dataesr/scientific-paragraphs-categorization huggingface dataset:
A. Gem5 Modeling of the Scramble Cache The Scramble Cache model that we developed in Gem5 handles requests coming from slave ports (CPU-side) and has a master port that interacts with the memory-side (usually a bus), as shown on Figure  5. Once a packet (Gem5's abstraction of read or write requests) is received on a CPU-side slave port, the Scramble Cache determines if the cache can accept the packet or not: the cache only handles a single request at a time. When the Scramble Cache accepts a packet, it switches into a blocked mode and delays the packet processing by a constant delay representing the hit access time. If the line is found (normal hit) the cache instantly sends the response to the CPU. Otherwise, the history table is browsed linearly to check if older data can be moved. Depending on the index of the entry, an appropriate latency is added (a multiple of the hit access latency).
B. System Architecture To evaluate performances, we instantiate a simple system, depicted in Figure  5 , that is similar in terms of memory architecture to an embedded system. The baseline configuration uses Gem5's built-in L1 data and instruction caches of 32KB, 8-Way associative, with a random replacement policy. The L1 caches are configured with a hit latency of 2 CPU cycles. A history lookup step of the Scramble Cache has a latency defined to 1 CPU cycle. For the rest of the section, unless specified, the Scramble Cache history has a depth of 8-entries and its permutation change interval is set to 8192 accesses. We use a Linear Feedback Shift Register (LFSR) to generate pseudorandom numbers, with latency modeled to 1 cycle. We evaluate Scramble Cache performances by running workloads from the Mibench  [23]  benchmark suite in the small and large profiles.
First, the simulations are validated on the baseline system without countermeasures, to obtain a reference time. Then, for different parameters, we replace the L1 data cache with the Scramble Cache and compare the performance results against the baseline configuration. Our analysis focuses on the following parameters: the size of the L1 cache, the depth history table, and the permutation change interval (expressed in number of cache accesses). 2) Impact of cache size: Figure  6  shows the hit rate change in a 4kB, 8kB, 16kB, and 32kB L1 data cache for different workloads. A higher hit rate overhead is better and 0% denotes no degradation. In comparison with the baseline cache, the average performance loss by the Scramble Cache using is 0. 49% in the worst case (patricia). These results suggest that as the cache size increases, the Scramble Cache needs more time to write back all the dirty lines when the history table is full.
D. Security discussion The Scramble Cache mitigates the FLUSH+RELOAD and FLUSH+FLUSH attacks thanks to the partitioning implemented in the history lookup table. If the attacker flushes a line, the next reload operation at the same address will fail with high probability. The only case for the attack to observe a hit, would be to guess the exact future location where the data will be stored after scrambling, thus allowing the attacker to perform the RELOAD operation on that location. The random nature of the permutation makes the new address of the data flushed uniformly distributed. Thus, an attacker has 2 -S (S is the number of bits in the set field) chance to observe the correct result. This means that a larger number of sets will decrease the efficiency of these attacks. For other classes of attacks (address conflicts, PRIME+PROBE), the Scramble Cache adds extra noise to the victim memory access patterns to make them unexploitable.
The noise level is directly related to the permutation change interval. To validate this statement, we perform a simple PRIME+PROBE attack on the Scramble Cache (data cache) using the Gem5 model. The victim and the attacker run in the same process. Between PRIME and PROBE, the victim reads two fixed memory locations once. Figure  9  shows the average cache access times measured by the attacker after the victim execution for each cache set. Times are expressed in cycles and obtained by the x86 instruction rdtsc. As measurements are noisy (especially with the Scramble Cache), we repeat the experiment 100 times on the unprotected cache and 10,000 times on the Scramble cache (permutation change every 8096 and a history table of 8 elements). For the latter, we plot the mean (as a circle) and the standard deviation (as a bar) of the measurement.
