esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### QRS and R-Wave Identification  
Each ECG recording is made up of 12 leads. Due to the sampling frequency, a total of 172 million samples for 48 h of data were analyzed. Each record is stored in ISHNE format. The file header is used to obtain the parameters of the sample rate, resolution, and total size of the record; then, the time vector is calculated. From the annotation file, the indices corresponding to the location of normal heartbeats (code 78 ASCII) and PVCs (code 86 ASCII) were extracted and stored.  
For the processing of the recordings, an ECG lead was selected, giving priority to the one in which the R-wave of the QRS complex presents the greatest positive deflection. The chosen lead in 78.4% (40 records) of the cases was V6, and the rest was DII. The analysis was carried out in one-hour blocks, composed of 3.6 million samples and segmented into blocks of 5 min made up of 300,000 samples, with an overlap of 0.77 min. As a result, 14 blocks that cover the entire record of one hour were obtained.  
The validation of the algorithm, designed to identify the R-wave in the ECG, was carried out using performance metrics such as the positive predictive value (PPV), sensitivity, and F-score (precision measure for the test). The hour with the highest heart rate from the 48 h ECG recording was selected for this validation since this period represents the greatest challenge for the algorithm due to the presence of various artifacts, especially those of mechanical origin.  
For the identification of the QRS complex, the process began with a preprocessing stage, in which a bandpass filter with cut-off frequencies between 0.5 Hz and 30 Hz was applied. Next, to isolate and highlight the QRS complexes the discrete wavelet transform (DWT) was applied. In this step, the previously filtered ECG signal was broken down into multiple levels of resolution using the mother wavelet order 4 Daubechies (db4). The DWT divides the signal into two types of coefficients: approximation coefficients anddetail coefficients; the latter captures the high-frequency components associated with QRS complexes. To focus specifically on these, the signal using the level 2 detail coefficients was reconstructed.  
In the final stage of the algorithm, the detection of the R-wave peaks in the reconstructed signal emphasizing the QRS complexes was carried out. This process included three steps: first, an adaptive threshold was calculated based on the standard deviation of the reconstructed signal, multiplied by a factor of 0.9, which allows small peaks or residual noise to be ruled out. Next, the peaks that exceed this threshold were identified, and finally, a minimum distance between peaks of 500 samples (equivalent to 0.5 s for a sampling rate of 1000 Hz) was established, which avoids the detection of multiple peaks within the same QRS complex, thus obtaining the locations of the peaks of the R-wave.
# Inter-Annual Variability of Peatland Vegetation Captured Using Phenocam- and UAV Imagery
## 3 Results
### Monitoring Vegetation Phenology
#### 3.2.4 Sensitivity of the Phenological Datasets to Drought  
Changes in greenness captured by UAV surveys in 2021 were examined over two dry spells. The first of these dry spells, 'Dryspell-1', occurred during green-up, extending from DOY 158-193; and the second, 'Dryspell-2', occurred during the peak growing season from DOY 200-223 (see Figure 7). We identified differences in: (i) the sensitivity of the various UAV-derived VIs; and (ii) the species-level response to the dry conditions.  
As shown in Figure 8, for Dryspell-1 no reduction in greenness for any species was apparent when examining the VIs gNDVI and reNDVI2 (Figure 8, upper row). In contrast, we observed a substantial reduction in greenness for the VIs REChl and reNDVI1. For these indices, the maximum observed reduction in greenness for individual species was ca. 13% of their seasonal cycle, except for _M. caerulea_ which displayed a slight greening throughout the dry spell. In contrast, during Dryspell-2 all indices displayed more sensitivity to drought, with a reduction in greenness observed in all cases except for _M. caerulea_ and _Vacinium_ spp. when using the gNDVI (Figure 8, bottom row). For the indices REChl and reNDVI1, reductions in the greenness of pixels containing _J. effusus_, _P. schreberi_, and _C. vulgaris_ were substantial (ca. 40% of their seasonal amplitude). In contrast, gNDVI and reNDVI2 were less sensitive, with maximum reductions in greenness observed for pixels dominated by _Sphagnum_ spp. (ca. 9% and 15% of seasonal amplitude for the gNDVI and reNDVI2, respectively).  
