esa-sceva/satcom-chunk-collection huggingface dataset:
# VPP Participation in the FCR Cooperation Considering Opportunity Costs
## 3 Results  
The results related to VPP participation in the market are presented in Table 3. Note that the results are split according to the intermediate steps corresponding to each part of the methodology (Section 2). For the disaggregated results per country and year, consult the tables in Appendix A. For the results of each day of the available data, refer to the provided tool at [15]. A brief interpretation of Table 3 is now presented using the figures regarding Scenario 1--\"pessimistic\" 2025 in Portugal for illustration. Note that the results in Table 3 are aggregated for all the available data, comprising the period between mid-2020 and the end of 2022. For this period, if the VPP was to participate in the market while disregarding the opportunity costs (part 1 of methodology), it would have participated (with at least a 1 MW bid) in 87% of the market sessions and would have covered 10% of the country's FCR needs (in this case, the remaining 90% were necessarily covered by the competing \"conventional\" BSPs). The VPP potential revenue \(VPR_{c,t}\) would have been over EUR 2M. Regarding the second part of the methodology, the sum of the upward and downward opportunity costs were computed, and it was found that such costs would have represented about 80% of the VPP potential revenue, which, when aggregated, was a very large percentage. The third part of the methodology was the decision taken by the VPP whether to participate in each particular market session, informed by the associated opportunity costs associated with participation for that tender: this naturally led to a decrease in the number of sessions that were participated in. Concretely for the illustrative case, the VPP ended up participating in 62% of the market sessions (instead of the 87% computed in part 1), covering 6% of the total country's FCR needs (instead of 10%). The VPP revenue \(VR_{c,t}\) ended up being over EUR 1.5M, which was about 75% of the \(VPR_{c,t}\). Since the VPP did not participate in the sessions where the opportunity costs exceeded the potential revenue, the shares of the revenues of the upward and downward providers, i.e., \(UPRS_{c,t}\) and \(DNRS_{c,t}\), respectively, were considerably smaller than the opportunity costs computed in part 2 of the methodology. As a result, the VPP revenue \(VR_{c,t}\) was distributed as follows:
## 1 Introduction
calculated the DMMP adsorption and decomposition on (110) and (111) CeO\({}_{2}\) surfaces with density functional theory modeling. Two possible reaction pathways were proposed [33]. The current studies on the catalytic decomposition of DMMP by CeO\({}_{2}\) are focused on elucidating the catalytic performance and mechanism. Despite the significant advancements in the development of CeO\({}_{2}\) in the thermocatalytic decomposition of DMMP, it is worth noting that the morphology, size, and surface properties of CeO\({}_{2}\) nanomaterials have an important influence on their catalytic performances [34]. For instance, [PERSON] et al. investigated the complete oxidation of toluene based on CeO\({}_{2}\) nanomaterials with different morphologies [35]. According to their results, CeO\({}_{2}\) nanorods exhibited a higher concentration of defects associated with their exposed crystalline planes, which led to their high oxidative catalytic activity. Moreover, CeO\({}_{2}\) nanoparticles have shown maximum catalytic decomposition activity for naphthalene [36], which is related to the high Ce\({}^{3+}\)/Ce\({}^{4+}\) ratio and the oxygen vacancy on the surface of CeO\({}_{2}\). When the particle diameter is less than the Bohr radius, the quantum confinement leads to an increase in the effective band gap of the material by decreasing the particle size [37; 38]. Currently, there is still a lack of research on the thermal catalytic decomposition of sarin simulant, i.e., DMMP, by CeO\({}_{2}\) with different morphologies and sizes. As such, it is crucial to have a systematic and deep exploration into the effects of physicochemical and surface properties on the catalytic performance of CeO\({}_{2}\) with different morphologies so as to design CeO\({}_{2}\) catalysts with high thermocatalytic DMMP decomposition performance. Herein, CeO\({}_{2}\) with different morphologies and sizes, e.g., irregular nanoparticles, nanorods, and nanocubes, were prepared via a hydrothermal synthesis method by adjusting the hydrothermal reaction temperature and the concentration of NaOH. The effects of the different physicochemical and surface properties of CeO\({}_{2}\) nanomaterials with different morphologies and sizes on their thermocatalytic decomposition of DMMP were investigated in this work. Finally, the DMMP decomposition mechanism based on CeO\({}_{2}\) nanomaterials was studied and proposed.
