esa-sceva/satcom-chunk-collection huggingface dataset:
# Whole Organ Engineering: Approaches, Challenges, and Future Directions
## 5 Recent Developments and Accomplishments
### Gastrointestinal
The vasculature of the lungs was then seeded with HUVECs by perfusion of cell suspension media through the pulmonary artery and vein. Epithelial cells were seeded into the bronchi in media suspension at a pressure of 80 mmHg followed by a period of perfusion culture through the pulmonary artery for 6 days to allow for endothelialization and epithelialization of the decellularized lung scaffold. The engineered lungs were then transplanted into adult pigs and evaluated for gas exchange and perfusion in vivo. The tissue-engineered lungs not only developed endothelialized vasculature and capillaries as well as a complete epithelium in the bronchial tubes, but the endothelial and epithelial cells rebuilt functional alveo in the decellularized ECM allowing for gas exchange to occur. While the capacity for gas exchange of the engineered lungs was about 50% of that of the native lung in the porcine model, this study is the first to successfully create a whole bioinformatic lung at a clinically relevant scale that recapitulates the function of the native lung in vivo. With further research, this technique could potentially produce clinically relevant bioartificial lungs for human transplant. [PERSON] et al. (2019). [PERSON] et al. (2019), demonstrated that focusing on preservation of GAGs when decellularizing kidneys can result in improved reendothelialization after infusions the kidneys with cells. They found that GAG preservation resulted in enhanced reendothelialization when coupled with preloading of growth factors, as the growth factors utilize GAGs to exert their effects. In addition, they developed a novel perfusion recellularization system that simultaneously infused acellular kidney scaffolds via the arteries and veins, which resulted in significantly improved endothelial covering of the vasculature by the infused endothelial cells derived from iPSCs. The methods presented in this publication were successfully used on both mouse and human cadaveric kidneys. As adequate endothelialization is vital for vasculature to function properly in organs, [PERSON] and colleagues’ work is a notable contribution to whole organ engineering. Their work in retaining specific ECM components during decellularization and developing a novel recellularization method, it translatable to other organs, would be a very useful protocol.
# Effective Use of Flax Biomass in Biorefining Processes
## 3 Results and Discussion
### Selection of Optimal Genotype for the Fiber Flax, Linseed and Dual Purpose
Since it is possible to effectively use both straw and seeds in the cultivation of flax, the total fat content in the seeds of three selected lines of flax was also analyzed (Table 5). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Breeding**} & **Total** & **Straw** & **Seed** & **Plant** & **Technical** & **Panicle** \\  & **Yield** & **Yield** & **Yield** & **Height** & **Length** & **Length** \\ \cline{2-7}  & **(g)** & **(g)** & **(g)** & **(cm)** & **(cm)** & **(cm)** \\ \hline PET 16/20 & \(122.8\pm 14.3\) & \(70.4\pm 8.5\) & \(36.8\pm 3.3\) & \(50.9\pm 3.0\) & \(41.7\pm 1.7\) & \(9.2\pm 1.6\) \\ PET 16/09 & \(113.2\pm 28.2\) & \(70.0\pm 22.9\) & \(28.4\pm 8.7\) & \(67.6\pm 5.2\) & \(50.4\pm 5.4\) & \(17.2\pm 1.3\) \\ PET 16/23 & \(125.2\pm 10.1\) & \(66.8\pm 11.5\) & \(37.6\pm 6.2\) & \(53.4\pm 3.2\) & \(41.2\pm 4.1\) & \(12.2\pm 2.6\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of tested fiber flax lines in terms of yield structure traits. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Breeding**} & **Total** & **Straw** & **Seed** & **Plant** & **Technical** & **Panicle** \\  & **Yield** & **Yield** & **Yield** & **Height** & **Length** & **Length** \\ \cline{2-7}  & **(g)** & **(g)** & **(g)** & **(cm)** & **(cm)** & **(cm)** \\ \hline SW 16/01 & \(153.6\pm 25.3\) & \(57.2\pm 16.2\) & \(52.8\pm 14.8\) & \(43.7\pm 8.6\) & \(33.4\pm 7.5\) & \(10.0\pm 1.9\) \\ SW 16/05 & \(123.2\pm 41.7\) & \(48.8\pm 18.0\) & \(48.0\pm 16.0\) & \(39.4\pm 3.6\) & \(29.7\pm 3.2\) & \(9.6\pm 1.4\) \\ SW 16/08 & \(120.8\pm 23.8\) & \(50.8\pm 14.3\) & \(38.8\pm 5.4\) & \(46.0\pm 2.0\) & \(38.0\pm 2.4\) & \(8.0\pm 1.7\) \\ SW 16/13 & \(143.6\pm 19.9\) & \(64.0\pm 14.6\) & \(48.8\pm 8.3\) & \(44.6\pm 6.6\) & \(35.0\pm 4.0\) & \(9.5\pm 2.6\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of tested dual-purpose lines in terms of yield structure traits. The highest fat content was found in the dual-purpose line SW 16/13. In this respect, it exceeded not only the fiber flax form (PET 16/20) but also the linesed form (PET 16/16). Whereas, fat content in the seeds of linesed forms is higher compared to fiber flax forms, which is confirmed by numerous studies [39; 40]. However, the difference between the best line SW 16/13 and the worst line PET 16/20 was only 2.6%. This proves the high ability of the fat content in flax seeds and the possibility of profitable use of seeds, regardless of the cultivation form.
