dataesr/scientific-paragraphs-categorization huggingface dataset:
Although EMS provides a high level of super visionary control in EnergyPlus, it requires a high level of coding to override the EnergyPlus source code  [111]. For employing EMS to control adaptive dynamic envelope elements, exterior roller blinds, and Venetian blinds in this study, different sensors read the data and then send them to the actuators. Finally, this control logic will convert to the physical reaction of dynamic shading elements. EnergyPlus Runtime Language (Erl) is employed to describe the control strategies for Ener-gyPlus when the model is running. All windows in all automated control algorithms have been controlled by the roller shades through EMS, and each window was separately controlled based on the local conditions and various sensors. A built-in plugin in Grasshopper, Ladybug-tools, was used for the simulation procedure.
Conclusions As indicated in the literature, there is no standardized method for evaluating control systems for adaptable façade elements, particularly dynamic shadings. As a result, ISO 52016-3 offered a series of default control strategies to compare buildings' energy demands. Therefore, this paper aims to increase current knowledge about the new ISO 52016-limitations and opportunities and to enhance the energy performance of office buildings incorporating adaptive envelope elements. This research consists of successive stages, from data collection to parametric study and dynamic simulations. The performance of fully automated control strategies of exterior roller blinds and Venetian blinds was evaluated afterward. A south-facing office room was chosen from an existing high-performance office building in Brussels to perform energy simulations.
The results of two scenarios, roller blinds and Venetian blinds controlled automatically by strategies proposed by ISO 52016-3 were assessed for different orientations. Two more scenarios, including no shading and fixed shading, were also considered to understand better the effects of control strategies and shading devices on building energy needs. The results of building energy demand, including heating and cooling loads, internal temperatures (indoor air temperature and indoor operative temperature) covered by ISO 52016-3, and artificial lighting demand covered by EN 15193-1 with exterior roller blinds and Venetian blinds, were reported. In order to conduct the simulation, different software was used. The model was created in Grasshopper, and the simulation procedure was carried out using a builtin Grasshopper plugin called Ladybug-tools.
Acknowledgments We would like to acknowledge the  Sustainable Building Design (SBD) Laboratory at the University of Liege  for using the monitoring equipment in this research and for valuable support during the experiments and data analysis. The authors would like to acknowledge the contributions of  Dr. Mohamed Hamdy  for his valuable input and comments. The authors would also like to gratefully acknowledge all ISO/ DIS52016-3 committee members and  European Solar-Shading Organization (ES-SO)  for their support and providing excellent discussions during different step of this research.
S1A ). Streptavidin-coated beads were washed two times by spinning down 10 µL of solution at 0. 5 % w/v diluted in 1 mL of mTOR buffer. After a final resuspension in 50 µL of mTOR buffer supplemented with 500 nM of rapamycin, the particles were injected in the AFS chamber and allowed to settle for few minutes so that they can bind to the extremity of the second shank, which is decorated with biotin molecules (Fig. S1A ). A gentle flow of rapamycin containing mTOR buffer was then applied to remove the untethered beads. All FKBP12-rapamycin-FRB data presented were obtained on the same AFS chip, 2 different injected samples, and 4 different fields of view (FOV) (beads ID1-5: Manuscript submitted to Biophysical Journal 5 sample 1 FOV 1; beads ID6-13: sample 1 FOV 2; beads ID14-19: sample 1 FOV 3; beads ID20-21: sample 2).
Measurement protocol and data acquisition The setup is controlled through the LABVIEW software provided by the manufacturer (Lumicks v1. 4. 0), which we have modified for our needs. More precisely, we have added an option to generate periodic acoustic force patterns corresponding to tunable steps of power P and duration T. For example, in a typical unbinding experiment, a 0 % power step of typical duration T A ≥5 min is used to determine the anchor point of each bead. Next, a cycle alternating a very low power (P L < 0. 01%) step and test power step (power P) is repeated typically 100 times. The corresponding durations T L and T need to be adapted to the nature of interacting partners, and can vary from a fraction of a minute up to 15 min. As a rule of thumb, T is set as, at least, 2 or 3 times the inverse of the expected off-rate.
