dataesr/scientific-paragraphs-categorization huggingface dataset:
Interpretation of result: In the following figures, we represent values of δðαÞ as the function of α. To simplify computation, we consider the case of two honest miners M 1 and M 2 (i. e m ¼ 2) and one SM-pool miner in the network (i. e l ¼ 1). We fix the distance between M 1 and M 2 equal to 1 (meaning k:d 12 ¼ 1). We also recall the choice of constants λ, while σ remains free and does not constitute the real values. The point of thinking in this paper is to demonstrate how the value of γ could be studied as a consequence of these assumptions: the propagation delay of information between two miners is normally distributed with mean proportional to the physical distance (k:d 12 ) and a constant variance independent of other transmissions (σ 2 ). Let us recapitulate the quantities which allow us to compute the following Figures with MATLAB : 8 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > < > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > : A À1 ðωÞ ¼ 1 ffiffi ffi 2 p 0 B B @ " 8ω π 2 þ d 4 12 #1 2 þ d 2 12 1 C C A 1 2 : p 2 ¼ λ σ : 1 ffiffiffiffiffi 2π p Z þ∞ À∞ Z þ∞ 0 e Àλω F A À1 2 ðωÞ ðuÞdωe ÀðuÀkd 12 Þ 2 2σ 2 du: E ¼ α 2 p 2 ; V ¼ α 2 2 p 2 À 1 À p 2 Á δðα; λ; σÞ ¼ 1À F Nð0;1Þ 1 À α 2 À E 1 ffiffiffi ffi V p : 9 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > = > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > ; In the first case (Fig.
Acknowledgements Author of this article,  M. BA , would like to thank the  laboratory MODAL'X of Universit e Paris Nanterre  to support this work. He would like to thank the members of the Laboratory MODAL'X for discussions he had with them, and the suggestions, remarks and lectures they have made on this paper. He would like also to thank the many thoughtful individuals from the  Bitcoin & Ethereum Forum , whose ideas helped us to form the basis of this work, as well as the community of bitcoin for their encouragement and enthusiasm.
Extrapolating the fitted data in Fig. 4(d) , and under the conservative assumption that only 50% of this power (i. e. 2 mW) is effectively injected into the laser, we estimate an available locking range of 18. 8 -24. 8 GHz (75 -102 µeV), depending on the bias current. This locking range is an important number for the technological optimization of the VCSEL array's spectral homogeneity which needs to match at least this range to allow for efficient photonic RC 10.
The corresponding experimental data for all 25 VCSELs is presented in Fig. 5 (e). The figure essentially shows the bias current needed to achieve a target wavelength in the available range of about 977. 8 nm to 978. 6 nm for the present array. Here, the wavelength increase above laser threshold with the bias current is due to heating and the corresponding change of the refractive index of the laser devices. Thanks to the high quality of the underlying wafer material and the well-developed device processing both, the input-output characteristics presented in Sec. III as well as the spectral properties are very homogeneous across the 5 × 5 array. To assess and discuss this important point in more detail, we determined the variation of bias currents within the array required to achieve a desired emission wavelength in the possible range of about 977.
42 at low target wavelengths and is decreasing with longer wavelengths to about 0. 13, as the average output power of the array is increasing. Overall, the measurements of the tuning abilities have shown that the fabricated array allows us to compensate any spectral inhomogenities of the array and align the lasers to achieve a globally injection-locked state. Con-sidering all the discussed data we find that a low target tuning wavelength is the most beneficial regime for operating the VCSEL array as a reservoir system, although the range of choice here is limited by the geometric dimensions of the array pitch and the DOE characteristics 1829. On the one hand the main advantage of low target wavelengths is an overall low output power level, which reduces the energy footprint. Considering a bias current of 0.
76 mA the average emission power of the lasers in the array is about (178±24) µW. Together with the spectral homogeneity in this case of about 42 µeV, as estimated above, one can determine with the data from Fig. 4 (d) a needed injection power ratio of about 3. 4 and with that a power consumption for the injection locking for one VCSEL of about 0. 609 mW. Together with typical bias voltages of about 2 V the total power consumption for one VCSEL would be about 2. 1 mW, and about 45 mW for the complete array. With this we estimate the energy needed for one induced non-linear transformation with a value of only 104 fJ per VC-SEL and 2. 6 pJ for the complete array, while considering a modulation bandwidth of the nonlinear transformation of up to 20 GHz 17. On the other hand, the major cost for operating at low bias currents and wavelengths is a relatively large distribution of output powers compared to the average value, which leads to a wider distribution of the applied power ratio.
