esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Field Maintenance
### Fatigue Damage Degree  
During the process of bridge operation, each passing vehicle can impose different stress amplitudes, and the cumulative contribution to fatigue damage caused by these stress amplitudes can also vary. In general, a high-stress amplitude can cause a major fatigue damage increase, but the number of cycles with high-stress amplitudes is lower. Conversely, a low-stress amplitude makes a very small contribution to fatigue damage. Fatigue damage degree refers to the accumulation of fatigue damage during the cyclic vehicle loads.  
Based on the stress range spectrums, [PERSON]'s linear damage accumulating theory was used to calculate the fatigue damage degree using Equation (3) [24].  
\[\mathrm{D}=\sum_{i=1}^{\infty}\frac{n_{i}}{2\times 10^{6}\times\left(\frac{ \sigma_{0}}{\sigma_{x,i}}\right)^{3}} \tag{3}\]  
where D is the fatigue damage degree; fatigue failure is considered to occur on the component when the value of D reaches to 1. \(\sigma_{0}\) is the designed value of fatigue strength of the diaphragm-to-rib weld, here the value is 80 MPa, according to the Chinese standard [25]. \(\sigma_{x,i}\) is the variable stress amplitude. In this case, the value refers to the median of each interval, for example, if the stress amplitude range is [5; 10] MPa, then the stress amplitude value is 7.5 MPa. \(n_{i}\) is the corresponding cycle number of stress amplitude.  
The fatigue damage degrees before and after reinforcement were obtained and are listed in Table 1. It appeared that the fatigue damage degree at the crack tip decreased sharply by 84.7% within one hour after reinforcement. Fatigue life before reinforcement was only 0.81 years, which rose to 5.28 years after reinforcement with an increase of more than five times. The result indicated that bonding a polygonal steel plate could significantly improve the stress concentration at the crack tip, hinder crack propagation effectively and prolong the fatigue life. The maintenance effect of polygonal steel plate reinforcement was proven.  
\begin{table}
\begin{tabular}{c c c c}  & **Before Reinforcement** & **After Reinforcement** & **Reduction Rate** \\ \hline
**Fatigue damage degree D** & \(1.41\times 10^{-4}\) & \(2.16\times 10^{-5}\) & 84.7\% \\
**Fatigue life (year)** & 0.81 & 5.28 & \\ \end{tabular}
\end{table}
Table 1: Cumulative fatigue damage degree and fatigue life before and after reinforcement.  
Figure 11: Comparison of stress spectrums.
## 4 Introduction of FAD Key Parameters
### Construction of Failure Assessment Curves  
Each option of the BS 7910 FAD method consists of an assessment curve, which is obtained by the curve equation \(K_{r}=f(L_{r})\), and a cut-off value \(L_{r,max}\). If the calculated rating point (\(L_{r}\), \(K_{r}\)) is located within the area surrounded by the vertical line of the axis, the rating line, and the cut-off value \(L_{r,max}\), then, the crack passes; if it is located outside that area, then, the crack fails. The cut-off value \(L_{r,max}\) is determined according to Equation (4), in which the average tensile strength is generally used. In this case, due to a lack of statistical data regarding the performance of the parent material, the minimum tensile strength of the X65 steel was used to calculate the cut-off value for conservative consideration.  
\[L_{r,max}=\frac{\sigma_{Y}+\sigma_{u}}{2\sigma_{Y}} \tag{4}\]  
As the stress-strain curve has no yield plateau, the Option 1 failure assessment curve can be determined according to Equations (5) and (6):  
\[f(L_{r})=\left\{\begin{array}{ll}\big{(}1+0.5L_{r}^{2}\big{)}^{-0.5}\big{[}0. 3+0.7 exp\big{(}-\mu L_{r}{}^{6}\big{)}\big{]}&L_{r}\leq 1\\ f(L_{r}=1)L_{r}(N-1)^{/2N}&1<L_{r}\leq L_{r,max}\end{array}\right. \tag{5}\]  
\[\mu=\min\biggl{\{}0.001\frac{E}{\sigma_{Y}},0.6\biggr{\}}N=\frac{1}{n}=0.3 \biggl{(}1-\frac{\sigma_{Y}}{\sigma_{u}}\biggr{)} \tag{6}\]  
Figure 4: Schematic diagram of cracks at the girth weld.  
