esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Analysis of the Experimental Results  
As shown in Figures 10-12, all resonant frequencies decreased when the temperature increased. These curves show how the resonant frequency varied as the temperature varied for each material.  
Figure 10: Resonant frequencies of XPE as a function of temperature.  
The results of the vibration tests showed a more emphasized influence of temperature on the performance of XPE compared to PE30 and PE25. Generally, PE25 showed the lowest influence due to temperature changes. When the temperature was increased from \(-20\)\({}^{\circ}\)C to \(+40\)\({}^{\circ}\)C, the smallest change was also measured in this material (7.7884 Hz, 6.976 kPa static load, \(-20\)\({}^{\circ}\)C to \(+40\)\({}^{\circ}\)C). The resonant frequency was moved on the transmissibility plot by at least 22 Hz for PE30 and 57 Hz for XPE, depending on the static load. The maximum changes were more than 70 Hz for XPE, 40 Hz for PE30, and 13 Hz for PE25, depending on the static load. Therefore, packaging engineers must take into consideration the effects of temperature on the resonant frequency of the applied cushioning material, especially for XPE, which showed the highest influence of varying the temperature, based on the experimental results.  
Packaged products can experience different climate conditions when shipped between continents. However, it is rare, even in modern supply chains, that packaged products can be exposed to all values in the wide temperature range used in our study. The temperature usually only ranges between 20 \({}^{\circ}\)C and 40 \({}^{\circ}\)C. Furthermore, most of the available data on the resonance frequency of cushioning materials was obtained at normal temperatures. For this reason, packaging professionals need to know the changes in the resonant frequencies under different temperature conditions. The resonant frequencies of PE25 and PE30 were less influenced than XPE by all changes in temperature. As the temperature moved from 20 \({}^{\circ}\)C to 40 \({}^{\circ}\)C, the change in resonant frequency was minimal for PE30 and PE25.  
Figure 11: Resonant frequencies of PE30 as a function of temperature.  
Figure 12: Resonant frequencies of PE25 as a function of temperature.  
These materials were mostly affected by a decrease in temperature. XPE was significantly influenced by both decreasing and increasing the temperature.  
The effect of the static loads on the function of temperature was not clear. At the same temperature, the resonant frequency decreased when the static load was increased. However, when the temperature was increased from \(-20\)\({}^{\circ}\)C to +40 \({}^{\circ}\)C, the highest changes in the resonant frequency were at 4.651 kPa for XPE and PE25, but at 3.488 kPa for PE30.
# Hard Fusion Based Spectrum Sensing over Mobile Fading Channels in Cognitive Vehicular Networks
## 4 Cooperative Sensing with Counting Rule
### Equivalent Local Probability of False Alarm and Misdetection
Besides, we also see that, as the reporting channel becomes more unreliable (low SNR situation, i.e., SNR \(\gamma_{i}\) in dB \(\rightarrow-\infty\) ), the equivalent probability \(P_{Di}\;(P_{Fi})\) is close to \(\frac{1}{2}\). As SNR \(\gamma_{i}\) in dB \(\rightarrow\infty\), \(P_{Di}\;(P_{Fi})\) comes near to \(P_{di}\;(P_{fi})\), that is to say, this is a perfect reporting channel.
