esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Cost Optimisation Methodology
#### 2.1.1 Buildings under Study  
In the city of Valencia there are approximately 90 public primary schools. For this research, general data regarding 135 school buildings was obtained, corresponding to 79 schools.  
An analysis of construction and architectural features of these buildings has enabled to group them together into six different building types.  
The study is focused on three building types (A, B and C). These were built before the entry of the first Spanish Regulation on thermal characteristics of buildings NBE CT 79 into force, so none of them has thermal envelope insulation, nor have they been recently renovated because of their relative age.  
The main factors that differentiate these school building types are structure and date of construction. Type A building was built using brick load-bearing walls and metal joints, and types B and C were built using a concrete structure. In type A the roof was made of ceramic tile mounted on wood, whereas the roof in types B and C was built by using a slab flat or pitched under the layers that make up the roof. Type B and C buildings have wooden windows, whereas type C includes metal windows.  
In addition to these construction differences, the design and interior spaces vary according to the three types. Type C buildings are elongated or L-shaped buildings, their facade has a historicist character, and were built between 1945 and 1955. Type B buildings were built in the 1960s and follow the designs of the Modern Movement. They have a greater number of floors and are elongated in shape. Type C buildings were built in the 1970s and they are X or XX-shaped (Figure 1).  
These three building types (A, B and C), represent a total of 6, 11 and 29 schools respectively, that is to say, 46 school buildings.  
For each type, a representative model school building is selected (Figure 2). They were built from school prototypes, adapting the architectural design to the site itself. This makes selected school buildings be representative in the city of Valencia, and also in other towns and municipalities.  
Type A and B buildings have a high historical value (listed or officially protected), or a unique architectural design. This means that any energy renovation cannot alter the building geometry and exterior design.  
Although some of them have undergone minor renovations, such as window replacement, the initial condition of the buildings is taken for the energy study as a reference, and former potential improvements are ignored, so that they serve as a baseline to any building type. Table 1 includes the main characteristics of each building type, and Table 2 shows the thermal transmittance of construction elements in the thermal envelope for each building type in its initial state considered for energy study.  
Figure 1: Examples of X or XX-shaped buildings.  
Figure 2: Representative school buildings in the city of Valencia built before 1979. (**a**) Type A school; (**b**) type B school; (**c**) Type C School.
## 4 Discussion
### Environmental Effectiveness  
The environmental evaluation of a cogeneration system primarily considers its carbon dioxide equivalent emissions in comparisons with the classical system. By reviewing the included studies, all those considering the environmental effect confirmed that the cogeneration system is environmentally friendly. For example, in the study of [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] [25], the proposed cogeneration system was predicted to have a low emission of gases, producing 25,708 kg/yr of carbon dioxide, 111 kg/yr of sulfur dioxide and 54.5 kg/yr of nitrogen oxide. It is important for the hospital community to ensure the area maintains healthy and green premises. Therefore, the proposed cogeneration configuration for the hospital is suitable for the environment. Similarly, the results in [PERSON] and [PERSON] [35] show that the modeled CHP system reduced emissions for all seven types of commercial buildings examined, with more than 21% of carbon equivalent emissions reduced for an outpatient healthcare building. In another model-based simulation study, [PERSON], [PERSON] and [PERSON] [22] reported that the optimal CPH system allowed for a reduction of the carbon dioxide equivalent emissions of up to 18.9%. Therefore, as stated in [PERSON], [PERSON], [PERSON] and [PERSON] [26], an optimal CPH configuration is a more efficient way of reducing gas emission. The demonstration of these desirable results indicates that the CPH implementation is a reliable effort on global climate change [37]. If the carbon emission savings are monetized, the annual worth will be higher [26].  
In short, the CPH system represents a more efficient way of economically and environmentally producing heat and power. However, the system viability and feasibility are crucially determined by several essential factors, i.e., energy demands (e.g., [14; 37]), energy supply (e.g., [14; 26]), system unit size (e.g., [15; 40]), operational costs (e.g., [21]), and other possible parameters. In reality, these factors will definitely influence the decision to install a suitable cogeneration type.