where \(L_{r}\) is the load ratio, which is the independent variable in the FAD; \(E\) is the modulus of elasticity; \(\mu\) and \(N\) are the coefficients in Equation (4), for the minimum performance parameters used in X65 steel, \(\mu\) = 0.4667 and \(N\) = 0.0477.  
The Option 2 failure assessment curve can be determined according to Equation (7):  
\[f(L_{r})=\left(\frac{E\varepsilon_{ref}}{L_{r}\sigma_{Y}}+\frac{L_{r}{}^{3} \sigma_{Y}}{2E\varepsilon_{ref}}\right)^{-0.5}\hskip 28.452756 ptL_{r}\leq L_{r,max} \tag{7}\]  
where \(\sigma_{ref}\) is the reference stress, and \(\varepsilon_{ref}\) is the corresponding strain in the true stress-strain curve of the material, i.e., \(\sigma_{ref}=L_{r}\times\sigma_{Y}\).  
Figure 5 displays the Option 1 and 2 evaluation curves of the X65 base material of the \(\mathcal{O}813\times 17.5\) mm pipe used in this paper.
# Arithmetic Study about Efficiency in Network Topologies for Data Centers
## 5 Developing Some Typical Use Cases
### Some Other Commonly Used Network Topologies in Data Centers  
In order to apply the aforementioned coefficient \(\eta\) to obtain a balance between performance and simplicity to network topologies being employed in large data centers, the topologies exposed in Section 2.3 are going to be used to calculate the aforesaid coefficient \(\eta\). This study is going to be made with the parameters exposed in that subsection that correspond to a data center with small to medium size. However, these parameters are higher in large deployments; hence, the use of coefficient \(\eta\) may be applied the same way as exposed in this section, although the results may vary depending on the values taken for the corresponding parameters.  
Anyway, Table 7 exposes the values for such a coefficient \(\eta\) regarding a compromise between performance and simplicity, where the parameters of each topology arealso shown, along with the number of nodes involved with those parameters, followed by the values for performance (\(\alpha\)) and simplicity (\(\beta\)) for those specific parameters.  
Additionally, Table 8 exhibits the values for coefficient \(\eta\) when the number of nodes involved in diverse data center network topologies is increased. For this case, fat tree has been selected with parameter \(k=8\), which contains 128 hosts withjust 1 port, along with 32 edge switches, 32 aggregation switches and 16 core switches,where all of them have 8 ports. Further, leaf and spine has also been set up to include 128 hosts with 1 port by taking 16 leaves and 8 spines, all of them being switches with 16 ports.  
Furthermore, BCube\({}_{2}\) with \(n=4\) is chosen, whichcontains 64 hosts with 3 ports and 48 switches with 4 ports. It is to be noted that a third of those switches belong tothe 16 level-0 cells within this topology, with 4 nodes hanging on each of those, another third is located in 4 level-1 cells, with 4 level-0 cells hanging on each of these, and the other third one is situated within the level-2 cell, with 4 level-1 cells hanging on each of them. Moreover, DCell\({}_{2}\) with \(n=4\) is also selected, which holds 420 hosts with 3 ports and 105 switches with 4 ports. It is to be said that those switches are distributed into 21 DCell\({}_{1}\), where each of themhas 5 switches, such that each of those switches accounts for a DCell\({}_{0}\), which in turn is furnished by 4 connected nodes.  
