esa-sceva/satcom-chunk-collection huggingface dataset:
# Numerical Study on the Bending Performance of Steel-Ribbed Composite Slabs for Substations
## 2 Design Scheme of Steel-Ribbed Composite Slabs  
### Project Background  
The Daocheng (Huangbuling) 500 kV substation, shown in Figure 1a, was upgraded from the original 220 kV substation. The introduction of new transformer equipment has increased the design floor loads to 34.2 kN/m\({}^{2}\), much higher than that for civil buildings. In order to meet the stringent requirements, the scheme of steel-ribbed composite slabs was adopted in the prefabricated construction. Meanwhile, a grid of inner beams was set beneath the floor slabs for enhancement. Figure 1b illustrates part of the structural layout plan for the 8.800 m floor. It can be seen that parts of the floors belong to one-way slabs. However, most floors enclosed by primary and secondary beams, where the ratio of the room's long side to short side is less than 2, will be subjected to bidirectional loading.
## 3 Engineering Application
### Performance Evaluation of the FTU  
The data from 20 January 2019 to 1 May 2019 in the complete data set \(\Psi_{C}\) were defined as the healthy standard data set \(\Psi_{H}\), including 4814 samples. The FTU was maintained before 20 January 2019, and it performed well in the restart test. Meanwhile, this period includes all possible operating conditions, especially the water head. The rest of the data were defined as the evaluated data set \(\Psi_{E}\), including 7824 samples.  
The operating parameters \(H_{H}\) and \(P_{H}\) in \(\Psi_{H}\) were selected as two independent variables, and \(V_{H}\) was selected as the dependent variable. The GPR algorithm was adopted to fit the mapping relationship between \((H_{H},P_{H})\) and the probability density distribution of \(V_{H}\), as the healthy-state model. Figure 13a shows the three-dimensional surface formed by the mean value of \(prob_{H_{H},P_{H}}(V_{H})\). In addition, three operating conditions ((\(H\) = 156.7 m, \(P\) = 600 MW), (\(H\) = 156.7 m, \(P\) = 300 MW), and (\(H\) = 130.0 m, \(P\) = 300 MW)) were selected as the example to draw the probability density distribution curve of \(prob_{H_{H},P_{H}}(V_{H})\), as shown in Figure 13b. Obviously, the distribution of the vibration amplitude of the top cover is highly related to the operating condition parameters. At the rated operating condition (\(H\) = 156.7 m, \(P\) = 600 MW), the vibration amplitude distribution is more concentrated.  
The operating parameters \((H_{E},P_{E})\) of the evaluated data set \(\Psi_{E}\) were inputted into the constructed healthy-state model to calculate the healthy standard distribution function of the vibration amplitude \(prob_{H_{E},P_{E}}(V)\). Then, \(V_{E}\) was put into the function, and the NLLP \(=-\log(prob_{H_{E},P_{E}}(V_{E}))\) was calculated as the PDI of the FTU. Moreover, considering that sufficient samples can reflect the characteristics of the probability density, one day (48 samples) was taken as the time window to generate a moving average for the calculated PDIs, and the finally obtained PDI curve is shown in Figure 14. The defined PDI based on the NLLP represents the difference in the probability density distribution between the current state and the healthy state. The PDI indicates the relative degradation trend of the FTU, so it is a dimensionless value. It can be seen that the PDI remains stable from 1 May 2019 to 18 May 2019, and the curve shows an apparent upward trend with oscillation after 18 May 2019.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Length of the input sequence & 20 \\ Number of hidden units in the generator & 32 \\ Number of hidden units in the discriminator & 32 \\ Clipping coefficient & 0.01 \\ Epochs of training & 250 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Main parameters of the GRUD–WGAN.  
Figure 12: The distribution of data imputation results: (**a**) water head \(H_{i}\) (**b**) active power \(P\); and (**c**) vibration amplitude of the top cover \(V\).
