esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology
### Measurement  
Evaluations were conducted using a Gecor 10 resistivity meter corrosimeter, illustrated in Figure 2a, which is an instrument designed to measure the level of corrosion in re-bars within concrete. This equipment facilitates measurements using sensors that apply potential variations or electric currents to the structure and subsequently examine the response.  
During data collection, each reinforcement was used as an active electrode and to perform the central reinforcement without an inhibitor as the counter electrode, using a silver-silver chloride reference electrode. Effective contact was ensured between the reference electrode and the concrete slab by maintaining a damp cloth between them. The Wenner or four-point method, in accordance with EN 12390-19 [51], was used. This procedure employs a sensor with four probes arranged in line at equidistant intervals, as shown in Figure 2. The outer probes initiate an alternating current while the reaction is measured by the potential difference between the two inner probes based on the induced current.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Chloride**} & \multicolumn{2}{c}{**With Inhibitor**} & \multicolumn{4}{c}{**Without Inhibitor**} \\  & **Name** & **Chloride Ion** & **Name** & **Chloride Ion (\%)** & **Name** & **Chloride Ion (\%)** & **Name** \\ \hline \multirow{4}{*}{0.8\%} & 0.8C-21 & & 2.0C-51 & & 0.8S-26 & & 2.0S-56 \\  & 0.8C-22 & & 2.0C-52 & & 0.8S-27 & & 2.0S-57 \\ \cline{1-1}  & 0.8C-23 & 2.0\% & 2.0C-53 & 0.8\% & 0.8S-28 & 2.0\% & 2.0S-58 \\ \cline{1-1}  & 0.8C-24 & & 2.0C-54 & & 0.8S-29 & & 2.0S-59 \\ \cline{1-1}  & 0.8C-25 & & 2.0C-55 & & 0.8S-30 & & 2.0S-60 \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._  
Figure 2: Gecor 10 device (**c**) and measurement with an active electrode (**a**) and four-point sensor (**b**).  
The corrosion rate (i\({}_{\text{corr}}\)) and the corrosion potential (E\({}_{\text{corr}}\)) were measured for each of the 10 re-bars present in every slab. The corrosion potential provides a qualitative measure of the corrosion state of the re-bars [52] and is greatly influenced by the moisture level of the concrete slab, with results dependent on the type of reference electrode used. This measure offers a qualitative indication, which reflects the likelihood of the steel being in a state of corrosion or in a passive state. Table 3 presents the probabilities of corrosion according to ASTM standards using a silver-silver chloride reference electrode [53; 54; 55]. The corrosion rate (i\({}_{\text{corr}}\)) provides a quantitative measure of the reinforcement deterioration process. Table 4 shows the expected corrosion penetrations (T) based on the corrosion rate [54].  
This section is divided by subheadings. It provides a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn.
## 2 Data Acquisition and Integration
### Construction of the City Graph  
Our data acquisition and integration process is divided into three parts: (1) obtaining the directed graph of segments and intersections and (2) integrating elevation and (3) sequential traffic data. First, we used the OSMnx library [25] to generate a basic city graph. Here, each node represents an intersection at any point where three or more seg ments meet. Each edge represents a segment that connects two nodes following the traffic directions, as shown in Figure 1.  
We assign each node its geographic coordinates and the number of adjacent segments. Each edge contains the identifiers of the source and destination nodes, the segment length, and relevant information on the road, such as its name, direction, number of lanes, and maximum speed.
## 1 Introduction  
Nasopharyngeal carcinoma (NPC) is a malignant head and neck tumor with a distinct racial and geographical distribution that is highly prevalent in Southeast Asia [1; 2; 3]. Currently, the main treatment for NPC is using radiation therapy or a combination of radiation and chemotherapy. Side effects are more difficult to tolerate, and hearing toxicity is inevitable [4; 5]. So, more effective and less toxic drugs are needed.  
