dataesr/scientific-paragraphs-categorization huggingface dataset:
2) Results In Figure  3 , we report the percentage of skipped loops (yaxis) and the corresponding SSIM index (x-axis) for the non-dominated solutions found with E-IDEA. Moreover, in 0. 9 9 9 8 8 0. 9 9 9 9 0. 9 9 9 9 2 0. 9 9 9 9 4 0. 9 9 9 9 6 0. 9 9 9 9 8 1 SSIM (higher is better) 0. 00%  Figure  4 , we report two examples of images produced with the approximate variants having the highest and the lowest SSIM. Figure  4a  and 4b depict the input and output images to the k-means algorithm, for its precise version (i. e. , without approximation). Figure  4c  and 4d report the images obtained with two of the approximate variants, with the highest and lowest SSIM, respectively. As the images clearly show, the proposed approach allowed us to find approximate variants of the code leading to skip from 16% up to 29% loops, without significantly impacting the output quality.
1) Setup As approximation technique, we adopted the loop perforation so that skipping the i-th iteration translates in skipping the computation of the i-th coefficient of the series. We instrumented Clang-Chimera to use two different loop perforation variants: 1) The one illustrated in Subsection III-A1, that we refer to as loop-first; 2) A technique, that we refer to as loop-second, which executes only loops having an index multiple of a certain value 'skip'  [46]. For instance, by using this variant, the mutated version of the example code shown in Subsection III-A1 is the following: 1 i n t main ( v o i d ) { 2 f o r ( i n t i = 0 ; i < N; i ++) { 3 i f ( i % s k i p 1 == 0 ) { 4 f o r ( i n t j = 0 ; j < M; j ++) { 5 i f ( j % s k i p 2 == 0 ) { MAE = max (x) |f (x) -f approx (x)| (4) We evaluated the error entailed by the approximate variants over 1,000 different x values and by calculating the Taylor expansion up to the order of 100 (n ∈  [1, 100]  in Equation  3 ).
r. t. to the precise one and (ii) the percentage of skipped loops as measure of the gain, since we aimed to reduce the execution time of a software implementation. Once again, E-IDEA produced a set of nondominated approximate variants of the original application, i. e. a set of configurations for the loop perforation to obtain a good trade-off between accuracy loss and performance gain. In Figure  7 , we report the percentage of skipped loops (y-axis) and the corresponding SSIM index (x-axis) for the non-dominated solutions found with E-IDEA. The precise version is the reference and is placed in (SSIM = 1, skipped loops = 0). Moreover, in Figure  8 , we report two examples of images produced with the approximate variants having the highest and the lowest SSIM. Figure  8a  and 8b depict the input and output images of the precise (i.
Moreover, since different approximation techniques are applicable to different targets, usually it is complicated to evaluate their impact on an application. For example, while the bit-width reduction is more suitable when targeting a custom hardware accelerator -since it is fully customizable -the loop perforation is mostly applied in software implementations. Nevertheless, with E-IDEA it is possible to easily explore the trade-off opportunities stemming from the different AxC techniques within the same framework. In this regard, JPEG and Sobel filter case studies proved the possibilities of exploring the trade-off opportunities brought by two totally different AxC techniques -bit-width reduction and loop perforation -to the same application. To do so, we simply defined different code mutators and fitting functions.
Thus, E-IDEA allows exploring the impact of different approximation techniques on different benchmarks, with different targets (i. e. , software, hardware accelerators) and error metrics. Finally, the approach introduced with E-IDEA is scalable. Indeed, as shown in the last case study, it allows analyzing complex applications as the CNNs. We instrumented E-IDEA to apply the precision scaling approximation technique to a 8-bit quantized CNN. This allowed us to find solutions achieving more then 30% savings, with a negligible accuracy loss (0. 48%). Besides, Table  8  summarize reported case studies, including the approximate technique being adopted and which are the parts of the application on which the technique is applied, the fitness-functions driving the DSE, and the execution time that E-IDEA spent to perform the latter.
