esa-sceva/satcom-chunk-collection huggingface dataset:
## Results and Discussion  
### Preparation of the Protein Hydrolysate of Monkfish Muscle  
The specificity of the enzyme significantly influences the bioactivity and production of APs ([PERSON] et al., 2016). In vitro GI digestion model is widely applied to investigate the digestibility, release of food components, and structural changes under simulated GI conditions ([PERSON] et al., 2016). Moreover, the model is popularly used to produce protein hydrolysates because of their safe and efficient properties ([PERSON] et al., 2016; [PERSON] et al., 2018). As shown in Table 1, defatted monkfish muscles were hydrolyzed under in vitro GI digestion, and the degree of hydrolysis (DH, %) of the resulting hydrolysate (referred to as MPTH) was \(27.24\%\pm 1.57\%\), which was significantly higher than those of hydrolysates using pepsin (\(23.51\pm 1.96\%\)) and trypsin (\(20.17\%\pm 1.55\%\)), individually. Furthermore, the scavenging activities of MPTH on DPPH- and HO- at the concentration of 5.0 mg protein/mL were \(44.54\%\pm 3.12\%\) and \(41.32\%\pm 2.73\%\), respectively, which were significantly stronger than those of hydrolysates using pepsin and trypsin, individually. Then, MPTH was chosen for the following separation process.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Protease**} & \multirow{2}{*}{**Degree of Hydrolysis (\%)**} & \multicolumn{2}{c}{**Radical Scavenging Activity (5.0 mg Protein/mL, \%)**} \\  & & **DPPH:** & **HO:** \\ \hline Pepsin & \(23.51\pm 1.96\) b  & \(33.24\pm 2.34\) b  & \(29.34\pm 1.48\) b  \\ \hline Trypsin & \(20.17\pm 1.55\) c  & \(29.21\pm 1.87\) c  & \(27.74\pm 2.15\) c  \\ \hline In vitro GI digestion & \(27.24\pm 1.57\) a  & \(44.54\pm 3.12\) a  & \(41.32\pm 2.73\) a  \\ \hline \hline \end{tabular} The data are presented as the mean \(\pm\) SD (\(n=3\)). a–– Values with the same letters in each column indicate no significant difference (\(p>0.05\)).  
\end{table}
Table 1: Degree of hydrolysis (%) and radical scavenging activity (%) of the protein hydrolysate of monkfish muscle using pepsin, trypsin, and in vitro gastrointestinal (GI) digestion model.
# Virtual Reality or Videoconferencing for Online Learning? Evidence from Comparative Meta-Analyses
## 4 Results and Discussion
### Moderator Analysis for VR-Supported Online Learning
#### 4.2.2 Technological Features in VR Studies  
We discussed the VR equipment used in the studies and found that desktops were the most frequently used equipment (70.3%), followed by HMDs (29.7%). The \(Q\) statistics revealed that the effect size for HMDs (\(g\) = 1.049) was slightly higher (g = 1.049) than for desktops (\(g\) = 0.866), but this difference was not statistically significant (\(Q_{B}\) = 0.514, \(p\) = 0.474). Surprisingly, this finding contradicts the results of [PERSON] et al. [10] and [PERSON] et al. [37]. This is understandable for two reasons. First, VR equipment has improved over time. Today's HMDs may offer a more immersive learning experience that has a greater impact. Second, the meta-analysis included studies in which most participants were college students. They may have rich experience with desktop VR and, thus, more positive expectations for immersive VR; this psychological expectation could potentially also improve their learning outcomes. Finally, it is important to consider the limitations of the number of studies. Only 11 studies explored the impact of HMD on online learning, which means that an element of chance may play a role in the results.
