dataesr/scientific-paragraphs-categorization huggingface dataset:
In silico simulations Initially, the participant was asked to select a device type and size, after which it could be freely placed in any location of the LAA using the interface of the Ansys Discovery Live software. The LA anatomy could also be moved. Once a device position was chosen, the simulation was launched, requiring several minutes to visualize the resulting blood flow patterns (Figure  5 ). Therefore, blood flow velocities near the device could be estimated, as well as flow recirculations and leaks due to the chosen LAAO positioning, potentially leading to DRT.
e. , which device was implanted, clinical output). Most participants (5/6) were familiar with 3D printing, as they have tested it before. Moreover, only one participant did not know about the use of any of these technologies for LAAO planning, while only one knew about all of them. Not a single participant had tested the VIDAA and VRIDAA platforms before the practical session and only two physicians had some experience with fluid simulations beforehand, although not with the Ansys Discovery Live software.
In addition, based on the SUS questionnaire, VIDAA was fast and intuitive, which covered several manual steps but with a fast learning curve. Participants stressed the added value of the webbased platform in complex cases, proposing to incorporate functional information from fluid simulations for a more complete solution. The current commercial solutions comparable to VIDAA are the stand-alone 3mensio Structural Heart software (Pie Medical Imaging, Bilthoven, the Netherlands) or Mimics (Materialise NV, Leuven, Belgium), which include MPR visualization, 3D rendering, and 3D surface visualization, and HEARTguideTM C1 A22* A25 A22* A22* A28 A22* A22 C2 A18 A18 A22 A16* A22 A18 A16 C3 A20 A22 A22 A18* A22 A18* A18 C4 A20 W24 A20 A18 A22 A18 A25 C5 A22 A25* A25* A25* A25* W20 A25 W: Watchman flex; A: Amplatzer Amulet.
Numbers refer to the device size (in mm). *The cases that matched the size of the device implanted to the patient (FEOPS NV, Gent, Belgium), which offers simulations of device deployment. The VIDAA platform provides a more comprehensive and interactive morphological characterization of the LAA, as well as interaction with 3D models of the LAA devices in a web-based environment that does not require any software installation and easily allows multicentric studies and collaborative decisions. Moreover, none of these solutions offer in silico fluid simulations. The price of these commercial software tools can also be an obstacle for including them in the clinical workflow of some hospitals. Participants in our study acknowledged the better exploration of the 3D LAA anatomy with the VR system, due to an enhanced depth perception, 6 degrees of freedom interaction with 3D objects (both the LA geometry and the device) and views from the interior of the cavity (not easy to see even in 3D-printed models), all points important for the device implantation  [27].
For example, it was challenging for participants to truly grasp the depth and scaling of human organs and device sizes (as well as their relation) only from 2D monitors, especially to detect possible leaks. Although the learning times for using the VRIDAA platform were short (i. e. , a few minutes), the participants preferred the combination of web-based 3D imaging software in conjunction with 3D printing since it would be easier to fit in the current clinical workflow. The evaluated VR setup that requires a certain allocated physical space is not adequate for use in most hospitals. However, affordable VR headsets with reasonable performance and resolution, including wireless solutions without requiring much room space (e. g. , the Oculus brand or even AR glasses), would be a more appropriate alternative.
Funding This work was supported by the  Spanish Ministry of Science, Innovation and Universities  under the  Retos I+D Programme  ( RTI2018-101193-B-I00 ), the  Maria de Maeztu Units of Excellence Programme  ( MDM 2015-0502 ), and the  Spanish Ministry of Economy and Competitiveness  under the Programme for the Formation of Doctors ( PRE2018-084062 ). In addition, this work was supported by the  H2020  EU  SimCardioTest  project (Digital transformation in Health and Care  SC1-DTH-06-2020 ; grant agreement No. 101016496 ).