# Real-Time Circuit Breaker Availability Assessment in the Transmission Network
## 2 State Estimation Model
### Generalized Model  
In the generalized state estimation model, parts of the grid are modeled at the bus CB level. The conventional measurement model (1) is extended with the addition of the CBs status. Additionally, modeling of the switch facilitates the analysis when incorrect switch states occur. For each CB, voltage angles and magnitudes (\(\delta_{nm}\), \(V_{nm}\)), active and reactive power flow (\(P_{nm}\), \(Q_{nm}\)), and probability (\(s_{nm}\)) to be closed are taken into account as additional state variables [29; 30].  
For every CB, we add:  
* measurement equations based on CB status \[\text{CB closed:}\] \[0=\delta_{nn}+v_{\delta}\] (17) \[0=V+v_{V}\] (18) \[\text{CB opened:}\] \[0=P_{m}+v_{p}\] (19) \[0=Q_{m}+v_{Q}\] (20)
* Equations based on the probabilistic model (21)-(24) \[0=s_{nm}\delta_{nm}+v_{s\delta}\] (21) \[0=s_{nm}V_{nm}+v_{sV}\] (22) \[0=(1-s_{nm})P_{nm}+v_{sP}\] (23) \[0=(1-s_{nm})Q_{nm}+v_{sQ}\] (24) \[\bullet\text{CB status equations}\] \[s_{nm}^{m}=s_{nn}+v_{s}\] (25) where \(s_{nm}^{m}\) is the measured status of CBs \(n\)-\(m\). Therefore, flow through the breakers can be written by: \[P_{nm}^{m}=P_{nm}+v_{p}\] (26) \[Q_{nm}^{m}=Q_{nm}+v_{Q}\] (27)
## 4 Performance Analysis
### Engineering Applications  
Data have grown more quickly as science and technology have advanced. In the big data era, people may find a ton of pertinent information. For instance, environmental factors that are regularly studied offer a significant dataset in coal mine safety. The feed-forward network random weighting algorithm presented in this paper is based on the decomposition method, which is more adaptable, divides a large dataset into local datasets rather than using sampling to reduce it, preserves the integrity of the original dataset, and is thus better suited for use in real-world engineering applications.
# Packet Injection Exploiting Attack and Mitigation in Software-Defined Networks
## 1 Introduction
It identifies malicious hosts who inject fake hosts by verifying information consistency. The simplified DoS detection module detects false nodes based on OpenFlow message and flow features. The flow rule management module is responsible for installing blocking rules against the attack source. These modules cooperate to protect the SDN network effectively. The contributions of this paper can be summarized as follows:  
* We propose the packet injection exploiting attack against SDN. To prove the feasibility of this attack, we carry out experiments in a software environment. The results demonstrate that this attack can effectively affect the control plane and the data plane. * In order to defend against the packet injection exploiting attack, we design and achieve PIEDefender on the SDN controller. This scheme is protocol-independent and does not require additional hardware equipment and any data plane modification. * We evaluate the PIEDefender in the injection detection precision, DoS detection precision, and defense overhead. The results demonstrate that the PIEDefender effectively mitigates the packet injection exploiting attack with limited overhead. The rest of the paper is organized as follows. In Section 2, we survey the background and related work. We demonstrate the feasibility of the packet injection exploiting attack and analyze the consequences in Section 3. We detail the implementation of the PIEDefender in Section 4 and performance evaluation in Section 5. Finally, we conclude our work in Section 6.