###### Abstract
To this end, we measured NO2 levels both indoors and outdoors in kitchens using natural gas and electric stoves in two distinct urban areas with different levels of outdoor air quality. One area complies with outdoor European Union NO2 standards, while the other typically exceeds these standards. The article begins with a literature review and an overview of NO2 air quality standards across various countries and time periods. Following this, the methodology is detailed, and the presented results are discussed. The article concludes by summarizing the main findings. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Ref.** & **Location** & **Environment** & **Fuels** & **NO2 Concentration Indoors** & & & **Exposure Period** \\ \hline
[22] & Adelaide & Urban and Suburban (193) & NG & \(33.28\pm 3.76\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) Without NG & \(15.61\pm 4.70\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & - & - \\ \hline
[15] & Wuhan, China & Urban & NG & Winter: & & 30 min \\  & & & & \(167.0\pm 215.1\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) Without ventilation: & \(31.5\pm 23.0\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & \\  & & & & \(294.5\pm 372.0\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) With ventilation: & - & \\  & & & & With ventilation: & & \\  & & & & \(97.9\pm 57.1\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & - & \\  & & & Electric & Winter: & & \(32.9\pm 15.1\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & \(29.0\pm 20.0\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) Without ventilation: & \\  & & & & \(28.7\pm 11.6\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) With ventilation: & - & \\  & & & & \(38.9\pm 17.8\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & - & \\ \hline
[20] & 6 Chinese cities & & & Summer: & & \\  & (different climatic areas) & Urban & NG (6) & \(20\pm 0\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) Cool gas (20) & \(100\pm 80\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & \(75\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & \(3\) h \\ \hline
[11] & Tanzania & Rural & Biomass & \(59.80\pm 66.19\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) (48) & \(12.79\pm 23.88\)\(\mathrm{\SIUnitSymbolMicro m}^{-3}\) & \(24\) h \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Studies of short-term NO2 exposure (less than 1 week) monitoring in kitchens using natural gas (number of samples).
## 4 Data Acquisition and Processing
### Survey Process  
Firstly, the interviewee was shown a map, and map information and main surface features were introduced through a three-dimensional model and a panoramic scene display mode to help the interviewee establish a spatial concept and form an intuitive impression of a spatial scene, and, at the same time, a schematic diagram of the current site pollution distribution was displayed, to help the interviewee understand the current site pollution situation.  
Secondly, the meaning of different brownfield landscape values and preference types was introduced to the interviewees. The interviewee was required to mark the places of personal value and preferences with marked points on the map, and each value or preference type was marked with a point, and according to the degree of importance, and where appropriate, scores out of 100 were given.  
Thirdly, the current regional planning scheme was introduced and the interviewees were asked to evaluate the impact of the current scheme against their marked values in combination with the site pollution situation and personal opinions.  
It can be seen from Figure 2, 365 basic samples were collected and 342 valid questionnaires were obtained through preliminary screening. In total, 6010 POIs were collected through the map-based questionnaire survey.
## 2 Dataset Description
### Satellite Data and in situ Measurements
#### 2.2.2 Optical Images  
Thirty cloud-free optical images were also acquired by SPOT-4, SPOT-5, LANDSAT-7 and LANDSAT-8 sensors over the study area (Table 1). SPOT-4 images were acquired within the framework of the Take 5 experiment ([[http://www.cesbio.ups-tlse.fr/](http://www.cesbio.ups-tlse.fr/)]([http://www.cesbio.ups-tlse.fr/](http://www.cesbio.ups-tlse.fr/))). In most cases, the optical and radar images were not separated by more than four days.  
Optical data processing includes orthorectification and correction for atmospheric effects. The atmospheric correction of SPOT-4 images was performed by CESBIO (Centre d'Etudes Spatiales de la BIOsphere) according to the method described by [PERSON] _et al._[73]. The atmospheric correction of SPOT-5 and LANDSAT-8 images was carried out using the simplified method of atmospheric correction (SMAC) [74]. Aerosol optical thickness at 550 nm and the water vapor content (g/m\({}^{2}\)), input variables  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Date**} & \multirow{2}{*}{**Sensor**} & \multicolumn{1}{c}{**Time**} & \multicolumn{1}{c}{\(\theta\)} & \multicolumn{1}{c}{**Range of**} & \multicolumn{1}{c}{**Range of**} & \multicolumn{1}{c}{**Range of**} & \multicolumn{1}{c}{**Range of**} \\
**dd/mm/yyyy** & & **(UTC)** & **(\({}^{\circ}\))** & **Mv** & **VWC** & **BIO** & **HVE** & **LAI** \\ \hline
19/04/2013 & TSX & 19:24 & 29.1 & [0.13–0.23] & [1.54–2.35] & [1.9–3.00] & [1.9–1.20] & [3.98–5.88] \\ \hline
22/04/2013 & TSX & 07:53 & 32.5 & - & - & - & - & - \\ \hline  
\hline \end{tabular}
\end{table}
Table 2: Main characteristics of the SAR images (TSX and CSK, all in HH and HV polarizations), and a summary of the ground-truth measurements performed on our sampled plots used in this study. 0: radar incidence angle (\({}^{\circ}\)), Mv: volumetric soil moisture (cm\({}^{3}\)/cm\({}^{3}\)), VWC: vegetation water content (kg/m\({}^{2}\)), BIO: vegetation biomass (kg/m\({}^{2}\)), HVE vegetation height (m), LAI: Leaf Area Index (m\({}^{2}\)/m\({}^{2}\)).  