They must also be transcribed and formalized into nonaudio data that can be more easily processed and compared. To do this, data must be classified and characterized. The case studied here is that of a cooperation dyad playing the same game of Tetris with complementary roles. The communicative interactions between the individuals were observed as short and repeated throughout the common task. The projective model of informational dialogue presented by  Vernant (1992)  is not suitable here since the modeling would have to be done for each exchange independently. Our objective is to represent the entire dialogue and all the exchanges that make it up on the same graphical representation in order to account for the dynamics of the exchanges and their fluctuations. Since we want to identify the elements of the dialogue to characterize the dynamics of the exchanges, we are interested in the nature of these exchanges.
They each have a screen in front of them that allows them to see the game and the actions performed. The experimental protocol takes place in two stages: 1) Participants play Tetris alone for 10 minutes to habituate to the controls; 2) they are then assembled in dyads and play cooperatively for 10 minutes. They are instructed to achieve the best possible score and are encouraged to communicate verbally as much as they wish, but they cannot see each other. In this situation, we record the conversational exchanges between the participants. This allows us to collect a corpus of data on which we develop and formalize our model for Analyzing Communication in Dyad Cooperation, called the ACDC model.
This application of the ACDC model to a qualitative database is conducted by several judges and results in integrated qualitative and quantified data, more detailed below. Finally, this data transformation allows us to compare different points of view through inter-judge measurements and to quantitatively validate the reliability of our analysis model. The integrated qualitative and quantified data are also used at the inference level, in order to allow a more solid understanding of the results of the experiment and to identify possible improvements to our analysis model. The final formalization of our analysis model integrates the qualitative and quantified data into a single visual plan. This formalization is linked to a mixed methods' technique called "joint display", as suggested by  Guetterman et al (2015).
In addition, they are directive, i. e. they ask explicitly the listener to perform a specific action. In  Vernant (1992) , this categorization corresponds to the 'directional initiator'. Searle (1990)  and Vernant (1992) group orders, advice, questions or requests for undertakings under these directive performative language acts. In order to validate the categories with respect to the task of the cooperative Tetris game, we conducted focus groups and card sorting sessions. Fourteen students aged 20 to 30, including 8 men and 6 women, were divided into three groups, each of which participated in a focus group organized around the characterization of the categories, followed by a card sorting session. Each group sorted 28 exchanges extracted from a 10-minute audio recording from a pre-experimental cooperative Tetris game.
-Constitution of dyads for the task of cooperative Tetris. The formation of the dyads for the experiment was carried out using the data collected during the pre-tests. Men and women were separated to form non-mixed dyads. In order to have subjects with homogeneous game performances (neither too weak nor too strong), we excluded subjects with performances in the first and last quartile. In total, we obtained a sample of 8 dyads: 3 male and 5 female.
-The Cooperative Tetris experience The 8 dyads formed participated in the experiment as follows: The participants were informed individually of their schedule without knowing that they were in dyads. The observers received them in a room equipped with two computers with the version of Tetris developed on Matlab and used in pre-test (see Fig. 1 ). The two participants were placed at tables next to each other and separated by a screen. They each had a screen and a keyboard with which they could use two keys to play Tetris. The participant "P1" of each dyad was always in charge of the rotation of the pieces and their rapid descent, via the "up arrow" and "down arrow" keys of the keyboard. Participant "P2" was always in charge of horizontal movements using the "O" (left) and "P" (right) keys of the keyboard.
Wilcoxon tests were conducted and showed that: (1) sets of stimuli of the same emotional valence did not differ from one another in terms of valence and level of arousal, (2) sets of stimuli of different emotional valence differed in terms of valence and the emotional sets differed from the neutral sets in terms of arousal. Table  1  shows the respective mean scores for valence and arousal for each set of stimuli. To manipulate image quality, we created a second, low-quality, version of the 58 3D models. To do so, we used the Autodesk Maya software to remove approximatively between 30 and 50% of the polygons of each 3D asset (in a way that still permitted recognition), while the poorest texture and a level of shade were chosen for assets and environments in the Unity editor.
