esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The current study sought to assess the antitumor, anticancer, and antioxidant efficacy of _Ulva lactuca_-mediated selenium nanoparticles by using an in vitro model of human hepatocellular carcinoma (HepG-2 cells) and HAV HM175 strain of hepatitis A virus, with the evaluation of antioxidant activity conducted using DPPH assay. The study showed promising cytotoxicity at the highest concentrations of 250 and 500 ug/mL, with viability rates of 19.43 and 8.75% for cancer cells, and the lowest toxicity with the highest viability rates of 59.41 and 30.64% for normal cells, respectively. These concentrations also exhibited the highest inhibition rates (51.28 and 76.31%, respectively) against the Epidermal Growth Factor Receptor (EGFR) enzyme and provide an explanation of the mechanism of such cytotoxicity, as this enzyme is responsible for the degradation of EGFR. Additionally, _U. lactuca_-mediated selenium nanoparticles (USeNPs) showed promising antiviral activity (+++) (50\(\sim\)75%) with EC\({}_{50}\) = 57.41 ug/mL and 74.13% antiviral rates against HAV HM175 at 100 ug/mL maximum noncytotoxic conc (MNCC). Using MTT assay, its selectivity index was 5.78 \(\geq\) 2, which indicates that USeNPs exhibited antiviral activity that outweighed its toxicity. Therefore, USeNPs is an active antiviral agent and warrants further study. Furthermore, the DPPH scavenging activity of such nanoparticles was moderate as the highest sample concentration (100 ug/mL) recorded 31.64 \(\pm\) 0.03% DPPH scavenging activity (with IC\({}_{50}\) = 158.02 \(\pm\) 0.07 ug/mL), a percentage which does not exceed that of standard ascorbic acid.  
Keywords:anti-HAV HM175; antioxidant DPPH; antiviral; EGFR; epidermal growth factor receptor; HepGG2; MTT assay; selenium nanoparticles; _Ulva lactuca_
## 3 Numerical Simulation and Verification
### Method Comparison and Factor Analysis
The CSAFT and DAS method are also compared for different angular steps, which are integral multiples of the minimum angular step 0.5\({}^{\circ}\). The numbers of the receiving signals for different angular steps are listed in Table 2.  
The effect of the excitation signals with different cycles is also studied and the results by the CSAFT method marked with the defect positions and angular bandwidths are shown in Figure 12. It can be observed that the widths of the defects along the radius and the angular bandwidths increase with the increment of the cycles. The defect localization accuracy decreases as well. The increment of the signal cycle is conducive to raising the energy of the incident waves for long testing ranges and narrow down the frequency bandwidth to reduce the influence of other frequencies. However, it extends the lengths of the excitation signals in the time domain, which determine the sizes of the focused defect spots. Both resolutions along the angle and radius are decreased. The cycles of the excitation signals should be selected in the consideration of both resolutions and testing ranges in field tests. The calculation time of the CSAFT and DAS methods are tested with the same number of the signals in the same computer. As in Figure 10b, the calculation time of the CSAFT method is much less than that of the DAS method, which increases linearly with the numbers of the signals. The advantage of the proposed method in calculation efficiency can be more significant when dealing with a larger amount of data. The images by three methods for different angular steps are presented in Figures 9 and 11. Since the angular sampling rate decreases with the increment of the angular step, the defect spots are coarser in the results of the Bscan and CSAFT method. In the results by the DAS method, over-adjustments get more severe with larger trailing in the image, which may become distractions in defect recognition. The proposed CSAFT method provides the best performance for each angular step. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Name** & \multicolumn{4}{c}{**Value**} \\ \hline Angular step (\({}^{\circ}\)) & 0.5 & 1 & 1.5 & 2 \\ Number of the signals & 91 & 46 & 31 & 23 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The numbers of the receiving signals for different angular steps.