# Modified Echo State Network Enabled Dynamic Duty Cycle for Optimal Opportunistic Routing in EH-WSNs
###### Abstract  
Minimizing energy consumption is one of the major challenges in wireless sensor networks (WSNs) due to the limited size of batteries and the resource constrained tiny sensor nodes. Energy harvesting in wireless sensor networks (EH-WSNs) is one of the promising solutions to minimize the energy consumption in wireless sensor networks for prolonging the overall network lifetime. However, static energy harvesting in individual sensor nodes is normally limited and unbalanced among the network nodes. In this context, this paper proposes a modified echo state network (MESN) based dynamic duty cycle with optimal opportunistic routing (OOR) for EH-WSNs. The proposed model is used to act as a predictor for finding the expected energy consumption of the next slot in dynamic duty cycle. The model has adapted a whale optimization algorithm (WOA) for optimally selecting the weights of the neurons in the reservoir layer of the echo state network towards minimizing energy consumption at each node as well as at the network level. The adapted WOA enabled energy harvesting model provides stable output from the MESN relying on optimal weight selection in the reservoir layer. The dynamic duty cycle is updated based on energy consumption and optimal threshold energy for transmission and reception at bit level. The proposed OOR scheme uses multiple energy centric parameters for selecting the relay set oriented forwarding paths for each neighbor nodes. The performance analysis of the proposed model in realistic environments attests the benefits in terms of energy centric metrics such as energy consumption, network lifetime, delay, packet delivery ratio and throughput as compared to the state-of-the-art-techniques.  
routing; energy harvesting; wireless sensor network; modified echo state network; whale optimization algorithm +
Footnote †: journal:  
0000-0001-5000-0000
# Towards High Usability in Gamified Systems: A Systematic Review of Key Concepts and Approaches
## 4 Discussion
The recommendations concerning learnability were most often mentioned: for children \(n=31\) (5.16 per paper on average); for adults, including elderly \(n=21\) (avg. = 3.5); undefined \(n=26\) (avg. = 3.25). The user interface aesthetics turned out to be the least-addressed usability characteristic. This came as a surprise, as aesthetics have a big influence on the mood the system creates and thus one could presume that for gamified systems, which are of an inherently ambiguous nature and must balance playfulness and seriousness, this factor should be quite important. The principle of consistency and standards was also not stressed by the analysed authors, which may indicate that the gamified systems, as a relatively new class of software, does not rely so heavily on following recognized conventions. On the other hand, it cannot be forgotten that certain usability recommendations are considered to be universally applicable to all systems without exceptions, and hence they may have been deliberately omitted by the analysed authors. RQ3. Do gamified system usability recommendations depend on the system application domain? As can be seen from the data given in Table 3, gamification in the domains of education and medicine was discussed most often (30% and 25% of the analysed papers, respectively). The authors of 35% of the selected publications did not indicate any gamification domain(s) that their recommendations were for. Not surprisingly, the largest total number of recommendations were positioned as aimed at the gamification of education. However, similar to the question RQ2, the review results show that the gamified system application domain did not have a substantial impact on the nature of outlined usability recommendations. In all of the application domains (medicine, education, business, sports and undefined), the most mentioned recommendations were related to the learnability aspect of the systems'usability: medicine \(n=18\) (avg. = 3.6); education = 30 (avg. = 5); sport \(n=5\) (avg. = 5). business \(n=4\) (avg. = 4); undefined \(n=21\) (avg. = 2.63). Speaking of the limitations of the conducted review, the generalizability of its results is somewhat compromised by the fact that the analysis only focussed on research journals and conferences. The usability of gamified systems is a highly practical topic and therefore it can be discussed in books as well as online blogs, forums and similar non-academic sources, which were not the subject of this analysis. Furthermore, the number of papers that were selected was not high-20 in total. One could observe a spike in relevant research activity in years 2017 and 2019, but, overall, the numbers of publications on the analysed topics were consistently low. This may have compromised the analysis with regards to the research questions RQ2 and RQ3, as the differences or, more precisely, similarities in the nature of the various recommendation sets could have been due to chance.
