esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Determination of Total Phenolic Content  
The total phenolic content (TPC) of each lyophilized extract was determined using the Folin-Ciocalteu method as described by [PERSON] et al. (2014) with slight modifications. 75 mg of each extract was dissolved in 3 mL of water for aqueous extracts or 50% (\(v/v\)) methanol for methanolic extracts. For the assay, 250 \(\mu\)L of the appropriately diluted sample solution and 250 \(\mu\)L of Folin-Ciocalteu reagent (diluted 1:1 (\(v/v\)) in methanol) were mixed by vortexing. After exactly 3 min, 500 \(\mu\)L of 75 g/L sodium carbonate solution and 4 mL of water were added to the mixture, which was then vortexed for an additional 10 min and allowed to stand in darkness for 60 min. The absorbance at 750 nm was measured using a BioTek microplate spectrophotometer (Agilent Technologies, Santa Clara, CA, USA), and the results were quantified using gallic acid as a standard. The total phenolic content was expressed as mg gallic acid equivalent (GAE)/g extract, and the limit of quantification was set at 4.0 mg GAE/g sample.  
Total Antioxidant Capacity by Direct ABTS (2,2'-azino-bis(3-etilbenzotiazoline-6-sulfonic acid) Assay  
The direct measurement of the total antioxidant capacity was performed according to [PERSON] et al. (2015) with slight modifications and adapted to the microplate reader. To produce 2,2'-azino-bis(3-ethylbenzothazoline-6-sulfonic) acid radical cations (ABTS*+), a stock solution of ABTS (7 mmol/L) was reacted with potassium persulfate (2.45 mmol/L) and left to stand in the dark at room temperature for 12-16 h. The resulting ABTS*+ solution was diluted with 50% ethanol to obtain an absorbance of 0.70 \(\pm\) 0.02 at 734 nm. Lyophilized extracts (5 mg) were dissolved in 10 mL of either water or 50% methanol. Next, 200 \(\mu\)L of the sample or Trolox standard was added to 3.8 mL of 50% ethanol and 1 mL of the diluted ABTS*+ solution. After 45 min, the absorbance was read using a BioTek microplate spectrophotometer. Calibration was performed using ethanolic solutions of Trolox with concentrations ranging from 0.08 to 0.25 mmol/L. The total antioxidant capacity was expressed as \(\mu\)mol equivalents of Trolox (TEAC)/g sample, with a limit of quantification of 11 \(\mu\)mol TEAC/g sample.
## 2 Related Works
SACRP considers two classes of cooperative routing protocols: _Class A_ for power minimization or throughput maximization, and _Class B_ for reducing the end-to-end delay. _Class A_ aggregates multiple channels and selects suitable relay nodes, and therefore achieves higher power efficiency and throughput. _Class B_ reduces the number of re-transmissions by selecting the relay nodes with better channel conditions, and therefore reduces the end-to-end delay. However, these schemes have the common limitation that they can not guarantee performance in terms of the users' delay for SA in CR networks.
###### Abstract  
Risers are an indispensable component of offshore oil and gas exploitation structures, and they are vulnerable to vortex-induced vibration (VIV). Although many studies have been conducted to investigate the VIV characteristics of risers, the effects of combination of multiple parameters and the relative significance of each parameter on the risers' VIV characteristics have rarely been considered. In this paper, 36 experimental cases were investigated to study the risers' VIV characteristics due to the combination of multiple parameters. The natural frequencies, response microstrains and frequencies of VIV for the risers were obtained. Meanwhile, the effect of each parameter and the relative significance of these parameters on the amplitude of VIV in risers were calculated using grey relational analysis (GRA). The results show that all the parameters considered--i.e., material property (modulus and density), end condition, top tension force and flow velocity--affect risers' VIV response, and the grey relational grade of these parameters are: \(r_{02(\text{velocity})}>r_{04(\text{constraints})}>r_{05(\text{density})}>r_{03 (\text{tension})}>r_{01(\text{modulus})}\).  