In general, the exploration time depends on the application, specifically on its requirements in terms of computation and code complexity. Also, the complexity of the metric calculation impacts the exploration time. Indeed, for instance, for all the applications used to process images (k-means, JPEG, and Sobel) E-IDEA had to calculate the related metrics (PSNR, SSIM) to determine the accuracy loss. Moreover, to calculate the approximate-CNN accuracy loss, the inference process must be executed and the results compared to the non-approximate CNN. On the other hand, the Taylor benchmark only needed the calculation of the Maximum Absolute Error which was pretty quick.
V. CONCLUSION In this paper, we presented E-IDEA, an automated framework able to generate approximate variants of a given input application described as C/C++ code. The approach is based on automatic code mutation and on an evolutionary engine, whose synergy enables the exploration of the best approximate variants in terms of trade-offs between accuracy reduction and efficiency gains. E-IDEA has been validated over different kinds of applications and target implementations (i. e. software, hardware accelerators). Experimental results presented throughout the article showed that E-IDEA can be very useful as a design exploration tool to help the user selecting the most suitable approximation technique, according to the desired requirements and constraints. E-IDEA is released under the GNU Affero General Public License and it is completely open-source  [34].
The tetravalent dengue vaccine (CYD-TDV) is approved for use as a 3-dose series for the prevention of dengue in seropositive individuals ≥9 years. A randomized, placebo-controlled, phase II study of a booster dose of CYD-TDV in individuals who completed the 3-dose schedule >5 years previously (NCT02824198), demonstrated that a booster restored neutralizing antibody titers to post-dose 3 levels. We present additional immunogenicity assessments up to 24 months post-booster, and B-and T-cell responses in a participant subset. Participants aged 9-45 years that had received all three doses of CYD-TDV were randomized 3:1 to receive a booster dose of CYD-TDV (n = 89) or placebo (n = 29). Neutralizing antibody levels at Months 1, 6, 12, and 24 post-booster were assessed by plaque reduction neutralization test.
Study design and participants This was a phase II, randomized, placebo-controlled study of a booster dose of CYD-TDV conducted in Singapore, and the design of the study has been described in full previously (CYD63; UTN: U1111-1161-2813, NCT02824198). 7 Briefly, participants were enrolled from the CYD28 study if they had received all three doses of CYD-TDV, were aged 9-45 years at first study injection and had sufficient baseline samples for additional analyses. Participants were randomized 3:1 to receive a booster dose of CYD-TDV or placebo at Day 0 of CYD63. The full CYD63 study period was July 2016 to January 2019, with primary vaccination in CYD28 from April 2009 to October 2010 and booster vaccination in CYD63 from July 2016 to February 2017. The studies were undertaken in compliance with the International Conference on Harmonization (ICH) guidelines for Good Clinical Practice and the principles of the Declaration of Helsinki.
Cells were then stained with surface markers CD3, CD4, CD8, CD45RA, and CCR7, and, once fixed, were stained with intracellular markers CD154, IFN-γ, TNF-α, IL-2, and MIP-1β and analyzed by flow cytometry, corrected by a negative control medium + DMSO solvent result; samples were acquired on LSR-II (BD Biosciences, San Jose, CA, USA) and data were analyzed using a computational-automated gating pipeline (this pipeline is based on a supervised Machine Learning approach using training datasets gated manually [Altrabio algorithm, www. altrabio. com]). Some unique approaches have been adopted to leverage data pre-processing, feature engineering, transfer learning and data augmentation to overcome the major challenges encountered in building predictive models for cytometry data automated gating.
All data were log 10transformed prior to statistical analysis. P-values were corrected for multiple testing using the False Discovery Rate procedure (q-values are reported). For plasmablast responses a non-parametric Wilcoxon signed-rank test was used; p-values of Signed Rank were reported. Analyses were performed with SAS software version 9. 4 (SAS Institute, Cary, NC, USA). Immunogenicity analyses were conducted on the perprotocol analysis set (PPAS) which comprised those who received booster dose, had valid post-injection serology results and had no protocol deviations; participants were included according to the group they were randomized. Safety analyses were conducted in the safety analysis set (SafAS) which comprised all participants who received an injection; participants were included according to the vaccine they received.