###### Abstract  
This study examines the potential of the soft computing technique, namely, multiple linear regression (MLR), genetic programming (GP), classification and regression trees (CART) and GA-ENN (genetic algorithm-emotional neuron network), to predict the ultimate bearing capacity (UBC) of cohesionless soils beneath shallow foundations. For the first time, two grey-box AI models, GP and CART, and one hybrid AI model, GA-ENN, were used in the literature to predict UBC. The inputs of the model are the width of footing (B), depth of footing (D), footing geometry (ratio of length to width, L/B), unit weight of sand (\(\gamma_{\text{d}}\) or \(\gamma^{\prime}\)), and internal friction angle (\(\phi\)). The results of the present model were compared with those obtained via two theoretical approaches and one AI approach reported in the literature. The statistical evaluation of results shows that the presently applied paradigm is better than the theoretical approaches and is competing well for the prediction of \(\text{q}_{\text{u}}\). This study shows that the developed AI models are a robust model for the \(\text{q}_{\text{u}}\) prediction of shallow foundations on cohesionless soil. Sensitivity analysis was also carried out to determine the effect of each input parameter. The findings showed that the width and depth of the foundation and unit weight of soil (\(\gamma_{\text{d}}\) or \(\gamma^{\prime}\)) played the most significant roles, while the internal friction angle and L/B showed less importance in predicting \(\text{q}_{\text{u}}\).  
ultimate bearing capacity; cohesionless soils; genetic programming; genetic algorithm-emotional neural network; classification and regression random forest; artificial intelligence
# A Survey of Candidate Waveforms for beyond 5G Systems
## 5 Conclusions  
This paper addressed the main KPI regarding the 5G and beyond candidates waveforms and also discussed the challenges they present in order to fulfill the diverse set of requirements for future wireless communications. It also described in the detail the advantages and disadvantages of each waveform, while providing a detailed overview of the transceiver architecture of each MC scheme.  
Ultimately, we can state that there is no ideal waveform that can fit all requirements, and trade-offs must be be beared in mind. Therefore, in order to select the most suitable waveform formats for a specific scenario, future wireless systems must be flexible by taking into account the different 5G and beyond services requirements and propagation conditions. An alternative solution consists of choosing and adapting the waveform format that suits the most service requirements for a specific type of application.  
Conceptualization, F.C.; methodology, F.C.; software, A.S. and D.C.; validation, M.G., V.S., R.D., A.S. and D.C.; formal analysis, F.C., M.G., V.S., R.D., A.S. and D.C.; investigation, F.C., M.G., V.S., R.D., A.S. and D.C.; resources, M.G. and V.S.; Software, A.S. and D.C.; data curation, F.C., M.G., V.S. and R.D.; writing-original draft preparation, F.C.; writing-review and editing, M.G., V.S., R.D., A.S. and D.C.; visualization, F.C. and M.G.; supervision, M.G., V.S., R.D., A.S. and D.C.; project administration, M.G., V.S., R.D., A.S. and D.C.; funding acquisition, M.G., V.S., R.D., A.S. and D.C. All authors have read and agreed to the published version of the manuscript.  
This work is funded by FCT/MCTES under the projects MASSIVE5G (POCI-01-0145-FEDER-030588) and UIDB/50008/2020-UIDP/50008/2020.  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
**Conflicts of Interest**: The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**KPI** & **OFDM** & **F-OFDM** & **GFDM** & **TIBWB-OFDM** & **TIBWB-OFDM with WTO** \\ \hline PAPR & High & High & High & Very High & High \\ \hline Spectral efficiency & Low & Low & Very High & High & Very High \\ \hline OOB emissions & High & Very Low & Moderate/ Low & Very low & Low \\ \hline Reliability (BER performance) & Moderate & Moderate & Low & Low/Moderate & Moderate \\ \hline Computation complexity & Low & Moderate & High & Moderate/ High & High/ Very High \\ \hline Processing delay & Low & Low & High & High & High \\ \hline Robustness to frequency selectivity & High & High & High & Very High & Very High \\ \hline Robustness to time selectivity & Low & Low & High & High & High \\ \hline Efficient MIMO implementation & High & High & Moderate & High & High \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of different MC schemes.