experiment with multiple parameters; grey relational analysis; riser; vortex-induced vibration (VIV) +
Footnote †: journal: Applied Sciences
# Efficient Top-\(k\) Spatial Dataset Search Processing
## 6 The Optimized Search Scheme
### The Ideas of Search Optimization  
The baseline search scheme involves traversing each dataset in the data repository to calculate the similarity to the exemplar dataset. However, certain datasets have distributions that are vastly different from that of the exemplar dataset (for example, the exemplar dataset is located in the Arctic, while some datasets are in the Antarctic), resulting in a similarity score of zero. Therefore, these clearly unrelated datasets can be directly filtered out without any similarity calculation. Based on this observation, we present the ideas of search optimization from two aspects:  
* If we can present a more efficient filtration strategy that requires only linear time to determine whether or not a dataset should be filtered out, then we can filter out parts of the datasets efficiently to reduce the time cost.
* If we can present a more effective filtration strategy that dynamically scales the grid divisions and compares the distribution of points on the same grid for two datasets, then we can filter out parts of the dataset and thus reduce the search time overhead.  
Inspired by the above ideas, we proposed two optimization strategies: GMBR-based optimization strategy and pooling-based optimization strategy, which can accelerate the top-\(k\) spatial dataset search processing.
# Autonomous Robotics for Identification and Management of Invasive Aquatic Plant Species
## 3 Results
### Autonomous Vehicle Performance
#### 3.1.4 Herbicide Dispersal System  
Laboratory testing, completed before lake trials, revealed that the dispersal system could provide moderate application rates of Aquathol-K (1.0-1.8 gal/A-ft) for typical pond depths, boat velocities, and transect widths. Figure 17b shows the range of chemical dispersal rates (Aquathol concentrate) achievable by varying the RC input.  
Figure 16: Tracking performance of a prototype at Lake Raleigh: (**a**) desired and actual trajectories as displayed from Mission Planner software and (**b**) corresponding boat deviations from intended trajectories (180\({}^{\circ}\) turns excluded).  
Functionality of the dispersal system with chemical dilution modality was also demonstrated in Lake Raleigh; water was substituted for the herbicide to avoid unnecessary release of chemicals into the water body. Herbicide application was completed in a small (approximately 0.29 acres) private pond with watermael infestation (Figure 18). Due to the small surface area and volume of the pond, a premixed herbicide/water solution was dispersed directly from the tank and manual control, rather than autonomous navigation, was utilized.  
Figure 17: (**a**) Battery voltage measurements for multiple test runs and (**b**) characterization of chemical dispersal rates as a function of RC input. Voltage fluctuations were a function of power supplied to the propulsion system.  
Figure 18: Treatment of watermael infestation in a small pond using manual navigation and minimal prop submersion.
## 2 Frequency and Active Power Control Schemes
### Alternative aFRR Participation Methods for BESS
#### 2.2.2 BAU SOC Control  
The business-as-usual (BAU) SOC control method is demonstrated in Figure 5. In this scheme, batteries participate on equal terms with thermal units on secondary frequency regulation, as well as in the ED problem of Section 3. When the SOC approaches its limits (\(SOC_{bi,min,BAU}\) or \(SOC_{bi,max,BAU}\)), the BESS will go into idling (\(P_{bi}^{*}=0\)) or provide regulation only in the direction of SOC restoration to its reference through \(P_{bi,f}^{*}\), e.g., in low-charge conditions, the battery active power will only track a recharging reference (\(P_{bi,f}^{*}<0\)), else it will remain zero. The transitions between idling state (zero power) and a non-zero \(P_{bi,f}^{*}\) are rate limited (at 0.1 pu/s). Moreover, a safety margin of 2.5%, as in the proposed method, is used in selecting \(SOC_{bi,min,BAU}\), and \(SOC_{bi,max,BAU}\) in relation to \(SOC_{bi,min-}\) and \(SOC_{bi,max+}\) (see Table 2). Through the rate limiter and the SOC safety margins, smooth switching between rules is achieved. In this simple power control scheme, the AGC does not incorporate any SOC- or power-related signals from the BESS station.  
Figure 4: Filter-based AGC method.