B-and T-cell responses Memory B-cell and T-cell analyses were conducted on frozen PBMC. The cell yield of around 10 6 cells per mL of blood collected was as expected, and the good cell viability (median around 96%) indicated the good quality of the cells and their ability to present good functionality in subsequent testing. The results from the Additional Immunogenicity Test subset on the plasmablast and memory B-cell and T-cell outcomes could *Data from post-dose 3 in CYD28, and Day 0 and Day 28 from CYD63 have been previously presented in Park et al  7. GMT, geometric mean titer; M, number of participants with available data for that endpoint. not be determined by baseline dengue serostatus as only 10 subjects out of the 56 recruited were dengue seropositive at baseline.
Acknowledgments The authors wish to thank the participants and their parents, the investigators, coordinators, and study teams. Editorial assistance with the preparation of the manuscript was provided by  Nicola Truss PhD , inScience Communications,  Springer Healthcare Ltd, London, UK. Funding for this assistance was provided by  Sanofi Pasteur. The authors would like to thank  Pascal Blanc ,  Daniel Larocque  for scientific advice,  Joseline Ruiz  for statistical analysis, and  Jean-Sébastien Persico  for editorial assistance and manuscript coordination on behalf of  Sanofi Pasteur.
Data sharing statement Qualified researchers may request access to patient-level data and related study documents including the clinical study report, study protocol with any amendments, blank case report form, statistical analysis plan, and dataset specifications. Patient-level data will be anonymized and study documents will be redacted to protect the privacy of trial participants. Further details on Sanofi Pasteur's data-sharing criteria, eligible studies, and process for requesting access can be found at: https://www. clinicalstudydatarequest. com.
Mating behaviours affect hypothalamic orexin/hypocretin neurons and vice versa. However, activity of orexin neurons has not been recorded during mating before. We report an anecdotal dataset of freely-moving miniature microscope recordings of orexin neuron activity during mating behaviours, as well as an oral sexual encounter previously undocumented in mice. Across the orexin neuron population in the male, firing rates were maximally diverse during ejaculation, similarly diverse though weaker during intromission, and inverse to this during anterior thrusting. In the female mouse, orexin neurons tended to decrease firing during intromission after a transient increase. We provide this brief dataset for re-use, to enable further studies of these rare behaviours with challenging surgical preparations.
Ca 2+ imaging frame rate was 10 frames/s. Behaviour was tracked with a CCD camera (Lumenera Infinity) from below the arena at 65 frames/s. An LED facing the behaviour camera and blinking in response to each Ca 2+ imaging frame was used to synchronize Ca 2+ imaging and behaviour videos. Behaviour analysis was performed in ImageJ by manually annotating behaviours. The full datasets are available for free re-use under a public domain dedication  [19].
Ca 2+ imaging analysis Ca 2+ imaging data were preprocessed for dropped frames and pixels, downsampled by a factor of three spatially, then motion corrected in Mosaic (Inscopix) and saved as 16bit TIFF stacks. Further processing was performed in Matlab with custom routines. Regions of interest (ROIs) were drawn manually around cells and average fluorescence was extracted across all pixels within each ROI as well as a neuropil 'halo' around each ROI consisting of the third to the sixth nearest pixels outside the outline that did not contain other ROIs. These signals were lowpass filtered with a moving average of three frames. Neural signals were calculated by subtracting the neuropil 'halo' signal from each ROI specific signal. This signal was then corrected for photobleaching by computing ΔF/F 0 using the mean over a 120 s moving window as F 0 and z-scored.
Some of these datasets were analyzed in less detail in Figure  1  of our previous article  [18] , and here we report in more detail on the mating behaviours observed in a limited subset of those, and previously undocumented recordings. The firing rate changes in male orexin neurons were large during mating behaviours, reaching, in different cells, peak and through values during ejaculation corresponding to the extremes of their 0 to 30 Hz firing range (Figure  1B, F, G ). The population firing pattern of orexin neurons during AT was inverted compared to that during intromission (Figure  1G ), and firing was less variable during AT (Figure  1H ) than other mating behaviours. Correlation coefficients of the population firing rate vector across behaviours revealed that intromission and ejaculation were highly correlated and both were inversely correlated with AT (Figure  1I ).