Figure 7: Time-series of species-level reNDVI1 over the growing season from the UAV surveys conducted in 2021. Shown are dry spells (yellow shaded areas), daily GPP90 from the EC data (grey), and reNDVI1 for each of the dominant species in the survey area (coloured lines and markers).
## 4 Calibration Methodology
### Modelica Models  
Modelica models are developed with components from the LBNL Modelica Buildings Library [29]. While one of the strengths of EnergyPlus is the ease at which large and realistic envelope models can be built, Modelica models with large and complex envelopes are harder to design: The strength of Modelica is the realism and flexibility at disposal for modeling and controlling technical systems like HPs, storage tanks, and AHUs. This is the reason why the currently included models come with very simple envelopes, but complex and realistic technical systems, the other case being covered by the EnergyPlus models at disposal. Future Modelica models with more complex envelopes are in preparation and will be integrated to the library. The authors also do not exclude incorporating models using Modelica for the control systems and Energyplus envelopes.  
The envelope model used for SimpleHouse and SwissHouse is a simple first order model calibrated with the thermal peak power, minimum outdoor temperatures and the building free oscillation time constant. The indoor temperature is averaged over the house geometry and modeled by a scalar \(T(t)\) obeying Equation (8).  
\[C\frac{dT}{dt}(t)=Q_{\text{flow}}(t)-G(T(t)-T_{out}(t)) \tag{8}\]  
Figure 1: Residuals from the Heat Pump (HP) calibration.  
Assuming equilibrium at very cold temperatures, the thermal conductance \(G\) [W/K] is deduced by setting the left-hand side equal to zero in these conditions. \(G\) [W/K] is then inferred to be equal to the ratio of the thermal peak power over the indoor-outdoor temperature difference for the four coldest consecutive days on the last 20 years (see SIA norm CT 2028:2010 [30]). Knowing the thermal conductance \(G\) and inferring the time constant \(\tau\) of the envelope from the available building data, we derive the heat capacity \(C\) [J/K] = \(G\tau\).  
For SwissHouse models, these \(G\) and \(C\) correspond to an overall U-value of 0.5 [W/m\({}^{2}\)K] and to a heat capacity per surface unit of 0.2 [M]/m\({}^{2}\)K], resulting in a time constant \(\tau\) of \(>\)4 days, for this type of low energy building with a heat demand of 15 [W/m\({}^{2}\)]. For air-to-water HP, the typical seasonal coefficient of performance (COP) is 3, which gives a nominal electric power of 5 [W/m\({}^{2}\)].
## 3 Experimental Results and Discussion
### The Cracking Load and Ultimate Load  
Figure 11 shows the cracking load of each test beam. As is shown in Figure 11, the cracking load of pre-cracked test beams decreased in different degrees compared with the WS beam, which is mainly due to the stress concentration effect at the prefabricated crack. For example, the cracking loads of beams ZSS1, ZSS2 and ZSS3 are 40 kN, 60 kN and 55 kN respectively, which decrease by 52.9%, 29.4% and 35.3%, respectively, compared with the WS beam (cracking load is 85 kN). The cracking loads of beams DSS1, DSS2 and DSS3 are 30 kN, 70 kN and 70 kN, respectively, which are reduced by 64.7%, 17.6% and  
Figure 10: Strain distribution at mid-span section. (**a**) WS beam; (**b**) ZSS1 beam; (**c**) ZSS2 beam; (**d**) DSS2 beam; (**e**) DSS3 beam.  
17.6%, respectively, compared with the WS beam. This is mainly because of the spatial heterogeneity of the concrete aggregate, and there are several weak points in the test beam. Cracks form easily in the weak positions under the action of the load.  