Disulfiram (DSF), a clinically used anti-alcoholism drug, can inhibit the enzymatic activity of aldehyde dehydrogenase (ALDH) [6]. Over the past decade, increasing evidence indicates that DSF possesses a great potential for the treatment of human cancers [7; 8; 9]. DSF was previously reportedto inhibit the activity of protease, cause the accumulation of polyubiquitinated proteins as well as the aggregation of cytotox protein, and lead to cancer cell death [10]. Recent studies showed that DSF/Cu induced NPL4 (an adapter of p97/VCP segregase) aggregation and induced a complex cellular phenotype, finally leading to cell death [11]. Moreover, DSF/Cu was reported to induce significant cell cycle arrest and apoptosis, cause the disturbance of the ROS balance, and activate the stress-related ROS-JNK pathway as well as downregulate the NF-E2-related factor-2 (Nrf2) and Nuclear factor-kB (NF-kB) pathways in some tumor cells [12; 13; 14]. In addition, the anticancer effect of DSF is also related to epigenetics [15]. Importantly, DSF can be combined with antitumor drugs to enhance the antitumor effect [16; 17]. These studies have highlighted the importance of DSF in antitumor therapy, such as acute myeloid leukemia, prostate cancer, non-small cell lung cancer, breast cancer and so on [13; 14; 15; 16; 17]. However, more research is needed on the role of DSF/Cu in NPC.  
Ferroptosis is an iron-dependent formation of nonapoptotic cell death, which involves lethal, iron-catalyzed lipid damage [18]. Lipid peroxidation damage on the cell membrane has been shown to be a necessary condition for ferroptosis [19; 20]. The cystine/glutamate antiporter inhibitors erastin and sulfasalazine can inhibit the uptake of cystine, cause glutathione peroxidase 4 (GPX4) inactivation and lead to increased accumulation of lipid peroxidation in tumor cells [21]. Furthermore, p53 was also found to be involved in mediating ferroptosis [22; 23; 24]. Notably, solute carrier family 7 member 11 (SLC7A11), spermidine/spermine N1-acetyltransferase 1 (SAT1) and lipoxygenases (ALOXs) have also been shown to be mediated by p53 [23; 24]. In addition, ferrooptic agents can increase the level of death receptor 5 (DR5) and initiate apoptosis [25]. Recent studies showed that targeting ferroptosis-associated metabolism could improve the efficacy of cancer immunotherapy [26].  
In the present study, we investigated the antitumor capabilities of DSF/Cu against NPC, and the signalling mechanisms by which DSF/Cu treatment induces NPC cell death. We demonstrated that DSF/Cu was highly cytotoxic to NPC tissues and elucidated the potential antitumor role of DSF/Cu via ferroptosis.
## 3 Results
### Analysis of Local Ecosystem Service Trade-Offs and Synergies  
#### 3.3.1 Spatial Cold and Hot Spot Analysis of Ecosystem Services  
This segment builds on the initial examination of global trade-offs and synergies within ecosystem services by delving deeper into their spatial clustering within ecological restoration zones through cold and hot spot analysis. This method evaluates the local spatial autocorrelation properties of each service, as depicted in Figure 7. The findings reveal that the eastern region of the study area, particularly within the WCR, is predominantly characterized by hot spots for most services, while the western regions mainly feature cold spots. Except for food production services, the four other ecosystem services demonstrate a consistent spatial arrangement of hot spots across all restoration zones. These areas typically form a D-shaped cluster within the WCR, reflecting its role as a key area for water conservation.  
Figure 7 illustrates the general consistency in the distribution of cold and hot spots across carbon sequestration and habitat quality services alongside the spatial patterns of soil conservation and water yield services, which display a high degree of similarity. Notably, the hot spots for food production are primarily situated in the expansive WSFR and its southeastern stretches, reaching into neighboring ecological zones. Conversely, significant cold spots for food production appear chiefly in the southwestern areas of IR and SWCR, and in the southeastern parts of WCR, surrounding the hot spots and creating a core-like pattern. The cold spots for water yield and soil conservation are predominantly found in WSFR, SWCR, and the northwestern sections of IR, marked by distinct boundaries. Soil conservation hot spots are prevalent throughout WCR and to a lesser extent, form narrow strips along the northeastern edges of IR. Meanwhile, water yield hot spots are broadly spread across IR. The cold spots for habitat quality and carbon sequestration services tend to gather in the southwestern regions of IR and SWCR, with less frequent occurrences elsewhere.  
Figure 7: Spatial distribution of ecosystem service cold spot and hot spots in ecological restoration subregions **(a)** FP: food production; **(b)** HQ: habitat quality; **(c)** SC: soil conservation; **(d)** WY: water yield; **(e)** CS: carbon storage.
# Improving Energy Efficiency on SDN Control-Plane Using Multi-Core Controllers
## 3 Materials and Methods
### Comparing Multi-Core and Single-Core Energy Consumption  
The work by [PERSON] et al. [26] shows that it is more energy-efficient, for applications with a measurable speedup, to have a multicore low-frequency processor than to have a single-core high-frequency processor keeping the deliver time constant. This assumption can be verified for SDN controllers as this application is very I/O bound but can also leverage the parallel capacity of modern multicore processors.