Statistical analysis The mean scores for correct free recall (item memory for virtual stimuli), sense of presence (score obtained by summing the scores of the five questions testing sense of presence), and emotional pleasantness and arousal (SAM test) were used for the statistical analysis. For more precise analysis of SoP, ANOVAs have been conducted on each of the five questions separately and have been reported in the Supplementary Material. The means were calculated for places presenting stimuli that induced the same emotion (Island -negative and neutral; City -positive, negative and neutral). The data were analyzed separately for the Island and City environments. Thus, the factorial design was 2x2x2 in the Island and 3x2x2 in the City, (emotion)x(device)x(quality) with emotion as within subjects factor and device and quality as between subjects factors.
Acknowledgments This work was supported by the  LABEX CORTEX  (Grant  ANR-11-LABX-0042 ) of  Université de Lyon , within the program " Investissements d'Avenir"  (Grant  ANR-11-IDEX-0007 ), operated by the  French National Research Agency (ANR). We thank  Tim Pownall , native English corrector, for proofreading the manuscript,  Manon Manassès ,  Manon Couzin  and  Camille Victor  for their help in data acquisition and the company VR Connection for their support. We also warmly thank  Thomas Fugier  for designing the virtual environments.
ACKNOWLEDGMENTS We thank  D. G. Angelakis ,  M. Estarellas ,  M. Hanks  and  H. Price  for valuable discussions. We thank  National Research Foundation Singapore , the  Ministry of Education Singapore Academic Research Fund Tier 2  (Grant No. MOE2015-T2-1-101 ), and the  Japanese QLEAP program  for support. The  Grenoble LANEF framework  ( ANR-10-LABX-51-01 ) is acknowledged for its support with mutualized infrastructure. The computational work for this article was partially performed on resources of the  National Supercomputing Centre, Singapore  (https://www. nscc. sg).
The mean signal intensity and SD for each phospho-specific antibody on the array were determined for these four samples (Fig. 1 ; the entire datasets are available in Supplementary Data 1). Despite some variation, individual data points for each antibody remained within 2 SDs of their mean, illustrating that sample-to-sample variation was minimal. Overall changes in phosphosignaling during infection. To assess the impact of infection on host cell signalling, whole-cell protein extracts were obtained from synchronized P. falciparum cultures at three time windows during the erythrocytic cycle: 4-12 h post invasion (hpi) (rings, n = 3), 24-28 hpi (trophozoites, n = 3) and 44-48 hpi (segmented schizonts, n = 2). Each of these extracts were loaded onto a separate antibody array and compared to the mean of the uRBC lysates collected in parallel and containing RBCs from the same donor as the iRBC sample (see above).
In stark contrast to the minimal variation between the uRBC samples (see above), analysis of the iRBC extracts showed that 6% (ring-stage), 23% (trophozoite-stage) and 12% (schizont stage) of the phospho-specific antibody intensities differed by more than 2 SDs from uRBC mean. The datasets for each of the three developmental stages showed no internal variation >2 SDs between the biological replicates (Supplementary Fig. 1 ), further confirming the robustness and reliability of the approach (Fig. 1 ; the complete datasets are available in Supplementary Data 1). Overall, this implies (i) that there is little variation between biological replicates of uRBCs, attesting to the reliability of the system, and (ii) that infection with P. falciparum causes significant variation in the signals yielded by phospho-specific antibodies, suggesting that P.
Some antibodies displayed a weak fluorescence signal, likely due to the low abundance of the target protein. The antibodies yielding a signal intensity below a fluorescence reading of 1000 units in both the erythrocyte control and parasite-infected samples were removed from further analysis, as recommended by Kinexus (Supplementary Data 1). This included 26 signals from the ring array, and 41 and 48 signals from the trophozoite and schizont arrays, respectively. Broad analysis of the post-filtering iRBC data set. Following low and cross-reactive signal removal, 1 of the ring-stage signals, 29 of the trophozoite-stage and 17 of the schizont-stage signals had fold changes > 2 or <0. 5 compared to their uninfected counterpart, revealing dynamic changes in the phosphorylation of host signalling proteins during P.
