esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Observation Simulations of GMR, GeoSTAR, and GIMS
### Upwelling Brightness Temperature TB  
Electromagnetic radiation transfer in the atmosphere involves the absorption, emission, and scattering of various gas components and hydrometeors, whose mathematical model is generally expressed by the differential radiation transfer equation (DRTE). The simulation of the upwelling brightness temperature TB at the top of the atmosphere is realized using the RT model to obtain the numerical solution of the DRTE.  
CRTM, developed at the Joint Center for Satellite Data Assimilation (JCSDA) in the United States, has been supporting satellite product retrievals, radiance validation for satellite programs, and satellite radiance assimilation for NWP, including WRFDA-4 DVar. In 2008, the CRTM simulated radiance was directly compared with the observed microwave radiances of the NOAA-18 Advanced Microwave Sounding Unit-A (AMSUA), Microwave Humidity Sounder (MHS) sensors. The simulated and observed brightness temperature fields were in good agreement for all microwave channels (on the order of 1-2 K bias) [42]. In 2013, the CRTM simulated brightness temperature was used to evaluate the accuracy of the Advanced Technology Microwave Sounder (ATMS) brightness temperature data. The results showed that the brightness temperature biases for temperature sounding channels were below 1 K [43]. Therefore, the CRTM was used to calculate the upwelling brightness temperature TB in the GEO-MW OSSE. The atmospheric state parameters in Nature Run, including vertical profiles of pressure, temperature, moisture, and hydrometeor content (cloud liquid water, rain, ice, snow, and graupel) with a temporal resolution of 0.5 h, were used as inputs for the CRTM. The simulated upwelling brightness temperature TB field of Typhoon Hagibis for all 8 channels is shown in Figure 4A-H. The corresponding TA of the three GEO-MW sounders is shown in Figure 4.
# Dynamic Initial Weight Assignment for MaxSAT
## 5 Conclusions  
An investigational study to examine and verify the performance efficiency of adopting the dynamic initial weight assignment in solving MaxSAT problems was proposed and discussed in this paper. The experimental findings showed that the initial weights' dynamical assignment positively impacted the DDFW algorithm's performance. The positive impact was observed and validated through the application of the proposed mechanism to solve MaxSAT problems mentioned in this study, as well as through the comparison with the state-of-the-art algorithms, which proved its effectiveness in addressing similar problems. More specifically, the results in Table 2 showed that DDFW+InitMaxSAT gained 33% over DDFW and performed twice as well as YalSAT and 53% better than ProbSAT, while being 51% better than Sparrow. It should be noted that the results of this study were related only to the problems addressed in the study. Therefore, in our future work, we will aim to extend this research to cover a broader range of problem sets from the Weighted Partial MaxSAT (WPMS) and the Partial MaxSAT (WPS) sets.  
**Author Contributions:** Conceptualization, A.I. and Q.A.A.-H.; Formal analysis, A.I. and Q.A.A.-H.; Investigation, A.I.; Methodology, A.I.; Project administration, A.I.; Resources, A.I.; Supervision, A.I.; Writing--original draft, A.I.; Writing--review & editing, Q.A.A.-H. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Problems** & **DDFW** & **DDFW+InitMaxSAT** & **YalSAT** & **ProbSAT** & **Sparrow** \\ \hline pigeon & 0.65 & **0.04** & 0.21 & 0.22 & 0.45 \\ aim & 1.03 & **0.54** & 0.97 & 0.67 & 0.77 \\ jnh & 1.01 & **0.04** & 0.62 & 0.78 & 0.05 \\ uuf & 2.23 & **0.98** & 1.76 & 1.31 & 1.84 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Average results of the problem set on 1000 run for each solver; the CPU time recorded for each solver when reaching the optimum solution (maximum number of satisfied clauses).