## 3 Results and Discussion
### Response Surface Modelling and Optimization
#### 3.6.3 Optimization Using RSM  
To optimize the experimental design, constraints (Table 8) had to be implemented. Specific to this case, all input and output parameters (factors and responses) were maximized. This generated 8 solutions (Table 9), and one was selected as the optimal solution (Figure 7) as it presented the highest desirability of 74.7% removal efficiency. The optimal solution suggests a turbidity and COD removal of 96.6% and 33.1%, respectively, were attained at a catalyst load of 0.6 g/L and a reaction time of 40 min.
## 3 Results
### NDFI Validity and Burned Area Recognition in China  
Further, the huge forest fire that originated in China's Daxinganling Mountains in 1987 was used to validate the validity of the NDFI. Burned area in China's Daxinganling Mountains is shown in Figure 2. TM2, TM4, TM5, and TM7 of TM are used to calculate the NDFI image. A lower value indicated a greater possibility of burned area. This result is consistent with the actual situation. The MODIS data were used to calculate the NDFI for estimating the burned area at a large scale. The possible burned area distribution in China is shown in Figure 3. A lower value indicated a greater possibility of forest fires. The northeast forest fire in 2010 is used to validate the burned area result obtained from MODIS data. The validation result (Figure 4) shows that the result is consistent with the actual forest fire distribution. Meanwhile, monitoring results are consistent with existing studies [34].  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Band 1** & **Band 2** & **Band 3** & **Band 4** & **Band 5** & **Band 7** \\ \hline Band 1 & — — & 0.993081 & 0.991975 & 0.992561 & 0.908178 & \(-\)0.63607 \\ Band 2 & 0.993081 & — — & 0.999959 & 0.999991 & 0.85274 & \(-\)0.72228 \\ Band 3 & 0.991975 & 0.999959 & — — & 0.999989 & 0.847965 & \(-\)0.72853 \\ Band 4 & 0.992561 & 0.999991 & 0.999989 & — — & 0.850461 & \(-\)0.72528 \\ Band 5 & 0.908178 & 0.85274 & 0.847965 & 0.850461 & — — & \(-\)0.25467 \\ Band 7 & \(-\)0.63607 & \(-\)0.72228 & \(-\)0.72853 & \(-\)0.72528 & \(-\)0.25467 & — — \\ \hline \hline \end{tabular}
\end{table}
Table 4: Correlation coefficient (r) value between different bands.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Random Point** & **Band 1** & **Band 2** & **Band 3** & **Band 4** & **Band 5** & **Band 7** \\ \hline
8 & 8477 & 8512 & 8795 & 9707 & 13,315 & 13,919 \\
9 & 8323 & 8676 & 8800 & 9557 & 13,604 & 14,465 \\
10 & 8599 & 8765 & 8732 & 9437 & 12,791 & 13,455 \\
11 & 8807 & 9059 & 9386 & 10,340 & 14,468 & 15,411 \\
12 & 8643 & 8644 & 8759 & 9302 & 11,915 & 12,622 \\
13 & 8850 & 9005 & 9196 & 10,216 & 15,731 & 16,260 \\
14 & 8398 & 8578 & 8712 & 9279 & 12,027 & 12,510 \\
15 & 8738 & 8876 & 9471 & 10,809 & 14,190 & 12,859 \\
16 & 8493 & 8734 & 8839 & 9723 & 12,312 & 12,368 \\
17 & 8416 & 8735 & 8707 & 9423 & 12,408 & 13,052 \\
18 & 8550 & 8568 & 8429 & 9114 & 11,535 & 12,782 \\
19 & 8729 & 8810 & 8901 & 10,207 & 14,624 & 14,952 \\
20 & 8635 & 8797 & 9024 & 9904 & 13,662 & 14,272 \\ \hline \hline \end{tabular}
\end{table}
Table 3: _Cont._  
Figure 2: _Cont._Figure 3: \(Cont\).  
Figure 2: Raw TM (**left**) (3, 4, 2 bands) and NDFI image (**right**) in China’s Daxinganling Mountains, TM2, TM4, TM5, and TM7 of TM is used to calculate the NDVI image. A lower value indicated a greater possibility of burned area.  
Figure 3: Possible fire distribution from 2009 to 2018 in China.