## 4 Optimizing the Node Structure
### Reusing Intermediate Results  
In information-bottleneck decoders, the actual decoding simplifies to look-up operations in the offline-generated tables. To compute an outgoing message, all incoming messages, except for the one received over the edge connected to the node we generate the outgoing message for, are considered. Hence, all outgoing messages are computed using a slightly different input vector \(\mathbf{y}\). However, parts of the input vector do not change for several outgoing messages. Thus, the total number of look-up operations per node can be reduced by the reuse of intermediate results.  
Assuming a sequential node structure, we note that for example if only \(y_{M}\) is changed, all \(t_{i}\) for \(i=0,\ldots,M-2\) previous results could be reused. Thus, the number of total operations for all outgoing edges for a node with \(M\) incoming messages can be found as  
\[(M+1)\cdot(M-1)-\sum_{i=1}^{M-2}i=\frac{(M-1)(M+4)}{2}.\]  
By exploiting the proposed tree structure, the number of look-up operations per node can be reduced even further compared to the sequential approach. The actual reuse potential depends largely on the internal structure of the tree. However, in the worst case, \(\mathcal{O}(M\lfloor\log_{2}M\rfloor)\) operations per node are required. In the next section, the achievable gains in terms of latency and memory efficiency are investigated.
# Lessons for Data-Driven Modelling from Harmonics in the Norwegian Grid
## 2 Methodology
### Data Origin  
SINTEF has conditional access to power quality data for the majority of the Norwegian power system through agreements with distribution system operators (DSOs) and the Norwegian transmission system operator (TSO) Statnett. The data cover the period from January 2009 to early March 2020. The nominal line voltages at the locations where the measuring instruments are installed varies from 10 to 420 kV. A total of roughly 270 years of PQ data have been collected from 49 measurement nodes, giving on average 5-6 years of historical data from each node. However, the number of years of available data varied significantly from node to node.  
In this work, we focus on three sites as full coverage of the available data would either: (i) require a different analytical approach; or (ii) clutter the presentation needlessly. The three sites were chosen to have different voltage levels, are placed in different locations in the Norwegian power grid and have long and robust time series. In conjunction, these sites constitute the basis for the below analysis and discussion.  
All sites are located in the Norwegian grid so they are exposed to the Norwegian power mix, barring bottlenecks between price zones. The power mix is dominated by power from hydroelectric plants (85%), followed by biomass (12%) and wind (4%) ((data from 2018).
# Hybrid Edge-Cloud-Based Smart System for Chatter Suppression in Train Wheel Repair
## 7 Conclusions  
A hybrid edge-cloud-based smart system for chatter detection and suppression in a specific operation of freight train wheelset repro profiling was developed. The system relies on an embedded accelerometer to detect chatter and uses a smart algorithm to select the most appropriate action in accordance with the measured signal. Thus, the process stability is assured. The data recorded by the sensor as well as the actions taken for every wheelset can be surveyed using the cloud-based monitoring system, which is connected to the machine PLC and to the process controller. This provides very useful information for follow-up and the traceability of the production system.  
The system was validated using a portal lathe in an industrial environment. The results were very satisfactory, achieving a proper automatic machining performance optimization.  
The developed system is an ad hoc utility for a specific industrial problem which has been previously characterized. The future challenge is to extend its application to different machining processes in which the actuation criteria can be determined automatically by the smart system itself, based on a thorough historical data analysis of the gathered information from previous events in a machine learning approach.  
Conceptualization and Supervision, J.M.; Investigation and Validation R.M. and I.B.; Review and editing, A.I.  
This work was partially supported by the ASTRACOMP Project (EXP-00102217) from the Innoglobal program of the Spanish Ministry of Economy, Industry and Competitiveness.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sequence** & **Status** & **Severity (mm/s rms)** & **Action** \\ \hline I & STABLE & Lower than 2.5 & Normal operation \\ II & ALARM & Higher than 4 & Spindle speed 80\% + CSSV are activated \\ III & STABLE & Lower than 2.5 & Spindle speed 80\% + CSSV remain on \\ IV & RESET & Lower than 2.5 & Resetting point. Normal operation. \\ V & WARNING & Between 2.5–4 & Spindle speed 80\% is activated \\ VI & STABLE & Lower than 2.5 & Spindle speed 80\% remains on \\ \hline \hline \end{tabular}
\end{table}
Table 4: Algorithm action sequence.