## 3 Digital Beam-Forming
### Log-Periodic Dipole Antenna  
The antenna in the array is the Log-Periodic Dipole Antenna (LPDA). The structure of the antenna is illustrated in Figure 3. The LPDA unit consists of 18 dipole elements with a boom length of approximately 14 m, while the longest dipole element is almost 15 m long. All of the elements are made with 10-mm-diameter aluminum tubes. The LPDA is top fed and the feed point is near the shortest dipole element. The 18 dipole elements are fed via a transmission line. The antenna balun is made of coiled coaxial cable, which is installed on the main rod.  
Figure 3: Sketch of the LPDA of the WIOBSS-AA.  
The antenna of the WIOBSS-AA was designed and validated by the Computer Simulation Technology MICROWAVE STUDIO (CST MWS) (Bad Nauheimer Strasse, Darmstadt, Germany). Each element of the LPDA is formed by wires in the model. The LPDA is excited by a voltage source. The simulations are performed for ground environment using lossless ground approximation. The computed radiation pattern of a single LPDA is shown in Figure 4.  
The symmetric antenna radiation pattern of a single LPDA pointing to elevation of 32\({}^{\circ}\) has a half power beam width of 71.4\({}^{\circ}\). The directive gain of the LPDA is 11.7 dBi.
# Recent Web Platforms for Multi-Omics Integration Unlocking Biological Complexity
## 2 Methods
### Platforms for Clinical Decision-Making and Personalized Medicine
#### 2.4.1 GraphOmics: A Network-Based Approach to Multi-Omics Data for Disease Biomarker Identification  
Designed for multi-omics network-based analysis, GraphOmics leverages Reactome pathways to identify disease biomarkers, with its clustering and pathway enrichment tools applied in metabolic syndrome research to identify novel therapeutic targets [29]. However, the platform's computational demands limit its accessibility for smaller clinical research teams. By integrating data from genomics, proteomics, and metabolomics, interaction networks are created, revealing how molecular elements are connected in the context of disease. Clinical decision-making is supported through the identification of disease-associated pathways and molecular signatures, which can be leveraged to predict treatment responses. Network-based analyses enable researchers and clinicians to explore the relationships between molecular factors and their impact on disease outcomes.  
The ability to handle large, multi-dimensional datasets while providing detailed network visualizations is one of the platform's essential strengths. However, significant computational resources and advanced expertise in network biology are required for effective use, making GraphOmics less accessible to non-expert users.  
Although GraphOmics offers a powerful means of analyzing large, multi-dimensional datasets, it requires significant computational resources and expertise in network biology, limiting its accessibility for non-expert users. To address this challenge, platforms like OmicsAnalyst aim to provide a more user-friendly interface for clinical research, enabling a broader range of researchers to explore multi-omics data.
# Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis
## 2 Business Integrity Management and Analytics Framework
### Big Data Processing and Analysis Services Offered by BIMA Framework
#### 2.4.3. Heston Model  
The Heston model is a specialized stochastic model aiming to calculate volatility concerning prices. It relaxes the constant volatility assumption in the classical Black-Scholes model by incorporating an immediate short-term variance process based on market volatility [42]. The Heston model contains the Wiener process and the CIR process. The Wiener process is a continuous-time stochastic process used under BSM to calculate pricing options [33]. The Heston model has been derived from the CIR model of [PERSON], Ingersoll, and Ross for interest rates. The CIR process is a Markov process with continuous paths defined by the following stochastic differential equation (SDE). The Heston model has the following advantages in financial derivatives demonstrated by [PERSON] [43].  
* Compute and track volatility--The Heston model can track the movement of volatility, which can help investors to make a better judgment for investment when prices are high and volatility is low (which happens but the period is short and it is not always available).
* Accuracy--The Heston model can compute pricing and risk values to several decimal places and also calculate its mean, lower, and upper range to get our results as accurate as possible. Accuracy can be measured based on the differences between the actual and predicted values and ways to get very close, as demonstrated by our previous work.