# Enhancing Resilience in Digital Twins: ASCON-Based Security Solutions for Industry 4.0
## 3 Proposed Solution
### Eclipse Ditto--Digital Twin Setup  
Eclipse Ditto, an open-source framework, serves as a platform for managing IoT devices to create Digital Twins. Integrated with MQTT brokers, it enables Digital Twins to connect with various backend systems using protocols such as AMQP, Apache Kafka, HTTP, and MQTT. Ditto can be deployed either on-premises or in the cloud. For this research, we deployed Ditto in the cloud, utilizing Docker as it requires fewer resources than the alternative Kubernetes cluster setup. Within a Docker container, we have a collection of five microservices that constitute Ditto, as well as two additional components. These microservices encompass Policies for defining access rights, Things for handling physical components, Things-Search for searching within the datastore, Gateway for HTTP and WebSocket API, and Connectivity for connectivity management. Additionally, an nginx instance serves as a reverse proxy, offering basic authentication functionality. Furthermore, we utilize MongoDB as the underlying datastore for Ditto. Running Ditto in a docker container has seven microservices operating in parallel, each fulfilling distinct functions. These microservices include _Nginx_ as the web server, _Ditto Connectivity_ for managing the device-to-Ditto connectivity, _Ditto Thing_ for managing things (counterpart of physical devices), _Thing Search_ for facilitating efficient search using MongoDB, _Swagger-Ull_ for providing a web-based user interface, and _Ditto Policies_ for maintaining controlled access over things. Since we aimed to test and compare the performance of different encryption algorithms, we utilized one of the Ditto example projects ([[https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-quick-introduction](https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-quick-introduction)]([https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-quick-introduction](https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-quick-introduction)), [[https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-bidirectional](https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-bidirectional)]([https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-bidirectional](https://github.com/eclipse-ditto/ditto-examples/tree/master/mqtt-bidirectional)) (accessed on 15 May 2023)) with minimal changes for setting up our experimentation system consisting of Ditto and a single ESP32 board. These changes included, for example, giving access rights in policies, defining ESP32 as a thing with humidity and temperature as its features, and defining customized payload mapper and published/subscribed MQTT broker topics in the connection configuration file.
# Food and Drinking Water as Sources of Pathogenic Protozoans: An Update
## 3 Waterborne and Foodborne Protozoan Infections
### Parasitic Protozoans in Immunocompromised Patients  
Intestinal protozoan parasites can cause opportunistic infections [60; 61], defined as \"serious, usually progressive infections by a micro-organism that has limited (or no) pathogenic capacity under ordinary circumstances, and that has been able to cause serious disease as a result of the predisposing effect of another disease or of its treatment\" [62]. Therefore, exposure of immunocompromised individuals to these pathogenic agents should be carefully prevented. However, intestinal protozoans, namely _Cystoisospora_ and _Cryptosporidium_ spp., in patients with diarrhea infected with the human immunodeficiency virus (HIV) showed a prevalence higher than in not-infected controls in South Africa [63], and prevalence of intestinal protozoans--including _Cryptosporidium_ spp., _E. histolytica_, _G. intestinalis_, and _P. hominis_--among HIV-infected patients in central Ethiopia was high (12.9%). Regularly eating uncooked food was a risk factor significantly associated with protozoan infections in these patients [64].  
Case-control studies carried out in Lybia and Ghana indicated a higher prevalence of _Cryptosporidium_ spp., _C. belli_, and _D. fragilis_ among diabetic patients compared to not-diabetic controls, most probably for the reduced activity of phagocytes and cytokine production resulting from chronic inflammation in diabetes [65; 66]. Coinfection with different parasites was more frequent in diabetic patients [65]. A global systematic review and meta-analysis indicated a higher prevalence of _Cryptosporidium_ spp. and _B. hominis_ among patients with diabetes compared to healthy individuals [67].  
In children with chronic liver diseases (CLD) of different etiology, protozoan parasites detectable by unstained microscopy were significantly higher compared to children with no CLD, most probably due to immunity impairment in CLD [68].  
In a case-control study carried out in Poland, the prevalence of pathogenic protozoans _G. intestinalis_, _Cryptosporidium_ spp., and _B. hominis_ was significantly higher in patients with hematological malignancies, especially those with large B-cell lymphoma and plasma cell myeloma, than in healthy controls [69].  