Optical Characterization Figure  3a  shows the photoluminescence spectra of UCNP and UCNPs@MA nanoparticles obtained under an excitation of 980 nm. The PL spectra show visible emission of NaYF4 co-doped with Er 3+ and Yb 3+ ions, with green emission (512 and 560 nm) and red emission (640 and 680 nm) corresponding to the characteristic transition of Er 3+ ion activators from 4 H11/2, 4 S3/2, and 4 F9/2 levels to the 4 I15/2 ground state, respectively. The effect of hydrophilic polymer bonds on the luminescent intensity of UCNPs is evidenced in Figure  3a. The existence of polymer binding on the surface of the UCNPs results in a reduction of the emission intensity by a factor of about three. The CIE chromaticity coordinates (x = 0. 349, y = 0. 612) taken from PL data of the UC emission spectra using Origin software show the color of materials to be green, as shown in Figure  3b.
Optical Characterization Figure  3a  shows the photoluminescence spectra of UCNP and UCNPs@MA nanoparticles obtained under an excitation of 980 nm. The PL spectra show visible emission of NaYF 4 co-doped with Er 3+ and Yb 3+ ions, with green emission (512 and 560 nm) and red emission (640 and 680 nm) corresponding to the characteristic transition of Er 3+ ion activators from 4 H 11/2 , 4 S 3/2 , and 4 F 9/2 levels to the 4 I 15/2 ground state, respectively. The effect of hydrophilic polymer bonds on the luminescent intensity of UCNPs is evidenced in Figure  3a. The existence of polymer binding on the surface of the UCNPs results in a reduction of the emission intensity by a factor of about three. The CIE chromaticity coordinates (x = 0. 349, y = 0. 612) taken from PL data of the UC emission spectra using Origin software show the color of materials to be green, as shown in Figure  3b.
It allows for a full monitoring of ascending adults and descending smolts, from which phenotypic and genetic data have been secured annually. In turn, this provides a unique long-term data set on the down-and up-stream migratory patterns of brown trout in this river, located in a major farming region where marine survival is known to be low  [49]. We analyzed microsatellite DNA variation in all anadromous trout ascending the river from 2006 to 2016 and in all smolts emigrating from the river in 2017. We assessed temporal trends in the number of ascending spawners across years and used genetic data to estimate effective population sizes. We tested the hypothesis that census and effective population sizes had declined over the time span studied. Second, as migratory behaviour in general may involve genetic components  [33, 35, 36]   and specifically as some heritability has been shown in the timing of migration in other salmonid species  [28, 50] , we used genetically based parentage assignment and sibship reconstruction to test whether related individuals are more likely to migrate together than non-related individuals.
A specific test showed that among 600 smolts retained in a prolonged recovery, only 4 individuals (0. 7%) died (Ø. Skaala, unpublished results). Hence, we do not expect that handling has severely affected the smolts, and any effects should be randomly distributed among individuals and families. In addition, an upstream trap is operated each year during the upstream migration to capture all anadromous trout ascending the river. Each fish is anaesthetised, fin-clipped, checked for PIT tag, measured and weighed before being released upstream to continue its migration. Tissue samples for both smolts and ascending fish were stored in 95% ethanol. For this study, we used data on 711 ascending fish collected between 2006 and 2016 (Table  1 ), representing all the adults entering the system in this period.
PCR was repeated for each sample until data were obtained for most loci. In the whole dataset, 3 individuals had missing data at 3 loci, 4 at 2 loci and 56 at 1 locus, out of the 21 loci genotyped. When several PCRs had been conducted for the same individuals, they were compared and the one with the most clear-cut signal was considered right in case of conflict. The locus BG935488 was excluded from the dataset due to difficulties with reliable scoring of alleles. As loci MHC-I and Sasa-TAP2A are closely linked to loci associated with immune responses and have previously been suggested to be under diversifying selection among trout populations from the Hardanger Fjord  [59] ; they were omitted from analyses of effective population size but were used for sibship reconstruction (see below). Tissue samples were accidentally missing for 20 of the ascending trout (Table  1 ).
Genetic diversity and effective population size Total number of alleles and allelic richness (A r ) per locus were computed with the R package diveRsity  [61] , using R 3. 6. 1  [62]. Observed (H O ) and unbiased expected heterozygosity (H E ), as well as inbreeding coefficient (F IS ) were computed with GenAlEx 6. 5. Tests for Hardy-Weinberg equilibrium were performed with Genepop 4. 7  [63]  using the following Markov chain parameters: 10,000 dememorisation steps, 1000 batches and 10,000 iterations per batch. False discovery rate (FDR) correction was applied to account for multiple testing  [64] , using the method by Y Benjamini and Y Hochberg  [65]  implemented in Myriads 1. 1  [66]. Effective population sizes (N e ) for the ascending sea trout and the smolts were estimated with the linkage disequilibrium method implemented in NeEstimator 2.