## 6 Conclusions  
The present work explored the feasibility of simultaneous detection of apple MC and pH using VIS-NIR HSI. Five different machine-learning models were employed to analyze HSI data. The correlation coefficients were identified as 0.868 and 0.383 for ANN, 0.844 and 0.307 for DT, 0.847 and 0.373 for KNN, 0.857 and 0.190 for MLR, and 0.864 and 0.231 for PLSR when predicting MC and pH, respectively. Hence, the predictions of the former and latter apple parameters were promising and poor, respectively. The superior performance of the ANN algorithms in analyzing VIS-NIR HSI data suggests that the well-known and commonly used PLSR approach is inferior to using ANN as a state-of-the-art intelligent algorithm. This exploration sets the stage for further research and developments in the field.  
E.K., visualization, software, implementing data curation, validation, AI and statistical methods, writing--original draft. N.C., conceptualization, formal analysis, investigation, methodology, data curation, resources, visualization, writing--original draft. B.Y., data curation, software, visualization, writing--original draft. M.N., results validation, writing--original, writing--revision. J.P., results validation, writing--revision. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data that support the findings of this study are available from the corresponding authors, upon reasonable request.  
**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
## 1 Introduction
The use of several red and red-edge bands for predicting the crop coefficient, \(Kc\), in cotton was studied in [18]. These prediction models were used for near-real-time irrigation decision support systems. Additional research was developed in [19] using color images from unmanned aerial vehicles (UAVs); a water deficit index (WDI) can provide accurate crop-water stress maps at different growth stages of barley and in differing weather situations. Another application of imaging in irrigation was published in [20], where the authors presented a device based on computer vision and multi-tasking processes to develop a small-scale smart agricultural machine that was able to automatically weed and perform variable rate irrigation within a field. Crop stress monitoring based on low altitude remote sensing technologies is proposed in [21]; a small UAV with multispectral and infrared thermal imaging sensors was used to collect data from bean field plots during 2015 and 2016. Indicators used included leaf area index (LAI), green normalized vegetation index (GNDVI), canopy cover (CC), and canopy temperature (CT). These indicators were suitable for detecting deficit irrigation treatments. In [22], another application of low-altitude UAVs is described; the system is called a Pheno-Copter and uses RGB, infrared, and thermal cameras to perform plant phenotyping on large areas. Thus, detection of the ripeness stages of fruits in orchards under natural light and background using a computer vision system can allow precise irrigation planning and a proper management of fruits during harvesting, transportation, storage, and market delivery. For this reason, the aim of this study was to develop a new algorithm to detect apples and estimate their ripeness stages in apple cultivars of the Red Delicious variety, using images captured under natural light and background, like those obtained from drones flying at a medium-low altitude. The proposed approach is based on a combination of hybrid artificial neural networks, genetic algorithms, and extraction of the most effective color features. To emulate the conditions of drone acquisition systems, video analysis is used instead of still image processing.