## 3 The Time-Varying Global Reliability Analysis Based on the HM-IMEM
### The High-Order Moments-Based Improved Maximum Entropy Method
#### 3.2.3 Convergence Mechanism  
Theoretically, as the order of moments in the constrained condition of Equation (6) increases, the probability density function (PDF) fitted by the MEM approaches the true value more closely. However, estimating high-order moments often requires significant computational resources to achieve the satisfactory accuracy. Therefore, it is important to keep a balance between accuracy and efficiency. To this end, the convergence mechanism in Ref. [30] is introduced to automatically determine the order of moments, namely  
\[\frac{\|H_{s}-H_{s-2}\|}{\|H_{s}\|}\leq\varepsilon \tag{17}\]  
where \(\varepsilon\) is a specific positive error precision value and is taken as \(10^{-5}\) here.  
If Equation (17) is satisfied, the Shannon entropy \(H_{s}\) converges to a stable value. That is, the first \(s\)-order raw moments can accurately reconstruct the maximum entropy PDF.
# Analysis of Hydration-Mechanical-Durability Properties of Metakaolin Blended Concrete
## 4 Conclusions  
This study presented an integrated hydration-mechanical-durability model for evaluating various properties of metakaolin blended concrete.  
First, a kinetic reaction model for the MK reaction was proposed. Like cement hydration, the MK reaction consists of three kinetic stages: an initial dormant stage, a chemical reaction controlled stage, and a diffusion controlled stage. The dilution effect and pozzolanic reaction due to the addition of metakaolin were analyzed. CH content and capillary water content were used as indicators to consider the interactions between the metakaolin reaction and cement hydration.  
Second, the reaction degrees of cement and metakaolin were calculated using the hydration model. As the MK replacement level decreased, or the water to binder ratio increased, the degree of MK reaction increased. The gel-space ratio of the concrete containing MK was determined considering the reaction degrees of the binders and proportions of concrete mix. Concrete compressive strength was calculated using the gel-space ratio.  
Third, the volumetric phase fractions were calculated based on the reaction degrees of the binders. Chloride penetrability can be described as a power function of the capillary porosity of paste. The coefficients for the hydration model, strength model, and chloride penetrability model did not vary for different concrete mixing proportions and curing ages. Regarding the multiple properties evaluations of blended concrete, such as the chemical-mechanical-durability properties, the reaction degree was much more effective than the efficiency factor given that the reaction degree can serve as a link between the macro properties and micro compositions of concrete.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, & Future Planning (No. 2015R1A5A1037548).  
[PERSON] conducted this research.  
The author declares no conflict of interest.
# Rapid Characterization Method for SMC Materials for a Preliminary Selection
## 4 Experimental Results
### Coercivity: Organic Layer  
The coercivity measured in SMCs with organic layers (0.2 wt% and 800 MPa, prepared by Turbula mixing) is shown in Figure 13. Epoxy-coated SMCs resulted in a better coercivity; in fact, it resulted in almost 380 A/m in respect to the coercivity measured in the phenolic SMCs of nearly 419 A/m. The high coercivity supplants the excellent response in terms of resistivity for the phenolic resin coating, which is a negative behaviour. This phenomenon was probably caused by the thinner coating realized with the epoxy resin with respect to the phenolic resin layer. This hypothesis is corroborated by the minor resistivity measured for SMCs with epoxy resin layer (41 u\(\Omega\)m).  
Although ball milling after 24 h or 48 h gave the best resistivity results, turbola mixing-coated specimens were selected for further measures. This selection was due because specimens after turbola mixing maintain appreciable resistivity even after a quicker coating process and, industrially, short processes are preferable because of cost savings.
## 3 Design Methodology Based on the Common Framework
### Robust Analysis: Simulation Results  
Firstly, note that the stability condition of the controller optimization is that all the eigenvalues of the state matrix of Figure 1 must be positive. The real part of the closest pole to the imaginary axis is \(-1.63\), which indicates that the system is stable. Secondly, the natural frequencies of the structure were considered variables with an error of \(\pm 25\%\). Figure 8 shows the plot of the identified model (blue) and the system with a variation of \(+25\%\) (yellow) and of \(-25\%\) (red).  