in the SMAC model, were obtained from the AERONET (AErosol Robotic NETwork) website ([[http://aeronet.gsfc.nasa.gov/](http://aeronet.gsfc.nasa.gov/)]([http://aeronet.gsfc.nasa.gov/](http://aeronet.gsfc.nasa.gov/))). Finally, LANDSAT-7 surface reflectance images were downloaded directly from the USGS website ([[http://earthexplorer.usgs.gov/](http://earthexplorer.usgs.gov/)]([http://earthexplorer.usgs.gov/](http://earthexplorer.usgs.gov/))). Atmospheric correction of LANDSAT-7 images was directly performed by the NASA (National Aeronautics and Space Administration) using specialized software called Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). This software applies the 6S (Second Simulation of a Satellite Signal in the Solar Spectrum) radiative transfer model to produce surface reflectance data as described in [75]. The NDVI was computed from the optical images. Then, NDVI pixel values were averaged for each plot and compared to vegetation _in situ_ measurements.
# Batch and Column Adsorption of Phosphorus by Modified Montmorillonite
## 1 Introduction
demonstrated that the amount of the herbicide paraquat adsorbed by montmorillonite increased with a decreasing adsorption temperature in a physical exothermic adsorption process [29]. On the contrary, [PERSON] et al. discovered that an increase in temperature could lead to an increase in the retention effect of metal on clay, presenting an endothermic reaction [30]. pH and temperature were two key factors used to discern the adsorption mechanism between the adsorbate and the adsorbent in the above adsorption experiments. In previous studies focusing on the adsorption abilities of modified MMt, batch adsorption has been a common method for studying the amounts of different pollutants adsorbed by modified MMt [31; 32; 33]. Batch adsorption is mostly conducted in the laboratory, making it difficult to apply in industrial wastewater treatment [34; 35; 36; 37]. Therefore, the design of a column adsorption facility is a necessary procedure that can be applied towards actual industrial water and wastewater treatments [38; 39; 40; 41]. It has been reported that the total phosphorus discharge in China was 0.54 million tons in 2015, according to statistics [42]. Most inlet phosphorus concentrations for wastewater treatment plants (WWTPs) in China are in the range of 5-20 mg/L [43; 44; 45]. High concentrations of phosphorus in water cause damage to the ecosystem and even to human health. Phosphorus discharge can lead to skin inflammation in humans and eutrophication in the water system [46; 47; 48; 49]. Therefore, the adsorption of phosphorus via the increased adsorbability of modified montmorillonite has been applied as a solution to this problem [50; 51; 52]. This study aims to reveal whether modified montmorillonite has an excellent adsorption efficiency for phosphorus in batch and column adsorption experiments. The optimal conditions of phosphorus adsorption were investigated by studying the effects of pH, concentration of phosphorus, temperature, and adsorbent dosage on phosphorus adsorption efficiency. In addition, an elution column was used to conduct a column adsorption experiment to determine the breakthrough time. Furthermore, XRD analysis was used to study the changes in the interlayer structure of the modified MMt before and after batch and column adsorptions to further confirm the enhancement of phosphorus adsorption resulting from interlayer variations in modified MMt. The results of this study may provide a new solution for the removal of phosphorus in factory sewage, as well as a waste-utilization methodology for the application of montmorillonite mineral-containing waste materials to fabricate environmentally friendly adsorbents.
# Low Delay Inter-Packet Coding in Vehicular Networks
###### Abstract  
In Cooperative Intelligent Transportation Systems (C-ITSs), vehicles need to wirelessly connect with Roadside units (RSUs) over limited durations when such point-to-point connections are possible. One example of such communications is the downloading of maps to the C-ITS vehicles. Another example occurs in the testing of C-ITS vehicles, where the tested vehicles upload trajectory records to the roadside units. Because of real-time requirements, and limited bandwidths, data are sent as User Datagram Protocol (UDP) packets. We propose an inter-packet error control coding scheme that improves the recovery of data when some of these packets are lost; we argue that the coding scheme has to be one of convolutional coding. We measure performance through the session averaged probability of successfully delivering groups of packets. We analyze two classes of convolution codes and propose a low-complexity decoding procedure suitable for network applications. We conclude that Reed-Solomon convolutional codes perform better than Wyner-Ash codes at the cost of higher complexity. We show this by simulation on the memoryless binary erasure channel (BEC) and channels with memory, and through simulations of the IEEE 802.11p DSRC/ITS-G5 network at the C-ITS test track AstaZero.  