The AFS software also allows one to track each bead on the fly and in 3D thanks to real-time image analysis. On a standard desktop computer, up to 100 beads can be tracked at 55 Hz. The x,y-position corresponds to the center of the bead diffraction pattern while the z-position is determined using a predefined look-up-table (LUT) ranging from 0 to 10 000 nm in 100 nm steps  (41). Importantly, whereas the coordinates in the horizontal plane are absolute, the one along the vertical axis is only relative. The individual bead traces are recorded in a tdms file (i. e. LABVIEW format) together with the power amplitude, chip driving frequency, and temperature.
A 1D gaussian filter of window size 1 s is first applied and the signal is normalized between 0 and 1. This duration is chosen in order to reduce noise while keeping the accuracy of on dwell time duration. The crossings of a 0. 5 threshold value are recorded and the step size is determined following the original procedure found in github. com/thomasbkahn/stepdetect. If no step is detected, the average altitude Z is compared with the middle altitude representing equidistance between the open and closed states plateau, typically Z * = 900 nm. If Z > Z * , one considers that the J-DNA did not close back at the previous low power interval (no-close event). If Z < Z * , one considers that the J-DNA did not open during the test power interval. The lifetime of the close state is measured between the onset of high power application plus a delay and the opening time.
The delay accounts for the time it takes to effectively apply the force on the bond, which is largely set by the duration of bead uplift and empirically estimated to be 1 s maximum. 6. Power spectrum calculation. The single sided power spectrum density (PSD) of the bead fluctuation signal is calculated separately on xx A and yy A thanks to the signal. periodogram routine from the PYTHON Scipy package. In a default mode that is used for the "force calibration on the fly", we take into account all the points tagged as belonging to the open state. Alternatively, in the independent calibration mode, a specific time interval can be selected, for which phases 1-4 are performed as above and phase 5 is skipped. This mode can also be used to calculate the PSD using data obtained at a high frame rate and specifically dedicated for calibration of large forces.
3B ). Performing an average of the latter results with the inverse of the SDs as weight yielded k 0 off = 30 ± 7 × 10 -3 s -1 and x b = 0. 34 ± 0. 32 nm (Fig. 3B , black square). Alternatively, all the off-rates determined on all 21 beads were pooled by force bins (Fig. 3A , black circles) and the obtained dataset was fitted using a single Bell plot, taking into account the error bars. It gave k 0 off = 30 ± 1 × 10 -3 s -1 and x b = 0. 37 ± 0. 03 nm (Fig. 3B , black circle). Therefore, the parameters provided by these two approaches are consistent. Furthermore, they agree with the ones retrieved with the same J-DNA mounted on magnetic tweezers: k 0 off = 30. 5 ± 0. 2 × 10 -3 s -1 and x b = 0. 43 ± 0. 01 nm (20) (Tables  S3 , S4 and Fig. 3B , green dashed-and-dotted lines). The off-rates extrapolated at zero force are also consistent with the determinations achieved by SPR, 20.
Of note, the measurement error of off-rate per molecule can be visualized on Fig. S18  (typically set by the measurement of ca. 80-100 events), while Fig. 3A  shows intermolecular heterogeneity. Each color dot on Fig. 3B  relies on the observation of 250 to 1020 rupture events (see Tables  S1  and S2  for detailed statistics). Similar measurements and analyses were performed for 9 J-DNA scaffolds functionalized with Nef and Nef19. This complex being much more long-lived than the FKBP12-rapamycin-FRB one, we aimed at applying higher forces to achieve unbinding with waiting times much shorter than 1/k 0 off 10 4 s. We used larger beads (3 µm diameter), in order to increase the acoustic force at equal power, without generating too much heat or shifting the resonance frequency too strongly. The force vs power data are represented on Fig  S19:  a sharp force increase can be observed when changing the diameter of the beads from 1.
ACKNOWLEDGMENTS We thank Lumicks (in particular  Douwe Kamsma  and  Eugen Ostrofet ), as well as  Pierre-Henri Puech ,  Jean-François Allemand  and  Yan Jie  for fruitful discussions. The AFS setup was acquired thanks to the grant Projet exploratoire région PACA 2017 -AcouLeuco obtained by FR. We thank  AMIDEX Emergence Innovation (project ForSelecAntibody) ,  Plan Cancer PhysCancer program  (project  ComPhysAb ),  European Research Council  ( ERC , grant agreement No. 772257 ),  Human Frontier Science Program  ( HFSP , grant No. RGP0056/2018 ),  PSL valorisation  (project  J-DNA ),  CNRS Defi Instrumentation aux Limites  (project  ForcaRapa ),  Marie Curie Sklodowska action (MSCA-IF , grant agreement  895819 ), and  Labex Memolife  (project  Gephyrin ). The Molecular Motors and Machines team at  IBENS  is an "Equipe labellisée" by the  Ligue Nationale Contre le Cancer.
