esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology
### Physical Properties of Nanofluid  
The Al\({}_{2}\)O\({}_{3}\)-water nanofluid composed of base fluid (water) and Al\({}_{2}\)O\({}_{3}\) are adopted in this study. The diameter of the nanoparticle is set to be 30 nm. Table 2 lists the physical properties of water and nanoparticle. A single-phase model and constant physical property are adopted. The nanoparticle is assumed to be spherical and homogeneously suspended in water.  
The models used to obtain the physical properties of nanofluid can be expressed as:  
* Density model \(\rho\): \[\rho_{nf}=(1-\phi)\rho_{b}+\phi\rho_{p}\] (5) where the subscription \(nf\), \(b\) and \(p\) denote the properties of nanofluid, water and Al\({}_{2}\)O\({}_{3}\) nanoparticle, respectively; \(\varphi\) is the solid volume fraction.
* Specific heat model \(C_{p}\)[32]: \[C_{p_{nf}}=\frac{(1-\phi)C_{p_{b}}\rho_{b}+\phi C_{p_{p}}\rho_{p}}{\rho_{nf}}\] (6)
* Dynamic viscosity model \(\mu\)[2]: \[\mu_{nf}=\mu_{b}(123\phi^{2}+7.3\phi+1)\] (7)  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Substance** & **\(k\)/W**-**m\({}^{-1}\)**-**K\({}^{-1}\)** & **\(C_{p}\)/J**-**kg\({}^{-1}\)**-**K\({}^{-1}\)** & **\(\rho\)/kg**-**m\({}^{-3}\)** & **\(\mu\)/Pa-s** \\ \hline Al\({}_{2}\)O\({}_{3}\) & 36.00 & 773.00 & 3880.00 & - \\ Water & 0.597 & 4182.00 & 998.20 & 9.93 \(\times\) 10\({}^{-4}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Physical properties of water and Al\({}_{2}\)O\({}_{3}\) nanoparticle (293 K).  
* Thermal conductivity model \(k\)[33]: \[k_{nf}=0.25\Big{[}(3\phi-1)k_{p}+(2-3\phi)k_{b}+\sqrt{\Delta}\Big{]}\] (8) where \[\Delta=\big{[}(3\phi-1)k_{p}+(2-3\phi)k_{b}\big{]}^{2}+8k_{p}k_{b}\] (9) The dimensionless local Nusselt number (Nu) [34] is defined as \[\text{Nu}\;=\;-\;\frac{k_{nf}}{k_{b}}\bigg{(}\frac{\partial\theta}{\partial Y} \bigg{)}\] (10) where \(\theta\) and Y are the dimensionless temperature and the y coordinate, respectively, and can be expressed as \[\theta=\frac{T-T_{c}}{T_{h}-T_{c}}\] (11) \[Y=\frac{y}{H}\] (12) The average Nusselt number (Nu\({}_{m}\)) of the middle section is defined by \[\text{Nu}_{m}=\frac{1}{L_{2}}\int_{L_{1}}^{L_{1}+L_{2}}Nu(x)dx\] (13) Besides, the Reynolds number can be expressed as \[\text{Re}= \frac{\rho_{nf}u_{c}H}{\mu_{nf}}\] (14)
# Monitoring Vegetation Change and Its Potential Drivers in Inner Mongolia from 2000 to 2019
## 3 Results
### Geographical Detection Model for NDVI Drivers
#### 3.4.3 Driving Factor Interactions  
The spatial pattern of the NDVI changes in Inner Mongolia is not influenced by a single factor, but rather by a combination of drivers. Therefore, interaction detectors were used to detect the interrelationships between different drivers that affect NDVI changes in vegetation (Figure 11). The results show that the interactions between different drivers are all bi-variable or non-linear enhancements, with most being bi-variable enhancements. There were no cases wherein the drivers were independent or weakened. As previously discussed, soil moisture and temperature have an important compounding effect on vegetation growth through a strong coupling of land and atmosphere [75]. Therefore, the coupling of precipitation and temperature plays an important role in vegetation growth  
Figure 10: Risk detector results for each factor of the NDVI in Inner Mongolia from 2000 to 2019.  