_G. intestinalis_ and _Cryptosporidium_ were the most common causative pathogens of diarrhea in kidney transplant recipients [70].
# WIPP: Wi-Fi Compass for Indoor Passive Positioning with Decimeter Accuracy
###### Abstract  
In recent decades, the proliferation of smart phones, tablets, and wireless networks has fostered a growing interest in indoor passive positioning. The Wi-Fi-based passive positioning systems can provide Location-Based Services (LBSs) to the third party such as market and security departments. Most of the existing systems are based on the Receive Signal Strength Indication (RSSI) information, which are generally time-consuming and susceptible to environmental change. To overcome this problem, we propose the Wi-Fi compass for indoor passive positioning system (WIPP), an Angle of Arrival (AOA) based passive positioning system using the existing commodity Wi-Fi network. In this paper, we first propose a new algorithm for the joint estimation of AOA and Time of Arrival (TOA) measurements based on the fine-grained Channel State Information (CSI), which is collected by an off-the-shelf Wi-Fi device equipped with only three antennas. Second, we use the affinity propagation clustering algorithm to identify the direct signal path from the target to each Wi-Fi Access Point (AP). Finally, we deploy the WIPP in an actual indoor environment to conduct the performance comparison with the well-known radio-frequency (RF) based system for locating and tracking users inside buildings (RADAR), as well as the conventional passive positioning system using the AOA solely. The experimental results show that the WIPP is able to achieve the median positioning error 0.7 m, which is much lower than the ones by the RADAR system and the conventional system using the AOA solely.  
indoor passive positioning; commodity Wi-Fi network; Angle of Arrival (AOA); Channel State Information (CSI)  
PACS:J0101
# FAIDM for Medical Privacy Protection in 5G Telemedicine Systems
## 3 Proposed Scheme
### Gateway Node Registration Phase  
In this phase, gateway node \(GW_{i}\) interacts with remote server node \(S\) for registration. To deal with the registration request submitted by the gateway node \(GW_{i}\), the remote server node \(S\) validates the gateway node \(GW_{i}\)'s legitimacy then issues the private key \(S_{i}\) and certificate \(\mathit{Cert}_{S\to GW_{i}}\) via a secure channel. Note that remote server node \(S\) computes a private key by gateway node \(GW_{i}\)'s registration information. Figure 3. illustrates process of gateway node registration phase. Detailed descriptions are stated as follows:  
Figure 2: System structure of proposed scheme.  
Step 1: The gateway node \(GW_{i}\) chooses an identifier \(ID_{i}\) and submits to remote server node \(S\).  
Step 2: Upon receiving \(ID_{i}\) from gateway node \(GW_{i}\), remote server node checks the format of \(ID_{i}\). If \(ID_{i}\) is valid, remote server node \(S\) computes \(S_{i}\) correspond to \(ID_{i}\), generates \(\mathit{Cert}_{S\to GW_{i}}\) from \(\mathit{Cert}_{HCA\to S}\), and sends (\(S_{i}\), \(\mathit{Cert}_{S\to GW_{i}}\)) via secure channel to the gateway node \(GW_{i}\).  
\[P_{i}=H_{1}(ID_{i}) \tag{1}\]  
\[S_{i}=T_{s_{0}}(P_{i})\bmod p \tag{2}\]  
Step 3: The gateway node \(GW_{i}\) chooses a random number \(s_{i}\) as secret value and computed \(Q_{i}\) and stores \(\mathit{Cert}_{S\to GW_{i}}\) to complete gateway node registration phase.  
\[Q_{i}=T_{s_{i}}(x)\bmod p \tag{3}\]
## 4 Discussion
### Petrogenesis of the Sanggeda Intrusion: A Trans-Crustal Magma Plumbing System  
The amphibole crystal population in the Sanggeda gabbros suggests that the formation of the intrusion required a complex magma assembly process, gathering dispersed crystals, crystal mushes, and cumulates from magma reservoirs at varying depths. Amphiboles may undergo reabsorption while ascending through the lithosphere, particularly near the surface, as they move outside their stability field [70; 71; 72]. This partially explains why amphiboles are rare in arc lavas but abundant in cumulate xenoliths and arc plutons, a phenomenon linked to \"cryptic amphibo fractionation\" [12]. A mechanism must exist for the Sanggeda intrusion to transport such a large number of amphibole crystals to the shallow crust with minimal resorption. The trans-crustal magma plumbing system (Figure 11a) may be the appropriate model [10; 71; 72; 73] to resolve these contradictions.  