# Optimization Study on a Novel High-Speed Oil-Free Centrifugal Water Pump with Hydrodynamic Bearings
## 2 Numerical Model  
### Physical Model  
The structure of the high-speed centrifugal pump is illustrated in Figure 1 and it is comprised of rotating and stationary components. Stationary components include inlet and outlet cover plates, a stay vane, guide section, shells, a motor stator, and supporting components. Moreover, rotating components consist of an inducer, an impeller, hydrodynamic bearings, and a shaft. The flow path is formed by the cavity between the rotating and stationary components. The liquid is speeded up and its cavitation is enhanced by the high rotating inducer. After the fluid flows through the impeller,the kinetic energy of the impeller transfers into that of the fluid. In order to reduce the flow loss, the stay vane after the impeller transfers the kinetic energy of the fluid into its pressure energy. Most of the fluid enters the flow path in the motor. After cooling the motor, it is collected by the outlet cover plate. Only a small percentage of the fluid passes through the gap under the stay vane, enters into the gap in the hydrodynamic liquid lubricated bearing and provides the bearing capacity by establishing a liquid film.  
The main hydraulic components of the high-speed centrifugal pump are shown in Figure 2a. The hydrodynamic bearings are made up of the rotational radial ring and the fixed thrust ring as a pair, as shown in Figure 2b. Except for the opposite rotational direction of spiral grooves, two rings have the same parameters and distribute at the inlet and outlet, respectively. When rotational ring rotates, the working fluid is sucked into spiral grooves and is blocked by the dam region. The retention of the working fluid promotes a high-pressure zone to form. The pressure is applied on the stationary ring providing the bearing capacity for the rotor.  
Figure 1: Structure of the novel high-speed centrifugal pump.  
Figure 2: (**a**) Main hydraulic components of high-speed centrifugal pump. (**b**) Details of Hydrodynamic Bearings.  
Table 1 lists the main parameters of the high-speed centrifugal pump at the designed point. Due to the limitation of processing technology, the impeller is designed as a semi-open cylindrical structure by the velocity coefficient method. The meridian profiles use the Bezier curves, whereas the cross-sectional area has a uniform changing. In order to ensure a square throat, the stay vane is designed to be two-dimensional, twisted by the area ratio method. Profiles of the inlet section uses the circular arc curves; those of the diffusion and outlet sections adopt the Bezier curves. The vane inlet angle equals the outlet fluid flow angle. In addition, labyrinth seals are designed on the stay vane to reduce the leak at the back gear. The guide section is a circular flow channel with no vanes. The radial flow from the impeller outlet can be changed into an axial flow by the stay vane and the guide section. In order to ensure a uniform change of the flow area and a smoother flow, the guide section is made up of two curves.
## 4 Experiments
### Extracting Foot Parameters
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Number of Models**} & \multicolumn{2}{c}{**Manual Measurement**} & \multicolumn{2}{c}{**960 \(\times\) 540**} & \multicolumn{2}{c}{**640 \(\times\) 360**} & \multicolumn{2}{c}{**480 \(\times\) 270**} \\ \cline{2-9}  & **FL** & **FW** & **FL** & **FW** & **FL** & **FW** & **FL** & **FW** \\  & **(mm)** & **(mm)** & **(mm)** & **(mm)** & **(mm)** & **(mm)** & **(mm)** & **(mm)** & **(mm)** \\ \hline