# Cycle Generative Adversarial Network Based on Gradient Normalization for Infrared Image Generation
## 2 Related Theoretical Work
### Loss Functions  
The loss function of the network consists of generator loss and discriminator loss. The former consists of generative adversarial loss, cycle consistency loss and the loss from converting the target domain to the source domain after generating the image. The generative adversarial loss is the loss obtained by the generator from converting the source-domain image to target-domain image. The constructed generative adversarial loss function of generating the target-domain image (infrared image) from the source domain (visible image) is shown in Equation (4).  
\[Loss_{GAN}(GA\_B,D_{Y},X,Y)=E_{y-P_{data}(y)}[\log_{10}D_{Y}(y)]+E_{x-P_{data}( x)}[\log_{10}(1-D_{Y}(GA\_B(x)))] \tag{4}\]  
of which, \(E_{y-P_{data}(y)}\) in the generator \(GA\_B\) is the expected value of the sample image taken in the target domain; \(E_{x-P_{data}(x)}\) is the expected value of the sample image taken in the source domain; y in the function is a sample in the Y sample space (infrared image), and x is a sample in the sample space X (visible image). \(GA\_B(x)\) is the image generated by the generator \(GA\_B;D_{Y}(y)\) is the probability that discriminator D discriminates whether y is a sample from the Y sample space, and \(1-D_{Y}(G(x))\) is the probability of discriminator D discriminating the image generated by generator \(GA\_B\) and judging whether the image is a sample taken from the Y sample space.  
The generative adversarial loss function with the target domain (infrared image) generating the source domain (visible image) is shown in Equation (5).  
\[Loss_{GAN}(GB\_A,D_{X},X,Y)=E_{x-P_{data}(x)}[\log_{10}D_{X}(x)]+E_{y-P_{data}( y)}[\log_{10}(1-D_{X}(GB\_A(y)))] \tag{5}\]  
This loss function is similar to that is used to generate the target-domain image from the source domain.  
The cycle consistency loss function learns both \(GA\_B\) and \(GB\_A\) mappings simultaneously. It expects \(GA\_B(GB\_A(y))\) to generate an image as close to y as possible and \(GB\_A(GA\_B(x))\) to generate an image as close to x as possible. The purpose of cycle consistency loss function is to prevent generator G from overlearning the samples in the Y sample space and thus over-altering the samples in the X sample space. The cycle consistency loss function is shown in Equation (6).  
\[Loss_{cycle}(GA\_B,GB\_A)=E_{x-P_{data}(x)}[||GB\_A(GA\_B(x))-x||]+E_{y-P_{data }(y)}[||GA\_B(GB\_A(y))-y||] \tag{6}\]  
Thus, the final loss function is shown in Equation (7).  
\[Loss(GA\_B,GB\_A,D_{X},D_{Y})=Loss_{GAN}(GA\_B,D_{Y},X,Y)+Loss_{GAN}(GB\_A,D_ {X},X,Y)+\lambda Loss_{cycle}(GA\_B,GB\_A) \tag{7}\]  
where \(\lambda\) is the weighting factor of the cycle consistency loss function.
## 3 Results
### Modeling of the EOPH Diffusion  
The optimal conditions (T = 25 \({}^{\circ}\)C, H = 70%, C = 0.01 \(\mu\)L-g\({}^{-1}\)-cm\({}^{-3}\)) were employed to perform the kinetic study, which controlled the mass percentage of oil as a function of time through simulations of analytical treatments during desorption (Figures 7 and 8). The research found a clear decrease in the mass percentage of essential oil, indicating the desorption mechanism. The diffusion coefficient (\(D\)) was estimated to be approximately 8.77\(\cdot\)10\({}^{-6}\) cm\({}^{2}\cdot\)h\({}^{-1}\) under optimal conditions. Furthermore, the experimental results from the simulation showed that 96.6% of the EOPH was desorbed over a span of 15 days (360 h).  
\begin{table}
\begin{tabular}{c c c c} \hline
**Model** & **Mean of Flux** & **Standard Deviation** & **Coefficient of Variation** \\  & **(g\(\cdot\)h\({}^{-1}\)cm\({}^{-1}\))** & **(g\(\cdot\)h\({}^{-1}\)cm\({}^{-1}\))** & **(\%)** \\ \hline
**Full Factorial Design** & 7.14 & 0.03 & 0.47 \\ \hline
**Coefficient of Determination \(R^{2}\)** & **Adjusted \(R^{2}\)** & **Predicted \(R^{2}\)** & **Adeg Precision** \\ \hline
**0.9999** & 0.9995 & 0.9954 & 120.161 \\ \hline \end{tabular}
\end{table}
Table 7: Statistical parameters of the design experiments model.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Model or Parameter (s)** & **dll** & **Ftest** & **Ptest** \\ \hline Model & 6 & 2335.34 & 0.0158 \\ \hline T & 1 & 11,577.67 & 0.0059 \\ \hline H & 1 & 429.77 & 0.0307 \\ \hline C & 1 & 174.89 & 0.0480 \\ \hline TH & 1 & 211.30 & 0.0437 \\ \hline TC & 1 & 1355.86 & 0.0173 \\ \hline HC & 1 & 262.55 & 0.0392 \\ \hline \end{tabular}
\end{table}
Table 8: Statistical parameters of the polynomial model of flux.  