Figure 12 shows the ultimate load of each test beam. As Figure 12 shows, the ultimate load of the pre-cracked test beams decreased in different degrees, compared with the WS beam. For example, the ultimate loads of beams ZSS1, ZSS2 and ZSS3 are 351.1 kN, 322.1 kN and 346.1 kN, respectively, which decrease by 13.4%, 20.5% and 14.6%, respectively, compared with the WS beam (the ultimate load is 405.2 kN). The results show that the prefabricated crack in the mid-span has significant impact on the bearing capacity of the test beam. The deeper the prefabricated crack height, the greater the reduction in the bearing capacity. For example, the depth of the prefabricated crack in the ZSS2 beam is 60 mm, and its ultimate bearing capacity is 322.1 kN, which is 29 kN lower than that of the ZSS1 beam with a 20 mm pre-cracked depth. Compared with the WS beam, the bearing capacity of the pre-cracked test beam at \(l/4\) position also decreased, to varying degrees. The ultimate bearing capacity did not decrease significantly when the crack depth was small (20 mm). Because the test adopts a three-point bending load, the failure mode of the test beam is that the main crack forms at the mid-span, and the roof concrete is crushed near the loading point. Therefore, the overall change in the law of stiffness and bearing-capacity degradation caused by the prefabricated crack at the \(l/4\) position is consistent with that of the test beam at mid-span.
## 4 Vehicle Dynamics Model
### Half-Car Dynamics Model  
In practical scenarios, the real vehicle influence of wheel base or track on vehicle system can be neglected under some special conditions. In this study, the effect of the vehicle's unsprung mass on roll dynamics is not neglected [15]. To obtain a functional relationship between road excitation and roll dynamics model, a half-car model is first presented, as shown in Figure 5. This model is a combination of a traditional 2-DOF bicycle model and a 4-DOF roll dynamics model used to describe yaw, lateral motion, and roll motion.  
It should be noted that left and right steering angles in general would be approximately equal [17]. Symbols used in Figure 5 are listed in Table 2. Parameters in Table 2 are from the \(\text{CARSIM}^{\otimes}\) (E-Class, SUV). Here, lateral load transfer is considered for every wheel.  
The half-car dynamics model is constructed based on the following assumptions [17; 18].  
1. Distance between two axes compared to turning radius was relative small, and steering wheel angle satisfies the following relationship: \(\text{sin}\delta_{f}=\delta_{f}\), \(\cos\delta_{f}=1\).
2. Longitudinal effect of road profile was ignored.  
Figure 4: Roll behavior of vehicle system.  
Figure 5: Half-car roll dynamics model.  
There is no slip between the tires and road surface, and influence of ground longitudinal force on cornering characteristics of the tires was not considered.
* The effect of the steering system was excluded, and front wheel angle was directly used as input.
* The effect of air force was ignored.
* Suspension elastic deformation steering and change of steering wheel alignment parameters were ignored.
* The influence of bearing-free gap and lubricant membrane was ignored, and the bearing was taken as an equivalent spring-damper system in the vertical direction.
# Analysis of Security Issues and Countermeasures for the Industrial Internet of Things
## 3 Security Issues in IIoT Systems
### Security Issue 12--Anonymity  
IIoT devices can transmit beacons that can be collected by a server and generate information of real-time activities, e.g., the device's physical locations, and different activities in a certain time frame performing locally or remotely [115]. Moreover, an IIoT device can communicate with another device with real-time notifications using Bluetooth low-power communication techniques to share a range of possible applications and information e.g., traffic information, retail, or shopping information (e.g., Google Physical Web [116]).  
This location-based information is a popular choice for attackers. More specifically, \"the idea is to build a map reflecting on the activities, mobility behavior, and other mobile patterns of an entity using the data gathered from other attacks\" [117]. The location- and tracking-related attacks (sometimes referred to as _inference attacks_) are major concerns in such cases, where a device may wish to keep its information confidential from a group of other devices [118]. With such location-based information, an attacker can take control over a device through device tracking or tag tracking and can be vulnerable to the other devices that are connected to them and sharing real-time information [119].  
Due to the massive scale of IIoT systems, dynamics in interactions, and resource-constrained (e.g., memory and battery) characteristics of the devices, as well as bandwidth-constraints, traditional TCP-based security mechanisms cannot be applied directly to them [47]. Therefore, it is a major challenge for securing access control by rejecting unauthorized data monitoring and unauthorized access [91].  