# ResnetCPS for Power Equipment and Defect Detection
## 6 Conclusions  
This study proposes a novel approach, namely ResnetCPS, to tackle the problem of scale fluctuations in datasets and ensure the lightweight characteristics of the model. This paper uses images of power equipment as validation, which can be considered for use in other fields with similar features. ResnetCPS mainly includes the following advantages:  
Firstly, by leveraging the scale-invariant design of image datasets, ResNetCPS demonstrates enhanced effectiveness in extracting features from the data. This design enables it to better capture the inherent patterns and characteristics within the power equipment images, regardless of variations in scale.  
Secondly, the parameter-sharing mechanism of ResNetCPS plays a crucial role. It can significantly reduce both the parameter count and the model size. This reduction not only alleviates the computational burden during training and inference but also holds great promise for practical industrial applications, where resources are often limited and efficiency is of utmost importance.  
Thirdly, ResNetCPS empowers the model to achieve faster convergence within a constrained training time frame, simultaneously attaining higher accuracy.  
In the experimental phase, when compared with the Resnet variant network, ResnetCPS achieved a remarkable 10-30% reduction in both the number of parameters and the model size. Moreover, when contrasted with networks of similar scale, its accuracy reaches the state-of-the-art level, highlighting its superiority in performance. Codes are available at [[https://github.com/wdzjs/ResnetCPS/tree/main](https://github.com/wdzjs/ResnetCPS/tree/main)]([https://github.com/wdzjs/ResnetCPS/tree/main](https://github.com/wdzjs/ResnetCPS/tree/main)) accessed on 16 November 2024.  
Conceptualization, X.Y. and D.Y.; methodology, X.Y.; software, X.Y. and S.X.; validation, X.L.; formal analysis, W.C.; investigation, D.Y.; resources, L.J.; data curation, H.C.; writing--original draft preparation, X.Y.; writing--review and editing, D.Y. and S.X.; visualization, X.L.; supervision, W.C.; project administration, X.Y.; funding acquisition, D.Y. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China (62306232), the Natural Science Basic Research Program of Shaanxi Province (2023-JC-QN-0662), the State Key Laboratory of Electrical Insulation and Power Equipment (EIPE23416), and Fundamental Research Funds for the Central University and HPC Platform, Xi'an Jiaotong University.  
Not applicable.  
Data Availability Statement: 3 rd Party Data Restrictions apply to the availability of these data. Data were obtained from State Grid and are available from the authors with the permission of State Grid.  
Authors [PERSON] and [PERSON] were employed by the company State Grid Information & Telecommunication Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Real-Time, Model-Agnostic and User-Driven Counterfactual Explanations Using Autoencoders
###### Abstract  
Explainable Artificial Intelligence (XAI) has gained significant attention in recent years due to concerns over the lack of interpretability of Deep Learning models, which hinders their decision-making processes. To address this issue, counterfactual explanations have been proposed to elucidate the reasoning behind a model's decisions by providing what-if statements as explanations. However, generating counterfactuals traditionally involves solving an optimization problem for each input, making it impractical for real-time feedback. Moreover, counterfactuals must meet specific criteria, including being user-driven, causing minimal changes, and staying within the data distribution. To overcome these challenges, a novel model-agnostic approach called Real-Time Guided Counterfactual Explanations (RTGCEx) is proposed. This approach utilizes autoencoders to generate real-time counterfactual explanations that adhere to these criteria by optimizing a multiobjective loss function. The performance of RTGCEx has been evaluated on two datasets: MNIST and Gearbox, a synthetic time series dataset. The results demonstrate that RTGCEx outperforms traditional methods in terms of speed and efficacy on MNIST, while also effectively identifying and rectifying anomalies in the Gearbox dataset, highlighting its versatility across different scenarios.  
Keywords:explainable AI; autoencoders; counterfactual explanations +
Footnote †: journal: Applied Sciences
## 3 In Situ AE Monitoring in Salt Mines
### Salt Mine Morsleben in Germany
The peaks of the curve are caused by the fact that the fresh concrete cools down the surface of the concrete body during the working week. At the weekend backfilling is interrupted and temperature rises quickly until the beginning of the next week. The quick temperature increase is accompanied by a very sharp and high increase in the location rate of AE events characterizing the intensity of microcrack processes taking place. When temperatures decreased after the weekend, the location rates also decreased instantaneously indicating that the microcrack activity was generated by thermoelastic effects due to the heating of the rock mass by the setting of the concrete. [PERSON] et al. [72] compare in a study the spatio-temporal evolution of the AE event distribution (Figure 12) with results from a 2D-finite element study of the evolving stress field well constrained by the known geometry of the structure and the material properties. They found out that for the first five thermal loading cycles a pronounced Kaiser effect can be observed. The so called Felicity Ratio is the ratio of the AE onset stress value to the previous peak stress [93]. It is a measure of the quality of the Kaiser effect with a value of 1 indicating a perfect stress memory effect. The observed Felicity Ratio of greater than 0.96 for the first five loading cycles indicates a very pronounced Kaiser effect. The deviation from the Kaiser effect during later loading cycles seems to be caused by the initiation of a  
Figure 12: AE location rate and temperature in a room in the central part of the salt mine Bartensleben during backfilling [38]. planar macroscopic crack, which is subsequently reactivated. AE activity tends to concentrate along this macro crack.
