dataesr/scientific-paragraphs-categorization huggingface dataset:
QUANTIFICATION AND STATISTICAL ANALYSIS All image analysis was performed in ImageJ (NIH). All the images present in the figures and movies of this manuscript are maximum intensity z-projections. Cell centroids were tracked manually using the ImageJ Manual tracking plugin. For corpse load analysis, macrophages were outlined in the GFP-channel and then mCherry-positive corpses were counted manually within this outline. The unprojected z stack was used to ensure the corpses were within the macrophages. To calculate peak phagocytic cup area, the maximum LifeAct-GFP cup size reached for every engulfment event during clearance of UV-generated corpses was identified within the unprojected z stack (0. 5 mm slices) and the area measured using the ImageJ measure tool. For quantification of mode and rate of engulfment, we defined Lamellipodial phagocytosis as engulfment involving a phagocytic cup surrounded by a sheet-like protrusion (lamellipod).
Fluorescence intensity plots were generated in ImageJ by using the line tool to draw a 15 mm long, 10 pixel wide (only central 2 pixels shown in figure so as not to obscure image) line across phagocytic cups and using the plot profile tool. For each channel, the lowest value (the background) was subtracted from the profile. To quantify spatial constriction, a 200 mm 2 circle was drawn around the macrophage, centered on the phagocytic cup. The mean fluorescence intensity of the Rhodamine B dextran within this circle was then calculated using the measure tool in imageJ. This value was normalized to the mean dextran fluorescence within the entire interstitial space. Unpaired, two-tailed t tests and one-way ANOVA with a Tukey's or Dunnett's multiple comparisons test were used to test statistical significance and generate p values using GraphPad Prism software.
ACKNOWLEDGMENTS We would like to thank the  Bloomington Stock Center (University of Indiana ;  NIH P40OD018537 ) for Drosophila stocks, as well as FlyBase. We would also like to thank  C. Amato  for her help with the Graphical Abstract. This work is funded by a  Wellcome Trust   senior fellowship  to W. W. ( 107940/Z/15/ Z ) and a  Wellcome Trust Sir Henry Wellcome postdoctoral fellowship  to  A. J. D. ( 107355/Z/15/Z ).
e. , performance level. We also used a mathematical modeling by means of Multivariate Regression Analysis (MRA) as a multidimensional prediction system, which helped us to define complex relations between the criteria (swimming performance and FINA Scores) and body composition variables used as predictors  [32, 33]. All statistical analysis were performed using corresponding statistical software SPSS 19. 0. The level of statistical significance is defined at 95% and the probability values of p < 0. 05 [34].
Introduction The theoretical particle physics community has needed complicated and cumbersome computations based on perturbative quantum field theory in order to precisely predict or explain observable quantities that have been measured in experiments. Nowadays the cutting-edge research often requires symbolic calculations that can never be performed by hand and thus it is common to use computer algebra systems. FORM  [1, 2, 3, 4]  is one of such software programs that has been used for formula manipulation especially in big calculations. Other computer algebra systems that have been used in theoretical particle physics include SCHOONSHIP  [5, 6, 7] , REDUCE  [8]  and GiNaC  [9]  as well as versatile systems like Mathematica and Maple. FORM is advantageous for handling gigantic mathematical expressions that do not fit inside the physical memory of computers; its dedicated sorting algorithms, which utilize sequential access to hard disk drives, enable users to manipulate huge expressions on disks efficiently.
Daily FORM coding Here we try to provide some pedagogical examples of FORM programs for beginners. In FORM, one of the basic operations is replacing a part of each term by using pattern matching. Typically, users first define expressions to be manipulated and then write code with pattern matchings in order to specify how they want to manipulate their expressions. Let us look at our first example in Listing 1. The first 2 lines declare objects that we will use in this example: a (commuting) function fib and a symbol n. Functions in the FORM language are not functions in the mathematical sense or those in other program languages; they just mean objects that can have zero, one or more arguments. The third line defines our input expression, which has a term of the fib function with a numeric argument, representing.
end a Fibonacci number. The goal of this small program is to evaluate Fibonacci numbers in the input. The next 3 lines specify the manipulations to be applied for each term. The symbol n with a question mark followed by a constraint n?{>=3} in the left-hand side of the id statement at Line 4 is a wildcard for a pattern matching. If a term has a part matched to this, then the corresponding part will be replaced in the right-hand side with an adequate substitution for n, which is the famous recursion relation of Fibonacci numbers. We repeat this replacement while all fib functions have (integer) arguments greater than or equal to 3. Then fib(2) and fib(1) are identified with 1 in a such way that all Fibonacci numbers with positive integer arguments are eventually all reduced to numbers. Running FORM with this example prints F = 55.