Anonymity refers to the situation where an entity performs a task but remains anonymous to others [120]. The anonymity in the system must ensure that the attacker can never be able to discover the entity's personal information to breach privacy and pose further privacy-related attacks. For example, an attacker can guess the initiator's information (through tracked stream) in an anonymous connection and, on that basis, modify the communication path to another insecure destination [121]. To ensure a device's or user's anonymity, the system should employ a robust authentication scheme. However, in the case of IIoT, the devices themselves lack insufficient resources (e.g., memory and storage) to run heavy-weight security mechanisms. This further suggests the need for lightweight security mechanisms for the IIoT systems [78; 122].
# Visible Spectrum and Infra-Red Image Matching: A New Method
## 4 Experimental Setup and Results
### Descriptor Matcher  
We use a Brute Force Descriptor Matcher (BFDM) of OpenCV for descriptor matching. BFDM is based on L2 norm (Euclidean distance) and Hamming distance. L2 norm is suitable for SIFT, CS-LBP, GLOH, LIOP, LBPG, LC-SIFT, DE-SIFT, NG-SIFT, MN-SIFT and Reg-SIFT descriptors whereas hamming distance is best for binary descriptors such as BRIEF, ORB, FREAK, and BRISK.
# The Influence of Processing on the Bioactive Compounds of Small Berries
## 5 Health Implications and Allergic Reactions to Small Berries  
The scientifically generally accepted idea is that berry consumption is beneficial to health, mainly because of the high content of bioactive compounds with antioxidant capacity. Nutritional guides recommend a daily intake of approximately 400 g of fruits, including berries, to achieve long-term health benefits [114]. However, according to [PERSON] et al. [115], a lower regular intake of 40 g of cranberries might ensure the management of the postprandial glucose increase.  
The most benefits associated with berry consumption were clinically observed in cancer, cardiovascular diseases, and type 2 diabetes management, and were attributed to phenolic compounds. However, not only polyphenols found in berries have been reported to provide health benefits. For example, in addition to bioactive compounds like polyphenols, carotenoids (mostly zeaxanthin), and vitamin C, goji berries contain water-soluble bioactive polysaccharides (WBPs), which are actually the main constituents of this fruit [116]. These polysaccharides are heterogeneous in terms of their monosaccharide composition, consisting mainly of galacturonic acid, galactose, arabinose, and glucose [117], being recognized for many therapeutic properties. WBPs are recognized for many therapeutic properties, such as antioxidant, immuno-protective, and cancer cell growth-inhibitory properties. WBPs are responsible for inducing apoptosis of human breast cancer MCF-7 cells through DNA damage and intracellular oxidative stress [117]. Moreover, the overall improvement of the digestive tract functionality, sleep quality, and well-being were also associated with WBP-rich berry consumption [117]. Besides polyphenic content, sea buckthorn fruits were found to contain phytochemicals like cerebrosides and oleanolic and unsolic acids [118], known for hepatoprotective, antitumor, and antiviral properties [119]. Correlian cherries contain iridoids, a group of plant glycosides produced as a defense mechanism against herbivores (as they have a bitter taste), with anti-inflammatory properties [120]. Cornelian cherry extracts are therefore acknowledged for their protective effects on many organ cells, like liver, brain, heart, and kidney cells [120]. Overall, regardless of the mechanism involved and health status, berries have to be included in the everyday diet for beneficial, protective, and preventive action against diseases.