# Building Information Modelling and Energy Simulation for Architecture Design
## 6 Application of the Methodology on an Existing Case Study  
In order to verify their correctness, the procedures for the energy analysis in the BIM environment, developed on a sample building, have been tested on a sample building. Indeed, only a building complete in all its parts can provide the necessary information, especially from the plant engineering point of view. Furthermore, in an existing building, the systems have already been measured and have precise characteristics. They can be traced back by recovering the technical sheets drawn up by the manufacturers. The research of the case study was conducted by preliminarily defining some characteristics that the case study building must possess. The aim was to validate the methodology and the final results of the energy simulation. These features are:  
* End use: The residential end-use is the one of greatest application interest, as well because many policies aimed to reduce consumption of residential architecture;
* simplicity of the case study: Both in terms of geometric or constructive characteristics, in terms of thermal zones and for the absence of peculiar characteristics (e.g., underground habitable rooms, large glazed areas, or systems designed ad hoc and different from the more common types);
* size: It is a medium size building. It implies the exclusion of individual housing units exposed to the external environment on all sides (this condition would prevent testing all the potential of the software), i.e., large apartment complexes consisting of a few thermal zones, but repeated for several floors (in this case there would be a large amount of data, not very significant from the point of view of the calculation), i.e., considering a 7-storey condominium, in the calculation phase, the significant floors are the ground floor that exchanges heat with the ground, the floor that borders two heated rooms both above and below, and the top floor that exchanges heat with the outside through the cover. For the purposes of this study, it would be enough to consider only one of the 5 floors bordering heated rooms. A good compromise is therefore offered by buildings with two (or rather three) elevations above ground;
* building envelope and thermal plants: All the information about stratigraphy, fixtures, and materials were known or can be inferred with a good approximation;
* it is an existing building.
## 3 Results and Discussion  
To obtain the best extraction performance of the HDE-SBME method, two approaches were used to optimize the influence of different experimental parameters. A univariate approach based on chromatographic peak area was used to evaluate the effect of using various types of synthesized HDEs and the effect of sample solution pHs, while for reduced labor and experimental effort, experimental parameters, including the number of SBME devices, extraction time, and elution conditions, were optimized using the multivariate methodology. These experiments used spiked ultrapure water (20 mL) with various BES, PRO, and TES concentrations. All experiments were run in triplicate, and the average of the results was used for optimization.
_Article_  
**Corrosion Protection Evaluation of Mild Steel: The Role of Hybrid Materials Loaded with Inhibitors**  
**[PERSON]\({}^{\textregistered}\) and [PERSON] \({}^{\textregistered}\)**  
Research Unit of Advanced, Composite, Nano-Materials and Nanotechnology, School of Chemical Engineering, National Technical University of Athens, GR-15773 Athens, Greece; [EMAIL_ADDRESS]  
\({}^{\star}\) Correspondence: [EMAIL_ADDRESS]; Tel.: +30-210-772-4046  
Received: 4 August 2020; Accepted: 18 September 2020; Published: 21 September 2020  
**Featured Application: The Ce\({}_{x}\)TiyO\({}_{x}\) nanocontainers that fabricated and loaded with 5-amino-1, 3,4-thiadiazole-2-thiol in this work, can be used in the interior side of mild steel pipelines conveying liquids in order to protect them from corrosion.**  
**Abstract:** In the present work, an assessment of the corrosion behavior of mild steel in the presence of an organic corrosion inhibitor loaded into hybrid composite materials is performed. Hybrid organic-inorganic nanocontainers based on cerium and titanium oxides were fabricated via a combination of radical polymerization together with the coprecipitation method and sol-gel technique. The corrosion inhibition role of these hybrid materials loaded with an inhibitor is considered. A set of characterization assays addressing morphology, composition and structural aspects of the exposed steels is illustrated, along with electrochemical evaluations. The results reveal enhanced stimuli responsive anticorrosion ability of the produced hybrid materials. Furthermore, upon corrosion, new compounds are formed onto the exposed areas of the treated metals. The conducted experiments shed light on the corrosion mechanisms for steel alloys as well as the actuation of the fabricated composite materials, paving the way for future developments in this area.  