Sibship and parentage assignment COLONY 2. 0. 5. 1  [71]  was used to infer full and half sibships both in the 2006-2016 ascending trout and the smolt 2017 datasets. This software infers all possible relationships (siblings and parentage) of all individuals (all offspring and all candidate parents) simultaneously in a full likelihood framework. Analyses of the ascending trout dataset were conducted with no information on parental genotypes, assuming both male and female polygamy as well as possible inbreeding. The full-likelihood method was used at very high precision for the full likelihood calculation and medium run length together with the options sibship scaling, no updated allele frequencies and no sibship priors. In the analysis of the smolt dataset, the trout ascending in or after 2010 were used as candidate parents.
Only the relationships found in the 3 runs were kept in the inferred pedigree. Allelic dropout rate in the input file was estimated with the PopGenReport R package  [73]. Genotyping error rate was set to 0. 01 for all loci. Each time, full and half-sibships were inferred from the "best configuration" COLONY output files, which is more accurate than the results found by the pairwise analysis in the files full and halfsib dyads  [74]. More than 50% of male parr in a population can be precocious  [75] [76] [77]. As it would be infeasible to sample all resident trout and not least precocious male parr from the system, we inferred the parentage of resident trout indirectly. Hence, when none or only one of the two parents of a smolt was identified among the anadromous candidate parents, it was assumed that missing parents were part of the resident proportion of the population.
Sibship and timing of migration events To test whether related individuals tend to migrate at the same time (both for ascending adults and descending smolts), Mantel tests were conducted between a distance matrix comprising the sibship previously found between pairs of individuals, coded as 1 for unrelated, 0. 75 for halfsibs and 0. 5 for fullsibs, and a matrix with the distance in days between their date of capture in the traps. The R package ecodist  [78]  was used for these analyses, and significance was assessed using 10,000 permutations together with 1000 bootstraps. The test was conducted separately for each year in the ascending spawners. Fish that did not have any siblings within the samples of the year or in the smolt sample were removed from the analyses, in order not to bias the results.
Genetic variation and effective population size estimated from ascending spawners A total of three deviations from Hardy-Weinberg equilibrium were found in the microsatellite DNA dataset for annually ascending trout after Benjamini and Hochberg  [80]  False Discovery Rate correction (Table  2 ). As they concerned three different loci that were not deviating in other annual samples, they were all retained in the analyses. Mean unbiased expected heterozygosity (H E ) was high and stable across years, ranging from 0. 74 to 0. 76, and F IS was not significantly different from 0, except in 2012 and 2013 where it nevertheless remained low (Table  2 ). Estimates of mean effective population size (N e ) showed considerable variation, ranging between 83 in 2014 and 3646 in 2010 (Table  2 ). The highest N e estimate coincided with the lowest sample size (N = 25) and showed a very wide 95% confidence interval (94-∞), indicating that the point estimate is not informative.
DNA was extracted using a DNeasy blood and tissue kit with an RNAse A step (Qiagen), following the manufacturer's instructions. The DNA was sequenced (HiSeq 4000) and cleaned by BGI (Hong Kong) (7 723 274 reads at 150 bp length). The T. brucei EATRO 1125 AnTat 1. 1 90 : 13 raw data have been submitted to the NCBI SRA (PRJNA720808). The complete list of genomes analysed in this study, including their accession IDs, are summarized in the Table  S1. The quality of the raw reads was analysed with fastqc (v. 0. 11. 9) and subjected to quality trimming with trimmomatic (v0. 39)  [21]. The reads were trimmed with the following filters: SLID-INGWINDOW 4 : 20; ILLUMINACLIP adapters. fa 2 : 40 : 15; MINLEN 25. The trimmed reads were aligned to the T. brucei TREU927/4 V5 reference genome  [22]  with bwa-mem (v.