Study Design: We conducted a retrospective cohort study on Thai residents aged 18 years or older, with a laboratory con rmed SARS-CoV-2 infection during 1 May -31 July 2022 period. Date of rst positive SARS-CoV-2 test served as the index date. Reinfections, de ned as a positive SARS-CoV-2 test at least 90 days prior, accounted for <0. 6% of this cohort. Baseline clinical characteristics and SARS-CoV-2 test details were extracted from the CMC-19 HIS. The types of COVID-19 vaccines, and dates of vaccinations were extracted from MOPH-IC immunization database. Severe COVID-19 outcome was de ned as requiring Invasive Mechanical Ventilation (IMV) during hospital admission and/or death during hospital admission. Records of all included subjects were followed till death, or up to 30 days from rst positive SARS-CoV-2 test.
In brief, all COVID-19 cases detected in Chiang Mai province are reported into the web based HIS of Chiang Mai Provincial Health O ce (CMC-19 HIS). Reporting of all COVID-19 cases is mandatory under the Communicable Disease Control Act. When a COVID-19 case is detected, either at screening centers, hospitals or out-patient clinics, the healthcare staff enter the patient details, including laboratory results into the CMC-19 HIS under a unique ID. Data on severity and progression of the disease including requirement of ventilatory support and treatments are recorded in each hospital's information system, which is linked with CMC-19 HIS. Deaths which occur within the province are reported to Chiang Mai Provincial Health O ce and are routinely updated in CMC-19 HIS. All national vaccination records are centrally captured in the Ministry of Public Health Immunization Center (MOPH IC) database maintained by the Ministry of Public Health, Thailand.
, 2018). There are no studies that compared basal inward rectifier currents between stem cell-derived CM treated with RA or not, but in small datasets activation of the I K,ACh was restricted to RA-treated stem cellderived CM  (Devalla et al. , 2015; Lee et al. , 2017; Argenziano et al. , 2018). In one study, the effect of muscarinic receptor activation on APD 90 in RA-treated atrial hESC-CM was hard to detect at all  (Devalla et al. , 2015) , but accounted to ~20%-30% in atrial hiPSC-CM or atrial EHT  (Lemme et al. , 2018; Goldfracht et al. , 2020) , close to the situation in human atrium  (Dobrev et al. , 2001). I K,ACh is another atrial-selective potassium current that undergoes electrical remodeling. Shortening of APD 90 upon activation of I K,ACh is lost in AF and constitutively active I K,ACh  (Dobrev et al.
Despite the progress of high-throughput methods, measuring everything in one lab is not realistic. Thus, when the dataset is expanded to include measurements from multiple labs, the physiological variability will be exacerbated by inter-lab variability. More importantly, due to practical reasons, the depth of phenotype characterization in this approach will be limited, as it was in the  Kernik et al. (2019) s study. Therefore, the model formulations need to be biophysically less detailed with fewer parameters so that their values can actually be measured in vitro. Thus, the model's application area is restricted to the phenotypic space, which the data in question present-limited robustness. On the other hand, the more detailed hiPSC-CM models that have been employed in the population-based approach follow the common iterative modelling tradition, inheriting some model components and their parameters from previous, non-hiPSC-based, model generations-limited specificity.
This criterion is not explicitly evaluated, but enforced by the exploration algorithm 1 (line 8), where score(s) returns the position of a given solution in the objective space, and pareto f ront(S) returns the set of non-dominated solutions. This algorithm was run 2-fold using TRAIN+DEV datasets, half of the dataset was used to generate MWE-Ls, and another half for OA evaluation. This was done twice per corpus, Algorithm 1: Bottom-up Greedy Pareto Data: f eatures: the set of all considered features s: starting subset of f eatures 1 Initialization 2 res n-1 ← { s } 3 res ← { s } 4 while res n-1 ̸ = ∅ do 5 Q ← ∅ 6 foreach s i ∈ res n-1 do 7 foreach f i ∈ features \ s i do 8 if score(s i ∪ { f i }) ̸ = score(s i ) 9 Q ← Q ∪ { s i ∪ { f i } } 10 res n-1 ← pareto_f ront(res ∪ Q) ∩ Q 11 res ← res ∪ res n-1 Result: res once with { lemma }, and once with { f orm }, as the starting set of features s.