Discussion This pilot study is an anecdotal report as it consists of two recordings in a male and a female mouse. The data however indicate that orexin neuron activity is strongly and heterogeneously modulated during mating behaviours, and suggest that mouse mating behaviours can exhibit more diversity than documented previously. Though AT seemed non-aversive to the female, it is possible that the size of the arena limited the options to retreat from this behaviour, as female mice pace mating behaviours when given the opportunity to retreat  [21]. We should note that the head mounted miniature microscope is ~3 cm high and thus may affect mating behaviours, such as AT when the female is recorded. Another potential caveat is that the GRIN lens implantation entails lesioning brain tissue in somatosensory neocortex, dorsal hippocampus and thalamus in one hemisphere, as these structures stand in the path of the lens.
However, the dispersion of MWCNTs in the E7 LC into different concentrations leads to the change in color of POMs, which is associated to the change in refractive index and/or birefringence (∆n) as reported previously  [42] [43] [44]. Besides, all the POM images have also been processed by ImageJ software to analyze the uniformity of color within a POM image. An intensity of ∼7 a. u. has been obtained via this processing, which further confirms that the LC molecules are homogeneously oriented towards long molecular direction in the cells. Figure  4  shows the room temperature (RT) V-T curves of the pristine and MWCNTdoped LC cells. No significant shift in V-T curves has been observed with increasing MWCNT concentrations, indicating that the petty amount of MWCNT dispersion does not affect the threshold voltage (V th ) and operation voltage (V op ) significantly.
The calculation of CR has been done by processing the bright (on-state) and dark (off-state) states POMs using ImageJ software. Carefully taking the same scale of bright and dark state textures, we have calculated the average value of T on and T o f f of the pure E7 and MWCNT composites; which in turn gives the value of CR. In general, the contrast ratio of LCs could be enhanced by adding a guest material via refractive index matching  [45]. LC/polymer-dispersed systems are somehow better for enhancing the CR [46]; however, in the present investigation, we have observed a reduced CR for the LC/MWCNTs composites due to the scattering of transmitted light from the MWCNTs and refractive index mismatching. On the other hand, ferroelectric LCs could render an enhanced CR with the addition of MWCNTs by enhancing the alignment  [47].
Acknowledgments: Authors are also thankful to the  A. P. J. Abdul Kalam Centre for Innovation  for the experimental facilities. Chi-Yen Huang  and  Che-Ju Hsu ,  National Changhua University of Education, Taiwan  are sincerely acknowledged for providing the experimental facilities and valuable discussion. D. P. S. gratefully acknowledges the financial assistance provided by the  UDSMM, ULCO. A. Hadj Sahraoui , Director UDSMM is highly acknowledged for their kind support.
Study Overview We conducted the pilot study between May 1, 2020, and December 31, 2020. The study was approved by the University of Arizona Institutional Review Board (Protocol #2005625231). The primary goals of the study were to develop the See Me Serene app and test our study procedures for feasibility. Our secondary goal was to gather preliminary data regarding the potential impact of the app on reducing perceived and physiologic stress; the study was not designed nor powered to test efficacy. The research was conducted in 2 phases: (1) development and internal testing of the app; and (2) feasibility and pilot testing with participants recruited online through earned media (eg, new stories), presentations on a university campus, and social media (eg, online sharing of earned media and presentations).
The feasibility study employed a mixed methods, within-subjects, pre-/posttest design. Feasibility outcomes included metrics for participant recruitment (goal of 100 within 2 months), participant retention (at least 75% at 1 month), and data collection (at least 90% at baseline and 75% at the 1-month follow-up). Exploratory outcomes included changes in self-reported measures of stress, anxiety, loneliness, and worry, and diurnal cortisol rhythm (collected via salivary cortisol assays) from baseline to 1-month follow-up. We also collected consumer satisfaction at the 1-month assessment.