###### Abstract  
The broad applications of sapphire substrates in many fields warrants an urgent demand for a highly efficient and high precision polishing method for the sapphire substrates. The authors proposed a novel sapphire substrate polishing method that is based on the dielectrophoresis (DEP) effect. The principle of dielectrophoresis polishing (DEPP) is described. A non-uniform electric field was added in the polishing area to drive abrasives moving in the direction towards the plate by the DEP force. The amount of abrasives that participates in the polishing action increases as the distribution of polishing slurry on sapphire surface changes, leading towards the improvement of sapphire polishing both in quality and efficiency. Comparative experiments between DEPP and traditional chemical mechanical polishing (CMP) were carried out. It was found that the maximum increase of sapphire MRR for DEPP is 71%, reaching 13 mg/h, and the minimum increase was 9.5%, reaching 4.6 mg/h. The surface roughness of the sapphire substrate decreases faster and more uniform with DEPP. The final surface roughness of the sapphire substrate after DEPP was \(R_{\text{a}}\) 0.87 nm and the flatness was 0.3078 waves (RMS value), which is better than 0.6863 waves (RMS value) of sapphire substrate with traditional CMP polishing.  
dielectrophoresis (DEPP); polishing; sapphire substrate; material removal rate; surface roughness; flatness 2019  
3
## 4 Resource Management and Energy Efficiency  
Limited on-board energy is one of the major limitations that hinders the potency of a UAV system. However, consideration of two important factors, i.e., energy-efficient deployment and energy-efficient operations, can pave ways for resolution. Energy-efficient deployment means interruption-less utilization of power reserves. Energy-efficient operations stipulate measures aimed at achieving the objectives with minimal on-board power. One way to achieve energy-aware deployment is to harness inter-UAV cooperation such that, at any given time, only one UAV can abandon its mission to top up its power reserves [32]. In the literature, the topic of energy efficiency and resource management has been consulted from various angles. For instance, in [33], the authors propose an analytical framework aimed at finding the optimal trajectory, which can minimize the energy consumption of a fixed-wing UAV. Energy efficiency is addressed by a scheduling framework for cooperative UAVs communication in [34]. In [35], the authors studied the energy efficiency of drones in target tracking scenarios by adjusting the number of active drones. Besides, a drone-assisted strategy is proposed in [36], which entails harnessing LoRaWAN architecture and the smart deployment of drones for energy conservation. In [37], an energy-efficient system is proposed for the drones to collect sensor data. The issues of data dissemination and energy conservation are addressed by a firefly optimization algorithm. Supported by acceptable modelling, simulation, and numerical results, a self-adaptive energy-efficient operation in UAV-assisted public safety networks is suggested in [38]. The authors in [39] investigated, for small UAVs, energy harvesting from vibrations and solar sources. Optimization of transmission time in a user-UAV communication set-up is proposed in [40]. This resulted in the maximization of the user's minimum throughput. Utilization of an antenna array on UAVs is investigated in [41] in order to improve SNR and reduce transmission power. A flying access point equipped with an energy harvesting mechanism is investigated in [42] with the objective of optimal resource allocation. UAVs servicing ground users face bandwidth and flight-time optimization problems, which is addressed in [43]. A resource allocation framework is proposed in [44] that enables cache-enabled UAVs to effectively service users over licensed and unlicensed bands.  
Undoubtedly, the area of energy efficiency and resource management demand insightful consideration since it affects the performance of FANET systems in terms of throughput and end-to-end delay.
