esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiments and Results
### Experiments  
In this study, several parameters needed to be determined. To accomplish this, we divided our query dataset into two sets of equal size: a training set and a test set. We utilized the queries within the training set to identify the optimal parameter values that yield the highest performance based on the mean average precision (MAP) metric. Table 1 outlines the candidate values considered for these parameters and the values ultimately selected for the study. By performing this parameter selection process, we aimed to enhance the overall effectiveness of our approach in terms of retrieval accuracy, as assessed through the MAP metric.  
In the vote-based retrieval approach, we assigned weights to each weak retrieval system as follows: \(w_{i}=1\) for \(\text{DIR}_{i}\) belonging to the weak category and \(w_{i}=2\) for \(\text{DIR}_{i}\) belonging to the strong category. It is worth noting that these weights have the potential to be learned from a training dataset, but we left this aspect for consideration in future research. To evaluate our approach, we conducted tests using query images and a dataset of 40,000 document images for each DIR system (OCR, Key-Based, Global Image, and Word-Based). Our evaluation was based on the MAP metric, computed for N = 5, where N represents the number of retrieved records sorted from the most similar to the least similar. This evaluation process allowed us to assess the retrieval performance of our system and compare it across the different DIR methods.  
The results of our experiments are as follows: Key-Based DIR, 0.5; OCR-Based DIR, 0.64; Global Image DIR height, 0.74. Notably, the outcomes for the Word-Based DIR system underscore its effectiveness as a strong retrieval system; however, it is important to acknowledge that it may not be scalable for use with large document databases. Despite this, we included the Word-Based DIR system's results in the paper for the sake of completeness and to provide a comprehensive view of our research.  
We also calculated the MAP for the SDBDIR and VBDIR ensemble methods. These calculations were performed with various combinations of weak and strong DIR systems, and the results are detailed in Tables 2 and 3. These tables provide insights into the performance of the ensemble methods across different retrieval scenarios, specifically for N = 5.  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Parameter** & **Candidates** & **Selected Value** \\ \hline C number of clusters in Key-Based & 20, 30, 40, 50, 60 & 50 \\ \(\lambda\) number of labels to generate keys & 3, 4, 5, 6, 7 & 4 \\ L threshold in Word-Based & 0.9, 0.8, 0.7 & 0.8 \\ Minimum contour size & 20, 30, 40, 50 & 20 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameter, candidates, and selected values used in the study.
## 4 Conclusions, Limitations, Future Directions
### Study Limitations  
While the proposed hybrid AI framework demonstrated strong performance in predicting thermal loads across different climates, several limitations must be acknowledged, as follows:  
1. First, the analysis did not include certain detailed building parameters such as the thermal performance of exterior windows, which may influence results in real-world applications;
2. Second, the models were developed using simulated data, which, while controlled and consistent, may not capture all the variabilities present in actual building operation;
3. Third, the framework has not yet been tested in real-time or online predictive environments, which are critical for practical implementation in Building Energy Management Systems (BEMS).
4. Lastly, while the study included three diverse climates in Morocco, the generalizability to other regions requires further validation.
## 2 Materials and Methods
### Life Cycle Inventory
#### 2.2.1 Battery Production Phase  
Automotive battery packs are commonly designed and manufactured in a pack-module-cell structure, in which cells can be clustered in modules [40], which can then be grouped into packs.  
As far as the inventory of the battery pack is concerned, _Argonne's Everbatt closed-loop battery life-cycle model_, published by the Argonne National laboratory, has recently been updated with primary data collected from large-scale commercial battery material producers and automotive LIB manufacturers [21]. The bill of materials (BOM) of the NMC111 battery was therefore derived from this model. An analysis (reported in Section 3.2) was conducted to evaluate the difference between NMC111 and two Nickel-rich cathode chemistries (NMC622 and NMC811). Again, in this case, the BOMs of NMC622 and NMC811 were derived from the Everbatt model. All three BOMs are reported in Table 2.  
