esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 MD Simulation Model
### HAp Substrate and HAp/BC Bilayer Models  
To evaluate the interaction between the BC and bone scaffolds with respect to the crosslinking degree, an HAp substrate model was considered, as shown in Figure 2a. We considered HAp (110) as the reference interaction plane, for estimating the possible maximal binding capability, for the highest planar atom density [22; 23]. The HAp model with the (110) surface had rectangular lattice parameters of a = 6.879 A, b = 16.323 A, c = 9.922 A and \(\alpha=\beta=\gamma=90^{\circ}\)[24]. The HAp substrate model was constructed by replicating the lattice with \(7\times 3\times 4\) in each direction. For the accurate description of the HAp substrate's behavior as well as its surface, the additional parameters produced by [PERSON], [PERSON] et al. [25] based on the PCFF were adopted for the bond, angle, and non-bond interaction terms. Periodic boundary conditions were used only for the \(x\) and \(y\) directions for the surface relaxation. The HAp model was equilibrated with the NVT dynamics at 300 K for 1 ns, and with the NPT dynamics at 300 K and 0.1 MPa for 2 ns, prior to merging with the BC model. During the series of dynamics, the HAp model well preserved their initial geometry including the surface region; the resulting HAp substrate had the dimensions of 48.01 \(\times\) 48.98 \(\times\) 38.7 A\({}^{3}\). The HAp/BC bilayer models were prepared by placing the BC models with different crosslinking ratios atop the HAp model, with the spacing of 1 nm. Interactions between HAp and BC occurred under the NVT dynamics at 300 K for 2 ns. As a result, the gap between the two dissimilar materials disappeared naturally, and both came into a full contact with each other, as shown in Figure 2b. Note that during the construction of the HAp/BC bilayer models, a sufficiently thick vacuum layer with a thickness of 7 nm was inserted at the top of the BC to completely remove interactions beyond the unit cell boundary along the z direction. The BC and HAp models were built using commercial software, Materials Studio(r) (Dassault Systemes), and the interactions between the BC and HAp models during MD runs were observed using the open-source code LAMMPS (Sandia Lab.).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Unit Cell Models** & **MMA Monomers** & **PMMA Chains** & **Crosslinking Ratio (\%)** & **Cubic Unit Cell Length (Angs.)** & **Equilibrated Density (g/cc)** \\ \hline BC-80 & & & 81.81 & 45.04 & 1.080 \\ BC-50 & & & 50.00 & 45.11 & 1.075 \\ BC-20 & & & 20.45 & 45.17 & 1.071 \\ BC-0 & & & - & 45.14 & 1.073 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The details of the modeled PMMA microstructures.  
Figure 2: Bilayer model of the HAp and BC models. (**a**) HAp substrate with (110) surface and (**b**) the configuration of the HAp/BC bilayer, at the crosslinking ratio of 80%.
## 4 Controller Tuning Methodology
### Base Case: FR Provided by Diesel Governor
The first two gain parameters (K\({}_{\text{dn}}\) and K\({}_{\text{pn}}\)) belong to inertial and proportional control loops of the VSWT, but the latter two parameters (K\({}_{\text{i,d}}\) and K\({}_{\text{p,d}}\)) represent the gains of the diesel governor. As mentioned above, the proposed SPBA methodology calculates the controller quality index, Z, for thousands of different gain combinations. As a result, a unique combination of gain parameters was found that reflects the minimum FD and reduced or low ISE and IAE during transients. To achieve this unique combination, we considered again a step response of 0.5 p.u (starts from 1.1 to 1.6 p.u) as P\({}_{\text{load}}\). After testing a series of combinations, the controller quality index improves, as shown in Figure 17, with gain parameter values of K\({}_{\text{dn}}\) = 0.47, K\({}_{\text{pn}}\) = 9, K\({}_{\text{i,d}}\) = 14.89, and K\({}_{\text{p,d}}\) = 21.01. Now, the frequency deviation is reduced by 1.8% compared to the base case. This means that the frequency response improved by 1.05 Hz (58.51224 Hz versus 57.45654 Hz). Similarly, the ISE and IAE were reduced by 16.75 and 159.65%, respectively. Furthermore, the inertial and proportional control loop (Figure 14) contribution against the 0.5 p.u increase in load demand is shown in Figure 18. In addition, the hybrid WDPS provides FR support to a maximum load increment of 0.6 p.u (at 10 s) (390 kW at rated power). The effect of pitch compensation is discussed in Section 5. Table 3 shows the various parameters of hybrid WDPS in this scenario (Case B). Figure 17: The VSWT hybrid WDPS response with the proposed control and the retuning of DPP gain parameters.
# AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation
## 3 Proposed Methodology
### Attention Mechanism  
For semantic segmentation, the scene can involve objects (e.g., cars) which are different in views, scales, and lighting. Thus, the features extracted by CNNs corresponding to the same object could have diversities, since CNN filters yield diverse local receptive fields. These diversities in the pixels corresponding to the same label/object cause intra-class inconsistency and affect the segmentation accuracy [29]. Regarding nodule segmentation, the nodules, in general, have different sizes that can yield features with intra-class inconsistency. Consequently, with our framework, we inserted global contextual attention models in both spatial and channel dimensions in the UNet network to explore relationships between features extracted in different layers of the encoder network before feeding to the decoder to reconstruct the segmented images.  
In the next sub-sections, we will present the two attention modules PAWE and CAWE, which help our network to capture contextual information in spatial and channel dimensions, respectively.
## 2 Containers Used for RBMK-1500 Spent Fuel Storage  
Three container types are used for RBMK-1500 spent fuel dry storage at Ignalina NPP site--cast iron (CASTOR(r)), metal-concrete (CONSTOR(r)), and metal-concrete (CONSTOR(r) M2). The third option has increased SF storage capacity and, thus, was not analyzed in this paper. The cast iron container has a cylindrical body manufactured of ductile cast iron. The height of the container is 4.33 m, the diameter is 2.07 m, and the wall thickness is 0.29 m. The container is closed with a leakproof bolted double-lid system. The mass of the cast iron container loaded with RBMK-1500 SF is about 75 tons. The sidewall of a metal-concrete container consists of inner and outer steel cylinders. Reinforced heavy concrete is within the space between these cylinders. The bottom of the container's body is similar, i.e., the space between the two steel plates is filled with reinforced heavy concrete. The total thickness of the sidewall is 0.43 m. The height of the metal-concrete container is 4.58 m, and the diameter is 2.34 m The leakproof lid system consists of a bolted lid and two welded lids. The mass of a metal-concrete container loaded with RBMK-1500 SF is about 88 tons. The dimensions of the inner cavity of a metal-concrete container are the same as a cast iron one; however, from the outside, the metal-concrete container is bigger (see Figure 1). The concrete covers are placed onto the containers when they are transferred and placed in position at the dry storage facility. The concrete covers are not taken into account while modeling dose rates at the top of the containers.  
Originally, the RBMK-1500 reactor was designed to operate with nuclear fuel with 2.0% U-235 enrichment. The Ignalina NPP used this type of fuel until June 1995, after which a new uranium-erbium fuel (2.4%, 2.6%, and 2.8% enrichment containing burnable Er) was introduced [16]. Only RBMK-1500 spent fuel assemblies with 2.0% enrichment are allowed for storage in cast iron and metal-concrete containers at ISFS-1. An RBMK-1500 fuel assembly (FA) consists of two fuel bundles (FB): a lower one and an upper one (see Figure 2). Detailed information on the RBMK-1500 FA was provided in [17]. After removal from the reactor core, the FA is transferred to the water pool for cooling, and, after a certain period of time, it is cut through the middle into two FBs, which are then loaded into 32M baskets for subsequent wet storage. The 32M basket is located in the center of the container and can contain up to 102 spent FBs.
