10: Results of MPPT test of the RED stack equipped with pseudo AEMs (Ag/AgCl) and pseudo CEMs (Zn). Flow rate (H and L) is 120 mL/min.  
Figure 9: Results of MPPT test of the RED stack equipped with pseudo AEMs (Ag/AgCl) and pseudo CEMs (Zn). Flow rate (H and L) is 60 mL/min.  
RED with Constant Current  
Again the stack was tested with constant current as shown in Figure 11.  
Discussion of RED Tests  
The flow rate had a rather large influence on the power density. With 60 mL/min (superficial velocity of 0.5 cm/s), the power density was 5 mW/m\({}^{2}\), and with 120 mL/min (1 cm/s), the power density increased to about 20 mW/m\({}^{2}\). Larger flow rates seemed not to improve the power density.
# Application of Blockchain Technology in Emergency Management Systems: A Bibliometric Analysis
## 5 Discussion
### Theoretical Insights and Practical Applications
#### 5.1.5 IoT Systems and Infrastructure Decentralization  
Cluster #8 highlights the convergence of blockchain and IoT technologies, focusing on eliminating central points of failure and enabling secure autonomous devices. Theoretical models have explored concepts such as proof-of-reputation, distributed trust, and smart contract-based control in large-scale IoT networks [110; 111; 112; 113; 114; 115].  
Practically, blockchains can facilitate secure data exchange in healthcare IoT, wearable devices, and fog computing environments [111; 113]. Solutions such as NetDAO [110] demonstrate how decentralized architectures can address trust issues between devices and gateways, ensure data provenance, and reduce susceptibility to cyberattacks. These features are vital in emergency response systems where reliability and security of sensor networks are critical.
## 5 Results and Performance Analysis
### Security Analysis  
In this section, we presented the security analysis of the proposed framework. We evaluate our framework against DoS and MITM attacks on IoT-enabled Zigbee networks. We employ cryptographic notations and mathematical modelling.  
DOS Attack: This attack may put a victim device on an unending retransmission cycle. The blockchain validators eliminate the single point of failure and prevent DoS attacks. The Zigbee Network Key Sniffing Attack exploits a vulnerability in the key transportation  
Figure 19: End-to-End Delay.  
Figure 20: Average throughput.  
issue of the Zigbee network, all while maintaining the minimum security level. The sniffing attack is prevented by the blockchain, as all the packet data are encrypted.  
Man in the Middle Attacks: The communication between the two parties creates a separate link between them in our model and is signed using ECDSA; the attacker requires access to one of the parties' private keys to steal or alter the messages. Creating a fake private key is computationally impossible and as complex as solving the ECDLP. Because of this, our suggested model is resistant to Man in the Middle Attacks.
###### Abstract
In this study, the city of Mariupol, which was severely damaged in the conflict between Russia and Ukraine on 24 February 2022, was taken as an example. The specific work was as follows: (1) The detection of urban burning areas during the battle of Mariupol was carried out by using public Sentinel-2A/B and Landsat-8/9 satellite images; (2) Temporal coherence image of Sentinel-1A satellite was used to deduce the distribution and evolution of damaged buildings in conflicts with Open Street Map, social media data and open data set, and the reliability of the method was tested by coherence changes of burned buildings. (3) This paper comprehensively evaluates the damage situation of urban buildings in Mariupol and discusses the advantages and limitations of using multi-source medium resolution remote sensing satellites in the assessment of armed conflict damage.
## 2 Key Technology Discussion  
### Linearity Enhancement Techniques  
(1) IM3 Cancellation Techniques:  
Cancellation of the third-order inter-modulation distortions (IMD3s) generated by the carrier and peaking amplifiers is the most important design issue in realizing a linear Doherty power amplifier [1; 2]. The IM3 and fundamental signal of class AB biased carrier amplifier are in anti-phase when gain compression occurs. By contrast, the IM3 and fundamental signal of class B/C biased peaking amplifier are in phase at the beginning of gain expansion. Thus, the IM3s of the two amplifiers can cancel each other in specific power region to improve the linearity of the Doherty amplifier.  
However, due to the RF swing controlled parasitic parameters in GaAs HBT, the phases of IM3 and fundamental signals from carrier and peaking amplifier deviate with input signal. For the linearity of this power amplifier, the \(\pi\)-shaped equivalent circuits of \(\lambda/4\) transmission lines are optimized to compensate the phases of IM3s for cancellation. Meanwhile, bias-controlled PDR is designed to compensate the magnitude of IM3 for cancellation. To validate this theory, a two-tone signal with 100 MHz space was applied in a simulation. Figure 1a,b show that IM3s of carrier and peaking power amplifier have opposite phases from low to moderate signal levels. On the other hand, as shown in Figure 1c,d, the fundamental carrier and peaking power amplifier signals present some phase offsets (40 degree) at a low signal level, but a small deviation (16 degree) in the high power region. It is a trade-off between linearity and PAE. Considering the priority of IM3 cancellation, this optimization is acceptable.  