because of the increased evapotranspiration caused by global warming [76]. The results of the interaction detectors in this study also reflect the influence of the interactions between the factors, whereof total annual precipitation, mean annual temperature, and soil type had greater influences, and most exhibited bi-variable enhancements. The interaction between mean annual temperature and total annual precipitation (Q value = 0.881) specifically had the greatest influence on the spatial distribution of the NDVI, for which the influence of the social and natural factors, especially land use type, livestock density, and soil type factors, increased significantly. The influence of social and natural factors, especially land use type and livestock density, increased significantly with the soil type factor, whereas the population and GDP factors, which were the least influential, showed mostly non-linear enhancements with the natural factors.
## 4 Active Antiresonance Assignment with No Additional Masses
### Comparison of Active Vibration Absorption Techniques  
In this section, the use of state-feedback [51], output-feedback [53] and VATMD are compared in solving the antiresonance assignment task of Section 4.4.1: an undamped antiresonance is assigned at 1.000 rads\({}^{-1}\) for the point-receptance \(h_{3,3}(j\omega)\). The state-feedback controller is synthetized by solving the linear system in Equation (20) through the pseudo-inverse (_pinv_). The output-feedback controller, whose control gains are obtained by  
Figure 15: The amplitude of the response of the primary system: a comparison of different actuator bandwidths, with \(m=1\) kg, \(k=1\) Nm\({}^{-1}\), \(\omega_{f}=0.95\)\(\omega_{0}\), \(\mu\) and \(\zeta_{d}\) tuned through Equation (39).  
solving Equation (27), is obtained by feeding back the displacement of the 1 st coordinate to the controller. The VATMD for the damped multi-DOF 6-mass system is designed through the control scheme proposed in Figure 16, i.e., the actuation is non-collocated with respect to sensor employed to feedback the displacement of coordinate \(q_{3}\) to the controller C(s). The control gains in Equation (40) are computed by setting \(c_{c}\) = 0 Nsm\({}^{-1}\), \(\mu\) = 0.1, \(m\) = 1 kg and \(\omega_{f}\) = 1 rads\({}^{-1}\). The actuator dynamics is neglected in the three cases by assuming that it is significantly higher than \(\omega_{f}\), by exploiting the general result discussed in Section 4.5.1 (see Figure 15 and the related comments).  
The steady-state displacement for coordinate \(q_{3}\) vanishes for all the three controllers and the control force \(u\)(s) is exactly the same. However, different frequency responses are obtained, as corroborated by the receptances shown in Figure 17. It should be noted that the VATMD introduces an additional pair of complex poles at \(\omega\) = 1.08 rads\({}^{-1}\) (that depends on the tuning rule adopted) due to the denominator of the controller transfer function in Equation (40). In contrast, state feedback and output feedback just change the pole frequencies. This is a great advantage of these approaches, due to the static feedback of speed and position. Besides, output feedback leads to higher robustness margins in this example as shown in Table 11.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Controller Type** & **State Feedback** & **Output Feedback** & **VATMD** \\ \hline
**Disk-based gain margin [dB]** & \(\pm\)0.36 & \(\pm\)0.39 & \(\pm\)0.03 \\ \hline
**Disk-based phase margin** [\({}^{\circ}\)] & \(\pm\)2.4 & \(\pm\)2.6 & \(\pm\)0.2 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Robustness margins of the closed-loop system for different controllers.  
Figure 16: Sketch of the closed-loop system with the non-collocated VATMD for the six-mass system.  
Figure 17: Open-loop and closed-loop receptance \(h_{3,3}\)(\(\omega\)): comparison with state-feedback, output-feedback and VATMD.
# HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence
## 3 Use Case Definition
### System Set-Up  
As shown in Figure 1, the set-up consists of two cameras (located in the train cabin) in properly calibrated stereo vision configuration, another two rear cameras (pointing at the passenger doors) and the Xilinx VCU118 board which incorporates the SELENE platform. Each camera sends a real time video stream into the system and all of these streams are analysed using the CV- and AI-enhanced algorithms to extract valuable data and send information to the next signalling equipment (decision making and actuators modules).  
Figure 1: Physical set-up of the solution. Equipment distribution on the train.
## 5 Conclusions  
We developed the first nomograms that accurately predict BCR-free survival in high-risk PCa patients treated with CIRT combined with ADT. These nomograms allow for more detailed risk classification of high-risk PCa patients. Moreover, when clinicians perform CIRT combined with ADT in high-risk PCa patients, the present nomograms will enable precise understanding and explanation of BCR-free survival to patients.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15020804/s1](https://www.mdpi.com/article/10.3390/app15020804/s1)]([https://www.mdpi.com/article/10.3390/app15020804/s1](https://www.mdpi.com/article/10.3390/app15020804/s1)), Figure S1: LASSO coefficient solution paths to identify predictors. (a) Five-year BCR-free survival and (b) seven-year BCR-free survival.; Figure S2: Calibration plots of the nomograms using the training, validation, and entire datasets. (a) Five-year BCR-free survival and (b) seven-year BCR-free survival.  
Conceptualization, H.S. and H.I.; methodology, T.U.; software, T.U.; validation, M.W., K.K., A.O., M.N., S.A. and T.S.; formal analysis, T.U.; investigation, M.W.; resources, H.I.; data curation, M.W., K.K., A.O., M.N., S.A. and T.S.; writing--original draft preparation, T.U.; writing--review and editing, H.S. and H.I.; visualization, T.U.; supervision, T.I., K.A., H.T. and S.Y.; project administration, H.S. and H.I.; funding acquisition, H.S. and H.I. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by JSPS KAKENHI, grant number JP21K07715.  
**Institutional Review Board Statement:** The study secured approval from the institutional review board at QST Hospital (approval no. N21-005).  
**Informed Consent Statement:** The potential participants were given the opportunity to opt out of being enrolled.  
**Data Availability Statement:** The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.  
**Acknowledgments:** [PERSON] re-evaluated all prostate biopsy specimens as a single pathologist.  
**Conflicts of Interest:** [PERSON] reports personal fees from Astellas, Janssen, AstraZeneca, Bayer, and Sanofi and scholarship donations from MSD, Janssen, Nippon Shinyaku, and Kissei.
## 4 Results and Discussion
### Limitations and Future Lines of Work  
This study proposes a conceptual architecture for the application of a multi-agent system (MAS) in roll-on/roll-off (Ro-Ro) terminal management. The model focuses on defining the agents' roles, coordination protocols, and expected benefits in terms of operational optimization. However, the work does not include experimental results, simulation-based testing, or empirical data.  
The lack of validation is a recognized limitation. The implementation of a MAS in real port environments requires significant institutional coordination, access to data, and technical resources, which are often restricted by budgetary and regulatory constraints. While several port authorities are actively exploring digitalization and AI-based solutions, large-scale pilots involving intelligent agents remain limited.  
Future research will focus on building simulation environments that replicate terminal operations and agent interactions under controlled conditions. In parallel, collaboration with operational terminals will be sought to deploy small-scale prototypes or pilot studies. These efforts will aim to evaluate the model's performance using operational indicators such as efficiency gains, reduced vehicle dwell time, and adaptability to real-time conditions.
# Joint Channel Estimation Algorithm Based on DFT and DWT
## 6 Simulation and Analysis
### Noise Power Estimation Performance in ST-DFT Algorithm  
Figures 4 and 5 show the value ranges for the total power of the noise removed by the ST-DFT channel estimation algorithm under different channel models. We observed that the theoretical upper and lower bounds in the figures correspond to the maximum and minimum values in Equation (24), and the total power of the noise on the actual zero-set samples is between the upper and lower bounds. At medium and low SNR, the total noise power actually removed is closer to the upper bound; at high SNR, since the threshold has a greater probability of screening out low power noises and removing them, the actual total noise power removed gradually deviates from the upper bound and approaches the lower bound.  