1 & 265 & 123 & 264.5/(0.5) & 122.8/(0.2) & 264.7/(0.3) & 122.8 (0.2) & 264.8/(0.2) & 122.9/(0.1) \\
2 & 247 & 98 & 247.4/(0.4) & 98.7/(0.7) & 247.2/(0.2) & 98.7/(0.7) & 247.3/(0.3) & 98.4/(0.4) \\
3 & 242 & 95 & 243.3/(1.3) & 97.4/(2.4) & 243.3/(1.3) & 97/(2.0) & 243.1/(1.1) & 96.7/(1.7) \\
4 & 285 & 125 & 288.5/(3.5) & 127.3/(2.3) & 288.3/(3.3) & 127.1/(2.1) & 288.2/(3.2) & 127/(2.0) \\
5 & 235 & 93 & 235.4/(0.4) & 93.3/(0.3) & 235.3/(0.3) & 93.3/(0.3) & 235.3/(0.3) & 93.2/(0.2) \\
6 & 261 & 119 & 262.7/(1.7) & 121.1/(2.1) & 262.6/(1.6) & 120.9/(1.9) & 262.4/(1.4) & 120.8/(1.8) \\
7 & 238 & 91 & 237.3/(0.7) & 90.5/(0.5) & 237.4/(0.6) & 90.5/(0.5) & 237.4/(0.6) & 90.4/(0.6) \\
8 & 235 & 92 & 238.5/(3.5) & 92.7/(0.7) & 238.3/(3.3) & 92.7/(0.7) & 238.4/(3.4) & 92.6/(0.6) \\
9 & 269 & 121 & 268/(1.0) & 121.8/(0.8) & 268.3/(0.7) & 121.7/(0.7) & 268.4/(0.6) & 121.6/(0.6) \\
10 & 272 & 127 & 274.1/(2.1) & 127.7/(0.7) & 273.9/(1.9) & 127.5/(0.5) & 273.8/(1.8) & 127.5/(1.5) \\ \hline \multicolumn{9}{c}{Avg. Time (min)} & \multicolumn{2}{c}{3.22} & \multicolumn{2}{c}{2.12} & \multicolumn{2}{c}{**1.35**} \\ \multicolumn{9}{c}{Standard deviation (mm)} & \multicolumn{2}{c}{1.03} & \multicolumn{2}{c}{0.97} & \multicolumn{2}{c}{**0.95**} \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of the effect of different resolutions on the foot and average time to create a 3D model. Figure 9: Demonstration of reconstructed 3D model #1 of the foot based on a series of images with resolution of 480 \(\times\) 270 (pixels). (**a**) Left side of the foot; (**b**) Right side of the foot.
## 4 Conclusions  
In conclusion, we employed electrodeposited-cobalt selenide (Co\({}_{3}\)Se\({}_{4}\)) co-catalyst on a silicon photoelectrode system for the water splitting reaction. The SEM image confirms the uniform distribution of the Co\({}_{3}\)Se\({}_{4}\) film over the electrode material. The controlled loading of Co\({}_{3}\)Se\({}_{4}\) over the substrates was effectively optimized by varying the deposition time. The prepared Co\({}_{3}\)Se\({}_{4}\) electrodes were successfully investigated and found to be efficient electrocatalysts for hydrogen evolution reactions. For the hydrogen evolution reaction, the Co\({}_{3}\)Se\({}_{4}\) catalyst electrodeposited on FTO substrate for 20 s requires very low overpotential of 215 mV to provide an improved current density of 10 mA/cm\({}^{2}\), compared to the other prepared electrocatalysts. Moreover, this electrocatalyst yielded a very low Tafel slope value of 42.5 mV/dec. From these enhanced HER catalytic activity results, we believe that Co\({}_{3}\)Se\({}_{4}\) prepared by this easy, one-pot electrodeposition method, seems to be the most promising candidate for commercialization as a low cost efficient electrocatalyst for water splitting.  
Conceptualization, U.S.; Methodology, U.S.; Validation, U.S.; Formal Analysis, Y.S. and S.S.; Investigation, S.S. and U.S.; Resources, U.S.; Data Curation, B.M. and S.S.; Writing-Original Draft Preparation, Y.S., J.J. and S.S.; Writing-Review & Editing, U.S., J.J., S.S. and Y.S.; Visualization, B.M. and Y.S.; Supervision, U.S.; Project Administration, U.S. + These authors contributed equally to this work.  
This research was supported by the National Research Foundation of Korea (NRF) and funded by the Ministry of Science, ICT & Future, Republic of Korea (2018R1C1B6001267 and 2018R1A5A1025224).  
The authors declare no conflict of interest.