# Chemical Characterization of Cider Produced in Hardanger--From Juice to Finished Cider
## 3 Results and Discussion
### Chemical Composition of Apple Jices and End Fermented Cider of Different Apple Fruit Cultivars
#### 3.1.1 Acids, Sugars, Ethanol, and YAN  
The concentration and composition of the organic acids in the cider affect the pH, taste, and microbial stability. The acids in the finished cider were present in the raw materials; however, their concentrations can change during fermentation by yeasts or malolactic bacteria [14; 15; 16]. Malic acid content decreased during fermentation for all cultivars (Tables 2 and S3). Such a decrease is common because of yeast metabolism of malic acid and conversion of malic acid to lactic acid [16]. The latter is also supported by the data in Table 2, showing some extent of malolactic fermentation conversions. In juices, the average titratable acidity (expressed as malic acid equivalent) ranged on average per cultivar from 6 ('Discovery') to 8.9 ('Aroma') g L\({}^{-1}\). The level of titratable acidity decreased during fermentation, likely because of possible chemical transformations and precipitation reactions [17]. After fermentation, the average titratable acidity ranged from 5.2 ('Discovery') to 7.2 ('Summerred') g L\({}^{-1}\). Malic acid is the dominant acid in apples [18]. The malic acid contents in apple juices varied from 2.5 g L\({}^{-1}\) ('Discovery') and up to 22.1 g L\({}^{-1}\) ('Aroma'). The average concentrations of malic acid in the juice of the four cultivars ranged from low to high in the following order: 'Discovery', 'Summerred', 'Gravenstein', and 'Aroma'. During fermentation, the content of different acids generally decreases [18]. Malic acid contents were reduced by 53%, 32%, 70%, and 9% on average during the fermentation of 'Aroma', 'Discovery', 'Gravenstein', and 'Summerred', respectively. The reduction in malic acid in cider from Hardanger was higher than that found by [PERSON] et al. [14], who found a reduction of malic acid during fermentation of up to 40%, while [PERSON] [16] reported a slight decrease in malic acid in two ciders from Croatia during fermentation. This reduction, as previously mentioned, is the result of many biochemical reactions and yeast assimilation of malic acid. Malic acid can also be reduced by lactic acid bacteria, and the amount of lactic acid produced at the end of fermentation indicates malolactic fermentation, as mentioned previously. The highest measured level of lactic acid in all ciders in the study was over 4.8 g L\({}^{-1}\) ('Aroma'). The reduction in malic acid content reduces the sour taste of the cider [19]. Lactic acid, on average, increased during the fermentation of 'Aroma', 'Discovery' and 'Gravenstein', but not for 'Summerred' ciders. The citric acid content was low in the monitored samples, which agrees with [PERSON] et al. [16]. We also detected small amounts of tartaric acid in all the samples, and no acetic acid.
## 6 Abuse Attack Techniques
### Steganography
#### 6.1.3 Insights  
Our review of steganography in the context of abusing the CPLS as C&C channels presents several important insights:  
* Steganography has become a popular method among threat actors for maintaining a covert communication channel, often serving as the primary C&C channel. Cases like ELISA, Stegobot, Punobot, HAMMERTOSS, and RegDuke demonstrate the use of different steganographic techniques--from Unicode and image steganography to the least significant bit technique--effectively hiding malicious commands and evading detection.
* Online social networks (OSNs), along with other online platforms, have become common targets for misuse. As seen with ELISA and Stegobot using Facebook and HAMMERTOSS exploiting GitHub, these platforms provide a vast, noisy environment in which malicious activities can blend in, thus enhancing the effectiveness of the steganography.
* The sophistication and complexity of steganographic techniques have been increasing. Advanced encryption standard (AES) keys, domain generation algorithms (DGAs), and obfuscation techniques like.NET Reactor have been used in conjunction with steganography to further hide and protect the malicious payloads.
* Mobile platforms are not immune to these types of attacks. As shown by Punobot, steganography can also be employed in attacks targeting mobile devices, in this case using Google Cloud Messaging as a C&C channel.
* Steganography is not only used for direct C&C communications but also serves as a means of redirecting to C&C domains. HAMMERTOSS and PolyglotDuke represent cases where steganography was used to decode the C&C URLs.
## 3 Results
### Implementation  
The implementation consists of using real wind values and determining the performance in terms of generator shaft rotation speed, thus evaluating the maximum possible power generation.  
The equipment used to measure wind speed and direction is an ultrasonic wind sensor from Lufft with part number V200A. The anemometer has a measurement range between 0 and 90 m/s, a resolution of 0.1 m/s, and an accuracy of \(\pm\)3 m/s [34].  
An ultrasonic wind sensor is used to reduce the uncertainty caused by a mechanical measurement system outdoors, besides the use of a RS-485 communication protocol between the instrument and the control system to avoid losses due to distance; therefore, the uncertainty to be considered is that corresponding to the instrument calibration of 0.03 m/s. This uncertainty is sufficient for the operation of the fuzzy logic control algorithm, which works by measuring ranges.  
For implementation, a record of wind speed in real conditions was obtained as presented in Figure 20. The results of the experiment are presented in Figure 21.  