Figure 3: Comparison of different channel estimation algorithms in channel UMi.  
Figure 2: Comparison of different channel estimation algorithms in channel D.
## 7 Conclusions  
1. With the 4301 tailgate as the research object, the combined use of physical experiments and numerical simulation software has successfully developed and applied the Double-Yield model and coal pillar seepage model. Additionally, the post-processing of simulation results was achieved through methods such as deviatoric stress, dissipated energy density, and plastic zone ratio.
2. This study revealed the influence of coal pillar width on surrounding rock failure patterns under seepage effects. When the coal pillar width is relatively small, there exists a concentrated stress zone within the coal pillar, which is fully penetrated by plastic zones and dissipated energy density distribution, indicating extreme instability. However, when the width exceeds 9 m, the impact of the goaf on the roadway diminishes. Within the coal pillar, a stress reduction zone forms, and the distribution of dissipated energy density changes from a penetrating shape to an independent double-core shape. Simultaneously, the plastic zones in the goaf and those in the goaf-side roadway become independent of each other, leading the coal pillar from an unstable state to a stable one.
3. By combining the AHP method, the roadway was divided into three regions: normal support area, reinforced support area, and special support area, establishing a zoning control system for roadway surrounding rocks. Finally, industrial experiments were successfully conducted, and field monitoring results showed that the overall control effect of each section of the roadway was satisfactory. Furthermore, this methodology demonstrates its applicability to other mines with similar conditions, underscoring the significance of this study for enhancing mine safety and operational efficiency in the industry.  
S.Y.: writing--original draft. S.L.: visualization. X.W.: software. J.B.: supervision. Y.G.: visualization. All authors have read and agreed to the published version of the manuscript.  
Figure 21: Surface displacement monitoring curve of roadway.  
**Funding:** This research was financially supported by National Natural Science Foundation of China (U21A20107), Ordos Science and Technology Plan Project (2022 EEDSKJZDZX005).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** Authors [PERSON] and [PERSON] were employed by Taiyuan Coal Gasification (Group) Corporation Limited. Author [PERSON] was employed by Qipanjing Coal Mine, Guoneng Mengoi Coal Chemical Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 3 Obstacles to the Implementation of LCA in the Procurement Process of Buildings
### Methodological Obstacles  
An identified obstacle on the methodological level was the lack of comparability for the different LCA tools and results in the LCA process, e.g., allocation or impact categories, for tender requirements [56; 57; 58; 59]. In this context, the different ranking results of variants for different indicators were also highlighted as obstacles [60]. Furthermore, in addition to the lack of practical and operational tools, the high complexity of the LCA process made the implementation of LCA in the tendering and awarding procedure difficult [59; 61; 62; 63; 64; 65; 66; 67]. Moreover, a lack of information, e.g., missing guidelines, handbooks, or toolkits, was mentioned as a problem for LCA implementation [59; 61; 65]. Process-based obstacles and problems in the procurement procedure context included different challenges to be tackled in the award criteria, meaning that environmental preferences were formulated in a way that is too unspecific or they were difficult to measure in the first place [67; 68]. On top of this, the assessment criteria and the award criteria did not always correspond to the importance of the environmental issue [68]. Additionally, the distinct use of tender processes or award criteria could also be an issue, as well as the tendency to use environmental criteria more often with higher project budgets or on a national level [61; 68]. Lastly, the lack of methods that enabled comparisons, quality control, and monitoring was mentioned [67]. In terms of data quality, the availability of data and data uncertainty were also identified as methodological obstacles [60; 67]. Table 1 provides an overview of the identified methodological obstacles. The applied methodological approaches of the research articles (italic), as well as the obstacles, are mentioned. Figure 2: Categories of obstacles to implementing LCA in the procurement process of buildings.