## 2 Materials and Methods  
[Pt(II)(tetra-_tert_-butylsalophen)] was prepared as previously reported [15]. The devices were fabricated by successive vacuum depositions (<10\({}^{-5}\) mbar) of the organic layers and a cathode on a glass substrate covered by a semitransparent electrode. Patterned Indium Tin Oxide (ITO) coated glass substrates from _Kintec_ (100 nm and sheet resistivity about 14-18 \(\Omega\)/sq at room temperature) were used as a transparent anode. A 20-nm thick of Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate layer (PEDOT:PSS) (CLEVIOS PJET HKV2 charge GSD from _Heraus_) was spin coated on the top of ITO glass substrates and was annealed at 100 \({}^{\circ}\)C for 10 min. PEDOT:PSS was used as hole injection layer. Thin layers of \(N\),\(N^{\prime}\)-Di(1-naphthyl)-\(N\),\(N^{\prime}\)-diphenyl-(1,1\({}^{\prime}\)-biphenyl)-4,4\({}^{\prime}\)-diamine (NPD) and Alq\({}_{3}\) (sublimated grade purchased from _Kintec_) were used as the hole (HTL) and electron (ETL) transporting layers respectively. A 150-nm thick calcium layer (99.99% from Aldrich) was used as the cathode. The doping of emissive layer with 5% of Pt(II) complex was performed by co-evaporation of Alq\({}_{3}\) as host material at a rate of 1 A/s and the Pt(II) complex labeled [Pt] at a rate of 0.055 A/s. The thickness of organic films was determined in situ by quartz-crystal monitor. The thickness and the homogeneity of the resulting films were controlled by profilometry (TENCOR P2 stylus profilometer) and AFM measurements (Dimension TM 3100 Atomic Force Microscope (Digital Instruments)). Monolayer device structures were: ITO/PEDOT:PSS/emissive layer (EML)/Ca. With Alq\({}_{3}\) doped with 5% [Pt] as EML. In bilayer devices, NPD was added between the ITO/PEDOT:PSS anode and EML. The active area of the devices was 18.3 mm\({}^{2}\). Schematic and energy band diagrams with the energy levels of the OLEDs are illustrated in Figure 1a,b, respectively. The The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) levels were previously estimated from cyclic voltammetry measurements [15].  
Characterizations of the OLEDs were obtained under inert atmosphere. Current-luminance-voltage (J-L-V) measurements were carried out by using current-voltage source (_Keithley_, model 2450). The electroluminescence (EL) spectra and the luminance of the OLEDs were measured by using a Spectroradiometer (_JET SpecBos_ 1201). For stability measurements, the current and the luminance of devices were recorded every 30 s at a constant driving voltage of 8 V. The stability of the following structures were studied: ITO/PEDOT/NPD(55 nm)/Alq\({}_{3}\)(85 nm)/Ca and ITO/PEDOT/NPD(55 nm)/Alq\({}_{3}\):5% [Pt] (85 nm)/Ca labeled as non-doped and doped devices respectively.