In the lower crustal magma chamber, olivine and pyroxene likely crystallize first from the primitive magma, with most accumulating and separating from the residual melt, leaving only a small fraction in the melt (Figure 11b). This fractional crystallization is beneficial for the formation of amphibole Types 3-4. Crystallization of anhydrous minerals progressively enriches water in the melt. This promotes the stability of clinopyroxene over orthopyroxene while suppressing plagioclase crystallization. The Type 3 amphibole will precipitate when the H\({}_{2}\)O-saturated magma encounters the amphibole stability curve [19], forming an idiomorphic morphology due to ample growth space, as mentioned earlier. The Type 4 amphibole forms via a rock-melt reaction, in which precursor clinopyroxene reacts  
Figure 11: Trans-crustal magma plumbing system: **(a)** subduction of the oceanic lithosphere and structure of multiple magma chambers; **(b)** individual magma storage and its chamber; **(c)** schematic diagram showing the crystal texture characteristics and composition differences of four amphibole types (not to scale).  
with residual or injected melts. During this process, clinopyroxene is entirely consumed (Figure 5c,d).  
The abundance of crystals increases magma viscosity, forming a crystal mush that hinders further magma ascent in the deep crust. Interstitial melt is extracted through compaction or buoyancy, while the cumulates delaminate back to the mantle (Figure 11b). This process contributes to the formation of SiO\({}_{2}\)-rich continental crust materials.  
Finally, cumulate enclaves and antercystis, such as amphiboles, clinopyroxenes, and plagioclase, are trapped in the ascending host magma [74]. Due to their high density and size, antercystis may not always reach the surface. Depending on the availability of antercystis in the magmatic system, antercyst-bearing or antercyst-free magmas are formed. The Type 1 amphibole crystalizes during ascent in the trans-crustal magma plumbing system, emplacing in the shallower crust (Figure 11c).
# Novel Fault Injection Attack without Artificial Trigger
## 1 Introduction
### Our Contributions  
In this paper, we propose a novel fault injection attack system that can be used to ease an attacker's assumption for triggering. This system implies utilizing an existing I/O signal as a trigger instead of generating an artificial one. However, it is a difficult task for the attacker to detect the time of a specific operation. To overcome this disadvantage, the proposed system collects an emission electromagnetic trace of a target device and analyzes it to identify the operating time of a specific algorithm. Evidently, the accuracy of such a detection approach is lower compared with that of artificial triggering. The proposed system is not capable of identifying precisely which byte is affected by a fault, while the conventional system can derive this information. To apply the proposed system for snatching confidential information, it is necessary to develop a differential fault analysis method without the premise of the index of byte in which a fault is injected is decided. In this study, we additionally develop a DFA method that can be used to reveal the secret key of the AES encryption algorithm even in the cases when the attacker does not know which bytes have been affected by an injected fault. Moreover, we demonstrate the applicability of the proposed system by conducting the secret key using Arduino UNO board [7].
## 4 Numerical Simulation
### Computational Model  
Based on the experimental model size and parameter design, a three-dimensional numerical model was constructed, as illustrated in Figure 14. Solid elements were used to simulate both the surrounding rock and the secondary lining, while the initial support was represented by shell structure elements [27]. The surrounding rock was modeled using the Mohr-Coulomb yield criterion and an elastic-plastic incremental constitutive relationship, whereas the secondary lining and initial support were characterized by a linear elastic constitutive model. Excavation simulation was carried out utilizing the \"model null\" function in FLAC3D, with a maximum grid size of 5 m. The model boundary conditions were defined using the free field mesh technology within FLAC3D software to establish free field boundaries, with a viscous boundary applied at the base. The free field boundary comprised four side-layered free field meshes surrounding the model and four corner-point layered free field meshes [28], connected to the main grid via dampers to mimic an infinite field model. The seismic input wave at the base corresponded to the renowned El-centro wave mentioned earlier.