III. SDR PLATFORMS The implementation of CR approaches follow designs that typically employ programming languages at low-level and/or at high-level. At low-level, hardware description languages (HDL), such as Verilog or VHSIC Hardware description language (VHDL), aim at designing the digital logic of the system with register-transfer level (RTL) abstractions, where the exchange of data between registers can be designed. The employment of HDL allows the implementation of low-level architectures providing more control in the design of its components. Nevertheless, it entails a large time in acquiring expertise to implement at low-level. In this regard FPGA-based SDR platforms can use dynamic partial reconfiguration in order to reduce reconfiguration time. On the other hand, the time of implementation at low-level can be avoided by generating HDL from programming language at high-level.
A. SOFTWARE TOOLS The selection of the software corresponds to the general requirements of a CR implementation. Next, we list the most employed tools: 1) MATLAB AND SIMULINK MATLAB and Simulink have become very common and widely adopted for most designers that start employing SDR tools  [68]. The high-level of language and block diagram environment, named Simulink, alleviates the task for the design and experimental evaluation of wireless transmissions. It is able to work with hardware platforms such as universal software radio peripheral (USRP)  [68] , RTL-SDR  [69] , ADALM-PLUTO  [70] , Zynq SDR, among others. On the other hand, the provided high-level tools may not be enough to the needs of our design. For instance, the implementation of more complex scenarios working in real-time, scalable designs and the lack of open-source code.
2) GNU RADIO GNU Radio is a set of open tools aiming to implement SDR systems  [71]. It provides signal-processing blocks that are interconnected to form a flow graph representing the implemented transceiver in software. Basically, these blocks consist of source blocks (data files, audio files, etc), processing blocks (modulators, filters, multipliers and amplifiers), and sink blocks (FFT sink, constellation sink, oscilloscope sink). One of the main advantages is the capacity to define and add new blocks by employing C++ or Python. It is carried out by using a gr-modtool  [72]  script that allows to create our digital processing block. Besides, an intuitive graphical user interface (GUI) called GNU Radio Companion (GRC) is provided to alleviate the task of designing a new transceiver. Moreover, GNU Radio can be used with an external RF hardware (e.
g. USRP  [73] , LimeSDR  [74] , RTL-SDR  [69] , ADALM-PLUTO  [70] ) or without it in a simulation-like environment. Unlike Matlab, it allows the implementation of real-time radio system. However, it requires some expertise and knowledge to be more familiar with the developing tools. Moreover, although there exists a large number of projects available on the web, compatibility issues and a lack of updates prevent a rapid prototyping.
3) LabVIEW National Instruments (NI) also offers a tool for the development of a SDR platform  [75]. Likewise, GNU radio and Simulink, the design can be constructed schematically by connecting a chain of various blocks together in a visual programming environment. The different blocks of the system can be implemented using high-level languages such as C or MATLAB, and it is compatible with USRPs. In addition, it provides application frameworks tailored for LTE and 802. 11 implementations among others to easily get a real-time prototyping. Thus, allowing researchers to focus on radio aspects of their interest. Nevertheless, the products and licenses are not free, and the price for them could be not affordable.
4) XILINX VIVADO HLS The Xilinx Vivado HLS tool  [76]  is a software suite produced by Xilinx. It provides a design environment for HLS that is widely employed on numerous Xilinx FPGA boards, where C, C++ and SystemC programs can be directly used into Xilinx devices avoiding the need to manually create RTL. However, its usage is limited by the expertise and knowledge of the researcher about low-level languages and hardware architectures. For that end, it is often utilized when 131896 VOLUME 10, 2022 the radio design can not be addressed with the current highlevel tools.
1) USRP USRPs are probably the most adopted and popular hardware platform. This board is generally composed of an RF frontend, ADC/DAC, and an FPGA, where the majority of operations (baseband processing) are offloaded to a GPP (host computer) via either USB, Ethernet, or peripheral component interconnect express (PCI-Express) connection. In addition, an embedded series comes with an internal GPP to operate in a standalone mode. On the other hand, due to the fact that SDR tools such as GNU Radio, LabVIEW, and MATLAB Simulink support these boards, it is often reported in several research experiments motivating even more its employment. Nevertheless, USRP-based testbeds do not necessarily meet the requirements of communication standards. The bandwidth of the RF front-end, the data streams with a host processor, latencies, and the hardware impairments, are common aspects that usually affects the throughput and timing characteristics of the platform.