The graphical results in Figure 21 show that the proposed PID-FLC controller has a better performance than a classical PID, as the value of rotation speed of the generator shaft is closer to the value of the nominal speed. According to a mathematical analysis made, with the PID-FLC controller, the generator shaft speed was kept at nominal values 70% of the time, while with the classical PID controller, it was only for 50% of the time.  
Figure 18: Pitch angle movement.  
To quantify the difference in power generation with both controllers, only generator shaft speed values lower or equal to the nominal speed are considered, as values higher than the nominal speed are tried to reduce and mitigate the dynamic loads on the rotor. Under these conditions, the proposed PID-FLC controller generated 7% more electrical power than with the classic PID controller.  
Figure 19: Comparison of the time transition of the gains between the proposed PID-FLC controller and the classical PID controller. (**a**) proportional constant \(k_{p}\), (**b**) integral time \(k_{i}\), (**c**) derivative time \(k_{d}\).  
Figure 20: Real wind speed conditions.  
Figure 22 shows the differences in pitch angle movements. PID-FLC makes anticipated changes in the angle movement from the classic PID controller. This is because of the measurement that is made in advance at 450 m; when the PID-FLC detects a sudden change in wind speed, the pitch angle movement starts when it is measured and not until it impacts on the turbine.
## 5 User Study
### Measures
#### 5.3.1 User Behavioral Tracking Metrics  
The computation of these engagement metrics was based on the data provided by the UBT system described in Section 4.2. This system allowed us to measure participants' attentional behavior throughout the interaction by gathering data from the head pose orientation, distraction events, and overall interaction time. We derived two engagement-related metrics from these data: distraction frequency and distraction duration ratio.  
Recent literature emphasizes attention as a core cognitive component of engagement in HRI. As noted by [PERSON] et al. [23], the cognitive facet of engagement comprises conscious processes such as effort, investment, and attention, with attention being the component most frequently associated with engagement. Following this idea, we interpret both the frequency of distraction events and the ratio of time spent distracted as indicators of attentional disengagement. We believe these metrics will allow us to evaluate changes in user attention throughout the interaction, thus complementing self-reported assessments with behavioral data.  
The first metric is the _distraction frequency_ (\(f_{d}\)). This metric reflects how often the participants disengaged from the task. As Equation (1) shows, it is obtained as the number of distraction events divided by the total interaction time:  
\[f_{d}=\frac{N_{d}}{T_{i}} \tag{1}\]  
where \(N_{d}\) is the total number of distractions and \(T_{i}\) is the total interaction time (in seconds). Then, we also defined the _distraction duration ratio_ (\(\rho_{d}\)). This metric quantifies the proportion of the session during which the participants were not paying attention to the robot or the game. It is computed as the total distraction time divided by the total interaction time, as shown by Equation (2):  
\[\rho_{d}=\frac{T_{d}}{T_{i}} \tag{2}\]  
where \(T_{d}\) is the total time spent distracted (in seconds), and \(T_{i}\), is again the total interaction time (also in seconds).
# Low-Cost RSAC and Adsorption Characteristics in the Removal of Copper Ions from Wastewater
## 2 Materials and Methods
### Determination of Copper Ion Concentration  
#### 2.2.1 Measurement Methods  
The method used for the determination of copper ion concentration was the bisglyoxal oxaldihydrazone spectrophotometric method (GB/T 5750.6-2006). The measurement instrument used was a 752 UV-Vis spectrophotometer, which had a minimum detection mass concentration of 0.04 mg/L. At pH 9, copper ions (Cu\({}^{2+}\)) could react with bis (cyclohexanone oxaldihydrazone) and acetaldehyde. The reaction product is a purple bis (acetaldehyde oxaldihydrazone) chelate, and the copper ion concentration is determined by the relationship between absorbance and copper ion concentration in direct proportion.  
Figure 1: Comparison of adsorption effect of different groups of adsorbents.  
Figure 2: Experimental RSAC pellet fabrication process.