Keywords:V2X; C-ITS; IEEE 802.11p; error-correcting codes; convolutional codes; fading channels +
Footnote †: journal: Computer Science
## 4 Discussion
### Influence of the Damping Factor on the Synchronism Phenomenon  
Although it is known that no ship will roll just in the moment of synchronism (\(\mathrm{Td}=\mathrm{Tw}\)) because it capsizes before reaching this moment, from a theoretical point of view, it can be interesting to represent the sum of all forces involved (free and induced motion) at this moment. For this reason, Figure 23 shows the ship's behaviour assuming that the ship starts to roll just when \(\mathrm{Td}=\mathrm{Tw}\), in this case, 12 s. A perfect synchronism with the induced and free motion is noted, which is reached from the first moments.  
Although the accurate calculation of roll damping is essential for roll motion prediction [36], relevant papers can be found in the literature that deal with the difficulty of predicting this roll damping as a consequence of highly non-linear components experienced on board ships and barges, regardless of type and size [37]. For this reason, in the present research, an average and constant damping factor is considered (0.015), although it is not an exact and constant value throughout the whole rolling process. This value is a subject of naval architecture, and the present paper, keeping the focus on the ship's operation, does  
Figure 21: Induced rolling motion for a small \(\mathrm{Td}\) (6 s). (a) \(\mathrm{Tw}=4\) s; (b) \(\mathrm{Tw}=14\) s.  
Figure 22: Induced rolling motion for a very large \(\mathrm{Td}\) (16 s). (a) \(\mathrm{Tw}=4\) s; (b) \(\mathrm{Tw}=14\) s.  
not pretend to address it. However, when many fishing vessels are engaged in fishing activities, they are at zero speed and receive beam waves, i.e., the assumptions considered in the present study. In these circumstances, the weight of nets and fishing catches causes an induced delay in the rolling motion. In other words, they increase the damping factor. In this case, the ship's behaviours are expected to be similar to those presented in the previous figures, and although the amplitude of the rolling angles is smaller, it can ensure adequate safety for any ship.
## 3 Experimental Setup  
### RTVE2020 Database  
The proposed ASR systems were evaluated under the IberSpeech-RTVE 2020 Challenge conditions. The RTVE2020 Database [38] was provided to the participants. This is an extension of the RTVE2018 Database, which contains a collection of Spanish TV shows and  
Figure 1: Architecture of the end-to-end LF-MMI approach applying DAT. An adversarial branch (TV show classifier) is added to the second layer of the main PyChain architecture (posterior classifier).  
broadcast news from 2015 to 2019. The training partition consists of audio files, partially subtitled, presenting the following limitations:  
* Subtitles were generated by means of a re-speaking procedure that sometimes changed the sentences and summarized what had been said, obtaining non-reliable transcriptions;
* Transcriptions were not supervised by humans. Only 109 h from the dev1, dev2, and test partitions contain human-revised transcriptions;
* Timestamps were not properly aligned with the speech signal.  
Regarding all these limitations, we tried to avoid the use of these low-quality transcriptions, which could poorly model the acoustic space. As shown in Figure 2, we carried out a semi-supervised annotation process, which allowed training accurate acoustic models. First, a baseline acoustic model was trained using our own databases (see Section 3.2). Once the acoustic model was prepared, the unlabeled speech data were initially aligned to obtain a provisional transcription. To improve the quality of these automatic transcriptions, a human annotator team was responsible for the supervision process.  
The RTVE training partition was prepared under this supervision process to obtain reliable transcriptions aligned with the speech signal. Hereafter, we were able to develop our first ASR models based on TV content [32].  
Due to some limitations during the supervision process, two resulting datasets were used for training the systems: RTVE_train350 (350 h from RTVE training set) and RTVE_train100 (100 h from RTVE_train350). The validation datasets were 20% of the training data. It is worth noting that we tried to balance the partitions at any time, trying to cover the different scenarios represented in the whole RTVE dataset, such as political and economic news, in-depth interviews, debate and live magazines, among others. Consequently, for testing purposes, several datasets corresponding to 1 h in duration each were built from the RTVE_dev1 and RTVE_dev2 development partitions.  
