dataesr/scientific-paragraphs-categorization huggingface dataset:
Shrinkage Shrinkage of samples was studied by measuring the projected area of slices before pretreatment, after pretreatment and at the end of the drying process. For this, around 50 celery slices were placed on a blue surface near to a length reference. The images were obtained by a cellphone camera (Huawei P9 pro model -64 MP resolution, China) 30 cm of distance from the samples. Then, images were processed using ImageJ software 1. 52a version (National Institutes of Health, USA)  [19]. First, the measurement scale was set by using the ruler in the photo as a reference using the "set scale" command. Then, the photos were converted to grayscale (8 bits) and binary scale using the "threshold" command. At this point, celery slices should be colored black on a white background. For obtaining slices area, the "analyze particles" command was used, which provide a response window with the area of each slice in the sample.
Experimental design, regressions and statistical analysis A completely random design with 3 process replications was performed. Nonlinear regression was used to find model parameters (Equation (  4 )) to fit drying kinetics data. For this, a generalized reduced gradient algorithm implemented in the "Solver" tool of Excel 2016 was used. In addition, variance analysis (ANOVA) was used to verify the significant effect (95% of confidence) of the treatment. In addition, Tukey's test was performed to evaluate differences among levels of the factor (drying kinetics parameters and shrinkage). Statistical analysis was performed using Statistica 7. 0 software (Statsoft Inc, USA).
Acknowledgment The authors are grateful to the  Programa Nacional de Investigación Científica y Estudios Avanzados (PROCIENCIA)  from the '' Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica" (CON-CYTEC, Peru)  for funding the project n • 409-2019-FONDECYT, to the  Universidad Privada del Norte (UPN, Peru)  for funding the project n •  20201005 , to the  São Paulo Research foundation (FAPESP, Brazil) , for funding the project n •  2019/05043-6 , and the  National Council for Scientific and Technological Development (CNPq, Brazil) , for funding the productivity grant of  PED Augusto  ( 310839/2020-3 ).
Methods: We included 890 patients who survived after an acute ischemic stroke from the MRI-Genetics Interface Exploration (MRI-GENIE) study, for whom data on vascular risk factors (VRFs), including age, sex, atrial fibrillation, diabetes mellitus, hypertension, coronary artery disease, smoking, prior stroke history, as well as acute stroke severity, 3-to-6-month modified Rankin Scale score (mRS), WMH, and brain volumes, were available. We defined the unaccounted WMH (uWMH) burden via modeling of expected WMH burden based on the VRF profile of each individual patient. The association of uWMH and mRS score was analyzed by linear regression analysis. The odds ratios of patients who achieved full functional independence (mRS < 2) in between trichotomized uWMH burden groups were calculated by pair-wise comparisons.
Standard Protocol Approvals, Registrations, and Patient Consents The image and clinical data were acquired from the MRI-GENIE study  (16). The MRI-GENIE study is a large international cohort study of 19 sites, contributing 6,600 AIS patients with phenotypic, radiographic, and genotypic data. Patients were recruited in a hospital-based setting through Stroke Genetic Network (SiGN). The informed and written consent forms, including sharing of de-identified demographic, clinical phenotypic, and imaging data, were obtained from all patients or their legally authorized representative  (18, 19). Each site received the approval of their internal review board.
Total brain volume was quantified automatically by a similar previously described framework  (21). Both WMH and total brain segmentation results were evaluated, and the quality was controlled by experts and experienced raters. WMHv was adjusted by the total brain volume and log-transformed to correct its skewed distribution. The brain-volume-adjusted and logtransformed WMHv will be denoted as WMHv for simplicity in the rest of this paper. Out of 6,600 patients, the complete clinical characteristics of 5,822 patients were reported. Acute stroke severity and longterm functional outcome data were available for 1,097 patients out of those 6,015 patients and measured by the acute NIHSS and the 3-to 6-month modified Rankin Scale (mRS) scores, respectively. After the quality control of WMH and total brain segmentation, 924 AIS patients remained.