## 4 Classification of MAC Protocols Based on Channel
### Random Selection Based  
The time slot is accessed randomly; the channel is split up into frames and further divided into slots. This mechanism provides better channel utilization and minimizes collision. Some slots may be left idle and may be overloaded, leading to resource wastage and collision.
## 2 Background
### Amazon Web Services  
Amazon Web Services is one of the most famous and oldest cloud platforms, offering services ranging from databases and data analytics to internet of things and mobile computing, besides many services dedicated to enterprises [57]. The smart appliance system proposed in this paper makes use of AWS IoT core, AWS Lambda, and two data storage services, AWS S3 and DynamoDB. Furthermore, Amazon Cloudwatch, a service used to monitor AWS resources and applications, is used to keep track of the performance and cost of each deployed service.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **NB-IoT** & **LoRaWAN** & **Sigfox** & **LTE-M** \\ \hline Spectrum & Cellular (LTE) & ISM & ISM & Cellular (LTE) \\ \hline Data Rate [46; 47] & \(\sim\)200 kbps & \(\sim\)0.3–100 kbps & \(\sim\)100–600 bps & \(\sim\)1 Mbps \\ \hline Payload (bytes) [47; 48] & 1600 & 243 & 12 & 1000 \\ \hline Tx Power (dBm) [48] & 23 & 13 & 14 & 23 \\ \hline Consumption [48] & Medium low & Low & Very Low & Medium \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of communication protocols for IoT and machine-to-machine applications.
# Satellite-Based Estimation of Carbon Dioxide Budget in Tropical Peatland Ecosystems
## 3 Results
### NBE Results and Validation with Flux Tower Data  
The NBE of tropical peatlands was calculated based on Equation (9). By using the \(R_{e}\) model established at the _UF_ site, the monthly average and the standard deviation of the NBE were estimated as 29.46 and 6.26 Mt C/month, respectively. When the \(R_{e}\) values of \(BF\) and \(DF\) were applied, the NBE values were estimated as \(-4.57\pm 4.12\) and \(24.91\pm 5.04\) Mt C/month on average (\(\pm\) standard deviations), respectively. From this estimation, the monthly average GPP (39.15 Mt C/month) was equivalent to 58.68% of \(R_{e}\) (66.71 Mt C/month), and the FE (1.90 Mt C/month) accounted for 2.84% of \(R_{e}\). Consequently, the NBE and resultant emissions of the monthly time series (Figure 12) were always high.  
Figure 11: Spatial distributions of the mean annual fire emissions (FE) from tropical peatlands in the study area from 2002 to 2018.  
Figure 10: Fire emissions from tropical peatlands in the study region found by using global fire emissions database (GFED) 4.1s data and satellite-based FE data in this study. The monthly averages of GFED and FE were 1.4 and 1.9 Mt C/month with standard deviations of 2.96 and 2.76, respectively. (**a**) Monthly time series and (**b**) a scatter plot of both datasets.
