esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Working Atmospheres on the Detection of Diacetyl by Resistive SnO2 Sensor
###### Abstract  
Nanostructured metal oxide semiconductors (MOS) are considered proper candidates to develop low cost and real-time resistive sensors able to detect volatile organic compounds (VOCs), e.g., diacetyl. Small quantities of diacetyl are generally produced during the fermentation and storage of many foods and beverages, conferring a typically butter-like aroma. Since high diacetyl concentrations are undesired, its monitoring is fundamental to identify and characterize the quality of products. In this work, a tin oxide sensor (SnO2) is used to detect gaseous diacetyl. The effect of different working atmospheres (air, N2 and CO2), as well as the contemporary presence of ethanol vapors, used to reproduce the typical alcoholic fermentation environment, are evaluated. SnO2 sensor is able to detect diacetyl in all the analyzed conditions, even when an anaerobic environment is considered, showing a detection limit lower than 0.01 mg/L and response/recovery times constantly less than 50 s.  
nanomaterials; MOS; resistive sensor; tin oxide; fermentation; diacetyl Article
# Energy-Efficient De-Duplication Mechanism for Healthcare Data Aggregation in IoT
## 3 System Model and Problem Statement  
This section discusses the system model of the proposed scheme along with the problem statement. In a heterogeneous environment, sensor nodes are attached to patients' bodies, generating data readings in various formats. The proposed scheme passes through three main phases, as illustrated in Figure 1, and implements a cluster-based approach for data aggregation. At Level 1, the deployed sensors take relevant readings from the patient's body and transmit them to the CH. Data will be concatenated at the aggregation node (AN) before being transmitted towards the Fog. Moreover, the data of one AN can also be transmitted through other AN, ensuring an optimum approach for handling healthcare data. In case there is no fluctuation in values, they are transmitted as Boolean digit 0 for overcoming data redundancy. At Level 2, all CHs forward aggregated data to the Fog servers, from which medical professionals can access patient's medical information and can make suitable decisions according to the condition of patients. The Electronic Health Record (EHR)/ Electronic Medical Record (EMR) are maintained at Medical servers in the hospitals, whereas the Fog Servers receive data from multiple medical servers. There may be one Fog Server in one big city or even in one province as well. This information is also shared with the central cloud server via fog servers at Level 3 and subsequently stored in the repository, so that data can be used soon after if needed.  
In the literature, it has been observed that the sensor devices at Level 1 collect readings from a patient's body, and they simply transmit it to the CH without checking for duplicate values. There is a high possibility that the majority of deployed sensors transmit normal range readings. When values fall in the normal range, it means that the patient is not  
Figure 1: System Model.  
experiencing any threatening condition. So, there is no need to transmit full 16 or 32-bit duplicate readings frequently. By transmitting this redundant data in full form, energy consumption, and communication cost arises. Therefore, for handling this voluminous data, a high storage capacity is also needed. To resolve these issues, an efficient scheme is required that handles duplicate data at the device level.
# Occlusion-Robust Multi-Target Tracking and Segmentation Framework with Mask Enhancement
## 2 Related Works
### Multi-Object Tracking and Segmentation Frameworks  
[PERSON] et al. [36] first integrated instance segmentation with tracking tasks. Subsequently, to improve the accuracy of existing multi-object tracking, [PERSON] et al. [1] constrained the tracking targets in VIS to pedestrians and vehicles.  
They also developed the TrackR-CNN framework that combined segmentation instances with tracking algorithms. Following the tracking-by-detection paradigm, TrackR-CNN extended Mask R-CNN [13] by adding a tracking branch. It employed 3D convolutions to capture temporal and appearance information in videos, computed target embedding vectors and IoU predictions from optical flow, and incorporated both as weights in a bipartite graph matching algorithm for data association.
## 6 Computational Results and Discussion
### Direct Deliveries  
In a first experiment, the indicator VKT for the distribution of all parcels is computed for direct deliveries. Three different levels of aggregation have been presented in Section 4. First, results are presented from comparing the estimation approach based on the sizes of the area and solving TSP instances for customers within a given area.