Unaccounted WMH Burden To measure uWMH independent of the VRF profile of a patient, we first modeled the association of WMH burden and the profile of the patient by multiple log-linear regression. Age, sex, AF, DM, HTN, CAD, SMK, and PS were considered in the analysis as explanatory variables, and WMHv was the target variable. NIHSS was included in the analysis as well to account for the effect of acute stroke severity on functional stroke outcomes for later analyses. The normality of WMHv data of the AIS population with respect to the multiple log-linear regression model was tested by the Shapiro-Wilks test. The expected burden of WMH with respect to the VRF profile of a patient was calculated as the trend of the multiple log-linear regression model. The uWMH burden measured the amount of WMH burden that was not accounted for by the clinical profile of a patient, i.
We performed the subgroup analysis regarding acute stroke severity by dividing the patients into mild and severe acute stroke severity groups. We divided the patients with respect to their acute NIHSS scores, with a threshold defined as the third quartile (Q3) of the NIHSS scores of the population. We performed the same trichotomized analysis of uWMH burden and investigated the odds ratios of patient who achieved full functional independence, defined as "excellent mRS" (with residual non-disabling symptoms, mRS 1, or symptom-free, mRS 0) between the uWMH burden groups of each acute severity subgroup. All statistical analyses were performed with Python SciPy 1. 5. 4  (22) , Sci-kit Learn 0. 23  (23) , and StatsModel 0. 12 packages  (24).
We do not suggest the uWMH burden as the strongest predictor of post-stroke functional outcomes. As shown in the subgroup analysis regarding the acute stroke severity, the acute NIHSS was a stronger predictor of poststroke functional outcomes. However, the subgroup analysis also showed that the uWMH burden could complement the prediction of functional outcomes with the admission NIHSS. This will be an interesting research direction to investigate further regarding the predictive capability of the uWMH burden, combined with other risk factors including the acute stroke severity, by using predictive modeling (e. g. , logistic regression, decision forests, deep learning models, etc. ). The predictive power of the uWMH burden and its association to functional outcomes will be benefited from cross-validation across multiple datasets and also from validation with a dataset from an independent cohort.
Sol-Gel Characterisation Real-Time FTIR Spectroscopy Synthesis reactions were optimised by recording ATR-FTIR spectra real-time at intervals of 1 min in the range of 600-2,800 cm -1. The spectra were measured with a ReactIR ™ 45 spectrometer with a resolution of 4 cm -1 , averaging 256 scans. An EasyMax 102 controller was used to control conditions during the reaction: stirring and reactor temperature. The closed atmosphere of the reactor prevented the evaporation of the solvent. The instruments were controlled by iControl EasyMax V4. 2 and iC IR 7. 1 software. The spectra are presented in the range between 700 and 1800 cm -1. The intensities of spectra are shown as log (absorbance) in absorbance units (A. U. ).
1 software. EIS measurements were acquired in the frequency range from 100 kHz to 10 mHz with a 10 mV amplitude (rms) signal. Before measurement, the open circuit potential (OCP) was measured for 10 min. The EIS measurements were performed first after 1-day immersion and then after selected intervals (4 and 6 days). EIS measurements were repeated at least twice and the representative measurement (at least two similar repetitions) was chosen to be presented in figures. EIS spectra were fitted using Nova 2. 1 software. The quality of the fits characterized using χ 2 values was usually less than 0. 03.
The degradation of the coatings was additionally confirmed by XPS analysis. The comparison of the high-resolution XPS spectra of Si/Zr-based coating before and after immersion confirmed unchanged spectra of Si, O, C and Zr. On the other hand, XPS spectra of the Si-based coatings show the presence of corrosion products of aluminium (peaks for Al and Cl detected), which diffused through the coating. The difference in the corrosion resistance of both coatings was also confirmed in the salt spray chamber, where the Si/Zr-based coating remained stable for more than 500 h. The presented results provide a valuable demonstration of the correlation between EIS and XPS data and are crucial to showing the evidence of distribution of the aluminium corrosion products and coating degradation. Better barrier corrosion protection and lower coating degradation on the aluminium surface were achieved with a Si/Zr-based hybrid coating.
ACKNOWLEDGMENTS The authors acknowledge The  Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins (CIPKeBiP ), Ljubljana, Slovenia, to access scientific equipment (real-time FTIR). The authors also acknowledge the  Centre of Excellence in nanoscience and nanotechnology-Nanocentre, Ljubljana , Slovenia to access the scientific equipment (SEM/EDXS/FIB). The authors acknowledge  Barbara Kapun, BSc , for performing FIB/SEM analysis.