## 4 Ternary and Multivariate Mn-Based Multi-Metal Oxide Catalysts  
As research progresses, scholars have identified persistent issues in the denitrification performance, water resistance, and sulfur resistance of Mn-based binary SCR catalysts, which pose challenges for industrial applications. Consequently, a large number of researchers have experimented with doping one or more metal oxides into these binary catalysts, aiming to enhance their denitrification efficacy and improve their resistance to water and sulfur poisoning. This has led to the development of high-performing ternary and multi-element Mn-based metal oxide catalysts. This paper categorizes these catalysts into MnOx-CeO2-X, MnOx-TiO2-Y, and other multi-metal oxide catalysts. Table 4 provides a summary of the catalytic performance of representative ternary and multi-element Mn-based metal oxide catalysts in the NH3-SCR reaction.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Catalyst** & **Preparation Method** & **Reaction Condition** & **Denitrification Activity** & **Refs.** \\ \hline Mn-Ce-Ti & sol–gel & (NO) = (NH3) = 300 ppm, 3\% O2, & (125–275 \({}^{\circ}\)C) \textgreater{}80\% & [70] \\ Mn-Ce-Pr & one-step impregnation & (NO) = (NH3) = 600 ppm, 5\% O2, & (180–345 \({}^{\circ}\)C) \textgreater{}90\% & [71] \\  & & & GHVS = 108,000 h\({}^{-1}\) & (180–345 \({}^{\circ}\)C) \textgreater{}90\% & [72] \\ Mn-Ce-Al & co-precipitation & (NO) = (NH3) = 500 ppm, 5\% O2, & (150–300 \({}^{\circ}\)C) \textgreater{}90\% & [73] \\ Mn-Ce-V & co-precipitation & (NO) = (NH3) = 600 ppm, 6.5\% O2, & (122–400 \({}^{\circ}\)C) \textgreater{}80\% & [74] \\ Mn-Ce-Sn & co-precipitation & (NO) = (NH3) = 1000 ppm, 2\% O2, & (80–230 \({}^{\circ}\)C) \textgreater{}100\% & [75] \\  & & & GHVS = 35,000 h\({}^{-1}\) & \\ \hline \end{tabular}
\end{table}
Table 4: Representative ternary and multi-component Mn-based metal oxide catalysts and their denitration activity in the NH3-SCR reaction.
# An NFC on Two-Coil WPT Link for Implantable Biomedical Sensors under Ultra-Weak Coupling
## 2 Dual-Carrier NFC System
### Dual Carriers  
The power carrier operates at 2 MHz (\(f_{\text{P}}\)) in consideration of the less energy loss upon biological tissues [20]. The downlink data are modulated on the power carrier. The downlink uses BPSK instead of ASK, which is widely used in RFID, because ASK reduces PTE due to the unavoidable carrier amplitude variation.  
The uplink data are modulated on the uplink carrier by using BPSK. The uplink carrier operates at 125 kHz (\(f_{\text{ul}}\)). It is \(\frac{1}{16}\)-times lower than \(f_{\text{P}}\) and offers sufficient transition band span to simplify the out-body receiving filter. The lower frequency of the uplink carrier also helps to keep away from the interferences of the power carrier harmonics.  
Since the uplink carrier is transferred through the inductive link resonated at 2 MHz, the 125-kHz uplink signal could be attenuated seriously through this link. In order to guarantee the reliable uplink communication, the minimum receiving signal power of the uplink is analyzed and guaranteed to be sufficient for the reliable demodulation in our operating range. The details will be presented in Section 4.
# Development of an Artificial 3D Liver Phantom for Analysis of Radiotherapeutic Effects In Vitro
## 2 Materials and Methods  
### Three-Dimensional-Printed Liver Model  
A 3D scan of a liver model was created using the Artec Eva 3D scanner (Artec3D, Luxembourg) and the acquired 3D data were postprocessed with Artec Studio 9. As the resulting model was solid and showed no uniform surface, it was shaped in Meshmixer (Version 3.0, Autodesk, San Rafael, CA, USA), where it was hollowed to an outer thickness of 3 mm. To fit the ten MCs (Fluidic 688 interaction chips, Microfluidic ChipShop GmbH, Jena, Germany) [11], holders were constructed using Inventor Professional (Version 2018, Autodesk, San Rafael, CA, USA) with a size of 76.3 mm \(\times\) 3 mm \(\times\) 26 mm each and positioned in the anterior and posterior part of the liver. In this way, MCs were distributed equally within the liver phantom. Additionally, the liver was halved in the anterior-posterior direction, and three straps for fastening the two halves with M6 screws were designed. The designed model was 3D printed with the Obiget500 (Stratasys Ltd., Eden Prairie, MN, USA) using VeroClear(Stratasys Ltd., Eden Prairie, MN, USA) (Figure 1, Supplementary Figure S1A,B). Two holes for filling of agarose were positioned in the cranial part of the liver.  
Figure 1: A 3D-printed liver model from the anterior (**A**), posterior (**B**) and cranial (**C**) side. In (**A**) the inserts for the MCs in the liver phantom are visible. The two holes at the cranial side were used for agarose filling. Schematic figure of MC (**D**) made of polystyrene with media (red) in the cavity for cells.