## 4 Experiments
### Results and Analysis
#### 4.2.5 Real-World Case Studies  
To validate ARCS's effectiveness in practical scenarios, we analyzed its performance in three real-world case studies, as shown in Figure 4. The first case involved a sophisticated phishing campaign targeting a financial institution, where ARCS demonstrates progressive improvement in detection capabilities, achieving a 94.2% detection success rate at the 30 s mark, as shown in Case 1 of Figure 4. The figure illustrates two key performance metrics: the detection success rate (solid blue line) steadily increasing to reach 94.2% at 30 s; meanwhile, the system response time (dashed red line) showed continuous improvement, decreasing from an initial 35 s to stabilize around 5 s, indicating enhanced system efficiency over time. The second case demonstrates the system's ability to handle a distributed ransomware attack. As shown in Case 2 of Figure 4, when the ransomware outbreak initially spread rapidly across the network affecting up to 400 systems (red line), ARCS initiated its response at the 20 s mark. Following the intervention, the number of affected systems plateaued and then slightly decreased, while the number of protected systems (green line) steadily increased, ultimately securing approximately 350 systems (89.7% accurately). This response pattern demonstrates ARCS's effectiveness in both containing the spread of ransomware and recovering compromised systems.  
In the third case, involving a complex APT attack utilizing multiple attack vectors, ARCS showed its adaptive capabilities by adjusting its response strategy as the attack pattern evolved. The system successfully identified the attack progression through dif  
Figure 4: Analysis of real-world case studies showing the attack progression and response timeline.  
ferent stages and implemented appropriate countermeasures, resulting in minimal data exfiltration and rapid threat containment.
# Sustainable Energy Solutions: Utilising UGS for Hydrogen Production by Electrolysis
## 2 Methodology and Concept Description  
A unique concept and methodology for the total achievable hydrogen production from energy transformations during the gas withdrawal process from a specific UGS facility in Croatia was proposed. The amount of electricity needed to produce 1 kg of H\({}_{2}\) was about 50-70 kWh with the PEM electrolysis system [12], and assuming a system efficiency of 65% and ever-lower prices of electrolysers, the mentioned concept became a commercially interesting technology. The gas storage process and the parallel production of hydrogen through an energy process due to pressure reduction were simulated using technical software [41; 42] and real storage operation data. The computer had the following features: Ram memory, DIMM 64 GG 2133 MHz; CPU, Intel Xeon E3-1535M [EMAIL_ADDRESS] GHz; L2 Cash, 1024 KB; L3 Cash, 8192 KB; operative system, Win 10 pro; graphic card, NVIDIA Quadro M500M 8 GB DDR5. When gas was withdrawn from the storage reservoir, associated water was also produced alongside the gas. Utilising generated simulation scenarios, the investigation aimed to determine the sustainability of the hydrogen production process, in particular whether the amount of water produced per withdrawal cycle could meet the quantities required for hydrogen production. A mathematical model of an underground gas storage facility was utilised to simulate the total energy output at TE during a standard gas withdrawal cycle. Considering the reservoir pressure drop during gas withdrawal process, it was possible to realistically simulate the total hydrogen production via the TE generator and electrolysis process. This simulation helped ascertain the required amount of formation water necessary for hydrogen production, which was the main objective of this research.
# Bitumen and Bitumen Modification: A Review on Latest Advances
## 2. Bitumen Polymers
### Thermosets  
Thermosetting plastics (TP)--two liquid compounds (resin and hardener) -- are first blended together and then with the bitumen a few seconds before application as surface coating/surface dressing (main use) or before mixing with aggregates for the production of hot asphalts (occaional use) [72]. Thermosetting plastics are polymers that turn into a solid state while heated or impose hardness. Before hardening, TP molecules have a linear structure, the same as thermoplastics molecules, but the size of their molecules is significantly smaller. TP molecules are chemically active. They contain either double (unsaturated) bonds or other chemically active groups. Therefore, under certain conditions (at heating, irradiation, or adding hardeners) thermosetting molecules react with each other and form a continuous network. Epoxy, phenol-formaldehyde, carbamide, polyester, silicone, and other resins belong to TP [73]. It has been shown that when epoxy thermosets polymers are blended with bitumen the modified bitumen displays the properties of the epoxy rather than those of the bitumen [74]. Since the epoxy bitumen presents the properties of the thermosetting polymer, the available time to use the modified bitumen is limited and is determined to a great extent by the mixing temperature. The higher the temperature, the shorter is the time of use. After producing, the thermosetting bitumen begins to 'cure' and increase its strength (hardens) once it is applied. The curing time is according to ambient temperatures. The higher the ambient temperature, the longer is the curing time. Once curing is completed, future temperature increase, which would soften the conventional bitumen, does not affect the hardness of the thermosetting bitumen at all. The completely cured bitumen is designated as an elastic material having no viscous behavior. Even though the PmBs with thermosetting plastics have relatively high adhesion to the mineral particles and great strength they are not common for paving applications. This is because firstly, when entering these polymers, owing to the imposed hardening, the technological properties of PmB are almost immediately deteriorated; secondly, the rigidity of the PmB is increased at low temperatures, which results in increased thermal sensitivity; thirdly, the use of TP complicates the system and raises its price; and finally, the effectiveness of thermosetting plastics appears usually at their large quantities in bitumen (more than 10 wt%). Asphalt mixtures produced with thermosetting polymer-modified bitumen have excellent adhesive ability, excellent resistance to deformation, excellent fatigue performance, and high stiffness modulus.