## 1 Introduction
### Research Scope and Previous Studies
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Senior Citizen Centers**} & \multirow{2}{*}{**Address**} & \multicolumn{2}{c}{**Year of Being Selected**} \\  & & & **as an Exemplary** \\  & & & **Center** \\ \hline \multirow{2}{*}{1} & Yeongno Senior Citizen & 333 Hana-gil & \multirow{2}{*}{2021} \\  & Center (YR) & (Sineon-Dong 3-ga) & \\  & & 27 Dongsam-ro 50 & \\ \multirow{2}{*}{2} & Dongsam Senior Citizen & \multirow{2}{*}{2021} \\  & Center (DS) & & beom-gil \\ \multirow{2}{*}{3} & Sineon Senior Citizen & \multirow{2}{*}{542 Hana-gil} & \multirow{2}{*}{2022} \\  & Center (SS) & (Sineon-Dong 2-ga) & \\ \multirow{2}{*}{4} & Gyeongjeon Apartment & \multirow{2}{*}{10 Dongsamdong-ro} & \multirow{2}{*}{2022} \\  & Senior Citizen & (Dongsam-dong) & \\ \multirow{2}{*}{5} & Daewon Apartment & \multirow{2}{*}{79 Namhangsaessak-gil} & \multirow{2}{*}{2023} \\  & Senior Citizen & (Yeonggeon-dong 4-ga) & \\ \multirow{2}{*}{6} & Center (DW) & & \\  & Isongdo Senior Citizen & \multirow{2}{*}{12 Hyangto-gil} & \multirow{2}{*}{2023} \\  & Center (ISD) & (Yeonggeon-dong 4-ga) & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Research scope and targets. Research on the utilization of senior citizen centers has primarily focused on analyzing the usage patterns of older adults and the psychological, social, and economic factors influencing these patterns. Such factors include reducing social isolation, improving physical health, promoting leisure activities, providing emotional stability and support, and facilitating social interaction. Most studies have indicated that older adults utilizing these centers are more likely to overcome isolation and enhance their quality of life through social interaction. In addition, some studies have suggested that older adults' motivations for using senior citizen centers vary according to their physical, emotional, and social needs, which are influenced by their personal backgrounds and circumstances. The eldercare system is divided into three models: home-based, community-based, and institutional care. Users' needs tend to differ depending on the type of service chosen. Older adults who opt for home-based care tend to seek independence [59; 60], whereas those who use community-based care value community connections and social interaction [61; 62]. Those who select institutional care prefer structured support and require medical and 24 h
## 5 Implementation and Testing Environment
### Experimental Data  
The details for the experimental data are presented in Table 3. For all experiments, we divided the data into 60% training data 20% validation data and 20% testing data. The total number of 294894 records. The raw data is collected in log files as shown in Figure 6 which we processed to generate session patterns.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**System Component** & **Specification** \\ \hline Operating System & Ubuntu 18.04.1 LTS \\ Memory & 32 Gb \\ Language & Python \\ GPU & Nvidia GFForce 1080 \\ Language Version & 3.6.1 \\ APIs & Tensorflow 1.13, \\ Key Liberates & Numpy, skearn, Pandas \\ Encoding & EUC-KR \\ \hline \hline \end{tabular}
\end{table}
Table 2: System’s components and specification.  
Figure 5: Data categorization from raw data.  
This data is very recent and is of around 1 year form Jun 2019 to July 2020. There are in total 51386 unique IP addresses in the data.  
For experimental purposes we have used three different kind of settings. The data records are built accordingly. We have experimented on different lengths of click sequences. For this purpose, we have generated three types of records each containing different numbers of user clicks sequence lengths. The minimum size of all click sequences is considered to be 3 and the maximum size is varied till the maximum number of clicks in a session by any user i.e. 40. The following Table 4 describes the data setting in detail.  
We have performed experiments based on the GCN, the optimized GCN. The parameters are shown in the Table 5 below.
## 2 Experimental
### Adsorption Experiments  
#### 2.2.1 4-MBC Adsorption on Biochar  
The adsorption experiments were conducted in duplicate at room temperature (20 \(\pm\) 2 \({}^{\circ}\)C) and a controlled pH of 6.5. In each experiment, a measured amount of biochar was placed in glass vials, and a background solution of 0.01 M CaCl\({}_{2}\) in deionized water, supplemented with 100 mg/L NaN\({}_{3}\) as a biocide, was added. Using only CaCl\({}_{2}\) creates a controlled solution where calcium ions (Ca\({}^{2+}\)) provide specific ionic strength without introducing the complexity of multiple salts, ensuring a more straightforward evaluation of the adsorption process. Prior to spiking the background solution, a stock solution of the organic compound (1000 ug/mL) was prepared in methanol. The amount of adsorbent in each experiment was carefully selected to achieve a sample/solution ratio resulting in 20-80% uptake of 4-MBC.  
The volume of the stock solution used for spiking was less than 0.1% (\(\
u/\
u\)) to minimize any potential interference with the sorption behavior of the organic compound.  
For the adsorption kinetics, 10 mg of biochar was measured into a glass vial, and 40 mL of the background solution, spiked with the methanol stock solution of the organic compound, was added. The initial concentration of 4-MBC in the background solution was approximately 600 \(\upmu\)g/L. The kinetics experiment involved shaking the samples at 180 rpm for varying time periods, ranging from 30 min to 96 h.  