\begin{table}
\begin{tabular}{l l c c c c} \hline
**Type** & **Instance** & **Nodes** & \(\alpha\) & \(\beta\) & \(\eta=\alpha\times\beta\) \\ \hline \multirow{4}{*}{Graph-like} & 3-ary 3-cube & 9 & 1.5 & 4 & 6 \\  & Petersen graph & 10 & 1.67 & 3 & 5 \\ \cline{1-1}  & Heawood graph & 14 & 2.08 & 3 & 6.24 \\ \cline{1-1}  & Robertson graph & 19 & 1.89 & 4 & 7.56 \\ \hline \end{tabular}
\end{table}
Table 6: Values for \(\eta\) for nodes not being a power of 2.
###### Abstract  
The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM) constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellite Retrievals for GPM (IMERG) product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42) and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF) against the Iran Meteorological Organization (IMO) daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day), IMERG is superior to the other products in all study areas and could be used in future for meteorological and hydrological models, _etc._  
GPM constellation satellites; IMERG; TMPA-3B42; ERA-Interim; satellite precipitation estimates; remote sensing; statistical analysis +
Footnote †: journal: Remote Sensing
## 6 Design Considerations for LPWAN Networks
### Capacity and Densification

Table 3: Design Considerations Summary for LPWAN Networkscommunication needs to be supported. For applications with device heterogeneity, standardized protocols are required. A large number of devices and dense deployments of base stations also cause high levels of interference between signals from different devices. The basic approach to reduce interference is to use frequency reuse as part of network planning. In some instances, communication may need to be made resilient to interference by using adaptive modulation schemes, multiple channels, and doing redundant transmissions [6]. Efficient exploitation of diversity in channel, time, space, and hardware may be used. In some specialized applications, parallelization in transmission may need to be implemented by taking advantage of techniques like multi-channels and multiple input multiple output (MIMO) configurations. As technology is advancing, the software defined radio (SDR) can be a good option for optimizing access and performance in an efficient manner. For selected applications where cost considerations and energy efficiency are important, such robust techniques are optional. In situations with a large number of devices and densification, as well as strong and efficient multi access techniques, are needed owing to limited air resource issues and the potential for cross-technology interference. A possible multi-access approach can be non-orthogonal multiple access (NOMA) [10]. It may be noted that NOMA is also being considered for 5G access networks. NOMA can be applied to support diverse quality of service (QoS) requirements for differing types of end devices. Using NOMA, devices can achieve multiple access by exploiting power and code domains techniques. All the devices can utilize resources simultaneously. However, this can create inter-device interference. To mitigate this, multi-device detection techniques, for example, joint decoding or successive interference cancellation, can be used to retrieve the device's signals at the receiver. Multiple and adaptable link level configurations may need to be supported with tradeoffs between different performance metrics such as bandwidth, latency, error rate, and so on. This implies a need for adaptive techniques that can readjust their parameters for better performance based on monitoring of link quality. Adaptive modulation schemes, selection of better channels to reach distances reliably, or adaptive transmission power control are some of the techniques that can be utilized. There is a significant need to develop novel densification approaches, especially in many proprietary solutions. Such technologies may not be able to utilize the synchronization technique and well-coordinated radio resource management. The dynamic state and context information need to be stored for the devices in the access station and the core entities. Managing the state information of the massive number of connected devices is also an issue that needs to be addressed.
# HVdc Circuit Breakers: Prospects and Challenges
## 4 HVdc Circuit Breaker Topologies
### Power Losses  
Electro-mechanical and hybrid dc breakers with no semiconductor switch in the main current path show low power loss than all the topologies. The reason for this is the low voltage drop across the metal contacts of the main breaker. Even a hybrid dc breaker configuration having a low rating semiconductor switch in the main current path shows reasonable power loss, no more than 0.1% of VSC station power loss. On the contrary, solid-state dc breakers suffer from high power losses as the number of IGBT or other semiconductor switches is installed in the main current path, which is why relatively high voltage drop across the CB. Power loss for SSCB reaches up to 30% compared to the VSC station.