Figure 7: Simulation of the kinetics of EOPH in the PG according to the optimized model.  
The results of the simulation closely match the experimental data, indicating that the developed analytical model is accurate and can be used to estimate other parameters.
## 2 Spatial Audio Recording Techniques for Soundscape Design
### Recording Techniques
#### 2.1.4 Ambisonic Recording  
Ambisonics is a method of recording and reproducing audio of a sound field in full-sphere surround. Essentially, ambisonics is a multi-channel surround sound format that does not contain any information or requirement for the playback configuration as demanded by other surround sound recording formats. This implies that the ambisonics recorded signals can be used in any playback setups. It is capable of full surround, including height and depth from a single point source in space [49].  
Ambisonics format, or more precisely first order ambisonics (FOA), which is widely known as B-format surround signal, can be achieved by a special type of microphone in the shape of tetrahedron using four nearly coincident capsules. In other words, ambisonics can be simply understood as an extension of \(XY\) stereo recording with addition of the two other dimensions. The four components are labelled as \(W\), \(X\), \(Y\) and \(Z\), where \(W\) is corresponding to an omnidirectional microphone and \(X\), \(Y\), \(Z\) corresponds to three spatial directions, i.e., front-back, left-right, and up-down, respectively, captured using figure-of-eight microphone capsules. For a given source signal, \(S\) with azimuth angle \(\theta\) and elevation angle \(\phi\), ambisonics pans the desired four components as:  
\[\begin{array}{c}W=\frac{S}{\sqrt{2}}\\ X=S\cdot\cos\theta\cdot\cos\phi\\ Y=S\cdot\sin\theta\cdot\cos\phi\\ Z=S\cdot\sin\phi\end{array}\]  
The resulting four-channel signal can then be transcoded into outputs of various formats, from a single source in mono to multichannel surround sound arrays. The major advantage being that with the initial capture, you can use post processing to vary the pan, tilt, zoom and rotation of the sound field, which is hard to achieve with other systems. The limitation of the first order ambisonics is the limited spatial resolution, which affects the sound localization and is only effective in a relatively smaller sweet spot. To improve the performance of first order ambisonics, higher order ambisonics are employed by adding more microphones to record sound field at higher orders. As a result, the reproduction of higher order ambisonics also requires more loudspeakers.  
Figure 4: Dummy heads (from left to right): KEMAR, Brüel & Kjaer 4128 HATS, Head Acoustics HMS III, and Neumann KU-100. Note that Neumann KU-100 dummy head is torso-free.  
Figure 5: Binaural microphones from 3 Dio, Free space binaural microphones.  
Examples of ambisonics microphones in the market include: Sennheiser AMBEO VR Microphone [50], Core Sound TetraMic [51], SoundField SPS200 Software Controlled Microphone [52], as shown in the Figure 6. Moreover, the spherical microphone arrays described in Section 2.1.2 can also be converted into first or higher order ambisonics format. For example, the Eigenmike consists of 32 microphones, which supports up to 4 th order ambisonics. A comprehensive objective and subjective comparative study regarding the use of different ambisonics microphones was conducted in [53; 54].
# Comparison of Cooling Different Parts in a High Pressure Ratio Centrifugal Compressor
## 3 Results and Discussion
### Effects on the Impeller Temperature  
Impeller temperature is a critical parameter for the compressor reliability. The impellers in centrifugal compressors are generally made of aluminum. Aluminum loses its strength at temperatures higher than 500 K. Therefore, this is very important to control the impeller temperature, especially in the area with high stress. The impeller maximum temperatures, with cooling on different walls, are shown in Figure 9.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Cooling Wall** & **Cooling Power (W)** & **Work Input (W)** & **Pressure Ratio** & **Efficiency** \\ \hline Back plate cooling & 2415.978 & 212,922.4764 & 6.83992 & 0.785197 \\ Shroud cooling & 2415.978 & 215,355.0418 & 7.08167 & 0.792815 \\ Diffuser cooling & 2415.978 & 211,545.8032 & 6.78116 & 0.785338 \\ Adiabatic & 0 & 211,763.3036 & 6.76869 & 0.7779 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Compressor performance by cooling on different parts.  