**Keywords:** steel; EIS (electrochemical impedance spectroscopy); Raman spectroscopy; hybrid materials
# Semantic Attention Guided Hierarchical Decision Network for Age Estimation
## 4 Experimental Results and Analysis
### Comparisions with State-of-the-Arts  
#### 4.4.1 Experiments on Morph II Dataset  
The proposed framework is first compared with recent state-of-the-art methods on the Morph II benchmark. Among non-hierarchical methods, the MV [37] reports an MAE of 2.16, with CS(3) at 75.00% and CS(5) at 89.90%, while DAA [9] achieves an MAE of 2.06 by combining delta-age encoding with a binary transformer. Classic ensembles of models such as DEX [32] achieves an MAE of 2.68. In hierarchical architectures, SSR-Net [15] reaches an MAE above 3.1, with CS(5) remaining below 80%. The compact ALD-Net [38], which usesno additional pre-training, achieves an MAE of 2.65. Transformer-based methods further improve the performance; for example, GroupFace [20] couples multi-hop graph attention with group-aware margins and attains 2.01 MAE. Table 1 summarizes these results in terms of MAE, CS(3), CS(5). Benefiting from its semantic attention guided two-stage design, the proposed model achieves an MAE of 2.18 with ImageNet pre-training, comparable to MV [37] and surpassing most hierarchical and CNN ensemble baseline methods. For cumulative scores, our model reaches 79.93% for CS(3) and 90.96% for CS(5), demonstrating superior performance in distinguishing adjacent age labels.  
Our proposed method follows a coarse-to-fine hierarchical strategy by first predicting a global age and then refining it locally. Compared to most methods, our framework achieves better performance through several key improvements. Instead of relying solely on the final CNN features, we extract multi-stage features from a Swin Transformer backbone and fuse them using enhanced bilinear pooling, capturing fine-grained age cues more effectively. Moreover, we introduce a lightweight semantic attention mechanism that leverages global age predictions to guide local feature refinement, allowing the model to focus on age-sensitive regions. The integration of multi-scale feature extraction, global context enhancement, and adaptive feature weighting further boosts the model's capacity to distinguish adjacent ages under varied conditions. All modules are jointly optimized in an end-to-end fashion, ensuring coherent learning between the global and local stages.
## 4 Conclusions  
CaWO\({}_{4}\) single crystals doped with Nd (0.1, 0.5, and 1%) were grown by the FZ method. The optical and scintillation characteristics were investigated. Typical luminescence and decay times due to the Nd\({}^{3+}\) transitions were confirmed when monitored at NIR ranges. To confirm the performance of NIR scintillation detectors, X-ray irradiated dose rate response properties were evaluated by using the crystals and an InGaAs-PD. The 0.5% Nd-doped crystal indicated the widest dynamic range (0.06-60 Gy/h) in all the present crystals. The result was comparable to the measurable ranges of other Nd-doped phosphors combined with an InGaAs-PD, such as Nd-doped SrY\({}_{2}\)O\({}_{4}\) and Nd-doped Bi\({}_{4}\)Ge\({}_{3}\)O\({}_{12}\), and it was superior to that of other scintillators emitting red light combined with Si-based detectors: Cs\({}_{2}\)Hf\({}_{6}\) and commercial Pr-doped Gd\({}_{2}\)O\({}_{2}\)S. From the study, Nd-doped CaWO\({}_{4}\) crystals were suggested to have the potential as NIR-scintillators used in high-dose field monitoring.  
Conceptualization, K.O.; methodology, K.O. and H.F.; validation, H.F., D.N., T.K., N.K. and T.Y.; formal analysis, K.O. and D.N.; investigation, K.O., D.N. and T.Y.; resources, T.Y.; data curation, K.O.; writing--original draft preparation, K.O.; writing--review and editing, K.O. and T.Y.; visualization, K.O.; supervision, T.Y.; project administration, T.Y.; funding acquisition, D.N., T.K., N.K. and T.Y. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Grant-in-Aid for Scientific Research A (22H0309), Scientific Research B (21H03733, 21H03736, and 22H03872), and Exploratory Research (22K18997) from Japan Society for the Promotion of Science. JST A-STEP, Foundation from Cooperative Research Project of Research Center for Biomedical Engineering, Nippon Sheet Glass Foundation, Terumo Life Science Foundation, Iwatani Naoji Foundation, and Konica Minolta Science and Technology Foundation are also acknowledged.  
Not applicable.  
The authors declare no conflict of interest.