# Enhanced Fully Generalized Spatial Modulation for the Internet of Underwater Things
## 5 Simulation Results
### The ABER Performance  
In this sub-section, the ABER performance of the suggested EFGSM is estimated by simulation numerically and analytically. We considered different modulation orders used to achieve 8 (bpcu) and 9 (bpcu) achievable rates. It is assumed that the same number of the transmitting and receiving (TX/RX) antennas are used in all schemes. The ABER of the proposed EFGSM compared to conventional SM, GSM and FGSM are depicted in Figure 3. The TX/RX antenna configuration assumed to be \((4\times 4)\) in all schemes, and the MQAM modulation orders are 64/32/8 for (SM and GSM)/FGSM and the primary signal constellation of the proposed EFGSM, respectively. The BPSK is used as a secondary signal constellation of the proposed EFGSM. As shown in Figure 3, the proposed EFGSM outperforms the conventional SM, GSM, FGSM in terms of ABER. The ABER of achieving SE of 9 (bpcu) are depicted in Figure 4. Here as well, the TX/RX antenna configuration is assumed to be (4\(\times\)4) in all schemes, and the \(M\)-QAM modulation orders are 128/64/8 for (SM and GSM)/FGSM and the primary signal constellation of the proposed EFGSM, respectively. In this case, the secondary signal constellation of the proposed EFGSM is quadrature phase shift keying (QPSK) modulation. Figure 4 shows that the EFGSM outperforms the conventional SM and GSM by 2.4 dB at nearly the same ABER of the conventional FGSM scheme. Based on that, the proposed EFGSM shows significantly better BER performance than current SM and GSM schemes and outperforms the performance of FGSM slightly. That allows the use of a lower modulation order than conventional SMSs. The FGSM has ABER performance nearly like that of the proposed EFGSM due to the varying of the antenna combinations (same data transmitted through more than one antenna providing high diversity with high power consumption).  
Figure 2: The maximum achievable data rates of the proposed EFGSM scheme compared to the maximum achievable data rates of the current SM, GSM, and FGSM at infinite SNR.
# Preparation and Application of ZIF-8 Thin Layers
## 2 Materials and Methods
### Doctor Blade Technique for Composite Layer Containing PVDF Binder and ZIF-8  
For creating a thin layer containing PVDF binder (Solef 21216, Solvay) and ZIF-8 (Basolite\({}^{\copyright}\) Z1200, Sigma Aldrich, St. Louis, MO, USA) on the Cu foil, we added 40 mg of PVDF and 160 mg of ZIF-8 into 800 \(\upmu\)L 1-Methyl-2-pyrrolidone [NMP] (99%, Sigma Aldrich, St. Louis, MO, USA). The components were mixed in a ball mill for 30 min at 25 Hz (8 steel balls, 3 mm in diameter were used). Approximately 500 \(\upmu\)L of the resulting dispersion was added to a doctor blade coating machine; the steel balls were removed mechanically. The blade was set to 20 \(\upmu\)m thickness and a forward speed of 5 mm/s. The resulting layer, with an average coating area of 100 cm\({}^{2}\), was than dried overnight at room temperature and for an additional 24 h in a drying chamber at 80 \({}^{\circ}\)C. Circles with a diameter of 20 mm were then punched out for later use and better manageability.  
The same procedure was done for other mixing combinations of PVDF/ ZIF-8 (20 mg/180 mg, 60 mg/140 mg and 80 mg/120 mg). The changed viscosity of the resulting suspension was roughly corrected by adding an additional 50 \(\upmu\)L of NMP.
## 3 Generic Routing Solutions  
Most routing protocols are designed for wired networks [24, 25] and Mobile Ad-hoc Networks (MANETs) [26, 27] in general. The routing protocols can primarily be classified into two main categories: (i) Link-State Routing Protocols (LSRPs) [28, 29] and (ii) Distance Vector Routing Protocols (DVRPs) [30, 31]. These two categories are discussed in detail in the following sections. A summary of the main generic routing protocols is shown in Figure 3.