## 3 Proposed MISAO
### Results Comparisons and Analysis of CEC2017 Benchmark Functions
#### 3.4.1 Effectiveness Validation of Different Components
It achieved the highest mean fitness and standard deviation in 22 out of 30 test instances. The MISAO-5 method fared the best in four cases, followed by MISAO-2 in three cases and MISAO-6 in one case. Based on the final Friedman mean ranked values, including MISAO variants in each strategy, a notable enhancement in the overall optimization performance was achieved compared to the original SAO. However, these variants still lacked a certain level of robustness. The order of the contributing effect of each strategy was as follows: random follower search > Gaussian diffusion > cyclic chaotic mapping initialization. For single-peaked functions F1 and F3, except MISAO, the solution of MISAO-5 is the closest to the theoretical value. This suggests that the cyclic chaotic mapping initialization strategy and the random follower search strategy contribute to improving SAO's local search capability. For the multi-peak functions (F4-F10), combining the cyclic chaotic mapping initialization strategy and the stochastic follower search strategy remains effective in overcoming local optimal stagnation. Furthermore, incorporating the specifically developed Gaussian diffusion method also enhances the algorithm's search depth to a certain degree, increasing the likelihood of finding the global optimum. MISAO-2 has superior performance on F14, F18, and F22 among the hybrid and combinatorial functions (F11-F30). Similarly, MISAO-5 beats the other benchmark functions, specifically on F17 and F27. Overall, MISAO demonstrates better performance than the other benchmark functions. These findings demonstrate that the enhanced approach outlined in this study can effectively reconcile the benefits and drawbacks. The significance of the stochastic follower search approach in complex optimization tasks cannot be overstated. Maintaining a balance between exploring new possibilities and using existing resources is crucial. Simultaneously, the utilization of the cyclic chaotic mapping initialization approach and the Gaussian diffusion technique both improve the overall exploration of the system and broaden the range of the search. The individual effect of a single technique may not be readily apparent, but the combined application of these three strategies has a substantial impact on enhancing the overall performance of SAO.
# Ontology-Based System for Dynamic Risk Management in Administrative Domains
## 6 Conclusions  
The research work presented within this document details a solution to the problem of obtaining the level of risk in an administrative domain in real-time. As the main result, this research provides a system architecture ready to infer in real-time security risk metrics for environments with a diffuse definition of assets. To solve this, the operation domains have been modeled by using an organic definition of assets, dividing them into citizens, companies, and university and research organizations, and characterizing them with attributes, e.g., knowledge about cybersecurity, impact over the administrative domain, and the adoption and impact of each type of device. In order to correlate the threats detected with assets, groups of devices have been defined, e.g., mobiles, personal computers, and IoT devices.  
By using ontologies and SWRL rules, the system can process the relationship between assets, threats, and both. That means, for example, if the system processes a threat event that affects Android, the semantic reasoner can infer all assets related to a mobile phone with this operating system will be affected. In addition, the system architecture has been designed to be aware of several information sources about threat events, setting its utility dynamically in terms of the trust of the source.  
To test the viability of the system architecture proposed, a proof of concept based on the development of a prototype has been carried out. This prototype has been validated against tests performed in a real operation environment, the Spanish administrative domain. Although this is a specific case study, the level of abstraction of the proposed metrics allows its application to be applied in any administrative domain, as long as an adequate adaptation of the domain characteristics and asset models is made during the initial configuration process.  
Conceptualization, V.A.V., R.R., and J.B.; methodology, M.V.-B., V.A.V., and F.M.; software, F.M., R.R., and X.L.-N.; validation, M.V.-B., and V.A.V.; investigation, V.A.V., M.V.-B., and F.M.; data curation, F.M., R.R. and X.L.-N.; writing--original draft preparation, F.M., M.V.-B. and V.A.V.; writing--review and editing, M.V.-B. and V.A.V.; supervision, V.A.V., J.B. and M.V.-B.; project administration, V.A.V.; funding acquisition, V.A.V., and J.B.  
This work has been partially funded with the support of the Spanish MINECO (DHARMA project, Dynamic Heterogeneous Threats Risk Management and Assessment, with code TIN2014-59023-C2-2-R) and by the European Commission (FEDER/ERDF).  
The authors are grateful for the support provided by the National Institute of Cybersecurity (INCIBE) in the undertaking of this work.  
The authors declare no conflict of interest.  
Figure 12: Real-time visualization of the global risk of Spain. The current risk is shown in red over a maximum possible in blue.
