esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### SEM Results  
Figure 7 shows the micrograph profiles of miniplates after undergoing degradation testing for 28 days of all samples with injection temperature of 180 \({}^{\circ}\)C. Figure 7a illustrates the surface condition of a miniplate with PLA/PEG 10% material, revealing surface roughness after degradation. The rough surface profile, indicated by small spots, represents starch particles that emerge during degradation. The circular profile with a brighter color on the surface indicates the presence of starch particles that are not perfectly dispersed in the PLA matrix during the injection molding process.  
Figure 7b displays the micrograph profile of the miniplate surface with a 20% sago starch/PLA mixture, providing information about the presence of a relatively large longitudinal crack profile with small perpendicular crack branches around the main crack after 28 days of degradation. The cracks indicate the weak interface bond between starch and PLA matrix due to differences in hydrophilicity.  
After a degradation period of 28 days, it is observed that the addition of 10% PEG to the PLA/sago starch mixture does not lead to the emergence of surface crack profiles, indicating that the plasticizing function of PEG is effective in improving the interfacial bond between starch and PLA matrix. The previously formed interface layer around imperfectly dispersed starch particles disappear, forming a clear boundary on the outer side of the starch particles, as in Figure 7c. This suggests that the PEG interface layer will disperse into the PBS solution and degrade more rapidly during degradation.  
A clearer profile is observed in the micrograph of miniplates with the addition of 20% PEG to the PLA/sago starch mixture as seen in Figure 7d. The presence of large crack profiles in the image indicates increased porosity due to the higher concentration of PEG dispersed in the PLA/sago starch mixture. The PEG interface layer on starch molecules will degrade faster, carrying along bound starch molecules, while the cracks indicate uneven distribution of plasticizer concentration, causing faster release of the PLA/sago starch interfacial bond compared to lower PEG concentrations. From the micrograph profiles, it can be concluded that the addition of 20% PEG will increase the porosity of miniplates during degradation compared to the addition of 10% PEG to the PLA/sago starch mixture.
# Automated Business Goal Extraction from E-mail Repositories to Bootstrap Business Understanding
## 2 Methods
### Filter Results  
At this stage, a goal list is created, however one more step is necessary to enhance its precision, thus usability. This is the automatic filtering of unwanted false positive results. This component was developed through an analysis of a random sample of 447 e-mails from the Enron corpus, while looking for common ground between the false positive matches, which was not shared with true positive matches. This analysis yielded the following results:  
* A high number of analyzed false positives concerns personal information exchange, which is not related to the organization, however gets labeled as a match due to the appearance of keywords within it. A high number of this type of false positives has the participants of the information exchange addressing each other personally, for example, by using the word \"you\". This is not as prominent within the true positives group, where the e-mail authors rarely address the recipients personally within the same sentence (or-sentence fragment) that contains the business goal;
* Another pattern identified within the false positives group concerns the organization of: lunches, dinners, meetings, conferences, sleeping accommodation and so forth. The language used often contains keywords, such as \"provide\" or \"ensure\";
* False positives tend to contain first and/or last names of people, for example, \"Provide [PERSON] with an update\". This is not encountered that often within the true positives, however there are instances where an excerpt from a sentence can be classified as a business goal, even while explicitly stating a person's name; Having these observations, the following filters were applied:
* Any match that personally addresses the recipient of the e-mail is filtered out, thus not being included in the results. This had an extremely positive effect on the precision of the tool, while having an insignificantly negative effect on the recall;
* Any match that includes the words \"lunch\", \"dinner\", \"meeting\", \"conference\", \"accommodation\" is filtered out as well. This filtering had a slightly positive effect on precision, while not affecting the recall at all;
* Since filtering first and last names from the results would require a next instance of a higher level natural language processing algorithm, which would in turn need much more computational power and time, while not improving the combined measure of precision and recall significantly, this idea was abandoned;  
It is important to note that this step of the method is not as generalizable as the other method steps. Depending on the area of application, whether it is a specific business, or an industry, the keywords for filtering might need to be re-adjusted.
# Innovative Application of Blockchain Technology for Digital Recipe Copyright Protection
## 3 Schematic Design
### System Design  
#### 3.2.1 System Composition and User Interaction Flow  
Our proposed digital copyright protection system is a multilayer, multirole network system initially designed to fulfill the needs of digital recipe copyright protection in a distributed network environment. The system, as a whole, is divided into a user layer, application service layer, node layer, contract layer, consensus layer, and data layer, as shown in Figure 1.  
The user layer is mainly composed of creators and customers, which interact with the system through the client. Users can switch roles according to their needs to complete the uploading and downloading of recipes.  
The service layer contains four main modules: copyright application, audit, transaction, and traceability. It is primarily responsible for accomplishing the overall functional requirements.  