Finally, the RTVE2020 database was completed adding a collection of TV shows that belong to a wide range of genres and broadcasts from 2018 to 2019. This was composed of 70.3 h of human transcribed audio. It was used as the test partition for the Speech-to-Text Transcription Challenge (RTVE2020_test).
# Backscatter Communications: Inception of the Battery-Free Era--A Comprehensive Survey
## 7 BackCom: Range Extension and Reliability
### Smart Homes/Cities using BackCom  
Figure 41 shows the concept of smart home that enables each object in the smart home having a backscatter tag to communicate through WiFi signals. Smart home consists of a considerable number of BackCom passive tags deployed at multiple locations (e.g., roof, walls, furniture, etc.). These tags can seek power from ambient sources such as WiFi access points, TV towers, or cellular eNBs/gNBs. The applications of passive tags are smoke detection, gas leakage check, movement monitoring, surveillance, and indoor positioning [186; 187]. Smart cities utilize ubiquitous BackCom passive tags in buildings, streets, bridges, and parking spaces. The tags could help to improve the quality of life by monitoring air pollution, traffic monitoring, and parking availability. Furthermore, due to the availability of ambient signals in each home, it is now possible to remotely access household items utilizing BackCom. It is expected that BackCom enable smart cities and homes, making life more easy and comfortable.  
The concept of BackCom in a smart home helps to monitor human breathing and heart rate without mounting any devices on one's body [188]. Researchers have also investigated object detection [189; 190] and activity recognition [191], using backscattered signals. Passive tags have fine-scale motion capture and localization accuracy up to 5-400 cm at a range of a few hundred meters [192]. Likewise, robots for in-house navigation can work by reflecting BackCom signals from tags, fixed on furniture and doors  
Figure 41: The concept of a smart home using BackCom.  
Figure 40: Applications of BackCom.  
[193]. Smart cities enable communication between each outdoor or indoor object. This application of BackCom helps to energize passive devices (such as signposts at bus stops) at outdoor spots to communicate without possession of any dedicated power connection. Smart posters are capable of broadcasting music to nearby users using FM BackCom. Moreover, FM receivers in nearby cars can receive that information [96].
# Wideband Eight-Antenna Array Designs for 5G Smartphone Applications
## 4 Hand Effect on the Proposed Eight-Antenna Array
### Double-Hand Mode (DHM)  
The relative positions of the user's hand in DHM and the smartphone drawn in the simulation software HFSS (High-Frequency Structure Simulator) are shown in Figure 17. Subsequently, Figure 18a presents the reflection coefficient of the proposed antenna influenced by the DHM, indicating a tendency for antenna modes to shift towards lower frequencies. However, overall, all eight antennas meet the bands-of-interest (3300-5925 MHz). Figure 18b illustrates the total efficiency affected by the double-hand mode, indicating that most antennas are impacted, with their efficiency dropping to over 40%. The cause of this situation may be interference from the positions where the hands are placed, affecting most of the antennas.  
Figure 17: Diagram of the double-hand model relative to the smartphone via HFSS.  
Figure 18: Double-hand model (**a**) refection coefficients and (**b**) total efficiency.
# Regression Equations for Estimating Landslide-Triggering Factors Using Soil Characteristics
## 3 Results  
### Rainfall Events  
Figure 2 shows rainfall events at the time when landslides occurred intensively in the study area. The Yangju area in Gyeonggi-do analyzed rainfall data from Geumcheon, Uijeongbu, and Goyang weather stations close to the area where the landslide occurred. From 4 August to 7 August 1998, a cumulative rainfall of up to 588.5 mm fell. During the rainfall period, on 7 August, many landslides occurred in Yangju area due to 111.5 mm/h of intensive rainfall. In Sangju, Gyeongsangbuk-do, rainfall data from Boeun, Hwasco, and Anggye weather stations were analyzed. From 10 August to 12 August 1998, a cumulative rainfall of 522 mm occurred. The landslide occurred on 12 August due to a rainfall of 95 mm/h. It was analyzed that the rainfall pattern when the landslide occurred intensively in the study area was within 3-4 days of rainfall duration and the cumulative rainfall was more than 500 mm.  
Figure 2: Changes in cumulative rainfall observed at meteorological stations located around the study area based on when the landslide occurred.