# Study on the Prediction Method of the Ultra-Low-Cycle Fatigue Damage of Steel
## 3 ULCF Life Prediction for the Q345 qC Base Material and Weld Joints
### ULCF Predictions for Base Material and Weld Joints  
#### 3.2.1 Establishment of a Finite Element Model  
Two-dimensional axisymmetric finite element model is modelled by ABAQUS, (Version 2016, Dassault Systemes Simulia Corp., Johnston, RI, USA) as shown in Figure 3, to simulate the behaviour of  
Figure 5: Post-fracture path of ULCF: (**a**) Base metal specimen and (**b**) weld specimen.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(\Delta\epsilon_{\text{fl}}\)/\% & **Number** & \begin{tabular}{c} **Crack Initial** \\ **Location** \\ \end{tabular} & \begin{tabular}{c} **Fatigue Life** \\ **N\({}_{f}\)** \\ \end{tabular} & \
\begin{tabular}{c} **Fracture** \\ **Life N\({}_{r}\)** \\ \end{tabular} &
\begin{tabular}{c} **N\({}_{f}\)/N\({}_{r}\)** \\ **Fatigue Life N\({}_{f}^{{}^{\prime}}\)** \\ \end{tabular} \\ \hline \multirow{4}{*}{7.0} & BMC01 & Section edge & 78 & 84 & 92.9\% & \\  & BMC03 & Section edge & 76 & 81 & 93.8\% & 77 \\  & BMC21 & Section edge & 78 & 80 & 97.5\% & \\ \cline{2-7}  & WMC04 & HAZ edge & 43 & 46 & 93.5\% & \\  & WMC12 & HAZ edge & 40 & 42 & 95.2\% & 37 \\  & WMC13 & HAZ edge & 29 & 34 & 85.3\% & \\ \hline \multirow{4}{*}{8.0} & BMC05 & Section edge & 51 & 57 & 89.5\% & \\  & BMC08 & Section edge & 55 & 57 & 96.5\% & 59 \\  & BMC22 & Section edge & 72 & 75 & 96.0\% & \\ \cline{2-7}  & WMC15 & HAZ edge & 32 & 35 & 91.4\% & \\  & WMC21 & HAZ edge & 32 & 33 & 97.0\% & 32 \\ \cline{2-7}  & WMC21 & HAZ edge & 33 & 36 & 91.7\% & \\ \hline \multirow{4}{*}{9.0} & BMC04 & Section edge & 47 & 51 & 92.2\% & \\  & BMC17 & Section edge & 41 & 45 & 91.1\% & 44 \\  & BMC18 & Section edge & 45 & 48 & 93.8\% & \\ \cline{2-7}  & WMC03 & HAZ edge & 24 & 26 & 92.3\% & \\  & WMC06 & HAZ edge & 29 & 31 & 93.5\% & 25 \\  & WMC07 & HAZ edge & 24 & 25 & 96.0\% & \\ \hline \multirow{4}{*}{10.0} & BMC15 & Section edge & 41 & 44 & 93.2\% & \\  & BMC16 & Section edge & 30 & 31 & 96.8\% & 34 \\ \cline{1-1}  & BMC19 & Section edge & 33 & 35 & 94.3\% & \\ \cline{1-1} \cline{2-7}  & WMC01 & Weld edge & 17 & 19 & 89.5\% & \\ \cline{1-1}  & WMC08 & Weld edge & 25 & 27 & 92.6\% & 21 \\ \cline{1-1}  & WMC20 & HAZ edge & 21 & 25 & 84.0\% & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Test results for ULCF.  
the base metal specimen, and the monotonic loading is changed to cyclic loading. The weld specimen is modelled by a 3D finite element model, as shown in Figure 6. The weld specimen includes weld metal, HAZ and base metal. Considering the calculation efficiency and accuracy, the weld specimen is modelled by a multi-scale model. The element size in the weld zone is small, and the element size far from the weld zone is large. The minimum element size is 0.2 mm. Mixed hardening model is used to simulate the material constitutive model. Displacement loading mode is adopted in this analysis. The strain amplitudes are 7%, 8%, 9% and 10%.