Instead, we will see the next program (Listing 2), which utilizes memorization on Fibonacci numbers. For this purpose, we use two very powerful features of FORM: • The preprocessor: this processes preprocessor instructions starting with # and manipulates the input text before sending it to the compiler. It provides preprocessor variables and their substitutions into the text, conditional branching, loop constructs, procedures (subroutines), and eventually provides a functionality of metaprogramming. • $-variables: variables starting with $ to store small expressions (expected to fit in physical memory), which can be accessed both in compile-time (i. e. , by the preprocessor) and runtime. The idea of the program in Listing 2 is as follows. The first half of the program, up to. sort at Line 12, searches for the fib function from the input expressions, and determines the maximum argument.
Once the maximum argument is known and stored into the preprocessor variable N at Line 13, then we build a pre-computed table for Fibonacci numbers up to N with an explicit memorization during their calculations. This is performed only once in compiletime. In run-time, all we need is to apply the pre-computed table for all fib functions, as at Line 24. If there is no fib at all in the input, then the code to build the table and apply it is discarded due to the #if. #endif construction. In this way, a result of one part of a FORM.
Recent developments FORM version 4. 2. 0, released in July 2017 and presented in the previous ACAT workshop  [12] , has introduced many new features, the development of which were inspired by realistic physics problems solved by Forcer  [13]  and local R * operations  [14]  as well as diagram manipulations  [15]. We have recently released a minor update, FORM version 4. 2. 1, in February 2019. It contains several fixes for bugs and performance issues, appeared in running big programs. For example, many annoying crashes related to compressions were fixed. For detailed instructions for installation of the up-to-date version, please refer to the Wiki page https://github. com/vermaseren/form/wiki/Installation.
For the second and third cases, however, they occur during symbolic computations for each diagram, thus one may prefer to implement them in a computer algebra system. This tends to be a quite non-trivial and tedious task. Typically computer algebra systems have their own languages as domain-specific languages, specialized for some tasks, which cannot be expected to have expressivity that general-purpose programming languages may have. It is also problematic that the performance of implemented algorithms may not be so excellent in a comparison with implementations in a low-level language like C. Hence it would be very convenient and useful if a computer algebra system provides fast and optimized graph routines for users. It seems natural and relatively easy for FORM (written in C and C++) to incorporate the graph generator of GRACE.
Summary As efficient symbolic manipulation is important for the HEP community and others, FORM has evolved with new features as well as bug fixes and improvements. A recent milestone of this evolution was the release of version 4. 2. 1. We are working on another new feature, graph generations, and others. We hope that efforts will lead to a release of the next version, shortly. The source code of FORM is hosted on GitHub and available from https://github. com/vermaseren/form.
14, 15 A prespecified subgroup analysis of patients with HCC with baseline alpha-fetoprotein (AFP) levels ≥400 ng/mL in REACH showed a significant overall survival (OS) benefit in this subgroup (hazard ratio [HR], 0. 67; 95% confidence interval [CI], 0. 51-0. 90)  15 ; this was confirmed in the REACH-2 trial (HR, 0. 710; 95% CI, 0. 531-0. 949; P =. 0199), without compromising patient-reported disease symptoms as assessed by the Functional Assessment of Cancer Therapy (FACT) Hepatobiliary Symptoms Index (FHSI)-8. 14 Ramucirumab had an acceptable safety profile in these trials and therefore may be considered for HCC treatment in elderly patients. This post-hoc analysis evaluated the efficacy, safety and patient-reported outcomes (PROs) for ramucirumab in three prespecified age subgroups (<65, ≥65 to <75 and ≥75 years of age) using the pooled data of patients with baseline AFP ≥400 ng/mL from the REACH and REACH-2 trials.