## 2 Literature Review
### Comments on Previous Research
Fifthly, existing research on predicting situation types is predominantly found in English literature, with most studies focusing on English as the research subject. While a few studies touch upon discussions in other languages such as Italian, there is a general lack of research targeting situation types in Chinese for prediction. Therefore, there is still further exploration space to achieve high-accuracy prediction of Chinese verb situation types. Given the current state of situation type research, this paper will focus on the following issues:  
First, how can we classify verb situation types in a more scientifically grounded manner to avoid controversies in classification research? Scholars have primarily relied on intuitive or introspective methods when constructing situation type systems, which have consistently lacked a unified foundation. Our goal is to establish a verb situation type classification system that can be measured by objective standards. Therefore, the use of statistical methods is crucial. Second, can we achieve high-accuracy prediction of verb situation types? Current prediction methods in research struggle to attain high accuracy. To address this, we not only need to improve the methods for constructing training datasets but also employ more advanced and complex algorithms for the automatic recognition of verb situation types. Specific research methods will be detailed in the next section. Only by achieving high-accuracy prediction of verb situation types can we possibly predict the situation types of phrases and sentences, thereby further verifying the compositionality and recursiveness of situation types and exploring the collocation rules between situation types and aspectual markers. Additionally, accurately predicting the situation type of verbs can enable us to make predictions on unknown language resources, helping researchers to more clearly categorize verb types. This, in turn, offers significant practical value for understanding the world, exploring the collocation patterns between words and advancing Chinese language teaching. In summary, this paper will focus on solving the problem of improving situation type prediction accuracy from an engineering perspective, aiming to train a practically useful situation type automatic recognition model.
# Supply-Scalable High-Speed I/O Interfaces
## 3 Design Considerations of Supply-Scalable I/O  
### Base Circuit Topology  
Figure 7 shows two major circuit topologies in CMOS technology, CMOS and CML circuits, which are most frequently used in modern analog and mixed-signal IC designs. Although current-mode logic (CML) circuits have been a majority for base circuit topology for high-speed I/O interfaces owing to their high-speed capability [46], using CMOS circuits as much as possible is preferred for supply-scalable I/O in order to maximize the frequency range and the benefit of the supply scaling [44; 47]. It is mainly because the power consumption of CML circuits follows the blue line in Figure 4 (static current consumption), whereas the CMOS exhibits cubic power scaling. In addition, besides the power scaling, the CMOS circuit dissipates less power as long as the fan-out is no less than 2 [23], and it also provides a higher swing than the CML. On the other hand, the CML circuit has a much better controllability of its speed compared to the CMOS counterpart whose speed is highly deterministic to the given process technology and supply voltage. The time constant of a CML circuit is a product of the load  
Figure 5: Relation between operating speed and supply voltage of the CMOS circuit.  
Figure 6: Survey of energy efficiency of scalable I/O across the maximum data rate.  
resistance (R) and the load capacitance (\(\mathrm{C_{L}}\)), so tweaking R is a powerful knob of controlling the circuit speed in the design phase. The CMOS circuit can be accelerated by reducing the fan-out; however, a too-small fanout (i.e., less than 2) is not feasible in a practical circuit implementation and also results in a non-linear increase of power consumption (see (1)). As a result, the CML circuit exhibits a better capability of high-speed operation, which is a dominant issue to achieve the maximum speed of the scalable I/O. It has been one of the main reasons to make high-speed interfaces highly rely on CML circuits, although their scalability is not as good as CMOS circuits. In order to resolve this issue, ref. [25] proposed adjusting the current bias of CML circuits in accordance with the supply scaling. For example, at the minimum data rate and supply voltage (0.65 V) condition, the current bias is reduced to half of the nominal value, whereas it is raised to 1.5\(\times\) when the data rate and supply voltage (1.05 V) are maximized. Instead of using a fixed resistance as CML load resistance, a symmetric load whose resistance automatically adapts with the bias current is employed in [25] to scale the circuit bandwidth while maintaining the voltage swing. As an alternative approach, a CMOS inverter with resistive feedback can be used to hit high bandwidth for fully utilizing CMOS circuits even above the CMOS limit, because the resistive feedback extends the bandwidth of the CMOS circuit at the cost of increased power consumption [48].