CRYPTREC CRYPTREC is the Cryptography Research and Evaluation Committees set up by the Japanese Government to evaluate and recommend cryptographic techniques for government and industrial use. The following activities have been carried out as part of CRYPTREC. The CRYPTREC cipher list was published in 2013, followed by the CRYPTREC Report 2014 on lattice problems. The Cryptanalysis Evaluation Working Group was formed in 2015. This group has published a Report on PQC in 2018. CRYPTREC plans to revise the CRYPTREC Cipher List to include post-quantum algorithms by 2022-2024. The details of the above activities are detailed in  [63]. Table  4  provides a summary of all the standardization efforts described. The Cloud Security Alliance Quantum-Safe Security Working Group's  [67]  goal is to address key generation and transmission methods that will aid the industry in understanding quantum-safe methods for protecting data through quantum key distribution (QKD) and post-quantum cryptography (PQC).
Codecrypt Codecrypt is the first free-of-cost software package available for quantum-safe encryption and digital signatures. Codecrypt  [68]   The cryptographic primitives of Codecrypt are similar to GnuPG software. The advantage of Codecrypt is that the complexity of all these quantum-safe cryptographic operations was scaled down to linear complexity from the respective exponential complexities in GnuPG. The speed of operations has increased significantly in Codecrypt due to this factor. The disadvantage of this software is that, although the signature schemes perform better than GnuPG, the encryption timing seems to be varying when the size of the message increases, except for the key generation part.
Open Quantum Safe Open Quantum Safe (OQS) is a project for implementing and evaluating various quantum-resistant cryptographic primitives. It is created by a team headed by researchers Douglas Stebila and Michele Mosca  [69]. The entire project is bifurcated into an opensource C library named 'liboqs' and a prototype integration suite of quantum-resistant algorithms in existing protocols and applications. The 'liboqs' library (https://github. com/open-quantum-safe/liboqs, accessed on 18 November 2020) provides the opensource implementation of various post-quantum key encapsulation mechanisms (KEM) and digital signature algorithms through a common API which can build on Windows, Linux and macOS. These can be executed overwork multiple platforms, including Intel x86, AMD, and ARM. The latest version of this library is 'liboqs 0.
6. 0' updated in June 2021, which is available in the Github repository, and is open to contributions. It includes all algorithms which made their entry to NIST Round 3 finalists or alternate candidates, except GeMSS. 'liboqs' can be integrated into different languages using language wrappers available with the package. Prototype integration is achieved by modifying original protocols and applications to provide post-quantum primitives. The developers forked OpenSSL and BoringSSL to integrate liboqs supporting quantum-safe hybrid key exchange and authentication (KEA) and cipher suites in TLS protocol. It also supports post-quantum algorithms in X. 509 certificate generation and S/MIME/CMS message handling. Test servers are provided to test the interoperability of these prototypes. OpenSSH is also modified into OQS-OpenSSH for implementing KEA.
jLBC The Java Lattice-based Cryptography Library (jLBC) (http://gas. dia. unisa. it/project s/jlbc/buildHowto. html, accessed on 17 November 2020) is a free Java library created by Angelo De Caro (https://github. com/adecaro/jlbc, accessed on 17 November 2020), a researcher at IBM Research Zurich. It is released under GNU public license. It has several modules providing API for the implementation of some lattice-based cryptosystems. 'jlbccrypto' is the main supporting library implementing such algorithms. It utilizes the Bouncy Castle Cryptographic API framework (https://www. bouncycastle. org/, accessed on 18 November 2020), which acts as an intermediary providing Java Cryptography Extension (JCE) and Java Cryptography Architecture (JCA) (https://docs. oracle. com/javase/7 /docs/technotes/guides/security/crypto/CryptoSpec.
Microsoft's Lattice Cryptography Library Microsoft product LatticeCrypto (https://www. microsoft. com/en-us/research/p roject/lattice-cryptography-library/, accessed on 20 November 2020) is a post-quantum cryptographic software that concentrates on lattice-based algorithms. It is created by a team of researchers including Michael Naehrig and Patrick Longa as principal contributors. The software is portable across a variety of platforms and is interoperable. It implements latticebased cryptographic primitives for key exchange and authentication KEA built on R-LWE for its security. The ring-based Learning With Errors (R-LWE) Problem is unbreakable with quantum computers, and thus the cryptographic schemes in this software are supposed to be efficient against resisting quantum attacks. The implementation includes novel techniques for computing the number theoretic transform to achieve higher performance.