(2) Adaptive Power Division:  
Adaptive power division is a key innovation that facilitates flattening of the AM-AM characteristic across a wide input power range. By dynamically adjusting the power-dividing ratio (PDR) based on the input signal conditions, the carrier and peaking amplifiers can be optimized to operate in their most linear regions [1; 2; 3; 4]. This is particularly important for reducing the distortion associated with gain compression and expansion in the two amplifiers. The implementation of real-time monitoring and control systems allows for continuous adjustment of the power division, ensuring optimal performance regardless of varying signal conditions. As shown in Figure 2, the bias-controlled PDR technique has a large and accurate dynamic range. This adaptability is vital for maintaining linearity in the context of 5G signals, which often exhibit high peak-to-average power ratios (PAPRs) and complex modulation schemes. In recent research on linear Doherty PAs, this technique has been widely adopted.
## 3 Proposed Method
### Malware Detection Algorithm
#### 3.3.1 Expression of Detection Results  
The results of each detection should be expressed numerically and uniformly to enable the system to handle different result representations from multiple anti-virus engines. Each engine might output different anomaly scores: signature-based methods might present a discrete value of 0 or 1, while machine learning methods might express the maliciousness as a probability value between 0 and 100. Some anti-virus engines might also present additional information, such as malware categories.  
In this study, the output of every engine was normalized to a value between 0 and 1 to obtain a voting value. The proposed system expresses benign results as \"0\" and malicious results as \"1\". If the value output by the engine does not fall within the range, it is normalized using the maximum value the engine can output.
## 4 Discussion
### How Land Use Change Affects Soil Respiration in Tropical Peatland Ecosystems
In comparison with other ecosystems, heterotrophic respiration of intact peat forest in this study was lower than upland tropical rain forests (138 Mg CO\({}_{2}\) ha\({}^{-1}\) yr\({}^{-1}\); [17]), logged peat forests in Jambi (68 Mg CO\({}_{2}\) ha\({}^{-1}\) yr\({}^{-1}\); [25]), and oil palm estate in Jambi (104 Mg CO\({}_{2}\) ha\({}^{-1}\) yr\({}^{-1}\); [25]) and Sarawak (55 Mg CO\({}_{2}\) ha\({}^{-1}\) yr\({}^{-1}\); [24]). Heterotrophic respiration in peat forests was also higher than other wetlands such as mangrove forests in Australia (20 Mg CO\({}_{2}\) ha\({}^{-1}\) yr\({}^{-1}\); [49]) and Thailand (8 Mg CO\({}_{2}\) ha\({}^{-1}\) yr\({}^{-1}\); [17; 50]). The land cover type had no impact on heterotrophic respiration in tropical peat forests landscapes [21; 47]. However, other studies have found that land cover change in tropical peat forests decreases [24] or increases heterotrophic respiration [25]. Rather than affecting heterotrophic respiration, we found that land-use change affects carbon dynamics principally through decreased carbon sequestration rates (NPP).
## 4 Results
### Optimal Placement Strategy for Air Quality Monitors
#### 4.4.3 Ranking of Regions Based on the Comprehensive Index  
After calculating the comprehensive index (S) for all the regions within Gangeo-gu, we ranked the regions based on their scores. This ranking helps prioritize the installation of air quality monitors, starting with regions that exhibit the highest values of S. The top 100 regions, based on their comprehensive index, were identified as the highest priority areas for air quality monitoring.  
By following this systematic approach, we ensured that the placement of air quality monitors was data-driven and targeted areas where they could have the greatest impact. Regions with the highest comprehensive index scores were proposed as optimal locations for the installation of air quality monitors, ensuring that vulnerable populations are better protected from the adverse effects of PM.