## 4 Engineering Example
### Data Preprocessing and Model Settings
#### 4.2.4 Feature Correlation Analysis  
The key to achieving optimization of adaptive MTGNN under a multi-feature dataset is to determine the optimal input feature combination for the nodes. In the example, the degree of linear correlation between different features can be quantified by calculating the Pearson correlation matrix. The Pearson correlation coefficient ranges from \(-1\) to 1, where a value of 1 indicates a perfect positive linear correlation between features, \(-1\) indicates a perfect negative linear correlation, and 0 indicates that there is no linear correlation between features. The Pearson correlation coefficient is calculated in Equation (10).  
\[r_{xy}=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{([n\sum x^{2}-(\sum x)^{2}][n \sum y^{2}-(\sum y)^{2}])}} \tag{10}\]  
where \(r_{xy}\) is the correlation coefficient between the two variables \(x\) and \(y\), \(n\) is the number of observed samples, \(\sum xy\) is the sum of the products of the two variables, and \(\sum x\) and \(\sum y\) are the respective sums of the variables \(x\) and \(y\).  
From the calculation results in Figure 9, it can be seen that there is an obvious positive correlation between corrosion current (0.94), open circuit potential (0.80), and corrosion rate, i.e., an increase in corrosion current and open circuit potential usually causes an increase in corrosion rate. There is a strong negative correlation between polarization resistance (\(-0.55\)), dielectric resistance (\(-0.64\)), concrete resistivity (\(-0.38\)), and corrosion rate, which suggests that an increase in resistance-based detection indicators contributes to the reduction of corrosion rate. Other indicators, such as PH (\(-0.24\)) and chloride concentration (0.16), had a weak correlation with corrosion rate.  
Figure 8: Corrosion rate curves of different monitoring points.  
In this paper, three combinations of features are established as node inputs to the embedding layer based on the strength of the correlation between the remaining features and the Corrosion Rate (CR), which are grouped as shown in Table 1. The optimal input features of the nodes can be obtained by comparing the prediction results of each combination, and then the optimal model can be further compared with other baseline models.
## 3 Results
### Simulation System and Result Analysis
#### 3.1.3 Computational Effort Analysis
The reduction gain \(G_{R}\) which is defined as \(G_{R}=(1-O/O_{\text{ref}})\), in percentage, is applied for comparing computational efforts with different methods, where \(O_{\text{ref}}\) and \(O\) are the number of CMs required by the proposed method and other methods, respectively. It is shown in Table 2 that our proposed method provides a reduction gain of 31.5% in comparison with conventional DBP with the same effectiveness. In order to compare our proposed method with GDA-based A-DBP and GDAM-based A-DBP, the relative step \(s\) is introduced to deal with the situations of divergence. Considering the fastest convergence by initial \(k\) = 2 \(\times\) 10\({}^{-3}\) in Figure 5, \(s\) is defined as \(s\) = 1/(1/\(ite_{1}\)+ \(ite_{2}\)+\(\ldots\)+ \(ite_{n}\)), in which \(ite_{n}\) represents different numbers of iterations employing different \(\mu\). Table 3 shows relative steps of three methods. The reduction gain is calculated based on \(G_{R}\) due to the positive correlation between the number of iterations and complexity. Our proposed method achieves reduction gains of 58.7% and 69.8% compared to A-DBP based on the GDA and A-DBP based on the GDAM, respectively. USA) operating at 120 GSa/s. To match with the sampling rate, 40-times up-sampling and 21-times down-sampling are adopted. The sampling rate of the oscilloscope is 128 GSa/s. We use an external cavity laser (ECL, IQS-2800, EXFO, Quebec City, QC, Canada) that has a central wavelength of 1550.33 nm and a linewidth of 100 kHz. The 26-WDM signals ranged from 1560.1638 nm to 1530.9051 nm with 75 GHz spacing and launched into a loop consisting of 15 spans of 80 km SSMF with a loss of 0.22 dB/km after multiplexing in a wavelength selective switch (WSS, Waveshaper 4000s, Finisar, CA, USA). And the chromatic dispersion coefficient \(D\) is 16.4 ps/nm/km, the nonlinearity coefficient \(\gamma\) is 1.31/W/km. We use a WSS as a gain equalizer (GEQ) in the loop and use EDFA (AEDFA-23, Amonics, Hong Kong, China) with a gain of 18.5 dB in each 80 km span to compensate for the transmission loss. Finally, the signal is detected by four balanced photodetectors (BPDs) to achieve photoelectric conversion. As shown in Figure 10, components of the off-line DSP are the same as in Figure 2.