Secondly, the controller was simulated with the three systems. Figure 9 shows the simulation results, where the closed-loop simulation with the identified model is plotted in blue and the system with a variation of \(+25\%\) and of \(-25\%\) in yellow and red, respectively. In addition, the real parts of the closest pole to the imaginary axis are \(-0.1007\) (\(+25\%\)) and \(0.0995\) (\(-25\%\)). Note that the peak at 1.72 Hz in the yellow plot corresponds to the shaker. This indicates a possible problem of stability if the natural frequency of the system is considered less than \(-25\%\). Note that the actuator bandwidth (i.e., frequency response) significantly affects the stability of the overall control scheme and limits the maximum damping imparted to the structure. Thus, the IRC parameters not only minimize the peak FRFs but also maintain the stability of the controlled system for the considered variation of \(+25\%\).  
Figure 8: Magnitude (in dB) plot of the identified model (blue) and the system with a variation of \(+25\%\) (yellow) and of \(-25\%\) (red).
# Reversible Data Hiding in Encrypted Images Based on the Mixed Multi-Bit Layer Embedding Strategy
## 4 Experimental Results and Discussion  
To demonstrate the validity and superiority of our scheme, the experiment adopts standard grayscale images from publicly available datasets [43]. They are Lena, Airplane, Peppers, and Baboon. The experimental configurations are a 3.60 GHz Intel i7 processor, a Windows 7 operating system, and Matlab R2018a.
# Spatial Distribution Pattern and Influencing Factors of Homestays in Chongqing, China
## 4 Discussion
### Possible Problems of Homestay Development and the Path of Urban-Rural Integration  
With the knowledge that the development momentum of homestays is still strong, the business form of homestays in Chongqing is excessively concentrated in the main urban area. Due to the lack of reasonable regional planning, unified industry associations, clear management norms, and a sound social service system, the problem of homogenization is serious, resulting in the internal consumption of resources and local vicious competition of homestays in urban areas, which is not conducive to the formation of scale effect and the shaping of the characteristics of local brands. While rural areas are blessed with good natural scenery, the lack of effective financing channels has resulted in inadequate infrastructure support, such as roads, water and electricity, car parks, fire-fighting facilities, and safety supervision systems, required for the development of homestays, as well as an inadequate system of social services, such as government laws and regulations, all of which are detrimental to the development of homestays. Although some areas have built and transformed a number of rural homestays with the help of the government, the overall industrial chain is imperfect, the added value is low, and there is a lack of long-term operation and management mechanisms, which leads to the lack of a sustainable development capacity of the rural homestay industry, most of which are short lived.  
Under the background of the sustainable development and promotion of rural tourism, in order to solve the dilemma of inefficient and excessive homestay economic development, we should start from the perspective of urban-rural relations and insist on promoting the rational allocation of urban and rural factors with the focus on integrated urban-rural development. On the one hand, full play should be given to the key role of the market and government in resource allocation. The government formulates the long-term development plan of the homestay industry, and provides preferential policies to new business types, such as rural homestays and characteristic ins, focusing on solving the supporting problems of relevant infrastructures in rural areas. At the same time, the future direction of local industrial development is guided by market forces under the macro control of the government, so as to realize the free flow of factor resources, such as land, capital, and talents, in urban and rural areas. On the other hand, we should formulate homestay standards and management measures; standardize the business scale, construction facilities, fire safety, and operation management; strengthen quality control, business operation, safety, and environmental protection; and improve the standards and grades of homestays in rural areas.