The NMC battery materials were divided into two groups (Table 2): the first one includes the materials of which the cells are made and the second one includes all the materials that complete the battery pack. As far as the energy demand for the production phase is concerned, the contributions for the cathode and cells were taken from [23] (see Sections 2.2.1.1 and 2.2.1.2 for details), whereas those for non-cell materials were estimated on the basis of [22] (see Section 2.2.1.3).  
As already mentioned, all the specific emissions were taken from the Ecoinvent 3.6 database.  
Global average emissions were considered for the raw materials and for the heat involved in the NMC battery production phase.  
Specific representative emissions of the Chinese national grid were used for electricity. In fact, even though there are over 200 LIB factories in operation around the world, since 2015, most of the production has been in China. Furthermore, although Nickel-Cobalt-Aluminium (NCA) cathodes are mainly produced in the United States and Japan, the global market leader for NMC cathodes is China, which changed its EV subsidies in 2017 to make NMC batteries eligible [41].
## 3 System Architecture and Service Process
### System Services
#### 3.2.3 Location Monitoring Service  
The location monitoring service is a service to provide location information on the server system and location information on the current monitoring place through the GPS module. The provision of location information is important because remote sites check for such information. The location monitoring service extracts latitude and longitude data from the location data received via the GPS module by the location information manager, and stores it into the database. Then, the Web server requests latitude and longitude data stored in the database to be sent it, and displays the location of the server system on a map based on the latitude and longitude data received through the GUI. Figure 4 shows the operating process of the location monitoring service.  
Figure 4: Operation Process of the Location Monitoring Service.  
Figure 3: Operation Process of the Image Monitoring Service.
# Evaluating the Expressive Range of Super Mario Bros Level Generators
## 4 Experiments and Results  
We generated 200 boards of 100 tiles for each of the generators to have a large amount of information and, thus, capture their true generative nature (Table 2 shows the symbology used). Then, the levels were imported into the software to calculate their metrics. We normalized these values, considering the maximum and minimum of all resulting values as the upper and lower thresholds, respectively. Finally, to create the charts, we divided them into four files (three for each generator and the original levels) and imported them into a Jupyter notebook ([[https://github.com/hansschaa/SMB-ERA-Graphs](https://github.com/hansschaa/SMB-ERA-Graphs)]([https://github.com/hansschaa/SMB-ERA-Graphs](https://github.com/hansschaa/SMB-ERA-Graphs)) (accessed on 13 June 2024)) to create the heatmaps and box/whisker graphs. Finally, the graphs were analyzed, and we describe each one and compare them.  
Regarding the format of the levels, the generator based on GA [9] considers a subgroup of the tiles used for the training of the GAN and MC algorithms. We were forced to simplify some game tiles to just one character. For example, 'Q' and 'S' (blocks that [PERSON] can break and an empty question block) from a study that implemented a GAN [9] were now blocks represented only by the character 'B' (block). Likewise, the shapes of the bottom of the pipes are represented only by 'X' (floor) and not with [, ], \(<\), \(>\). This logic allows us to unify metrics and make the logical representation of each PCG algorithm comparable.  
We also include the original levels used in the MC generator ( [[https://github.com/TheVGLC/TheVGLC/tree/master/Super%20](https://github.com/TheVGLC/TheVGLC/tree/master/Super%20) Mario%20 Bros/Original]([https://github.com/TheVGLC/TheVGLC/tree/master/Super%20](https://github.com/TheVGLC/TheVGLC/tree/master/Super%20) Mario%20 Bros/Original) (accessed on 13 June 2024)) for an additional point of comparison and analysis. Some final results can be seen in Figure 2. The hyperparameters of the algorithms were extracted from each of the articles [8; 9]. Tables 3 and 4 show the hyperparameters for the GA and the GAN, respectively, and the MC-based algorithm only has one hyperparameter called n-level, which is 2.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Character** & **Type** \\ \hline X & Ground and power-up blocks. \\ - & Empty space. \\ B & Block in the air. \\ P & Power-up. \\ E & Enemy. \\ S & Enemy Spiny or plant. \\ C & Coins. \\ \hline \hline \end{tabular}
\end{table}
Table 2: Symbols used for SMB level encoding.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Hyperparameter** & **Value** \\ \hline Population size & 250 \\ Chromosome size & 100 \\ Mutation probability & 0.3 \\ Crossover probability & 0.9 \\ Elite size & 1 \\ Tournament size & 2 \\ Stop criteria & 50 gen \\ Ground entropy & 0 \\ Blocks’ desired sparseness & 1 \\ Enemies’ desired sparseness & 0.5 \\ Coins’ desired sparseness & 0.5 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Hyperparameters for the Genetic Algorithm.
# Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
## 4 Discussion
### Forecasting Sewer Flows
Starting the forecast 30 min later improved the ability to predict flow peaks and the RMSE for radar ensembles was nearly a third of the previous forecast. In the event represented in Figure 13, there were no rain gauge data available. So, the advantage of using radar rainfall ensembles is more evident. The RMSE indicates that the radar ensembles overperform the STEPS ensembles during the first hour forecasted. Analysing the 13 events for longer forecasting lead-times, the performance is case dependent, but both radar ensembles and STEPS ensembles tend to lose their accuracy as forecasting lead-time increases. In the majority of the events there is a time-lag between the measured and forecasted flows, however, this time-lag is not consistent. In some events, the flow peaks are predicted in advance of the actual flow and in other cases, the forecasted flow has a delay when compared to the measured flow. The simulated flows for both radar and gauge do not present the same time lag, confirming that these are uncertainties inherited in the rainfall forecast. The fact that the area studied is an urban area of small dimensions with both permeable and impermeable surfaces means that the catchment response time is very small, and any uncertainties related to the rainfall forecast have an almost immediate effect in the flow forecast. Tests performed with the ensembles forecasts, where high-intensity rainfall pixelswere only displaced a few kilometres, could have a great impact in the flow simulation. This highlights the importance of improving the accuracy of rainfall forecasts for applications in urban areas.
# Double Unloading Gas Control Technology for Fracturing Soft Coal Seams in Overlying Key Strata
###### Abstract  
Based on the 'three highs and one low' geological conditions of high gas pressure, high gas content, high ground stress, and low permeability in deep coal seams, this study proposes a dual method of hydraulic fracturing of key layers of overlying rock layers combined with pre-extraction of gas via large-diameter caving boreholes. The aim is to unload and dissipate the coal seam by fracturing the overlying key strata, allowing the stress and energy from the excavation working face to be transmitted and transferred to the deep coal seam. Additionally, large-diameter drilling effectively increases the effective drainage radius of the coal seam, resulting in a shorter extraction time. To validate this approach, a fracturing model and a gas extraction model were established for the key layers of the overlying rock layer using the engineering background of the 15,111 excavation working face of a mine in Shanxi. FLAC3D software v.6.0 was utilized to simulate the stress and energy changes of the coal seam before and after fracturing of the key layers, while COMSOL software v.6.0 was used to analyze the gas migration conditions, permeability, and effective drainage radius changes before and after drilling and caving drilling. The findings, combined with the engineering test results, conclude that key strata fracturing combined with large-diameter caving can effectively increase the permeability of coal seams and improve gas extraction. This study serves as a theoretical basis for guiding the design of gas drainage technology under the effects of coal seam pressure relief and permeability enhancement.  
key strata fracturing; gas extraction; large-diameter borehole; permeability; effective extraction radius +
Footnote †: journal: Applied Sciences
## 3 Defining the Use Cases: The Gaia-X-Med Project
### Requirements of the Use Cases for Gaia-X  
The use cases are centered around different applications, each with different requirements but also some common challenges, mainly the secure exchange of data between specific stakeholders while respecting data protection regulations. The main stakeholders for all use cases each have their own intentions (see Figure 2):  
* Hospitals, as well as doctor's offices, want to provide patients with their data and also to use it internally, if possible.