To determine the initial concentration of 4-MBC for each kinetic point, control samples without any sorbent were prepared and treated identically to account for any losses of the investigated compounds other than adsorption. This control procedure is crucial for accurately assessing the true adsorption capacity of biochar. The adsorption isotherms were conducted in triplicate at room temperature (\(20\pm 2\)\({}^{\circ}\)C). In these experiments, pre-measured amounts of adsorbent were placed in glass vials, and the background solution was added. After agitation, the methanol stock solution of organic compounds was spiked, and the mixture was equilibrated at room temperature. The suspension was then continuously shaken at 180 rpm for 48 h, the equilibrium time determined from the previous kinetics experiment. The concentration range of 4-MBC tested was 20-2000 \(\upmu\)g/L. Control samples without any sorbent were also prepared and treated in the same manner to determine the initial concentration of the investigated organic compounds for each isotherm point. The recoveries were within the acceptable range of the applied analytical procedures, indicating no significant losses other than adsorption.
###### Abstract  
This paper presents a novel baseband architecture that supports high-speed wireless VR solutions using 60 GHz RF circuits. Based on the experimental observations by our previous 60 GHz transceiver circuits, the efficient baseband architecture is proposed to enhance the quality of transmission. To achieve a zero-latency transmission, we define an (106,920, 95,040) interleaved-BCH error-correction code (ECC), which removes iterative processing steps in the previous LDPC ECC standardized for the near-field wireless communication. Introducing the block-level interleaving, the proposed baseband processing successfully scatters the existing burst errors to the small-sized component codes, and recovers up to 1080 consecutive bit errors in a data frame of 106,920 bits. To support the high-speed wireless VR system, we also design the massive-parallel BCH encoder and decoder, which is tightly connected to the block-level interleaver and de-interleaver. Including the high-speed analog interfaces for the external devices, the proposed baseband architecture is designed in 65 nm CMOS, supporting a data rate of up to 12.8 Gbps. Experimental results show that the proposed wireless VR solution can transfer up to 4 K high-resolution video streams without using time-consuming compression and decompression, successfully achieving a transfer latency of 1 ms.  
Keywords:60 GHz transceiver; baseband processing; error-correction code; wireless VR +
Footnote †: journal: Electronics Letters
## 1 Introduction
[PERSON] et al., presented a method of determining the cutoff for separating the modes based on mutual information, and denoising the high-frequency group by Wavelet Threshold Denoising (WTD) [21]. [PERSON] and [PERSON] presented a method for photoplethysmography denoise using wavelet transform to process the noise dominant components obtained from CEEMDAN [22]. [PERSON] et al., presented a denoising method for surface electromyography signals using WTD for the CEEMDAN reconstructed signals [23]. However, these methods do not consider the possible ineffective modes in low-frequency. The shortcomings of conventional WTD also affect the denoising effect. In this paper, an improved CEEMDAN-WTD method based on autocorrelation is proposed for the harmonic vibration signal measured by MHD ARS. Autocorrelation function (ACF) is used to determine relevant modes, and improve wavelet threshold. First, the modes are obtained by CEEMDAN. The autocorrelation of each mode is used to determine the relevant modes where the effective signals are located. This step can remove some noise and ineffective modes. Then, the relevant modes are denoised using the improved WTD algorithm. The autocorrelation of each wavelet coefficient sequence is used to adjust the wavelet threshold, which can improve the denoising ability of the WTD algorithm and protect the details of the signal. Meanwhile, a new wavelet thresholding function is proposed to overcome the shortcomings of conventional thresholding functions. Finally, the denoised signal is obtained by combining the denoised relevant modes. In static test, the proposed method effectively reduced the quantization noise, angular random walk, and bias instability. In dynamic test, the proposed method improved the signal-to-noise ratio (SNR), and reduced the root-mean-square error (RMSE). Results in both tests show that the proposed method outperforms the conventional methods. Therefore, the proposed method has good prospects for processing spacecraft harmonic vibration signals measured by MHD ARS.