# Removal of Chromium(VI) by Chitosan Beads Modified with Sodium Dodecyl Sulfate (SDS)
## 3 Results and Discussion
### Adsorption Isotherms  
Adsorption isotherms of Cr(VI) on SDS-chitosan beads were studied with varying initial concentrations from 0.010 to 3.0 mg/L, under optimized conditions in terms of the pH (pH 4), contact time (72 h), and dosage of the adsorbent (0.8 mg/L) at 298 K in this work. Adsorption isotherms are generally used to reflect the performance of adsorbents in adsorption processes. Herein, two common adsorption models, consisting of Langmuir [61; 62] and Freundlich [61; 63] equations, were employed to explain the adsorption of Cr by SDS-chitosan beads (Figure 11). The adsorption data acquired for Cr(VI) using SDS-chitosan beads were investigated by Langmuir and Freundlich equations, and the results are shown in Figures 12 and 13, respectively. All isotherm parameters calculated from the two models are listed in Table 4, along with the correlation coefficients (\(R^{2}\)). High correlation coefficients indicate that Cr(VI) sorption can be well-described by the Langmuir and Freundlich isotherms. In particular, the Langmuir model was preferable, and the maximum adsorption capacity was estimated to be 3.23 mg/g. The Langmuir isotherm model is known to elucidate the monolayer adsorption on homogeneous surfaces. The results implied that the adsorption of Cr(VI) was a monolayer coverage process [64]. This indicated a strong potential in the application of SDS-chitosan beads for Cr(VI) removal from an aqueous phase. On the other hand, it was found that the \(R^{2}\) value obtained from the Freundlich model was not small, and favorable adsorption was suggested, judging from the value of \(1/n\)[65]. The isotherm parameters revealed that the SDS-chitosan bead with special structures could efficiently enhance the adsorption capacities.  
Figure 11: Adsorption isotherms of Cr(VI) using the SDS-chitosan beads.  
Figure 12: The Langmuir isotherm of Cr(VI) adsorption on the SDS-chitosan beads.
## 2 Materials and Methods
### Test Methods
#### 2.3.3 High Temperature Rheological and Fatigue Properties Tests
Figure 5 describes the permittivity loss angle tangent and the permeability loss angle tangent of the limestone filler and the magnetite filler at different frequencies. It can be seen that the tan\(\delta_{E}\) of the magnetite filler is between 0.01 and 0.11. It has the smallest value at a frequency of 4 GHz and the largest value at a frequency of 14 GHz. The tan\(\delta_{E}\) of the limestone filler is between 0 and 0.26 and that of the limestone filler is between 0 and 0.05. In general, the magnetite filler has a larger tan\(\delta_{E}\) and tan\(\delta_{M}\) than the limestone filler. Furthermore, the tan\(\delta_{E}\) and tan\(\delta_{M}\) of the magnetite filler change significantly with frequency, while those of the limestone filler charge slightly. Figure 6 shows the tan\(\delta\) of the limestone filler and the magnetite filler at different frequencies. As can be seen in the figure, the tan\(\delta\) of the magnetite filler is between 0.05 and 0.28, and that of the limestone filler is between 0.01 and 0.07. The value of tan\(\delta\) for the magnetite filler is the largest at a frequency of 4 GHz. The magnetite filler has a larger tan\(\delta\) than the limestone filler, indicating that the magnetite filler has a better microwave absorption ability. The tan\(\delta\) of the magnetite filler changes significantly with frequency, while that of the limestone filler changes slightly. In summary, both the microwave-absorbing ability and microwave sensitivity of magnetite are significantly better than those of limestone. Therefore, using magnetite powder as a substitute for limestone filler in asphalt mastic can substantially enhance microwave sensitivity and improve microwave heating efficiency.