4  All solutions generated in this way were then re-evaluated by instantiating the lexicon from TRAIN+DEV, and scoring it against the TEST dataset. In the end,  12, 142, 14, 36, 7, 20, 22, 22, 16, 22, 16  solutions were selected for DE, EL, FR, HE, HI, IT, PL, PT, SV, TR, ZH respectively. 5 Table  1  presents the solutions provided by algorithm 1 on the French corpus. A clear distinction between solutions can be made depending on whether they use f orm or lemma. The former have high precision and low recall, while the latter have more balanced precision and recall. Solutions using both act as the former. As shown in table 2, the solutions with the highest precision always use f orm and most of them use deprel. The solutions with the highest recall systematically use lemma. The most harmonious solutions (i.
2 -to our { lemma, deprel }-CSS lexicon and the union of their predictions. Hewbrew (HE) and Chinese (ZH) aside (due to lemmatization issues), Fscores from our lexicons are higher than MTLB-STRUCT on 3 languages and within 10 points on the other languages, which shows that OA achieved by { lemma, deprel }-CSS lexicons can at the very least be high enough to be of interest. As for the unions of our lexicon and MTLB-STRUCT annotations, their F-scores are higher than MTLB-STRUCT's scores on 5 languages and are only within 2 points of MTLB-STRUCT's on 4 others. Given the highly naive nature of the combined use of MTLB-STRUCT and { lemma, deprel }-CSS lexicons those results are certainly encouraging. These show that { lemma, deprel }-CSS lexicons do match MWEs that traditional identifier would miss and therefore that they hold information that identifier could use.
The most powerful astrophysical constraints on pre-recombination scattering between DM and baryons come from the Milky Way satellite abundance measurements  [14, [20] [21] [22]  and Lyman-α-forest measurements  [23] [24] [25] , while the CMB provides the most competitive bounds for post-recombination scattering  [26, 27]. At the same time, constraints from the CMB data have very different sources of uncertainty than other observational probes, do not require modeling of baryonic physics arising from galaxy formation, and probe the same physics at different physical scales. Notably, small-scale polarization measurements of the CMB have.
Previous CMB constraints were driven primarily by data from the Planck satellite  [10, 11, 13, 14, 27]. In this work, we use the ACT DR4 data  [32, 33] , collected during 2013-2016, to search for DM-baryon scattering. In combination with the 2018 Planck data, we use these data to improve the CMB constraints on DM-baryon scattering. In section 2, we review how observables predicted by the Einstein-Boltzmann equations change in the presence of DM-proton scattering. In section 3, we describe the data we use for our analysis and detail the fitting procedure. We present our main results in section 4 and conclude in section 5.
Throughout this work, we include only linear P (k) computations. Nonlinear growth tends to amplify power at small scales, which would tend to amplify CMB power spectra at scales most sensitive to dark matter scattering with baryons. Incorporating nonlinear growth thus amplifies the scattering signal relative to the instrumental noise. Thus, we argue that the bounds we present in this analysis are conservative bounds derived from linear cosmology. This has particular impact on the lensing of the CMB, and may affect parameter constraints. We leave the treatment of nonlinear structure formation within dark matter-baryon interaction cosmologies for a later work, which we expect would provide even tighter constraints from the larger matter power signal. [37]  showed that the ACT DR4 data were sufficiently precise to have a difference in cosmological parameters of order 0.
Data and sampling In our main analysis, we use a combination of Planck 2018 and the Atacama Cosmology Data Release 4 (DR4). We use the foreground-and nuisance-marginalized versions of these likelihoods, representing the best estimates of the CMB bandpowers provided by these experiments. These marginalized likelihoods are Gaussian and each have one remaining nuisance parameter. We thus additionally sample over {A Planck , y p } , ( 3. 2) representing the Planck absolute calibration and ACT polarization efficiency respectively. We perform this likelihood analysis using the sampling framework cobaya  [38]. We include planck_2018_highl_plik. TTTEEE_lite and planck_2018_lowl. TT for Planck, and pyactlike. ACTPol_lite_DR4 for ACT. We do not use the CMB lensing data from ACT. Following  [33] , we exclude ℓ < 1800 data in T T when combining the ACT data with Planck, in order to avoid double-counting the same sky measured at the cosmic variance limit.