## 4 Mobile Localization Algorithms
### Centralized Localization Algorithms
#### 4.1.5 Three-Dimensional Underwater Target Tracking (3 DUT) Scheme  
A Three-Dimensional Underwater Target Tracking (3 DUT) scheme is proposed in [43]. As shown in Figure 9, at least three anchor nodes float at the surface of water. One of these nodes is the sink (node \(A\)) which collects the information from underwater sensor nodes and carries out the calculations. The black nodes collect and send information from the target to the sink. The gray node is the designated projector node. 3 DUT is a two phase algorithm. During the first phase, Passive Listening, sensor nodes listen to the underwater environment for potential targets. The second phase of the algorithm, Active Ranging, is to localize the target. 3 DUT selects a projector node which sends pings periodically. The target is assumed to be a point target so that the echoes are radiated isotropically. Once the echo is received by the projector, it calculates its distance to the target and transmits to the sink node. Sink node uses trilateration to localize the target. The location and the calculated velocity of the target are then exploited to achieve tracking. Depending on the results of the calculations, sink node selects a new projector node.  
To save energy, the nodes which are not located at the network edge have low duty cycles. The nodes which are at the boundary of the sensing region have higher duty cycles in order to detect the target entering into the sensing region immediately. Therefore, to avoid rapid energy depletion of boundary nodes due to continuous surveillance, 3 DUT employs an adaptive procedure to find, designate, and activate new boundary nodes. Furthermore, 3 DUT does not depend on the number of nodes. The algorithm runs even if the number of sensor nodes changes. However, 3 DUT can only track one target at a time. Moreover, the tracking accuracy is heavily influenced by the target's velocity.  
Figure 8: The Collaborative Localization Scheme.  
Figure 9: The Three-Dimensional Underwater Target Tracking.
###### Abstract
During the agents' sensorimotor learning in tasks, they not only observe the current state of the environment but also experience their emotion changes, which further affects the learning process. Researchers in the fields of neuroscience and psychology also demonstrated that emotion is an important part of decision making [35], and both positive and negative emotions can lead to changes in learning motivation. [PERSON] et al. [36] proposed a framework to incorporate an emotional model into the decision-making process of a machine learning agent and used a hierarchical structure to combine reinforcement learning with a dimensional emotional model. [PERSON] et al. [37] proposed an algorithm of pursuit task allocation based on an emotional contagion to study the interaction between affective robots in multi-agent cooperative systems. [PERSON] et al. [38] proposed a model for adaptation and implicit coordination in multi-robot systems based on the definition of artificial emotions. Emotions are defined as the robot's situation, and emotions are classified as neutral, fear, frustration, urgency, and confusion. [PERSON] et al. [39] used the surprise emotion as intrinsic motivation and enabled the agent to succeed in a wide range of environments with high-dimensional state spaces and very sparse rewards. [PERSON] et al. [25] used the boredom emotion as an intrinsic motivation to generate routes in scenarios where rewards were absent and to facilitate the robot navigation toward the goals. However, in most of these works, emotional intrinsic motivation is applied to a single-agent learning task and is rarely applied to multi-agent collaborative target search. In this work, considering the multi-agent collaborative target search problem, and based on the MADDPG algorithm [21], firstly, an emotion intrinsic motivation module is designed so as to provide intrinsic rewards, and then a new MADDPG algorithm with emotion intrinsic motivation named MADDPG-E is proposed. In the emotion intrinsic motivation module, according to the multi-agent target search task, three emotions are introduced and defined, which are joy, sadness, and fear. An emotional steady-state variable function is designed to judge the goodness of the emotions and decides the final value of the proposed emotion-based intrinsic reward function. With the introduced emotion intrinsic motivation module, it is hoped that the multi-agent system could always lean toward positive emotions, so as to speed up the task learning speed and optimize the learning performance. The remainder of this paper is structured as follows. Section 2 introduces some background information. The proposed algorithm as well as the emotional intrinsic motivation design are introduced in Section 3. The simulation experiment results and discussions are presented in Section 4. Section 5 concludes this paper and envisages some future work.