2) LimeSDR A low cost option and open source SDR, LimeSDR, is also available on the market, it has a similar architecture to the USRPs, and is comprised of a field programmable RF transceiver, an Intel FPGA, and a microcontroller. Moreover, it is connected to a GPP via USB 3. 0, where the transceiver has the task to transmit/receive the wireless data, while the GPP generates the data and process the incoming signal. LimeSDR comes with LimeSuite software including source code, firmware, and schematics, and it is also supported by GNU radio.
3) ADALM-PLUTO ADALM-PLUTO is an active learning module aiming to introduce the fundamentals of SDR. It is composed of a Xilinx Zynq-7000 SoC, and an analog-device-based RF front-end. Like previous architectures, it is connected to a GPP via USB, and a variety of software can be utilized such as MATLAB, Simulink, GNU Radio, or custom applications (C/C++,C#,Python). Although, it has been designed for teaching purposes and has some limitations such as the RF coverage, the number of antennas, and bandwith frequency 20 MHz, it has been used for experimental evaluations whenever it fulfills the requirements.
5) bladeRF bladeRF  [77]  is a promising powerful waveform development platform. It provides a 2 × 2 MIMO SDR, covering a large frequency range up to 6GHz, and connected to a GPP via USB. Supported by GNU radio and Matlab/Simulink, a HDL platform is also provided for the implementation of VHDL modem on FPGA meeting low latency and timing control required for the modulation/demodulation of 802. 11 packets.
3) WIDEBAND The implementation of larger WSS schemes on SDR platforms imposes other challenging aspects. For instance, any SDR architecture requiring a connection to a GPP via Ethernet cable (e. g. 1 GbE), will be limited to stream up to 25 Msps (for 16-bit samples), thus creating a bottleneck for larger values of Msps and consequently for larger bandwidths. This is the case in  [87] , where the authors require a sustainable signal acquisition at very high sampling rates, and consequently high data rate throughput and storage (e. g. 400 Msps covering a bandwidth of 320 MHz). In this regard, a radio frequency network on chip (RFNoC) development framework provided by Ettus Research enables the FPGA processing in USRP devices (e. g. X310), so that data streaming between the FPGA and the host PC is used to implement an acquisition platform for off-line processing.
2) SDR IMPROVEMENTS One of the challenges for GPP-based SDRs is to provide a generic runtime environment (e. g. to meet the performance for 5G Networks), for which low latencies and high throughput are among the desirable enhanced features of SDRs. Although, the new generation of SDR platforms is incorporating advanced features such as LabVIEW FPGA module and RF Network on Chip (RFNoc), the advantage of this computational power is still underused. An interesting work is the employment of these tools to provided an embedded solution (e. g. using RF Network on Chip). In this way, it allows to introduce our designs into the SDR boards instead of implementing them on the host PC, thus mitigating the communication bottlenecks between the SDR board   and host PC, for achieving lower latencies and/or higher throughput.
Study Population and Data Loggers We captured 44 brown bears (27 females, 17 males, 14-233 kg, 1-23 years of age) by immobilizing them from a helicopter from April to June 2010-2020 according to an established protocol  (Arnemo and Evans, 2017)  and as part of an ongoing ecological study, the Scandinavian Brown Bear Research Project (SBBRP). All bears were equipped with a global positioning system (GPS) collar (Vectronic Aerospace GmbH, Berlin) with dual-axis acceleration sensors to monitor activity  (Friebe et al. , 2014). GPS positions were recorded every 60 min. We used the bear's body mass from the last time the bear was captured, which happens annually in spring. However, some individual bears were captured in February and June instead. Activity was measured as true acceleration six to eight times per second on two orthogonal directions.