# Remote Sensing for Land Administration
## 2 Overview of Contributions
[39] seek to further developments on automated boundary extraction, based on the use of high-resolution optical sensors mounted on UAV platforms. They investigate the potential of the ENVI feature extraction (FX) module for data processing using Slovenia as a case location. The results of the accuracy assessment showed that almost 80% of the extracted boundaries are correct, when compared to the reference data. [PERSON] et al. argue the proposed workflow has the potential to accelerate and facilitate the creation of cadastral maps, especially for developing countries. However, they caution that the boundaries must be validated by landowners and other beneficiaries after being extracted. Finally, in a detailed socio-technical study for Rwanda, [PERSON] et al. [40] determine the overarching alignment between land administration stakeholder perceptions, the characteristics of the UAV data acquisition workflows, and the final spatial data products obtainable. Additionally, three different UAVs are tested for the quality of data obtainable and the possibilities for using of the technology within the current institutional setting. A priority list of needs for cadastral and non-cadastral information, as well as insights into operational challenges, and data quality measures, of UAV-based data products is presented. It is concluded from the results that UAVs match most of the prioritized needs in Rwanda. However, it is also revealed that institutional and capacity conditions undermine the potential. Overall, the selected works in this Special Issue demonstrate the growing opportunities for applying innovations in remote sensing and photogrammetry (including laser scanning) to the domain of land administration. This applies to outdoor, indoor, underground, and above ground environments. The opportunities highlighted cover a wide range of land administration applications, from 2D land tenure data capture, cadastral updating, land use classification in developing contexts, through to underground utilities administration, 3D cadastral development, and indoor boundary identification in more developed contexts. The range of available and applicable remotely sensed data types and techniques is shown to be highly relevant to the land sector, and this should encourage further fusion of the disciplines into the future. Conceptualization and writing--original draft preparation, R.B. ; writing--review and editing, M.K., P.v.O., C.L. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors would like the acknowledge the support of colleagues at academic and governmental organisations that supported this work, in particular Kadaster Netherlands, Swinburne University of Technology, ITC Faculty University of Twente, and TU Delft. The authors declare no conflict of interest.
# Improved Remote Sensing Image Classification Based on Multi-Scale Feature Fusion
## 5 Discussion
### Effect of Feature Fusion on Accuracy  
WFCNN, WFCNN-1, and WFCNN-2 all used feature fusion methods to generate feature vectors for each pixel. Since the convolution kernels used in different convolutional layer levels may be different, potentially causing differences in the feature map depths, it is necessary to adjust the latter before fusion. Choosing an appropriate fusion strategy can help improve the accuracy of the results.  
WFCNN used a dimensional reduction strategy while WFCNN-1 used a dimensional increase. Although both can achieve consistent depth adjustments of the feature graph, our results showed that WFCNN performed better, indicating that dimensional reduction is more effective. Our analysis suggests that the effect of the classifier may be influenced by a high dimensionality. In a future study, we intend to test additional fusion strategies to further improve the accuracy of the segmentation results.  
Like WFCNN, WFCNN-2 used dimensional reduction, but the former adjusted the characteristics of the participation fusion by using the weight layer beforehand, while the latter directly used dimensional reduction. Once the resulting feature map was fused, it was clear that the weight layer used by WFCNN improved the accuracy of the segmentation results.