# Auralization of High-Order Directional Sources from First-Order RIR Measurements
Alternatively to measuring with high-order arrays, we introduced measurements with greatly reduced hardware effort in [21], where first-order source and receiver arrays are employed. The desired higher-order resolution at the receiver is obtained through our Ambisonic spatial decomposition method (ASDM) [22] that is based on [PERSON] et al. [23]. As an extension involving the source side, we propose the SRD ARIR algorithm that assigns a highly resolved direction of departure (DOD) and direction of arrival (DOA) to each sample of the omnidirectional-source-to-omnidirectional-receiver RIR. _Contents_: In this contribution we present the concept and processing steps of a measurement-based auralization for high-order directional sources from hardware-efficient first-order measurements in Section 2. To facilitate an interactive real-time auralization, the source- and receiver-directivities, as well as the SRD ARIR are represented in the Ambisonic domain. The design and implementation of a comparative listening experiment are discussed in Section 3.2. For the sake of reproducibility and generalizability we employed the 20-channel icosahedral loudspeaker array (IKO, [[https://iko.sonible.com/](https://iko.sonible.com/)]([https://iko.sonible.com/](https://iko.sonible.com/))) as a source with well-described controllable directivity [24]. The five measurement-based auralization techniques under test are described in Section 3.1 and include (i) dummy head BRIR rendering as defined in [22], (ii) rendering with MIMO RIRs as defined in [25], (iii) rendering using multi ASDM RIRs (upscaled for each individual IKO transducer), (iv) rendering using the upscaled SRD ARIR and a generic 3 rd order directivity, and (v) rendering using the upscaled SRD ARIR with the real IKO directivity. The underlying measurements were taken in the Gyorgy Ligeti Saal (V = 5630 m\({}^{3}\), \(T_{60}=1.4\) s). A statistical analysis and discussion of the ratings is given in Section 3.3.
# Multi-Modality Cardiovascular Imaging Assessment in Fabry Disease
## 6 Managing Complications
### Arrhythmia  
Arrhythmia is a frequent manifestation in FD, both atrial and ventricular [61]. This is likely due to local myocardial inflammation altering the electrochemical properties of cardiomyocytes and other cell tissue [62]. The presence of left atrial (LA) dilation has been associated with new onset atrial fibrillation (AF) in the general population [63]. Impairment of LA function in the general population may also be a predictor of development of AF and may have a role in risk stratification of stroke in patients with AF [64]. LA reservoir function (expansion during ventricular systole) can be impaired in adults with FD [65] and in a retrospective cohort study of adults with FD, LA function was assessed using speckle-tracking echocardiography and compared to healthy controls. Significantly higher baseline LA dimensions were found in the FD cohort with greater phasic LA volumes and lower LA strain and strain rates. Compared with FD patients on no therapy, significant improvements in LA reservoir function, as well as reduction in LA volume were found in 15 FD patients following ERT (median follow up 355 days) [66]. LA dilatation in FD may be due to higher LV filling pressures as a result of sphingolipid deposition, impaired diastolic relaxation and LVH but may also be due to direct sphingolipid deposition within the LA itself. Reduced peak LA reservoir function was confirmed in a further study of 22 FD adults on speckle-tracking echocardiography. These findings were notable because LA dilatation and impaired LA function correlated with the quantity of white matter lesions on cerebral MRI and high Fazekas score. The exact aetiology of white matter lesions in FD is uncertain but these data raise the possibility that altered atrial size and function may predispose the FD patient to atrial arrhythmia and stroke, in addition to simultaneous sphingolipid accumulation in the heart and brain [67].
# Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images
## 3 Common Attacks
### Vector Quantization Attack  
Vector quantization (VQ) attack [8] is another attack algorithm targeting the semi-fragile watermarking algorithm based on block operation. The prerequisite for this attack is that there is no connection between the watermark information embedded in each image block and the contents of the other blocks. The attacker has to know some message of the watermark and classify every sub-block contained in the watermarked image into the corresponding equivalent class, and then the VQ codebook can be generated, so this attack belongs to the KMA set. Through the VQ attack algorithm, other images without watermarks can be faked into watermarked images. Sometimes, in order to make a forged image have a certain meaning, but also has good quality, attackers need to collect and use multiple images. One effective way to resist this attack is to make the watermark information contained in each image block dependent on it in the other blocks. Assuredly, this method may have some bad effects on the tampering and location ability.