We also include a Gaussian prior on τ reio = 0. 065 ± 0. 015 to replace the large-scale polarization likelihood. We also experimented with the addition of some other common cosmological datasets (Planck low-ℓ polarization, Planck lensing, and BAO from SDSS DR12  [39] ), but found these do not improve constraints on DM-baryon scattering. The lack of improvement when including the Planck lensing is consistent with previous analyses with the Planck data [e. g. , 11], but we expect this to change with next-generation surveys  [40].
Velocity-independent constraints For the fiducial model of velocity-independent (n = 0) scattering with a 1 GeV DM particle, we find the inclusion of the ACT DR4 data reduces the upper limit on the cross section for proton scattering by ∼ 40%, with 95-percentile upper limits of σ GeV, n=0 0 < 4. 7 × 10 -25 cm 2 (Planck) 2. 9 × 10 -25 cm 2 (Planck + ACT DR4). (4. 1) We illustrate these results in figure  2 , showing the marginalized 1D posterior of the DM scattering cross section. We find almost no correlation of this parameter with the ΛCDM parameters. For this model the data show no evidence for a nonzero cross section. This model demonstrates the constraining power of the ACT DR4 data, which provide improved measurements of the CMB damping tail and additional acoustic peaks in TE and EE, cutting the space of allowed cross sections compared to Planck alone.
For other masses, and for the case of electron scattering, we provide upper limits derived from the Planck and ACT data in appendix table 1. Since the cross section parameter has a positive prior we check if the improved upper limit is compatible with expectation. In the appendix we perform a Fisher matrix analysis, finding an expected ∼30% improvement in errors from adding the ACT data to Planck for the n = 0 model, consistent with our findings with the real data. Both the Planck and ACT likelihoods used in this analysis include spectra and covariances that have been marginalized over models of foreground parameters. The effect of DM-proton and DM-electron scattering is imprinted in the CMB and is frequency-independent, but could still be biased by astrophysical foregrounds such as by infrared galaxies and radio sources.
3 (TT, TE, EE) 4. 0 (TT) 0. 9 (TE) -0. 3 (EE). (4. 2) For two extra parameters applied to more than 100 degrees of freedom, this is not a significant improvement. Overall from a model selection viewpoint we find no evidence for DM-baryon scattering in any of the six models considered in this work (n ∈ {-4, -2, 0, 2, 4, 6}). Approximately one in three datasets would randomly exhibit a similar ∼ 2σ statistical fluctuation, when testing six models like n ∈ {-4, -2, 0, 2, 4, 6}, and for two additional parameters (mass and cross section). JCAP02  In testing the impact that ACT DR4 has on parameter constraints, we show in the appendix that ACT improves on Planck uncertainties by less than 10% for n < 0 models. For n ≥ 0 models the improvement on the uncertainty is 30-50%, with these models benefiting more from the smaller scale data.
This also confirms that ACT would have been expected to improve constraints on σ 0 for these models, if not for a presumably statistical fluctuation towards nonzero best-fit values. n s 0 10 ¡12 2£10 ¡12 3£10 ¡12 4£10 ¡12 5£10 ¡12 6£10 ¡12 We show the derived posterior densities for the combined Planck and ACT data in figure  3 , for the eight-parameter model for proton scattering. These samples are presented with a flat prior in the logarithm of the cross section, instead of the flat prior in the cross section used in 4. The approach of sampling in the logarithms of the DM particle mass and cross section is useful for exploring the space of allowed models. The CMB constraints exhibit a significant degeneracy between DM particle mass and cross section, and the allowed cross sections vary by several orders of magnitude as the mass changes from 1 MeV to 1 TeV.
JCAP02(2023)046 5 Conclusions and discussion We have used new measurements of the CMB, particularly at small scales and in polarization, to look for evidence of elastic scattering between DM and baryons (protons and electrons). Compared to previous work, the inclusion of the ACT DR4 data provides more precise measurements of the high-ℓ acoustic peaks and damping tail in TE and EE. Relative to a ΛCDM model, the scattering models affect mostly the small scales, so the inclusion of the ACT DR4 dataset is especially suited to investigating this physics. Indeed, although the addition of the ACT DR4 likelihood does not significantly improve constraints on the standard ΛCDM parameters  [33] , we find that for the fiducial model of velocity-independent dark matter scattering with a 1 GeV dark matter particle, the combination of ACT DR4 and Planck improves the upper limit on the scattering cross section by ∼ 40%.