* Companies want to generate value from data by creating commercial services and products from it.
* Patients want to maintain their data sovereignty, including full control over access and distribution.  
Figure 1: A diagram showing the six use cases of the Gaia-X-Med project, with one color each. The top row shows the sources of data, the middle their kind, and the bottom their usage.  
Figure 2: A diagram showing stakeholders in the Gaia-X-Med project, their intentions, and agreements between them, which facilitate their interaction, while adhering to data security rights. The colors and numbers correspond to Figure 1.  
* Researchers want use patient data for research, and share the results, including the data they are based on.
* DICs aim to provide patient data to researchers, after anonymization and ethical approval.  
Acting upon these intentions requires the involved stakeholders to enter into certain agreements, so that their interactions respect the data protection rights of all parties involved. These agreements range from cooperation contracts between institutions like hospitals and companies, to usage contracts with patients as the user of a company's offering, to consent management agreements between patients, researchers, and data integration centers.  
They all have to be agreed upon beforehand, before any data are exchanged, since many of them represent the consent to the exchange itself. The content of agreements has to be informative enough for all parties to make an informed decision about consent, especially in the case of individual patients. The given information has to be correct and both parties should be able to verify it, preferably via a neutral third party with sufficient credibility. Underlying all of this is the mutual trust in the other involved parties, which in a digital context has to be based on verifiable identities and information, as well as a legal framework in the case of misbehavior. Therefore, in summary, the stakeholders in the use cases want to be able to maintain each others trust and obtain and respect their informed consent to data exchanges before they take place. In the rest of this paper, we will refer to these requirements as trust and consent. In the following, we will briefly present the scope of the overall study.
# Phytosterols in Seaweeds: An Overview on Biosynthesis to Biomedical Applications
## 2 Biosynthesis of Phytosterols
### Phytosterol Synthesis  
The biosynthesis of phytosterol exhibits a parallel pathway of cholesterol synthesis in eukaryotic cells [24]; 2, 3-oxidosqualene serves as a common precursor for all sterol synthesis i.e., sterols like cholesterol in humans, ergosterol in fungi and phytosterols in plants. The biosynthesis of cholesterol and ergosterol is catalyzed by lanosterol synthase (LAS), whereas phytosterol synthesis from oxidosqualene is catalyzed by cycloartenol synthase (CAS) [25]. As in plant species, seaweeds metabolize 2, 3-oxidosqualene to phytosterol by CAS and exhibit the hybrid cholesterol pathway as well, indicating an evolutionary relationship between these two phototrophic organisms [14].  
Numerous studies have highlighted the importance of the CAS gene in phytosterol biosynthesis. In extensive research by feeding experiments using [6-13C2H3] MVL, [PERSON] et al. [26] demonstrated that a mere 1.5% of sitosterol, encoded by the LAS1 gene, emphasizes its crucial role in the biosynthesis of phytosterols. Cycloartenol is metabolized into 24-methylenophenol through six enzymatic reactions, such as methylation, double demethylation, double isomerization, and a reduction. From 24-methylenophenol, the pathway branches off into two separate pathways, giving rise to epist sterol and \(\Delta\)7 avenasterol via 24-ethylidenophenol and end up in campesterol and \(\beta\)-sitosterol, respectively.  
Figure 1: Biosynthesis pathways of phytosterols. **(A)** Isoprene unit, IPP, and DMAPP synthesis. A product of glucose metabolism, acetyl-CoA and pyruvate is converted into isoprene units through MVA and MEP pathway, respectively. **(B)** (i) Condensation of isoprene into triterpenoids and (ii) phytosterol synthesis. SMT, sterol C-24 methyl transferase; SMO, sterol C-4 methyl oxidase; CPI, cyclopropyl sterol isomerase; CYP51, sterol C-14 demethylase; C-14R, sterol C-14 reductase; 8, 7-SI, sterol 8, 7 isomerase; CS-5D2, sterol C5(6) desaturase; 7 DR1, 7-dehydrocholesterol, SSR1, sterol side-chain reductase 1.  