In contrast, phosphorylation of B-Raf at S729, a Ras-independent phosphorylation event carried out by AMP-activated PK (AMPK) in response to energy stress, increased at all three life cycle stages with a fold change ranging from 1. 69 to 2. 63 across parasite development (Figs. 3  and 4a ). Of the two AMPK antibodies on the array, one was discounted due to cross-reactivity with a parasite protein, whereas the other (AMPKa2 S377) shows a slight increase (1. 17-fold change) in phosphorylation at the trophozoite time point, supporting that this kinase may also be activated in iRBCs (Supplementary Data 1). We next determined the total amount of B-Raf and phosphorylated B-Raf S729 at each life cycle stage using western blotting. Detection of total B-Raf protein using a pan-antibody independent of phosphorylation showed that the amount of fulllength B-Raf was greatly reduced at trophozoite and schizont stages compared to uRBCs and rings (Fig.
An antibody against Glycophorin-C was used as a loading control (lower panel), n = 3 independent experiments. d Synchronized P. falciparum cultures were treated in 4 h windows with 2. 45 µM SB-590885 (5× IC 50 , see Fig. 6 ), 0. 091 µM artemisinin or DMSO (vehicle control), starting at 0 (rings), 22 (trophozoites) and 38 (schizonts) h post invasion (the black arrows indicate the end of treatment, where the medium was replaced with fresh medium without drug). The parasitemia was then monitored until the next cycle of parasite development to assess parasite survival. Starting parasitemia was normalized to 5% across the biological replicates (n = 3) error bars represent the SEM. Source data are provided as a Source Data file. inhibitors of these kinases, display low µM potency against P. falciparum in vitro  15.
Full western blottings are available in Supplementary Fig. 6. IC 50 determination. P. falciparum-The IC 50 values of Crizotinib, PHA-665752, SB-590885, Sorafenib and Artemisinin were determined with asynchronous cultures with a starting parasitemia of 0. 25% in 2% haematocrit. Cultures were incubated with the compounds for 72 h before adding SYBR-gold nucleic acid stain (1 : 10,000 dilution) (ThermoFisher Scientific) modified from ref. 67  substituting SYBR-green for SYBR-gold. Plates were incubated with SYBR-gold for 1 h in the dark prior to reading fluorescence on a Tecan plate reader (I-control software) and the inhibitory IC 50 determined using GraphPad PRISM (GraphPad software). P. knowlesi-P. knowlesi growth inhibition assays using ring-stage parasites were set up at 1% parasitaemia and 1% haematocrit in 96-well round-bottom plates at a final volume of 45 µL as described  68, 69.
A 10× final concentration of drug and controls was added to make the final volume to 50 µL and the drug assay cultured for 50 h until parasites reached late trophozoites in the next growth cycle. Assays were stained with 10 μg/mL ethidium bromide (EtBr, Bio-Rad) for 1 h and washed prior to flow cytometry (Becton Dickinson LSR) assessment of parasitaemia with gating as per established protocols  70. Parasitaemia counts were quantitated using FlowJo software (Tree Star) and the inhibitory IC 50 determined using GraphPad PRISM (GraphPad Software). Time-dependent inhibitor treatment of parasites. Highly synchronous cultures (0-4 h post invasion) at 2% haematocrit treated with dimethyl sulfoxide (DMSO) (vehicle), Crizotinib, PHA-665752, SB-590885 or artemisinin at 5× the IC 50 values were monitored at 12 h time intervals over two full asexual intra-erythrocytic cycles (84 h) by flow cytometry.
They were fed a commercially prepared autoclaved dry rodent diet and water, both available ad libitum. The health of animals was monitored by routine daily visual health checks. Cohorts of seven female, 10-week-old BALB/c mice per treatment group were infected by intravenous inoculation with 10 6 infected erythrocytes. Assays to determine parasite growth were performed as described  71  , using the reporter parasite line PbGFPLuc con (RMgm-29 in the rodent malaria genetic modification database, http://www. pberghei. eu/index. php?rmgm=29), which expresses a green fluorescent protein-firefly luciferase fusion protein under the control of the constitutive eef1a promoter  72. Treatment with PHA-665752 or solvent control was 3 h thereafter and on day two post infection by intraperitoneal injection of 25 mg/kg/day of PHA-665752.