# Automated Dataset-Creation and Evaluation Pipeline for NER in Russian Literary Heritage
## 2 Related Work
### Language-Specific NER Dataset Creation  
A commonly used method for creating datasets in other languages involves translating existing datasets from English into the target language. This approach is discussed in [5,22]. However, one significant challenge for some languages is the imbalance in training sample sizes across classes, often due to the lack of annotated texts. This issue is highlighted in [23],where the authors explored methods to balance training samples and expand datasets through part-of-speech (POS) analysis. The primary objective was to enhance overall accuracy by mitigating class imbalance.  
Many datasets have been collected for building an NER for the Russian language (see Table 1). In ref. [24], the authors provided a dataset for Russian NER for general purposes. The corpus was collected from the top 10 \"Business\" feeds on Yandex News. They randomly selected 10 news items for a given day while making sure that the depicted data were removed. After removing titles and HTML elements, the final corpus has 97 documents with source URLs preserved as metadata. Only two types of entities were annotated in the dataset (person and organization) and IOB (inside-outside-beginning) tagging was used for annotating. The dataset is not publicly available (it is only for academic purposes), and there is a copyright to use it. The FactRuEval [25] corpus was created to provide a dataset of Russian texts for building, evaluating, and testing an NER. Russian newswire and analytical essays on social and political problems make up the FactRuEval corpus. The texts were extracted from Private Correspondent and Wikinews. The dataset was annotated by the models that covered the main tasks in the competition held for this purpose. The final corpus consists of 255 documents annotated with the following tags (person, organization, and location). The dataset is publicly available for usage and development. The NEREL [26] corpus was collected for NER and RE in Russian texts. The majority of the corpus is made up of Russian Wikinews articles that have been released under a Creative Commons license, which permits repurposing of the content. There are 49 relation types and 29 entity types in the NEREL dataset. The collection includes 39K relations and 56K entities annotated in more than 900 Russian Wikinews articles. The dataset is publicly available for common use. In ref. [27], the authors provided an approach for preparing data for multilingual Named Entity Recognition. The WikiNEuRal dataset contains annotated data extracted from Wikipedia articles for nine languages (Russian is one of them). They focused on providing entities for (PER, LOC, ORG, and MISC). The WikiNEuRal_RU dataset contains more than 2 million tokens extracted from 105k articles. An approach for automatic creation of NER systems is also presented in [8]. It utilizes the Open information-extraction system combined with mapper to automatically annotate dataset.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
## 3 Results and Discussion
### Volatile Compounds Analyzed by HS-SPME-GC-MS  
The volatile profiles of the four rose beverage samples (UFR, LFR, SFR, and LSFR) were analyzed using HS-SPME coupled with GC-MS. A total of 245 volatile compounds were identified and classified into various chemical groups: 52 alcohols, 27 esters, 19 ketones, 21 aldehydes, 8 phenols, 15 benzene compounds, 7 acids, 51 terpen, 18 alkanes, 8 ethers, and 19 other compounds. Specifically, 202 compounds were identified in UFR, 223 in LFR, 181 in SFR, and 222 in LSFR. These results demonstrate that fermentation, particularly by lactic acid bacteria, enriched the diversity of volatile substances in the rose beverages, aligning with findings from previous studies [22; 52].  
A Venn diagram was constructed based on the volatile compounds identified in Table S2 (Figure 3A) to visualize the relationships between the four rose beverage samples. The observed differences in volatile compound profiles among the groups are directly attributable to the distinct metabolic activities of the different microbial fermentations. LFR and LSFR shared 214 compounds, while SFR and LSFR shared 164 compounds, indicating a greater similarity between the aroma profile of LSFR and LFR. Each beverage type also contained unique volatile compounds. Only one unique volatile compound was identified in the UFR sample, suggesting that most of the original volatile compounds were altered during fermentation by the single or co-cultures, potentially serving as substrates for biotransformation. In total, 1, 10, and 2 unique compounds were found exclusively in the LFR, SFR, and LSFR samples, respectively, likely arising from the specific metabolic pathways active in each microbial treatment.  