The node layer is divided into interaction nodes and processing nodes. Interaction nodes represent user interaction nodes, which are primarily involved in user interaction, including creating, uploading, downloading, and decryption of recipes. Processing nodes are responsible for data processing, validation, and storage.  
The contract layer mainly realizes the modules used by the server side. It contains four primary smart contracts: RecipeUploadContract, DataStorageContract, RecipeDownloadContract, and CopyrightTraceabilityContract.  
The consensus layer comprises an improved DPOS consensus mechanism. Transactions are quickly agreed upon between nodes in a distributed system. To ensure the security and integrity of transactions, we introduce an authentication system. Each node that participates in the consensus needs to go through an authentication process that ensures that it is a registered and trusted node. In addition, we design a credential management system to store, update, and revoke the credentials of nodes. This ensures that only nodes with valid credentials can participate in the consensus process, enhancing the security of the system.  
The data layer is divided into the main chain and side chain. The main chain stores the hash address of the user's data. It ensures that the creator's work is public and cannot be tampered with. The side chain holds the user's copyright transaction information, which is convenient for later rights holders to trace the copyright.  
Figure 1: Blockchain architecture diagram.
## 4 Conclusions  
In summary, CF composites were successfully prepared by regulating the content of free carbon in CF ceramics using DVB and employing Fe, derived from the decomposition of FeAC, as a catalyst to promote the graphitization of free carbon and the growth of CNTs. The results demonstrated that this anode material maintained structural integrity throughout the charge-discharge cycles, exhibiting remarkable capabilities in rate performance and cycle life. Notably, after 1000 cycles at a high current density of 2000 mA g\({}^{-1}\), a specific capacity of 401.40 mAh g\({}^{-1}\) was retained. In conclusion, this research provides a simple and effective solution for controlling the amount, degree of graphitization, and morphology of free carbon in SiOC ceramics, offering valuable insights for the utilization of these materials in rapid charging and discharging and suggesting their excellent cycling capability in lithium-ion batteries.  
The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/molecules29184461/s1](https://www.mdpi.com/article/10.3390/molecules29184461/s1)]([https://www.mdpi.com/article/10.3390/molecules29184461/s1](https://www.mdpi.com/article/10.3390/molecules29184461/s1)), Figure S1: XRD spectrum of a SiOC sample; Figure S2: Raman spectrum of a SiOC sample; Figure S3: XPS full spectrum of the CF series samples; Figure S4 (a-d): Charge-discharge profiles of the CF series samples for the first three revolutions at 100 mA g\({}^{-1}\) current density; Figure S5: Charge-discharge curves of CF-75 at a current density of 100 mA g\({}^{-1}\); Table S1: Specific surface area and pore volume and pore size of the CF series samples; Table S2: Si 2p XPS spectroscopic results for the CF series samples.  
Conceptualization, Y.Q. and J.X.; methodology, C.H. and P.F.; data curation, Y.S. and K.L.; writing--original draft, Y.Q.; funding acquisition, X.J. and J.X.; software, Y.Q. and P.F.; visualization, YQ. writing--review and editing, Y.S. and J.X.; data curation, Y.Q. and P.F. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work received funding from the National Natural Science Foundation of China under grant numbers 52075526, 91860204, the Fundamental Research Funds for the Central Universities under grant number DUT22-LAB605, and the \"Ningbo 3315 Plan Innovation Team\" under grant number 2017A-28-C.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available upon request from the corresponding author.  
**Conflicts of Interest:** There are no financial competing interests to declare.
# Image Resolution Enhancement of Highly Compressively Sensed CT/PET Signals
## 8 Discussion
The technology employs several state-of-the-art methodologies, such as a discrete dense displacement sampling, a Bayesian probabilistic model shaping the blur kernel, image priors as well as noise estimates. The constructed solution is nearly insensitive to in-plane motion artefacts being able to successfully overcome noise and blurs kernel odds. Thus, it is clearly shown that the developed procedure can provide enhanced and sharper images while keeping radiation levels at the lowest possible levels. It is clearly detailed (see Tables 1-10) that the compression ratios highly affect the PSNR and Mean Absolute Error (MAE) values. Moreover, the presented methodology argued its value in making artefacts caused by undersampled data much lower, even under the influence of motion blur. This paper reveals a very promising application of super-resolution of highly sensitively compressed CT/PET signals. It is clearly exposed (see Tables 1-10) that the Compressed Sensing quality ratios highly affect the PSNR and MAE values. The average PSNR is calculated between the numerous methods outputs and the ground truth images. Each simulation scenario was repeated 100 times in order to generate statistically meaningful quality measures. Note that satisfying results were obtained at a compression ratio equal to 50%, i.e., further decreasing the total number of input samples improves the PSNR slightly (see Tables 5, 8, 10 and Figures 3-9). Data from preliminary trials can also be valuable in providing background information useful in reducing examinations times. However, although the motion estimation algorithm can significantly eliminate diagnostic images' artefacts, which maximise the chance of a correct diagnosis. Qualitative assessment of the neuroimages and chest scans of 10 different patients showed the advantages of the applied algorithm. In the trials, the PET and the CT data of 10 oncological patients were simultaneously obtained on an integrated CT/PET scanner. The phantom studies were conducted using 20 simulated patient brain PET data volumes with corresponding CT scans. For quantitative measurement, the PSNR of each reconstruction procedure was also calculated. The (18) FJfludeoxyglucose ([(18) F]FDG) as a tracer was employed. In this experiment in vivo, as well as phantom, inputs have been analysed. Fully sampled CT/PET raw data were often used as the ground truth reference, and were either obtained, or already were available in the case of CT/PET reconstruction procedures.