ACK N OWLED G EM ENTS Medical writing assistance was provided by Sandra Kurian, MPharm, and Tania Dickson, PhD, CMPP, of ProScribe -Envision Pharma Group, and was funded by Eli Lilly Japan KK ProScribe's services complied with international guidelines for Good Publication Practice Note: The data for any dose adjustment were obtained from exposure analysis and the data for dose adjustments owing to TEAEs were obtained from safety analysis, and the difference between both sets of data is owing to different definitions used in the respective analyses. Abbreviations: AFP, alpha-fetoprotein; max, maximum; min, minimum; TEAE, treatment-emergent adverse event. F I G U R E 1 Kaplan-Meier plots of OS for patients receiving ramucirumab or placebo in the pooled REACH (patients with AFP ≥400 ng/mL) and REACH-2 age subgroups: (A) <65 years, (B) ≥65 to <75 years and (C) ≥75 years.
Both pooled analyses and age cut-off values of 65 and 75 years were prespecified in the protocol before REACH-2 database lock. Both trials were conducted in accordance with the Declaration of Helsinki and International Conference on Harmonisation Guideline for Good Clinical Practice. The ethical review board of each participating site approved the protocol. All patients provided informed consent before treatment. Both trials were registered at www. clini caltr ials. gov (NCT01140347, NCT02435433).
Patients' electronic medical records were reviewed, and 125 patients were eligible for this analysis. Patients who were treated with ICIs for more than 6 weeks after PD were defined as IBP, while those who received ICI treatment for less than 6 weeks or discontinued it due to the PD were defined as non-IBP. The clinical data of the patients were collected, including age, gender, tumor histology, smoking history, Eastern Cooperative Oncology Group (ECOG) performance status, tumor stage, liver/brain metastases, previous lines of therapy, best response to the previous line, initial immunotherapy regimen (monotherapy/combination therapy). ICIs used included nivolumab, pembrolizumab, atezolizumab, and durvalumab. Tumor response, including complete response (CR), PR, SD and PD, were assessed by referring to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria version 1.
Subsequently, panelists defined, evaluated and discussed different reference products to help achieve concept alignment and build a consensus reference scale per attribute. During the last training sessions, panelists assessed melon samples in separate booths, using the developed descriptors and reference scales, and received feedback on their performance. From each biological replication of stored fruit, flesh melon balls (2 cm in diameter) were carved from each wedge and mixed in a bowl. A set of two sensory replications, defined as "samples" for the panelists, were presented to each panelist. Each sensory replication (or "sample") consisted of a set of four melon balls, placed into one 120-mL plastic soufflé cup with lids and labeled with a random three-digit code, generated by Red Jade sensory science software (2019; RedJade Sensory Solutions LLC, Redwood City, CA).
Bottom: frequency of fork stalling. ns not significant; ****p-value < 0. 001. d DNA fiber analysis of U2OS cells double transfected with a control siRNA (Ctrl), with siRNAs targeting XRCC3 (48 h) or RAD51D (60 h) to investigate replication fork restart upon HU treatments; labeling protocol as in a. Top: indicated protein levels, assessed by western blot; KU70, loading control. Bottom: frequency of fork stalling. ns not significant; **p-value = 0. 0024; ***p-value = 0. 0007. Source data for a-d are provided in the Source Data file. Although both BRCA2 and XRCC3 were shown to play a role downstream of fork remodeling, they display rather different, yet possibly coordinated reversal-dependent functions. While BRCA2 defects lead to reversed fork degradation, but mild fork restart defects  13, 17, 20  , XRCC3 inactivation does not impair fork stability, but severely impairs single-fork reactivation once the stalling agent has been removed (Fig.
Multiple gels/blots were processed in parallel, ensuring equal and comparable loading across gels. Source data are provided in the Source Data file. b Proposed model for the sequential role of BCDX2 and CX3 paralog complexes in replication fork remodeling, protection and restart: the BCDX2 complex helps RAD51 and ZRANB3 in driving fork remodeling. During fork stalling, regressed arms are protected from unscheduled nucleolytic degradation by BRCA2-mediated stabilization of RAD51 nucleofilament. Preventing fork remodeling by BCDX2 inactivation suppresses genetic instability of BRCA2-deficient cells upon sustained replicative stress. Similarly to RAD51, BCDX2 may be involved in fork protection (and possibly fork restart), but this role may be genetically masked by its upstream role in promoting fork reversal.