## 3 Results and Discussions
### Density Functional Theory Calculations
In an intramolecular reaction mechanism, the P-H\({}^{\bullet}\) molecule would be reduced and protonated for a second time to form a P-H\({}_{2}\) intermediate. For simplicity, it was assumed, based on the results discussed above, that the first proton would bind to C1. As shown in Figure 7, two possible P-H\({}_{2}\) states were then considered leading to two possible intramolecular mechanisms: (i) the second H+ binds to C2 (C1-H-C2-H) and (ii) the second H+ binds to O (C1-H-O-H). C1-H-C2-H was more stable compared to C1-H-O-H. However, this results in the higher activation energy for the C1-H-C2-H pathway (E\({}_{a}\) = 1.16 eV, black line in Figure 7) compared to the C1-H-O-H mechanism (E\({}_{a}\) = 0.66 eV, the red line in Figure 7). This means that the H\({}_{2}\) formation would proceed faster through the C1-H-O-H mechanism from a kinetic perspective. Thus, H\({}_{2}\) formation on PCzPO will likely proceed through an intramolecular mechanism after overcoming the barrier of 0.66 eV. We also elucidated the intramolecular H\({}_{2}\) formation using PNoFPO to show that PNoFPO indeed generated a very similar reaction coordinate and barrier (0.61 eV) to PCzPO moiety (Figure S3). To study the intermolecular mechanism, a reaction between two molecules of H-PCzPO\({}^{\bullet}\) with the most stable configuration, C1a (\(\Delta\)G\({}_{\rm H}\) = 2.83 eV), was initially chosen as the starting structure. However, the optimisation of two H-PCzPO\({}^{\bullet}\) moieties with C1a configurations led to the formation of a phosphorous-phosphorous bond which inhibited the interaction of the H atoms and H\({}_{2}\) formation (Figure S4). Because of this, C1b configuration was chosen as a starting structure to find the MEP for the formation of H\({}_{2}\). The calculated reaction coordinate for this mechanism (Figure 8) shows a hydrogen formation reaction with activation energy (E\({}_{a}\)) equal to zero. This implies a barrierless and spontaneous (\(\Delta\)G = \(-\)0.116) formation of H\({}_{2}\) through this intermolecular reaction mechanism. However, it is important to note that the two P-H molecules needed to be oriented such that the hydrogens involved in the reaction are closely pointed to each other, implying that intermolecular H\({}_{2}\) formation is only likely to occur when the repulsion between polymers is low. The higher HER rate from the higher molecular stacking of PCzPO polymers might be possibly due to the higher possibility of forming H\({}_{2}\) via an intermolecular reaction mechanism. Figure 6: Possible configurations of proton binding onto C1 and C2.
### Monte Carlo Simulations
The diffusion model is based on the assumption that scattering is dominant over absorption (\(\mu_{s}{{}^{\prime}}\)\(>\)\(\mu_{a}\)), so the parameter of \(\mu_{s1}{{}^{\prime}}\)/\(\mu_{a1}\) was also selected for investigating its effect on optical property estimation. Hereinafter, these relative values are called influencing factors for convenience. Our previous study has investigated the effect of top-layer thickness on optical property estimation of two-layered medium and also determined the constraining conditions [13], indicating that the top-layer's maximum thickness could not exceed 2 mm, in order to have acceptable estimations of optical properties of the bottom layer. Hence the top-layer thickness was chosen to be 2 mm for all the simulation samples in this study.