Figure 8: Effect of cooling different walls on the impeller temperature.  
Back plate cooling reduces the impeller temperature the most, while shroud and diffuser cooling do not have any effect on the impeller temperature. Shroud cooling slightly increases the impeller temperature. This is because the shroud cooling considerably increases the pressure ratio and the flow temperature. Meanwhile, the flow temperature near the blade tip is reduced by shroud cooling, as shown in Figure 7. The convective heat transfer coefficient is very high at the tip clearance due to the high velocity of the flow. The impeller losses heat at the tip and gets heat from the flow with higher temperature. As a result of these two heat transfers, one to the impeller and one from the impeller, there is a small increment in solid impeller temperature.  
Diffuser cooling does not have any effect on the impeller temperature because there is no convection between cooled down flow inside the diffuser and the impeller. With 500 W of cooling power on the back plate, the impeller reduced from 549.4 K to 539.88 K. By intensifying the cooling power to 2400 W, impeller temperature drops to 504.5 K. Roughly by each 500 W of extra cooling power on the back plate, the impeller temperature reduces by 10 K.  
Temperature contours in the compressor with cooling on different parts are demonstrated in Figure 7. Back plate cooling reduces the temperature of the air inside the gap area. The high rotational speed of the impeller induces a high convective heat transfer on the impeller back face. By reducing the air gap temperature, the impeller temperature will be reduced.  
Shroud cooling considerably increases the pressure ratio and the flow temperature. Meanwhile, the flow temperature reduces by losing heat to the cooling wall. As a result, based on Figure 10, there is a negligible increment in solid impeller temperature by shroud cooling.  
Figure 9: Temperature contours inside the compressor with cooling on different walls.
## 4 Sensitivity Analysis of RPC-FST
### Monte Carlo Simulation (MCS) Method  
MCS is an accurate technique to solve complex multi-dimensional integrals [37]. The problem solution is transformed into the expectation of the probability model. Meanwhile, statistical analysis is adopted to evaluate the probability approximation of the multi-dimensional integral [38]. The conversion of Equation (5) based on MCS can be expressed as:  
\[P_{f}=\int\limits_{F}I_{F}(x)f_{X}(x)dx=E(I_{F}(x)) \tag{7}\]  
where \(F\) is the failure domain of RPC-FST, and \(I_{F}(x)\) is the indication function of the failure domain, which can be obtained by:  
\[I_{F}(X)=\left\{\begin{array}{c}0\ G(X)>0\\ 1\ G(X)\leq 0\end{array}\right. \tag{8}\]  
Therefore, the failure probability of RPC-FST can be calculated by:  
\[P_{f}=\frac{1}{N}\sum\limits_{j=1}^{N}E\big{(}I_{F}\big{(}x_{j}\big{)}\big{)} \approx\frac{1}{N}\sum\limits_{j=1}^{N}I_{F}\big{(}x_{j}\big{)} \tag{9}\]
###### Abstract  
It is an effective method to prepare geopolymer with recycled brick and concrete fine powder (RP) and slag as main materials for the resource utilization of construction waste. However, its hydration products have large drying shrinkage and high efflorescence risk under normal curing conditions. Until now, the durability of recycled brick and concrete fine powder-slag-based geopolymer (RPSG) has not been well documented, such as drying shrinkage and efflorescence. In this study, the effects of slag content, alkali equivalent and modulus on the durability properties of RPSG were evaluated. The results show: (1) slag can significantly reduce the drying shrinkage and efflorescence of RPSG. (2) The potential for the efflorescence of RPSG increases with increasing alkali equivalent. The drying shrinkage of RPSG increases with the increase of alkali equivalent in the case of a low alkali equivalent (6 wt.% in this paper) and decreases with the increase of alkali equivalent in the case of a high alkali equivalent. (3) The drying shrinkage of RPSG increases with increasing modulus. In contrast, the degree of efflorescence decreases with increasing modulus. In this study, RP-S45-M1.3 Nc (slag content: 45 wt.%; alkali equivalent: 6 wt.%; modulus: 1.3) is the best proportional design for RPSG with excellent durability. Compared to RP-S0-M1.3 Nc, the drying shrinkage of RP-S45-M1.3 Nc is reduced by 76.32%, the capillary porosity is reduced by 60.9%, the visual efflorescence is significantly alleviated, and the early pH value is reduced by approximately 2.0. This paper systematically analyzed the drying shrinkage pattern and the efflorescence pattern of RPSG, which has a positive significance for promoting the recycling of RP from construction waste.  
recycled brick and concrete powder; slag; geopolymer; drying shrinkage; efflorescence