Cell extract were diluted with NuPAGE LDS sample buffer (Thermo Fisher Scientific) containing DTT and heated at 60 °C for 10 min. Proteins, together with the PageRuler Plus Prestained Protein Ladder (Thermo Fisher Scientific, 26620), were resolved on NuPAGE 4-12%, Bis-Tris or 3-8% Tris-Acetate gels (Thermo Fisher Scientific) using MOPS and Tris-Acetate SDS running buffers respectively, and transferred on nitrocellulose membranes. Membranes were blocked with TBS containing Tween-20 (0. 1%) and 5% milk powder for 1 h at room temperature (RT), incubated with the indicated primary antibodies overnight at 4 °C and secondary antibodies for 1 h at RT. Protein were visualized using WesternBright ECL reagent (Advansta) and the Fusion Solo S imaging system (Vilber Lourmat). Uncropped and unprocessed scans of each blot are provided in the Source Data file.
Quantitative image-based cytometry (QIBC). QIBC experiments were performed on an Olympus ScanR Screening System equipped with an inverted motorized Olympus IX83 microscope, a motorized stage, IR-laser hardware autofocus, a fast emission filter wheel with single band emission filters, and a digital monochrome Hamamatsu ORCA-FLASH 4. 0 V2 sCMOS camera (2048 × 2048 pixel, pixel size 6. 5 × 6. 5 μm, 12 bit dynamics), as described previously  70, 71. For each condition, image information of large cohorts of cells (typically at least 500 cells for the UPLSAPO ×40 objective (NA 0. 9) and at least 2000 cells for the UPLSAPO ×20 objective (NA 0. 75)) was acquired under non-saturating conditions. Identical settings were applied to all samples within one experiment. Images were analyzed with the Olympus ScanR Image Analysis Software, a dynamic background correction was applied, nuclei segmentation was performed using an integrated intensity-based object detection module using the DAPI signal, and foci segmentation was performed using an integrated spot-detection module.
All downstream analyses were focused on properly detected nuclei containing a 2C-4C DNA content as measured by total and mean DAPI intensities. Fluorescence intensities were quantified and are depicted as arbitrary units. Color-coded scatterplots of asynchronous cell populations were generated with Spotfire data visualization software (TIBCO). Within one experiment, similar cell numbers were compared for the different conditions. For visualizing discrete data in scatterplots, mild jittering (random displacement of data points along the discrete data axes) was applied in order to demerge overlapping data points. For the siRNA screen, genes were ranked according to a z-score (z = (x -μ)/σ with x being the mean number of RAD51 foci per cell for each knockdown, μ being the mean number of RAD51 foci per cell across all conditions, and σ being the standard deviation of the mean number of RAD51 foci per cell across all conditions).
Images were acquired using an Olympus IX81 fluorescence microscope equipped with a CCD camera (Orca AG, Hamamatsu). CldU and IdU tract lengths were measured using the line tool in ImageJ64 software. In all the fork restart experiments (Fig. 4 ), defective fork restart (i. e. , fork stalling) was defined as a ratio (length of green vs red) <0. 1. Electron microscopic analysis of genomic DNA. Following the depletion of the protein of interest, asynchronous subconfluent cells were treated with 50 nM CPT for 1 h or 4 mM HU for 5 h. Where indicated, cells were pretreated with 50 μM Mirin for 1 h. Cells were collected, resuspended in ice-cold PBS and crosslinked with 4,5′, 8trimethylpsoralen (10 μg/ml final concentration), followed by irradiation pulses with UV 365 nm monochromatic light (UV Stratalinker 1800; Agilent Technologies).
For each experimental condition at least 50 metaphases were analyzed in three different biological replicates. Statistical analysis. For QIBC analysis, between 9 and 15 images per condition, depending on the microscope objective used and the cell confluence were acquired in an unbiased fashion from asynchronous cell populations grown on glass coverslips or multi-well plates. Typically, between 2000 and 5000 cells per condition were analyzed and representative single-cell data of cell cohorts of comparable size are shown as two-dimensional cell-cycle-resolved or one-dimensional scatterplots. For DNA fiber length measurements, at least 150 fibers were scored for each condition every experiment was repeated at least twice. The results are depicted as median plus 10-90 percentile whisker plots and Kurskal-Wallis test was used for statistical analysis.