## 3 Results
### Signal Crosstalk Between Akt and NF-\(\kappa\)B  
Akt, referred to as protein kinase B, can be activated by several platelet agonists that regulate platelet activation and hemostasis [25]. As described previously [16], PTE markedly diminishes the phosphorylation of Akt stimulated by collagen. In the present study, we further investigated cellular signaling events between PI3K-Akt and NF-\(\kappa\)B. When platelet suspensions were treated with PTE (7 \(\mu\)M), BAY11-7082 (7 \(\mu\)M), and MK-2206 (10 \(\mu\)M; an inhibitor of Akt), all these reagents nearly abolished collagen-stimulated IKK, p-p65, and Akt phosphorylation (Figure 6A-C). The confocal study also provided evidence that demonstrated MK-2206 diminished p-p65 fluorescence (Figure 6D), convincingly suggesting that Akt and NF-\(\kappa\)B activated each other during platelet activation and are also involved in PTE-mediated antiplatelet activation.  
Figure 6: Regulatory profiles of pterostilbene (PTE), BAY11-7082, and MK-2206 on NF-\(\kappa\)B and Akt activation in human platelets. Washed platelets (1.2 \(\times\) 10\({}^{9}\) cells/mL) were preincubated with 0.1% DMSO, PTE (7 \(\mu\)M), BAY11-7082 (7 \(\mu\)M), or MK-2206 (1 \(\mu\)M) and then treated with collagen (1 \(\mu\)g/mL) to trigger (**A**) IKK, (**B**) p65, and (**C**) Akt phosphorylation. Data are presented as mean \(\pm\) standard error of the mean (\(n\) = 4). ***\(p\) < 0.001, compared with the resting control (group treated with Tyrode’s solution), ***\(p\) < 0.001, compared with the 0.1% DMSO-treated group. (**D**) For further study, washed platelets (1.2 \(\times\) 10\({}^{9}\) cells/mL) were preincubated with MK-2206 (10 \(\mu\)M), followed by collagen treatment (1 \(\mu\)g/mL) to trigger platelet aggregation. The confocal images of p-p65 (green fluorescence) and \(\alpha\)-tubulin (blue fluorescence) were observed by using goat anti-rabbit \(\mathrm{CF}^{\mathrm{TM}}\) 488A Dye and goat anti-mouse \(\mathrm{CF}^{\mathrm{TM}}\) 405M Dye, respectively, as described in the Section 2. The profiles represent four similar studies. Bar: 7.5 \(\mu\)m.
## 3 Results
### Optimal Input Features Selection by mRMR  
The variables \(\delta\), \(\omega\) and \(P_{e}\) of 10 generators and the \(V\) of 39 buses constitute of a 690-dimensional feature set. The 69 groups of trajectory variables are arranged in the following order: \(\delta\) numbered 1-10, \(\omega\) numbered 11-20, \(V\) numbered 21-59, and \(P_{e}\) numbered 60-69. The basic result sorted by mRMR is shown in Figure 10.  
It can be seen from Figure 10 that 7 out of the top 10 groups of features most relevant to transient stability are bus voltage variables \(V\) (in blue), which can be seen as a good feature type to assess the transient stability of power systems.  
However, bus \(V\) has 39 groups of input features, which is far more than the number of generator variables \(\delta\), \(\omega\) and \(P_{e}\). Therefore, in order to analyze the priorities of the other three types of generator-related features to transient stability, it is necessary to temporarily remove bus \(V\) data from the ranking results. Then the numerical order of the generator-related features \(\delta\), \(\omega\) and \(P_{e}\) are respectively added, and the sums are shown in Figure 11.  
As can be seen from Figure 11, the order sum of the \(P_{e}\) (in yellow) group is far less than those of the variables \(\delta\) and \(\omega\). In other words, the new feature of \(P_{e}\) can be acknowledged as more relevant to the system transient stability than \(\delta\) and \(\omega\), which is also consistent with the accuracy comparisons of transient stability prediction in the previous Section 3.2.  
Figure 11: Sum of the order in three types of features.  
Figure 10: Sorting result of input features by mRMR.  
It can be seen from Table 6 and Figure 13 that the WTA model is able to improve the prediction accuracy of unstable samples (in blue) greatly, from 90.38%, 92.31% to 99.26%, while the overall prediction accuracy also increases slightly. Due to the special treatment to improve the model conservativeness for unstable situations, the accuracy of the proposed WTA ensemble model is higher than the recent work, such as the DSEC ensemble model of less than 97.03% in Reference [6]; the datasets were generated from the same IEEE 39-bus system. Therefore, the proposed WTA ensemble learning model can provide a strong basis for the online applications of TSA, based on machine learning technology.