Data Preparation We obtained T a and snow depth data of all Swedish weather stations from the Swedish Meteorological and Hydrological Institute (SE-601 76 Norrköpping, Sweden). We used inverse distance weighted interpolation from the R package gstat  (Pebesma, 2004)  and the function krige to spatially interpolate daily mean, minimum and maximum Ta and snow depth to hourly GPS positions of each bear or the den location during hibernation based on the three closest weather stations. We calculated day length for each day and bear with the function daylength from the R package geosphere based on the mean latitude for the study area. We defined female reproductive state during hibernation as either pregnant or non-pregnant based on T b and activity profiles  (Friebe et al. , 2014). During the study period, 9 out of 15 (60%) adult female bears became pregnant.
Pregnancy was later confirmed through observation of cubs during the annual monitoring in June. Based on these observations and the pregnancy status, we defined a status category and categorized a bear as either pregnant, solitary or accompanied by cubs. Except for bears followed from birth, aging was done by sectioning of the root of one of the first premolar teeth  (Harshyne et al. , 1998). We defined bears of at least 4 years of age as adults  (Zedrosser et al. , 2013). All bears younger than that were defined as subadults. Unrealistic T b (T b < 30 °C,  Tøien, et al. , 2011 , Evans et al. , 2016a; Evans et al, 2016b)  values were excluded from analysis, as well as the 2 weeks of data following a capture and 3 days following known episodes of disturbance including the annual cub monitoring from helicopter and experimental approaches  (Ordiz et al.
Detection of Biological Rhythms We used Lomb-Scargle periodogram (LSP) analysis implemented in the R package lomb to investigate periodicity in T b , HR and activity of the bears throughout the year and different states. It is recommended to perform this analysis on at least ten periods (in our case days) in order to detect biological rhythms  (Sokolove & Bushell, 1978). Since we also wanted to investigate the possibility of multiday rhythms, we chose a general time span of 25 days to search for periodicities but also included time spans of >= 15 days in order to be able to detect possible flexibility around transition states around den entry and den exit. We excluded irregular time spans, with data gaps >2 days, which originated from the exclusion of capture and disturbance periods. The beginning of a new state (active, transition, hibernation) determined the beginning of a new 25 days time span (Figure  1 ).
We searched for periodicities within each time span and selected the highest peak detected by the LSP algorithm. We followed characterization of rhythms based on van Beest et al. , 2020 and classified theses peaks as either ultradian  (2-18 h), diel (18-36 h)  or infradian (36-168 h) or, in the case of non-significant peaks as arrhythmic. The results of this analysis act as the response variable for the subsequent analysis. Additionally, we created actograms, thermograms and rasterplots of heart rate of the raw data for one representative 7 year old male brown bear with the geom_tile function in the R package ggplot.
Statistical Analysis We fitted generalized linear additive mixed models to investigate (Objective 1) the probability a certain rhythm in T b , HR or activity is shown depending on the seasonal state of the bear and (Objective 2) which internal and external factors may influence the probability of a certain rhythm to be shown. In order to address the varying environmental effects throughout a year, investigated in the second objective, we split the data sets and investigated hibernation and active states separately. We addressed both objectives in a Bayesian framework and analyzed them with the R package brms  (Bürkner, 2017). We used multinomial logistic regressions to model the categorical response variable Rhythm, included the default flat priors of brms and fitted the models with 3 MCMC chains.
A group-level effect for the individual Bear ID and Season was included (Table  2 ). For Objective 2 we set up a list of a priori candidate models (Table  2 ) and used leave-one-out cross-validation values (LOO) to select the most accurate model  (Vehtari et al. , 2017). In case several models were within a theoretical expected log pointwise predictive density (elpd) of <4, we used stacking of predictive distributions to evaluate which of these models has the highest probability to be the most accurate model  (Yao et al. , 2018)  and chose to present the model with the highest stacking weight. We excluded observations where no information about environmental conditions was available. Due to the low sample size for the HR data set (N = 177 for the whole year) we were unable to test Objective 2 for HR.