Acknowledgements We thank the  Center for Microscopy and Image Analysis of the University of Zurich  for assistance with microscopy and imaging analysis. We are grateful to  Eli Rothenberg ,  Huijun Xue ,  Petr Cejka ,  Swagata Halder  and members of the  Lopes and Altmeyer labs  for technical assistance and fruitful discussions, and to  Jean-Yves Masson  for critical reading of the manuscript. Work in the Lopes lab was supported by the  SNF  grant  31003A_169959 , the  ERC  Consolidator Grant  617102  and the  Swiss Cancer League  grant  KFS-3967-08-2016  to M. L. M. B. was also supported by the  H2020 Marie Sklodowska-Curie postdoctoral fellowship   704817. Work in the Altmeyer lab was supported by  SNF  grants  PP00P3_150690  and  PP00P3_179057  and the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program   ERC Starting Grant   714326  to M.
Method A survey of graduating cohorts of the medical school from 2011 to 2013 was conducted through email and telephone. Results There were a total of 175 alumni for the period 2011 to 2013. Data was collected on 92% (161/175) through an online survey, follow-up email and telephone interview, and was triangulated with searches of professional registration databases and information from key informants. Between 6 and 8 years after graduation, a total of 43% of alumni were engaged in general practice as a career.
Data analysis Correspondence analysis (CA) was performed on the contingency table containing the average citation frequency of terms. The average score of astringency subqualities grouped for percentage (%) of Sangiovese in wine was projected as an illustrative variable in the CA map. CA and principal component analysis (PCA) were carried out using XLSTAT software (Addinsoft, XLSTAT 2017). Drivers of liking were evaluated using Pearson's correlation coefficients between the standardized CA residuals of attributes and liking scores. Multiple factor analysis (MFA) was performed using the FactoMineR  (Lê et al. , 2008)  package.
A B resulting from step changes in exhumation rates, accounting for the effect of heat advection during exhumation. Comparison with the detrital thermochronology data is achieved through neighborhood-algorithm inversion; the model inverts for the exhumation rates and the timing of rate changes  (Braun et al. , 2012). Inversions use either the full data set or only the internally consistent ages, and incorporate uncertainties in both minimum-peak ages and depositional ages. Two-stage and three-stage exhumation scenarios were tested. A full description of the procedure and the different inversions is provided in the Supplemental Material. Our best-fit inversion uses the internally consistent data set and implies a three-stage exhumation history for the Namche Barwa massif, with an early (8. 2 ± 1.
ACKNOWLEDGMENTS This work is part of the  Marie Curie Initial Training Network "Investigating Tectonic-Erosion-Climate Couplings " (iTECC) funded by the  European Union Research Executive Agency  (grant agreement  316966 ). It was supported by the  UK Natural Environment Research Council (NERC ;  IP-1500-1114 ). C. Mark  is funded by  Science Foundation Ireland  ( 18/ SIRG/5559 ). E. Enkelmann,  K. Lang , and  P. Zeitler  provided constructive reviews. Data for this study are available in the Supplemental Material and in the geochron. orgdatabase.
org/10. 17882/62352 (Dumas et al. , 2018). Long transects of the first 400 m below the surface were sampled with a horizontal resolution on the order of 2 km in the Western Mediterranean Sea. The hydrographic and dynamics background of this region are given in Sect. 2. The objectives and implementation of the surveys are presented in Sect. 3. The details of the measurements (platforms, sensors, methodology, metrology, data control, ancillary data) are reported in Sect. 4. To illustrate the potential of the dataset, an overview of the observed processes is displayed in Sect. 5. Lessons learned during surveys and summary are displayed in Sect. 6.
Previous high-resolution observations The finest part of the mesoscale dynamics often escapes the usual sampling strategy (CTD -conductivity, temperature, depth -arrays, glider deployments) because of being shortlived, small in size and quickly advected. A development in the last decade of glider fleets revealed nevertheless the mesoscale variability in the Western Mediterranean basin. Recent field experiments based on the multi-platform integrated monitoring program MOOSE  (Coppola et al. , 2019)  or on the intensive targeted experiment HYMEX  (Estournel et al. , 2016)  have revisited the hydrography and the dynamics of the northwestern part of the Western Mediterranean basin. A strategy of regular and repeated gliders lines as well as dedicated deployments allowed characterizing the variability in the dynamics and describing crossed fine-scale structures.