Principal component analysis (PCA), a multivariate statistical technique, was applied to the quantitative data of the 245 volatile compounds to highlight the differences among the samples [53]. The PCA score plot (Figure 3B) effectively separated the four rose beverage samples based on the first two principal components (PC1 and PC2), which accounted for 76.3% and 17.7% of the total variance, respectively, with a cumulative contribution of 94%. The separation between the sample groups was more pronounced than the variation within each group, indicating that the different microbial fermentations had a significant impact on the volatile metabolome of the functional rose beverages. The unfermented rose beverage (UFR) showed the largest deviation from the other samples, highlighting the substantial changes in volatile compounds induced by fermentation. The greater overlap between the LSFR and LFR groups compared to the overlap between LSFR and SFR suggests that _L. plantarum_ exerted a more dominant influence on the volatile flavor substances compared to _S. cerevisiae_ in the co-fermentation.
###### Abstract  
Electric machines with hybrid excitation have increased torque density while maintaining a wide range of speed control. This article presents the results of the optimal design of a synchronous homopolar generator (SHG) with ferrite magnets on the rotor and excitation winding on the stator for passenger cars. The use of ferrite magnets on the rotor of a synchronous homopolar generator makes it possible to use the stator surface more efficiently, which in turn increases energy efficiency and reduces the dimensions of the generator. At the same time, the excitation winding on the stator provides a reliable brushless design and the ability to control the excitation flux. The problem of long-time calculation of the three-dimensional SHG structure, which is especially relevant when using multi-iterative computer optimization, is solved by using the computationally efficient Nelder-Mead method and a simplified SHG model using two-dimensional finite element analysis. It is also clear that the low torque ripple of SHG with ferrite magnets with two stator-rotor stack combinations (SRSC) is largely provided by the fact that the torque ripples of individual SRSCs are in antiphase. The problem of considering the magnetic properties of magnetic core sections made of structural low-carbon steel is discussed. It has been found that with an increase in both the saturation level of the magnetic circuit and the magnetomotive force (MMF) of the SHG excitation winding, resistance to irreversible demagnetization of ferrite magnets on the rotor can be increased by increasing their height. In addition, it is shown that there is a significant increase in performance when using the hybrid excitation, in comparison with the conventional SHG design without magnets.  
brushless; design optimization; electric machine; ferrite magnets; hybrid excitation; Nelder-Mead method; passenger car generator; synchronous homopolar generator; synchronous homopolar machine; wound field machines +
Footnote †: journal: Applied  
Acticle Analysis of Performance Improvement of Passenger Car Synchronous Homopolar Generator with the Addition of Ferrite Magnets
###### Abstract  
The normality polynomial and multi-linear regression approaches are revisited for estimating the reliability index, its precision, and other reliability-related values for coastal and structural engineering applications. In previous studies, neither the error in the reliability estimation is mathematically defined nor the adequacy of varying the tolerance is investigated. This is addressed in the present study. First, sets of given numbers of Monte Carlo simulations are obtained for three limit state functions and probabilities of failure are computed. Then, the normality polynomial approach is applied to each set and mean errors in estimating the reliability index are obtained, together with its associated uncertainty; this is defined mathematically. The data is also used to derive design points and sensitivity factors by multi-linear regression analysis for given tolerances. Results indicate that power laws define the mean error of the reliability index and its standard deviation as a function of the number of simulations for the normality polynomial approach. Results also indicate that the multi-linear regression approach accurately predicts reliability-related values if enough simulations are performed for a given tolerance. It is concluded that the revisited approaches are a valuable option to compute reliability-associated values with reduced simulations, by accepting a quantitative precision level.  
reliability index error; power law; normality polynomial; multi-linear regression; sensitivity factors; coastal engineering; structural engineering 1