The library successfully resists all timing and cache attacks reported so far. It supports Windows and Linux, and can be used on a wide range of platforms, including x86, x64, and ARM, and provides at least 128 bits of classical and quantum security. Besides these, there are other packages like ISARA Radiate Quantum-Safe Library that give a free sample code license, Palisade Homomorphic Encryption Library (http s://palisade-crypto. org/, accessed on 20 November 2020) which is an open-source lattice crypto-library, and Lattigo, which is a Go module that implements ring-learningwith-errors-based homomorphic-encryption primitives and multiparty-homomorphicencryption-based secure protocols. The implementation of post-quantum cryptographic schemes on the Android platform is highly necessary, as 90% of the mobile devices work on it.
The liboqs, jLBC, and LatticeCrypto are all capable of adapting the algorithms to the ARM platform, and are efficient candidates for developing quantum-safe schemes for Android devices. 'liboqs' library is mostly used by developers for building such applications. The source code can be compiled and integrated into several applications via cross-platform compilers and APIs. A licensed library of quantum-safe cryptographic schemes has been created by O. S. Estrada and team14, which is a ready-to-use package for quantum-safe development in an Android environment. Moreover, numerous independent researchers are working to integrate quantum safety on android devices.
5. libPQP libPQP (https://github. com/grocid/libPQP/blob/869dfbf86b8fe3a56ba3dbddc86f 1291ee0263d1/README. md, accessed on 20 November 2020) is a Python post-quantum library that stands for post-quantum PGP. The source code of this library has not yet been audited and can be used only for testing purposes, as declared by the developer. It concentrates on improving the efficiency of the QC-MDPC variant of the McEliece cryptosystem and has several vulnerabilities. The final product was supposed to use Salsa-20 and Poly 1305 cryptographic primitives. The current version of the library was deprecated due to a key recovery attack10 on QC-MDPC variant published in 2016.
was originally written by Miroslav Kratochvíl in 2013-2017, and is available in the Github repository (https://github. com/exaexa/code crypt, accessed on 18 November 2020). The C++ language has been chosen for the development of this package. It uses McEliece Cryptosystem with IND CCA2 secure QD-MDPC variant for encryption and Hash-based Merkle Tree Algorithm (FMTSeq variant) for digital signatures. It has a command-line interface which provides multiple commands under the following categories:.
3. 4 4. 5. libPQP libPQP (https://github. com/grocid/libPQP/blob/869dfbf86b8fe3a56ba3dbddc86f 1291ee0263d1/README. md, accessed on 20 November 2020) is a Python post-quantum library that stands for post-quantum PGP. The source code of this library has not yet been audited and can be used only for testing purposes, as declared by the developer. It concentrates on improving the efficiency of the QC-MDPC variant of the McEliece cryptosystem and has several vulnerabilities. The final product was supposed to use Salsa-20 and Poly 1305 cryptographic primitives. The current version of the library was deprecated due to a key recovery attack10 on QC-MDPC variant published in 2016.
was originally written by Miroslav Kratochvíl in 2013-2017, and is available in the Github repository (https://github. com/exaexa/code crypt, accessed on 18 November 2020). The C++ language has been chosen for the development of this package. It uses McEliece Cryptosystem with IND CCA2 secure QD-MDPC variant for encryption and Hash-based Merkle Tree Algorithm (FMTSeq variant) for digital signatures. It has a command-line interface which provides multiple commands under the following categories: • Encrypt, decrypt, sign and verify data • Key management operations • Input and output from standard I/O, as well as files • View options including help and ASCII formatting.
Statistical analysis All the lab experiments were carried out at least in triplicate. The physiological data were analysed by the Sigma Plot 12. 5 software, and the results were expressed as mean and standard deviation. To evaluate statistical significance, two-tailed t-student tests were applied with a p-value of 0. 05. P-values were corrected for multiple testing by the Bonferroni test. The phenotypical data were fitted to the reparametrized Gompertz model by non-linear least-squares fitting using the Gauss-Newton algorithm as implemented in the nls function in v. 3. 6 of the R statistical software. The cytometry results were tested by a one-way ANOVA and a Tukey HSD test (α = 0. 05, n=2). The FAME and sterol data were submitted to a one-way ANOVA with a subsequent analysis using the Tukey HSD test (p-value ≤ 0.