# A 12-20 GHz Wideband High-Power SP2T Switch Based on Gap Waveguide Technology
## 1 Introduction
The proposed structure of the switch is complicated as it uses a cylindrical pin structure, and therefore, a complex manufacturing process is required to fabricate the switch. The proposed switch operating frequency bandwidth is narrow and limited between 10.5 and 13.5 GHz (25%). In this article, groove gap waveguide technology is utilized to design and develop a single-pole two-throw (SP2T) microwave switch with a simple planar structure and a 50% operating frequency bandwidth covering the range of 12-20 GHz. The proposed switch has wide bandwidth, low insertion loss, high isolation, and power handling capability for high power applications. The proposed switch can be used in radar systems, satellites, and any wideband Ku-band applications.
## 5 Experimental Analysis
### Ablation Experiment  
In this section, we aimed to illustrate the effectiveness of different parts of our proposed model. We designed a set of ablation experiments to further evaluate the importance of different components in the ECKEI model. First, we set up a series of methods to compare the performance of BREXIT and ELECTION. Specifically, the ECKEI model and its variant models are compared as follows.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{3}{c}{**BREXIT**} & \multicolumn{3}{c}{**ELECTION**} \\ \cline{2-7}  & **Avg\_–MF1** & **Avg\_-Acc** & **Avg\_-Recall** & **Avg\_–MF1** & **Avg\_–Acc** & **Avg\_-Recall** \\ \hline SVM-ngram & 53.18 & 54.48 & 62.30 & 64.22 & 65.50 & 73.06 \\ NB & 51.76 & 52.59 & 61.18 & 56.28 & 58.80 & 63.54 \\ MITRE(RNN) & 64.35 & 65.81 & 73.14 & 71.64 & 72.96 & 80.62 \\ Pkudblab(CNN) & 61.59 & 62.61 & 69.67 & 66.12 & 67.88 & 75.06 \\ TAAT & 60.44 & 61.78 & 69.48 & 69.45 & 71.08 & 78.45 \\ Aff-Feature & 59.26 & 60.89 & 68.45 & 69.59 & 70.38 & 79.80 \\ ECKEI & **68.65** & **70.05** & **78.48** & **72.86** & **73.44** & **83.27** \\ \hline \hline \end{tabular}
\end{table}
Table 4: Avg\_–MF1, Avg\_–Acc and Avg\_–Recall of our approaches on BREXIT and ELECTION.  
Figure 8: Micro-F1, accuracy and recall results on two datasets for the neutral stance.  
Figure 7: Micro-F1, accuracy and recall results on two datasets for the support stance.  
Figure 9: Micro-F1, accuracy and recall results on two datasets for the opposing stance.  
* ECKEI-BiLSTM: In order to analyze the effect of commonsense knowledge, we used ordinary BiLSTM instead of CK-BiLSTM in ECKEI.
* ECKEI-Topic: In order to evaluate the impact of topic information on stance classification, we removed the topic part for comparison.
* ECKEI-Attention: In order to evaluate the effect of the attention mechanism, we removed the attention mechanism part for comparison.
* ECKEI-Neighborhood: In order to evaluate the influence of neighbor information, we removed the neighbor information module for comparison.  