## 3 Simulation Results  
The SST-VSC incorporated within the inner-outer control loops and voltage droop control maintained both active and reactive power requirements while the SST-VSI fulfilled variable frequency control requirements at the consumer end. The SST-VSC connected with the 11 kV grid, maintained a DC -link \(V_{DC,\mathit{mes}}\) at 20 kV whose specifications are already given in Table 1, while the SST-VSI, specifications given in Table 2, generated variable voltage and variable frequency at the load end.  
Since the proposed circuit was symmetric, so the bidirectional power flow could be achieved just by changing the gate pulses only without any amendment in the circuit. To assess the flexibility and validity of the proposed circuit, simulations using the MATLAB/Simulink environment were carried out for four different test cases: SST to deliver active power, SST as a variable frequency drive, bidirectional power flow interfacing RES and SST as a power factor improvement (PFI) device.
## 1 Introduction
Hence, DEH constitutes a novel and powerful approach for solving dynamic optimization problems with time dependencies and synchronization issues ([PERSON] et al., 2010). Figure 2 shows the evolution, over the last decade, in the number of Scopus-indexed documents referred to the following searching terms: (i) 'TTILE-ABS-KEY ((synchronization OR time dependencies) AND optimization)'; and (ii) 'TTILE-ABS-KEY ((discrete event) AND optimization)'. One can notice that the first search seems to provide an increasing trend over the years, while the second one seems to be more stable in time. As discussed in this paper, however, there is a lack of effective methods in the literature to solve dynamic optimization problems with synchronization issues, which can be certainly complex due to the time dependencies they generate. Figure 1: A simple example of a dynamic optimization problem with synchronization issues. The main contributions of this work are: (i) to provide the theoretical fundamentals of the novel Biased-Randomized DEH (BR-DEH) methodology; (ii) to discuss some examples of how it can be used to solve dynamic optimization problems with time dependencies and synchronization issues; and (iii) to highlight future research perspectives related to BR-DEH algorithms. The remainder of this work is structured as follows. Section 2 provides a precise description of the concept of discrete event simulation. Next, a description of the fundamentals behind BR-DEH algorithms is presented in Section 3, and an overview of the optimization problems that can be solved with BR-DEH algorithms is offered in Section 5. Then, Sections 6 and 7 analyze existing works that employ similar approaches and summarize their computational results, respectively. Finally, conclusions and future research perspectives are reported in Section 8.
## 5 Simulation Results
### Third Case Study  
The effect of feeder impedance on controlling the network is studied in this section. Suppose that the serial branch of the feeder impedance is available in accordance with Table 2. In this case, only 1 digit is in the circuit and supplies the load. At \(t=1\) s, a serial RL branch, similar to what is used in the output of the inverter, connects to the previous branch in parallel. As a result, the impedance of the RL sum branch is halved. It can be observed from diagrams in Figure 11 that not only is there no change in the produced power of the DG unit, but also the circuit frequency only undergoes few fluctuations in high frequencies and goes back to the stable state. Now, with the new filter impedance, at \(t=2\) s load decreases by \(0.2+j\,0.3\) pu. In spite of fluctuation in filter impedance, frequency quickly stabilizes on 50 Hz and the transient error becomes critically damp and power distribution is conducted.  
At \(t=3\) s, the new filter impedance branch disconnects from the circuit, so that the network goes back to its previous state. It can be seen that frequency and power fluctuation dampens after 0.08 s, and stability at the former quiescent point, returns to the system. Figure 15a-d show the output active and reactive powers of DG and its frequency and voltage diagrams, respectively.  
Figure 14: Network frequency (**a**), the voltage of source DG\({}_{1}\) (**b**), the voltage of source DG\({}_{2}\) (**c**) in the second case study.