Acknowledgements We thank  Dr. Kylie Quinn  for lending her Flow Cytometry expertise and the staff of  Monash FlowCore Facility , in particular  Andrew Fryga  and  Adam Dinsdale , for their continued experimental assistance. We also thank  Professor Roger Daly ,  Dr. Teresa Carvalho , A/ Professor Jose Garcia-Bustos  and  Professor Brian Cooke  for fruitful discussions. This work was supported by the  Australian Government National Health and Medical Research Council  (Project Grants  APP1082619  [CD] and  APP1143974  [DW]),  Australian Research Council PhD Scholarship (AB) ,  Hospital Research Foundation  Fellowship (DW) and internal support from  Monash University  and the  University of Adelaide (Beacon Fellowship (DW).
Beam splitting ratio of the polarizing beam splitter The respectively. By the ray tracing calculation, we can obtain the interference fringe intensity on the CCD is: ( ) ( ) ( ) ( ) 0 2 1 3 1 1 ' 1 cos 2 4 2 1 1 sin 2 1 2 4 i i I S S Ux S Ux S       = + + - - - (8) Compared with Eq. (  2 ), the extra S3 term in Eq. (  8 ) will cause reconstruction error in S0 and affect the demodulation accuracy of S1 and S2. Set the Stokes parameter of the incident light as  Select a suitable rectangular filter as shown in Figure  5 , do inverse Fourier transform, and calculate the degree of the linear polarization (DoLP) as 0. 86. Compared with the DoLP of the original incident light, the reconstruction error is 13. 5%. Figure  5. The red and blue marked squares denote the data area that carries the information of S0 and S21 In the same way, we can calculate the modulation degree of Figure  2  (a) -(  c ) is all 0.
Microsoft has recently released a mixed reality headset called Holo-Lens. This semi-transparent visor headset allows the user who wears it to view the projection of 3D virtual objects placed in its real environment. The user can also grasp these 3D objects, which can also interact with each other. The framework of this new technology taking into account this physical approach (interactions, collisions) is called mixed reality. We had the opportunity to digitally transform a conventional nutrition workshop for patients waiting for bariatric surgery by designing a mixed reality software using the HoloLens headset. This software is called HOLO_NUTRI. In this paper, we present this software and its assessment (acceptance of this technology) by a cohort of thirty patients.
Interests in digitalizing the conventional workshop We have proposed the digitalization of the classical workshop CONV_WORK, previously described in section 1. 2. This new workshop, named DIGIT_WORK afterwards, has the following main objectives to propose: the digital version of the menu composition using a software that should be rather playful. This software application is called HOLO_NUTRI, a more detailed analysis of the elaborated menu (several quantities associated by food, meal time estimation, taking into account of the chewing time, etc. ), the numbers and quantities of foods being more important for this digitalized workshop make it possible to develop more personalized menus, an analog, in the computer application, of the patient's gesture when he or she takes one card representing a food and the associated quantity in the CONV_WORK workshop.
Development environment Whatever the type of reality envisaged, the development of computer applications to use this hardware is done either from proprietary SDKs (Software Development Kit) or by using interactive 3D graphical application development engines such as Unity  [53]  and Unreal Engine  [54] , originally designed for the development of video games but now also addressed to wider professional sectors (automotive, AEC -Architectural, Engineering and Construction-, etc. ). For our application, we first design several 3D resources (3D models and animations made in Blender software  [55] , see Section 2. 3). The development was carried out with the Unity engine  [53]  (import of 2D images, 3D models and animations). Several scripts were designed to describe the wanted user interactions on 3D objects; these scripts (integrated in our Unity framework) were written with the C# language from the Microsoft Visual Studio programming environment  [56]  and with the HoloToolKit library  [57]  specialized for mixed reality with the HoloLens headset.
Once all these assets are compiled, it produces our software HOLO_NUTRI (that can be tested on a PC through an emulator). By plugging the HoloLens headset into the PC, the application can then be deployed/embedded into the headset. The user, wearing the headset, can then run HOLO_NUTRI from the HoloLens main menu without the headset being connected to a PC (by either cable or WiFi).