The results of the ablation experiment are shown in Figures 10-12. Further, we compared the experimental results concerning average accuracy, average micro-F1 and average recall, as shown in Table 5. From Figures 10-12, we can observe that for most stance categories, detection performance will be lower when removing each of the three key components. Specifically, in the ECKEI model, we use BiLSTM instead of CK-BiLSTM to significantly reduce the performance of the model, which shows that the introduction of commonsense knowledge can improve the quality of stance classification. In Table 5, we can observe that the ECKEI-Topic model has a significant decline in average accuracy, average micro-F1 and average recall. It indicates that the topic module in the paper is essential because our neighbor's tweets are passed. The topic information can obtain tweets with the same topic as the user, so the topic information plays a decisive role here. We find that when one clicks neighbor tweets, it has the least impact on the entire module because topic information plays
## 4 Multi-Objective Parameter Tuning
### Empirical Procedure  
This section details the empirical procedure followed in evaluating M-race. M-race was evaluated on a PSO [19] as well as a DE algorithm [26]. The test functions that were used as problems were as follows:  
* [PERSON] [22]: \[f(\mathbf{y})=10D+\sum_{i=0}^{D-1}\left(y_{i}^{2}-10\cos(2\pi y_{i})\right)\]
* [PERSON] [27]: \[f(\mathbf{y}) = \sum_{i=0}^{D-2}\left[y_{i}\cdot\cos a(y_{i+1},y_{i})\cdot\sin b(y _{i+1},y_{i})\right.\] \[+ \left.(1+y_{i+1})\cdot\sin a(y_{i+1},y_{i})\cdot\cos b(y_{i+1,y_{ i}})\right]\] where \[a(y_{i+1},y_{i}) = \sqrt{\left|y_{i+1}+y_{i}+1\right|}\] \[b(y_{i+1},y_{i}) = \sqrt{\left|y_{i+1}-y_{i}+1\right|}\]
* Schwefel [28]: \[f(\mathbf{y})=418.9829\cdot D\sum_{i=0}^{D-1}y_{i}\sin\sqrt{\left|y_{i}\right|}\]  
Each function was tested in \(D=20\) dimensions. The search space was a hypercube, centred on the origin, with lower and upper bounds defined in Table 6. A significance level of \(\alpha=0.05\) was used for the Friedman test. An initial sample of 2048 parameter configurations were considered. Tuning was performed based on two performance objectives, namely accuracy and efficiency (see Section 3.2 for definitions), and a threshold value of \(n_{min}=10\) was used.  
Additionally, an analysis of the sensitivity to the initial sample was performed by running M-race on all the benchmark functions 10 times. The hypervolume measure [29] was used to compare the quality of the calculated Pareto fronts over the different tuning runs, for different initial sampling sizes of \(2^{k}\), where \(k\) ranged from [5,10]. The calculated  
\begin{table}
\begin{tabular}{l c c} \hline
**Function** & **Lower Bound** & **Upper Bound** \\ \hline Rastrigin & \(-5.12\) & \(5.12\) \\ Rana & \(-512\) & \(512\) \\ [PERSON] & \(-500\) & \(500\) \\ \hline \end{tabular}
\end{table}
Table 6: Lower and upper bounds of the hypercubes defining the search spaces.  
front is taken as the average of the performance of each parameter configuration with respect to each objective over the course of the tuning run. Since M-race has a minimum threshold where the algorithm is stopped prematurely, some configurations that remain may be dominated configurations. For the sake of this analysis, all such dominated configurations are removed before the hypervolume of the front is calculated. Furthermore, to compare the performance of M-race across different benchmark functions, the objective space is scaled to the interval \([0,1]\) for each objective. This is performed using min-max normalisation. The reference point for the hypervolume measure is taken as \((0,0)\). Thus, the smaller the hypervolume measure, the better the quality of the Pareto front. A PSO was tuned for the sake of the sensitivity analysis. In addition to the functions used for the general evaluation, sensitivity analysis was also conducted on the Ackley function defined in Section 3.2.
## 10 Conclusions  
In this paper, we investigated a new scheme to generate securely symmetric encryption keys for IMDs with the aim to cipher the communication wireless packets. We introduced the chaotic system implemented for generating the keys. This system relies on Henon mapping to form the pseudo-random keys, relying on the synchronized initial conditions. The generation is based on a shared seed between the devices to create the same cryptographic key at both ends. This key is used in a simple encryption scheme that explores the path loss characteristics of the channel to create a diffusion effect in the sent packets, hardening the adversary's task to understand and/or intercept the communication. We then analyzed in a further step the randomness of this pseudo-random generator, ensuring that the generated keys are cryptographically random and impossible to guess in a statistical approach. We have also evaluated the security performance of the encryption system while ensuring its hardware efficiency regarding IMDs. We concluded that the proposed system can be used by any implantable medical device, and can ensure users' secure wireless communication while protecting them from intruders.  
Conceptualization, T.B. and M.G.; Methodology, T.B. and X.D.; Formal Analysis, T.B.; Resources, M.G. and A.M.; Visualization, A.M. and A.K.A.-A.; Writing-Original Draft Preparation, T.B. and X.D.; Writing-Review & Editing, A.M., A.K.A.-A. and M.G.  
This publication was made possible by NPRP grant #8-408- 2-172 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.  
The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.