## 2 Results and Discussion
### Toxin \(\zeta\)Hydrolyses ATP in the Presence of UNAG
Samples containing 2 mM UNAG and increasing concentrations of ATP (0.5, 5 and 10 mM (with a fixed concentration of \(\alpha^{32}\)P-ATP, 10 nM), lanes 2–4) or 2 mM UNAG and a fixed concentration of ATP (0.5 mM [\(\alpha^{32}\)P-ATP, 10 nM]) and increasing GTP concentrations (1.25, 2.5, 5, 7.5 and 10 mM, lanes 5–9) were incubated with 0.5 \(\upmu\)M \(\zeta\) toxin for 30 min at 30 \({}^{\circ}\)C in buffer B. ATP hydrolysis was analyzed by thin-layer chromatography (TLC) performed on polyethyleneimine-cellulose plates with 0.85 M KH\({}_{2}\)PO\({}_{4}\) (pH 3.4) as the mobile phase, followed by autoradiography. (free of \(\varepsilon_{2}\) antitoxin) would also transfer the P\({}_{i}\) to form UNAG-3P, but it remains to be shown whether the 3'-OH group of the sugar moiety of UNAG is the only target of the phosphorylation reaction. To verify the structurally suggested preference for ATP _vs._ GTP (as reported for other phosphotransferases) as substrate, we performed competition experiments. Here, \(\zeta\) toxin was incubated with increasing ATP or GTP concentrations containing a fixed amount of ATP (0.5 mM ATP containing [\(\alpha\)-\({}^{32}\)P]-ATP 10 nM) and UNAG (2 mM). Toxin \(\zeta\) can hydrolyze ATP with similar efficiency in the presence of a 2.5-fold excess of GTP (Figure 1, lane 5). GTP:ATP ratios of 5:1 to 10:1, marginally decreased \(\zeta\)-mediated [\(\alpha\)\({}^{32}\)P]-ATP hydrolysis (Figure 1, lanes 6 and 7). At GTP:ATP ratios of 15:1 and 20.5:1, \(\sim\)37 and \(\sim\)46% of [\(\alpha\)\({}^{32}\)P]-ATP was not converted to [\(\alpha\)\({}^{32}\)P]-ADP, respectively (Figure 1, lanes 8 and 9). It is likely therefore that: (I) \(\zeta\) toxin is preferentially a UNAG-dependent ATPase; (II) the phosphotransfer reaction might not simply be a one-step coupled reaction; and (III) \(\zeta\) toxin preferentially hydrolyzed ATP-Mg\({}^{2^{+}}\) over GTP-Mg\({}^{2^{+}}\) in the presence of UNAG.
# Hyperspectral Image Super-Resolution Based on Spatial Group Sparsity Regularization Unmixing
###### Abstract  
A hyperspectral image (HSI) contains many narrow spectral channels, thus containing efficient information in the spectral domain. However, high spectral resolution usually leads to lower spatial resolution as a result of the limitations of sensors. Hyperspectral super-resolution aims to fuse a low spatial resolution HSI with a conventional high spatial resolution image, producing an HSI with high resolution in both the spectral and spatial dimensions. In this paper, we propose a spatial group sparsity regularization unmixing-based method for hyperspectral super-resolution. The hyperspectral image (HSI) is pre-clustered using an improved Simple Linear Iterative Clustering (SLIC) superpixel algorithm to make full use of the spatial information. A robust sparse hyperspectral unmixing method is then used to unmix the input images. Then, the endmembers extracted from the HSI and the abundances extracted from the conventional image are fused. This ensures that the method makes full use of the spatial structure and the spectra of the images. The proposed method is compared with several related methods on public HSI data sets. The results demonstrate that the proposed method has superior performance when compared to the existing state-of-the-art.  
hyperspectral imaging; super-resolution; image fusion; hyperspectral unmixing; group sparsity +
Footnote †: journal: Applied Sciences
###### Abstract
Study [25] summarizes the application of speech technology in education, emphasizing the importance of acoustic features in intelligent assessment. The authors of [26] investigate improved methods for speech recognition technology in multilingual contexts, indicating that the refined analysis of formant features contributes to enhancing the accuracy of speech recognition. These studies provide important references for the objectives of this research. Despite the numerous achievements made by scholars in China and abroad in the classification of vowels produced by Mandarin learners, existing research still has some limitations. Firstly, there is a lack of systematic studies on learners at different proficiency levels, particularly the in-depth exploration of pronunciation level stratification assessment based on formant features. Secondly, the application of machine learning algorithms in vowel classification mainly focuses on single algorithms, lacking comparative analysis of multiple algorithms. Moreover, existing research rarely combines acoustic features with machine learning algorithms to explore their practical application value in computer-assisted language teaching. By combining SVM and ID3 algorithm [27], this study conducts a systematic analysis of vowel classification for Mandarin learners at different proficiency levels, aiming to validate the effectiveness of formant features in vowel classification and compare the performance differences in various algorithms. This study further investigates the pronunciation characteristics of learners at different levels and their application value in teaching, providing new theoretical foundations and methodological references for Mandarin teaching and pronunciation evaluation. The research findings not only contribute to promoting the development of computer-assisted language teaching systems but also provide important evidence for enhancing the accuracy of multi-ethnic Mandarin speech recognition.