## 3 Experiment and Results Analysis
### Experimental Environment  
The experiments presented in this paper were conducted on a computer running Windows 10, equipped with an Intel(R) Xeon(R) Platinum (Intel Corporation, Santa Clara, CA, USA) 8358P @2.60 Ghz CPU, an NVIDIA RTX 3090 GPU (Nvidia Corporation, Santa Clara, CA, USA) with 24 GB video memory, and 64 GB RAM, using CUDA 11.8 and Python 3.8 with PyTorch 2.0.0 framework. During the model training process, we employed the Adam [29] optimizer to adjust parameters while introducing the Dropout [30] mechanism to randomly deactivate neurons for reducing overdependence between them and prevent overfitting; furthermore, a gradient trimming technique was utilized to mitigate the effects of gradient vanishing and explosion. Specific model parameter settings are shown in Table 4.
## 2 Materials and Methods
### SSR Amplification and Electrophosis  
PCR amplification was carried out in a final volume of 25 \(\mu\)L containing 25 ng of genomic DNA, 1 mM dNTPs (Promega, Milan, Italy), 0.3 \(\upmu\)M each primer, 1\(\times\) Buffer (Promega), and 0.5 U Taq DNA polymerase (Promega). The reactions were performed in the Mastercyler Gradient thermocycler (Eppendorf, Milan, Italy). The sequences of the 10 primer pairs, the type of labeling at 5\({}^{\prime}\) of each forward primer, and the annealing temperature (Ta) are shown in Supplementary Table S1[34; 35; 36]. The amplification conditions were one cycle at 94 \({}^{\circ}\)C for 5 min, followed by 35 cycles consisting of a 30 s step at 94 \({}^{\circ}\)C, a step at the specific Ta for 15 s, and an elongation phase at 72 \({}^{\circ}\)C for 1 min. An ending polymerization stage was carried out at 72 \({}^{\circ}\)C for 10 min. The PCR products were first analyzed first by horizontal 2% (\(w/v\)) agarose gel electrophoresis in a 1\(\times\) TAE buffer [33] and then by denaturing capillary electrophoresis in an ABI PRISM 3100 Genetic Analyzer (Applied Biosystems, Milan, Italy). Each run lasted about 45 min and was performed at 15 kV and 60 \({}^{\circ}\)C using the POP4 polymer (Applied Biosystems). The signal height of each peak and the allele size were calculated using the ABI Prism Genotyper (v. 3.7) software (Applied Biosystems) according to the GeneScan 500 Liz dye molecular weight marker (Applied Biosystems). Duplicate analysis of each variety provided the same SSR profile.
# Path Planning for Laser Cladding Robot on Artificial Joint Surface Based on Topology Reconstruction
## 1 Introduction
Thus, it is not an optimal choice to prepare coatings on a femoral head or acetabular cup with such large and complex equipment or a robot equipped with a laser head. Moreover, most research has focused on the detection of cladding coating quality and failed to explain the methods and algorithms of path planning in detail. Therefore, the design of a reasonable processing mode and detailed path planning algorithm still need to be studied, especially in the field of coatings preparation on artificial joint surfaces. In this paper, a novel processing mode was introduced, whereby the artificial joint parts clamped by a robot moved while the laser head was fixed on the workbench. The robot was used to adjust the relative position between the laser head and the processing surface, so that the laser beam and powder beam are always consistent with the normal direction of the surface and focus on the processing surface. This mode ensured the effectiveness and safety of cladding processing and saved processing space. Furthermore, an automatic path planning method for a laser cladding robot on an artificial joint surface was developed. The CAD model of artificial joints was analyzed to extract the surface information and to reconstruct the topological relation. Based on an established topological relation, the surface transversals were generated using the intersection of the surface and the parallel plane cluster and transformed to the cladding path using the arch height error method. The proposed method was applied to a sample model of the acetabular cup with an external diameter of 46 mm. The results showed that the laser cladding path can be generated more quickly and accurately using the proposed method than the traditional manual teaching method.