Objective 1 Detection of Variation of Rhythms in Activity, T b and HR throughout the Year We used three different data sets (Activity, T b , HR) in our analysis for biological rhythms in free-ranging Scandinavian brown bears. We included 40 bears and 425 individual 15-25 -day time spans   S3-S6  for Objective 1 and 2 for T b , activity and HR datasets. All models for Objective 1 were fit with a group-level effect for the individual Bear ID. All models for Objective 2 were fit with a group-level effect for the individual Bear and Season.
T b Data Set The seasonal changes in raw T b data throughout the year are represented in Figure  4A , which shows the gradual adjustment of T b around den entry and den exit dates and generally low T b during hibernation (  Figures 4E, F ). During their active period in late spring, summer and early autumn, bears show a pattern of higher T b from sunset to late morning and low T b during midday (Figures  4A-C ). Rhythms in T b were present as diel, ultradian and infradian rhythms. During the active state bears had a 69% [62-76%] chance of showing diel (Figure  3 , Figure  4D ) and 22% [16-29%] chance of showing ultradian rhythms in T b , respectively. During hibernation, this changed to bears having a higher probability of showing infradian rhythms (79% [CI 71-87%]), (Figure  3 , Figure  4G ) but only a 21% [CI 13-29%] chance of a diel rhythm.
Natural deep eutectic solvents (NADES) represent a promising group of green solvents employed for the extraction of bioactive compounds from medicinal plants. Due to the wide range of polarities of investigated solutes, and an outstanding number of combinations of NADES components, fine tuning and selection by software for modeling and evaluation of thermodynamic properties of solvents and solutes is a necessary step preceding the extraction from real samples. In this study, four hydrophilic NADES were chosen for the prediction of solubility of 19 bioactive compounds from Mediterranean plants, which was performed by COSMO-RS software. NADES structure optimization was performed by pseudocomponent approach and individual constituent approach. Change of hydrogen bond donor components of NADES did not show a significant influence on the solubility of screened solutes.
[21, 22] ue to a vast number of possible combinations between compounds forming NADES and different outcomes of extraction resulting from simple modifications of NADES, in silico methods are used to select the most suitable candidates for a specific application before any experimental procedure. COSMO-RS software was developed by Klamt and coworkers as a statistical thermodynamic method for the calculation of molecular descriptors and physicochemical properties based on a quantum chemical approach. [23] COSMO-RS prediction is performed by an initial step in which the observed compound is placed in a dielectric continuum to probe the charge density on the molecular surface and to perform energy minimization. In this way, the σ-profile and σ-potential curves are generated, giving the information on the polarity distribution of molecules.
COSMOthermX Calculations COSMOthermX program (version C30 release 13. 01) was used to calculate the relative solubility of solutes in NADES in terms of the logarithm of the solubility in mole fractions (log10(xsolub)). As in the previous reports by our group, the logarithm of the best solubility was set to 0 while the other solvents were shown relative to the best solvent. Additionally, the logarithm was expressed into a probability of solubility (%). The calculation was performed at 25 °C and 30 °C for each solvent. As the structures of the solutes were absent from the COSMOtherm database, their molecular geometries were optimized to the lowest energy minimum using TURBOMOLE GUI (TmoleX). For every tested solute, a single conformer generated by Turbomole was used for solubility screening.
RESULTS AND DISCUSSION The aim of this preliminary study was to explore the potential of NADES as environmentally friendly and affordable solvents for concurrent extraction of polar and nonpolar bioactive compounds (Figure  S1 ) from various Mediterranean herbs by in silico approach. Up to date, there are only a few reports on the computational modeling of NADES for purpose of extraction of bioactive compounds from natural sources. Solubility prediction was performed by COSMO-RS software under different initial conditions for a group of bioactive components from Mediterranean plants in four selected NADES. Structural optimization of the selected NADES was performed by individual constituent approach and pseudocomponent approach. The referent compound for extractions of bioactive compounds, against which the series of NADES were compared, was n-hexane, a commonly used solvent with low polarity, optimal boiling point, and easy procedure of extract recovery.