Stigmasterol is synthesized directly from -sitosterol, whereas campesterol is converted into brassinolide through subsequent reactions [24] (Figure 1 Bii).
# Strategies for Deploying a Sensor Network to Explore Planetary Lava Tubes
## 6 Power Transfer
### Electricity to Laser Conversion  
Electrical power \(P_{s}\) is provided by a power supplier to the laser transmitter, which depends on the current \(I_{t}\) and voltage \(V_{t}\) such that \(P_{s}=I_{t}V_{t}\). The supply power stimulates the gain medium to generate a laser beam of power \(P_{l}\) which relies on current \(I_{t}\) as shown in Equation (7) [40].  
\[P_{l}=\zeta\frac{{{h}\
u}}{q}(I_{t}-I_{th}) \tag{7}\]  
where \(\zeta\) is the modified coefficient, \(h\) is the Plank's constant, \(\
u\) is the laser frequency, \(q\) is the elementary charge constant, and \(I_{th}\) is the current threshold. Thus, the electricity to laser conversion efficiency is given as Equation (8).  
\[\eta_{E-L}=\frac{P_{l}}{P_{s}} \tag{8}\]
# Streetlight Control System Based on Wireless Communication over DALI Protocol
###### Abstract  
Public lighting represents a large part of the energy consumption of towns and cities. Efficient management of public lighting can entail significant energy savings. This work presents a smart system for managing public lighting networks based on wireless communication and the DALI protocol. Wireless communication entails significant economic savings, as there is no need to install new wiring and visual impacts and damage to the facades of historical buildings in city centers are avoided. The DALI protocol uses bidirectional communication with the ballast, which allows its status to be controlled and monitored at all times. The novelty of this work is that it tackles all aspects related to the management of public lighting: a standard protocol, DALI, was selected to control the ballast, a wireless node based on the IEEE 802.15.4 standard with a DALI interface was designed, a network layer that considers the topology of the lighting network has been developed, and lastly, some user-friendly applications for the control and maintenance of the system by the technical crews of the different towns and cities have been developed.  
street lighting system; wireless sensor networks; IEEE 802.15.4; DALI protocol +
Footnote †: journal: Sensors
## 2 Materials and Methods
### Optimal Process Parameter Definition  
Before manufacturing the SPT coupons, the DED-LB process parameters needed to be defined. For this purpose, a suite of experiments was run with 18 tests, where we varied the laser power (500, 550, and 600 W), machine feed rate (500, 525, and 550 mm/min), and powder mass rate (5.5-6.0 g/min). The test conditions are summarized in Table 1 and the deposited clades are shown in Figure 3a. Individual tests specimens were cross-sectioned and prepared following the appropriate metallographic procedure. Three sections were analyzed for each test. Cross-sections were polished with a Forcipol 102 Metkon automatic polisher (Bursa, Turkey) and etched using Kalling's 2 reagent to reveal the microstructure of the material. The microstructure and quality of the individual clads, as well as the deposited coatings, were evaluated under an optical microscope, a Leica DCM 3D (Wetzlar, Germany).  
Once the optimal parameters were defined for single-clad deposition, the overlap distance between two adjacent clads was defined as a function of the clad width percentage. Overlap values of 20%, 25%, 30%, and 35% were tested and the stability of the deposited five-clad layer was analyzed. Similar to the single-clad tests, three sections for each overlap value were analyzed as well.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test Number** & **P [W]** & **F [mm/min]** & **Q [g/min]** \\ \hline  
\hline \hline \end{tabular}
\end{table}
Table 1: DED-LB process parameter optimization tests, where the laser power (P), machine feed rate (F), and powder mass rate (Q) were varied.  
Figure 3: (**a**) Single clad tests and (**b**) overlap tests to define the optimal process parameters.