# Smart Road Traffic Accidents Reduction Strategy Based on Intelligent Transportation Systems (TARS)
## 2 Literature Review
### Traffic Accident Avoidance and Prevention Based on Routing Scheme
After detecting traffic congestion, the drivers of the vehicles provide multiple options about the magnitude and location to avoid getting stuck in the traffic congestion. In Vehicle 2 Infrastructure (V2I) communication, after detecting traffic congestion in the lane due to a traffic accident, the affected vehicle, which is involved in the traffic accident, broadcasts the warning message to the other forwarder vehicle and RSU to inform them of the present condition of the lane. In this way, the next upcoming vehicle changes their decision to avoid traffic congestion and road accidents. This scheme achieved efficient bandwidth utilization and minimum message overhead. [PERSON] et al. [32] proposed a traffic congestion detection routing scheme to avoid traffic accidents. The beauty of this proposed scheme is that it depends on the data collection and central network infrastructure. In data collision, data are gathered from the real-time environment. Vehicles are equipped with GPS to communicate with other vehicles. Collected data only become beneficial when it is shared with other vehicles, including velocity and present location. When any vehicle broadcasts the message to the path, the forwarder vehicle collects the congestion message and then checks whether the area is congested or not. If not, then the vehicle stores this message in its own memory. Otherwise, it simply shares the congestion location with the other vehicles. The proposed scheme achieved less transmission overhead and efficient utilization of the bandwidth. However, this scheme only worked in a homogenous vehicular environment, but was not tested in a heterogeneous vehicular environment.
# Progress in Transparent Nano-Ceramics and Their Potential Applications
## 4 Transparent Armor Nano-Ceramics
### Alon
The densification of AlN transparent nano-ceramics was regulated by the sintering aids and sintering duration, allowing their optical performance to be efficiently tuned. Furthermore, co-doping with MgO and Y\({}_{2}\)O\({}_{3}\) enhanced densification more effectively than either MgO or Y\({}_{2}\)O\({}_{3}\) alone. The optical test demonstrated that 1 mm-thick fabricated samples of AlON transparent nano-ceramics, doped with 1 wt.% MgO and 0.08 wt.% Y\({}_{2}\)O\({}_{3}\), reached the maximum of 60% in-line transmittance at 600 nm after sintering in N\({}_{2}\) for 12 h at 1950 \({}^{\circ}\)C. In 2018, [PERSON] et al. [91] adopted the pressureless sintering method to fabricate AlON transparent nano-ceramics with CaCO\({}_{3}\) doping. For a sample with a thickness of 2 mm, the transmittance of AlON transparent nano-ceramics doped with a mass fraction of 0.3-0.4% CaCO\({}_{3}\) reached 83-85% at around 3700 nm. In the wavelength range of 200-6000 nm, the transmittance of AlON doped with CaCO\({}_{3}\) was always higher than that of AlON doped with an ideal amount of Y\({}_{2}\)O\({}_{3}\). In 2021, [PERSON] et al. [92] prepared AlON transparent nano-ceramics by HIP assisted by the dissolution of gas inclusions. They investigated the influence of additive content, pre-sintering, HIP, and annealing parameters on the performance of AlON transparent nano-ceramics. The fabricated samples and transmittance curve are depicted in Figure 13, and the sample doped with 0.5 wt.% SiO\({}_{2}\) exhibited the best performance. By comparing different sintering additives and pre-sintering atmospheres,  
Figure 12: Sample size and XRD pattern; (**a**) SEM images of the morphologies, (**b**) particle size distribution, and (**c**) XRD pattern measured of the AlON powders after ball milling [89]. Reprinted with permission from Ref. [89]. Copyright 2022, copyright ScienceDirect. the densification mechanism of the material was studied. The prepared AlON transparent nano-ceramics maintained a high transmittance of 85.8% at 2000 nm. As mentioned above, ALON ceramics have excellent optical and mechanical properties and extremely strong light transmittance (up to 85.2%), which makes them light-transmitting materials with excellent application prospects. Secondly, because of their good wear resistance; good scratch resistance; and light, thin, and strong properties, even if they are rubbed and damaged, the light transmittance will not be affected, so they can be used as a reinforcing material in transparent armor. In the civilian field, because of its high hardness and good durability, it can be used in the casing of precision instruments such as watches and goggles [93].
# A Review-Unguided Optical Communications: Developments, Technology Evolution, and Challenges
## 5 Advancements in Optical Wireless Communications  
This section gives a review of the advancements of OwC technology for the short-range high-data-rate optical connectivity/scanning applications. Today's short-range OwC technology covers light fidelity (Li-Fi), visible light communication (VLC), vehicular visible light communication (V2 LC) and optical camera communication (OCC). The general architecture, working principles, developments, and pros and cons of these OwC technologies are reviewed below.
# Intelligent Handover Decision-Making for Vehicle-to-Everything (V2X) 5G Networks
## 4 Performance Evaluation
### Performance Measures  
In addition to HO KPIs, including HO attempts, successful HOs, failed HOs, delay HOs, pingpong HOs, and prevented unnecessary HOs, packet loss, latency, and energy consumption were used as the QoS parameters involved in measuring the handover performance of V2X networks [31]. In wireless network communication, it is essential to maintain the packet loss and delay at a low rate to decrease the probability of handover issues (unwanted HOs) and increase the occurrence of the number of necessary handovers (wanted handovers). The specifications of the performance measurements are as follows.