# Integrated Silicon Photonics for Enabling Next-Generation Space Systems
## 2 Potential for Silicon Photonics in Optical Communications Systems
While silicon, for the most part, cannot provide the requisite lasing at 1550 nm, all of the other components can be integrated onto a single silicon chip, as outlined in the dashed red box in Figure 2. Furthermore, what is not shown is the necessary electronics that take the digital data and produce the electrical PPM signal. These components, which include the digital-to-analog converter (DAC), pulse shaping filters, and the electrical drivers that are needed for the intensity modulators, can also be integrated on the same silicon chip, massively reducing the necessary form-factor. An example of a terrestrial all-silicon optical transceiver that achieves a high-density integration of optical and electrical components with comparable performance was demonstrated by [PERSON] et al. [28]. Similar techniques can be used to condense the LTA design into a smaller footprint. However, it should be noted that this modulator achieves roughly 4 dB optical extinction ratio. In comparison, an LTA needs \(>\)33 dB pulse extinction ratio to meet flight requirements. While this might seem like a huge technology performance gap, silicon optical modulators have not been optimized for space systems where such a high extinction ratio is needed. Some designs have improved the extinction ratio (\(\sim\)18 dB) [29], but more focused design efforts are still needed to meet flight requirements. Temperature control for silicon systems is also important to consider for space systems. For example, silicon modulators' bias point can shift with changing temperature. However, many silicon modulators are designed with on-chip thermal tuners to provide DC bias control, and retain their modulation efficiency across temperature [30; 31; 32]. While the heater does tend to raise the power consumption of the modulator, it is only on the order of several mW, and thus, is not a huge concern from a power and size perspective. The LTA in Figure 2 has two subsequent stages that use fiber amplifiers to boost the optical output power. These amplifying stages also relax the insertion loss constraints imposed by the modulator. While in theory some of these components can also be integrated in silicon (e.g., the taps and PDs), the optical power is typically too high (\(>\)23 dBm) to be supported by integrated waveguides due to potential non-linear optical effects [33]. Overall, the development and maturation of silicon photonics can result in a large reduction in size and weight for space optical systems. The integration approach can further reduce the size constraints by limiting the need for individual component packaging and removing unnecessary electrical and optical interconnects between components.
# Ambiguity-Resolved Model Tests for Carrier-Phase GNSS
## 5 Summary and Conclusions  
In this contribution, we introduced a class of mixed-integer model (MIM) tests for carrier-phase GNSS and studied its characteristics. As a first indication of its significant power potential, we compared the power performance of two of its limiting forms, the ambiguity-float (AF) test and the ambiguity-known (AK) test. It was shown that for carrier-phase GNSS, the AK test significantly outperforms the AF test. The AK test, however, is not an operational test, since for carrier-phase GNSS, the ambiguities can never be assumed known. Therefore, its best operational alternative is the MIM test for which, for different circumstances, different forms were presented, see Table 1. The relevant probability distributions were also provided, including the highest-density versions of the testing. For the case when the null hypothesis is tested against the most relaxed alternative hypothesis, the MIM test provides ambiguity-resolved detection, while identification is enabled in case the design matrix' range space of the alternative hypothesis is a strict subspace of the observation space. As a special case of the latter, we also described the significance test, which--in contrast to the general MIM test--only requires integer ambiguity resolution under the alternative hypothesis. As a third field of application, we described how the MIM test specializes to integer testing. Such testing is relevant for carrier-phase GNSS models in which the integerness of ambiguities, or the lack thereof, needs verification--for instance, due to suspected stability issues in its instrumental hardware delays. Several illustrative examples of the MIM test performance were given, demonstrating its improved power over that of the ambiguity-float test. Noteworthy is hereby that such improvements generally do not need the same high ambiguity success rates as required for ambiguity-resolved parameter estimation.  
This research received no external funding.  
**Data Availability Statement:** All data generated or analysed during this study are included in this contribution.  
**Acknowledgments:** [PERSON] and [PERSON] provided the graphical and numerical support.  
**Conflicts of Interest:** The author declares no conflicts of interest.