Acknowledgement The authors are particularly grateful to the  Lallemand Company  for providing us a collection of their commercial strains. This work has been financially supported by the  Spanish Government  through  MINECO  and  FEDER  funds ( AGL2016-77505-C3-1-R  and  PCIN-2015-143  grants) awarded to JMG. This study has been carried out as part of the European Project  ERA-IB "YeastTempTation ".
In metastatic colorectal cancer, there are few data on associations between early tumor shrinkage (ETS), depth of response (DpR), and patient characteristics. We assessed ETS and DpR by baseline Köhne category and tumor load. High-risk patients or those with BRAF mutations have lower chances of achieving an ETS of 30% or greater or a high DpR. An ETS of 30% or greater and a high DpR were associated with prolonged survival. Baseline tumor load was not linked with achieving an ETS of 30% or greater or a high DpR. Background: In metastatic colorectal cancer (mCRC), there are limited data on associations between early tumor shrinkage (ETS), depth of response (DpR), and patient characteristics. Methods: Data from patients with RAS wildtype mCRC who had participated in the PRIME (NCT00364013) and PEAK (NCT00819780) studies were analyzed retrospectively.
Study Design and Treatment This study was retrospective and not prespecified for either the PRIME study or the PEAK study. Details of the PRIME and PEAK studies have been reported previously. 33 , 34 Therefore, the study methods are described only briefly here. PRIME (NCT00364013) was a randomized, open-label, phase III study in which patients received panitumumab 6 mg/kg and FOLFOX4 every 2 weeks or FOLFOX4 alone every 2 weeks. 33 PEAK (NCT00819780) was a randomized, open-label, phase II study in which patients received mFOLFOX6 and either panitumumab 6 mg/kg or bevacizumab 5 mg/kg every 2 weeks. 34 he PRIME and PEAK studies, including the additional analyses reported here, were performed in accordance with the Declaration of Helsinki. The protocol of each study was approved by the ethics committee at each participating site.
Patients from the full pooled dataset were categorized into quartiles according to baseline tumor load: Q1, number of patients with baseline tumor load value of quartile 1 or less; Q2, number of patients with baseline tumor load value of more than quartile 1 and quartile 2 or less; Q3, number of patients with baseline tumor load value of more than quartile 2 and quartile 3 or less; and Q4, number of patients with baseline tumor load value of more than quartile 3. PFS and OS were assessed according to ETS, DpR, baseline Köhne category/ BRAF status, and baseline tumor load.
Statistical Analyses and Analysis Set The current analyses were conducted in the RAS wild-type efficacy analysis set, which comprised the subset of patients in the intent-to-treat efficacy analysis set whose tumors were confirmed as RAS wild type. To assess the relationship between LLD and an ETS of 30% or more versus less than 30% on outcomes, further analyses were performed in RAS wild-type patients with LLD, pooled across baseline Köhne category/ BRAF status. An ad hoc analysis of ETS and DpR in the high-risk Köhne category according to ECOG PS was also carried out. For all analyses, study treatment groups were pooled to increase the sample size. For the assessment of end points according to the baseline tumor load, data from the PRIME and PEAK studies were pooled. The median PFS and OS were estimated using the Kaplan-Meier method.
Baseline Köhne Category/BRAF Status Analysis (PRIME) ETS was analyzed in 436 participants from the PRIME study, of whom 216 received panitumumab plus FOLFOX4 and 220 received FOLFOX4 alone. The DpR was analyzed in 456 patients: 233 from the panitumumab plus FOLFOX4 arm and 223 from the FOLFOX4 arm. The number of patients differed between the 2 analyses because the ETS data were not available for patients with disease progression or who died before week 8. The likelihood of patients achieving an ETS of 30% or higher or a high DpR decreased with increasing baseline Köhne risk and was even lower in patients with a BRAF mutation ( Tables  1  and 2  ). The percentage of patients achieving an ETS of 30% or greater ranged from 63. 8% in the low-risk Köhne category to 21. 7% in the BRAFmutant category.