Program Development In Phase 1, we developed and conducted internal testing on the See Me Serene app. The app was developed based on feedback regarding guided imagery for relaxation obtained in a previous study  [25]. Initial guided imagery scripts were reviewed by the investigators and project staff and vetted by an advisory board that consisted of faculty, staff, and students at the University of Arizona. During this process, the advisory board suggested the addition of outdoor activities to relaxing nature scenes to enhance the appeal of the app to a more diverse population of users and differentiate See Me Serene from other relaxation apps in the marketplace. The app was programmed by undergraduate students in the Department of Computer Science with oversight by the investigators (CG and JG).
We developed Android and iOS versions of the app using the Thunkable platform, which allows simple design and app development. This process streamlined development and accelerated deployment by automatically generating native apps for both Android and iOS platforms. We used Google's Firebase which provides database and authentication services targeted for mobile apps. The app audio and image files were stored in the Firebase database along with user preferences. This allowed for easier updates of guided imagery files without requiring app updates. Beta testing of the See Me Serene app was conducted by the project team and members of the Advisory Board. Once complete, the app was deployed to the App Store and the Google Play Store. See Me Serene was updated twice during the study to fix bugs and make improvements to usability.
Study staff provided reminders to participants to collect samples at both baseline and follow-up. Participants were instructed to use the app at least once each day for 4 weeks. Follow-up assessments (online or telephone-delivered self-report surveys and salivary cortisol assays) were conducted at 30 days after access to the app. Use of the app was collected automatically within the Firebase database (in which specific app use data were stored), and through Google Analytics and Apple Developer Tools (eg, app downloads and current users). Upon completion of all study activities, participants received a US $50 electronic gift card.
Data Collected At baseline, we collected demographics including age, gender, race, ethnicity, education, marital status, number of people and pets in the household, mental health diagnoses, and amount of moderate to vigorous physical activity per week. We also collected data on COVID-19-related variables including stay-at-home orders, essential personnel status, length of restrictions, leave the house every day status, amount of time spent outdoors, and amount of time spent doing fun outdoor activities. At baseline and 30-day follow-up, we assessed stress-related variables via validated self-report measures and saliva for determination of cortisol concentrations.
Analyses Study data were collected and managed using REDCap electronic data capture tools hosted at The University of Arizona  [48, 49]. REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies, providing (1) an intuitive interface for validated data capture; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for data integration and interoperability with external sources. Descriptive statistics were compiled using the REDCap reports and stats function. Our feasibility analyses focused on change in the main psychological outcome variables over time using paired-samples t tests. Open-ended responses to the question, "What suggestions do you have to improve the app?" were summarized using a matrix analysis approach, which is an efficient method of descriptively organizing and interpreting qualitative findings for program integration  [50].
Participant Characteristics We recruited 101 participants from August 3, 2020, to October 5, 2020. Following enrollment, 2 participants withdrew from the study (1 due to technical issues and 1 due to a family emergency), leaving 99 participants with complete data at baseline. As displayed in Table  1 , the majority of participants were non-Hispanic White (83/99, 84%) females (85/99, 86%) who had at least some college education (93/99, 94%), and were married or living with a partner (66/99, 67%). The average age of participants was 51. 4 (SD 14. 7) years. COVID-19 restrictions affected 68% (67/99) of participants, and of those under stay-at-home orders, 92% (61/66) reported that they had been staying at home for more than 3 months. Participants reported diagnoses of generalized anxiety disorder (24/99, 24%), major depression (18/99, 18%), and PTSD (12/99, 12%).
Feasibility As displayed in Table  2 , we met or surpassed all our feasibility benchmarks. We were able to recruit 100 participants within 2 months, collected 98% (99/101) of baseline survey data, 91% (90/99) of 30-day surveys, and 85% (84/99) of cortisol samples were returned. Five samples contained some missing data and were excluded from analyses for a total of 80 (79/99) usable samples. Using a conservative definition of retention (complete survey and cortisol data at 30 days), we surpassed our goal with an 85% (84/99) retention rate.