Monomorphism arose independently at least four times To determine the evolutionary relationships between monomorphic Trypanozoon, genomic data from 17 isolates were aligned to the T. brucei TREU 927/4 reference genome. This included publicly available data from monomorphic (n=9) and pleomorphic isolates (n=8). Across the T. brucei TREU 927/4 v5 reference genome, 472 794 variant sites (574 775 unique variant alleles, 370 154 SNPs and 204 621 indels) passed the strict quality filtering steps. These sites were filtered further to identify 244 013 homozygous variant SNPs across the genome. A total of 91 853 of these SNPs were present in a CDS on one of the 11 Mb chromosomes of the T. brucei TREU 927/4 v5 reference genome. The SNPs across the whole genome and those in a CDS were used to generate two unrooted phylogenetic trees.
Gut microbiota Statistical analyses were performed, and graphs were plotted with R software (version 3. 6. 0). Total bacterial count (as log10-transformed), alpha diversity, Shannon index ITS/16S ratio were analyzed as change from baseline using linear mixed model (nlme 3. 1-140) as described above or using Mann-Whitney or Wilcoxon signed rank test when normality was rejected. Betadiversity was analyzed using PERMANOVA (vegan 2. 5-6) and pairwise group mean dispersions using Tukey HSD. Quantitative Microbiome Profiling (QMP) was done as described by Vandeputte et al. 13. Differential analyses were performed with DESeq2 (version 1. 24. 0) on 16S based QMP and ITS datasets. Fold changes were evaluated with the Wald test (FDR adj. p < 0. 1). P-values were adjusted for multiple testing with the Benjamini-Hochberg procedure (padj).
Gut mycobiota response to Hp treatment and product intervention We monitored fungal dynamics across the study. While there was no change in ITS Shannon index in response to Hp treatment (Figure  4A ), we observed a transient increase in the fungi to bacteria (ITS/16S) Shannon ratio at V4 (padj = 5. 79  E-03  ) which then reverted to baseline at V7 (padj = 0. 864), with a trend for a lower ITS/16S ratio (p = 0. 08) in the Test group (Figure  4B ). The abundance of Candida was transiently enriched following 14-day Hp treatment (adj= 1. 81 E-25 ), followed by a recovery to baseline level (V2 to V7 padj = 0. 467), with no difference between groups (Figure  4C ). Additional data are provided in Additional file 5: Results.
Bioinformatic analysis Raw sequences, forward and reverse, were merged in order to obtain the complete sequence using the 'pear v0. 9. 6' software. The amplification primers from the sequences obtained in the sequencing step were trimmed to reduce the bias in the annotation step, with 'cutadapt v 1. 8. 1' and parameters by default. Once the primers removed, sequences smaller than 200 nucleotids were removed from the analysis. After obtaining the clean complete sequences, a quality filter was applied to them to delete poor quality sequences. Those bases in extreme positions that did not reach Q20 (99% well incorporated base in the sequencing step) or a greater quality score were removed. Subsequently, sequences whose average quality did not surpass the Q20 threshold, as a mean quality of the whole sequence, were also deleted.
The resulting sequences were inspected for PCR chimera constructs that may occur during the different experimental processes. Chimeras were removed from further analysis. Analyses were performed using QIIME (v. 19). After filtering for quality, a mean of 99,437± 36,973 sequences per sample were retained. Reads were clustered into operational taxonomic units (OTUs; 97% identity threshold) using VSEARCH, and representative sequences for each OTU were aligned and taxonomically assigned using the SILVA database (v. 119) and the Unite database (v. 7. 2 (ITS). To characterize diversity, rarefaction was used to obtain 22,000 sequences per sample. Alpha diversity (within samples) was assessed using Shannon index) and Simpson's Reciprocal index for 16S rRNA and using Shannon index for ITS). The ITS/16s ratio was computed for Shannon index  8.
Beta diversity was represented using Bray-Curtis dissimilarity and UniFrac distances (weighted and unweighted) for 16S rRNA and Bray-Curtis dissimilarity for ITS. 2 cigarettes; 1 big cigar = 5 cigarettes). Subjects dietary habits during the past month was reported at V2 and V6 at investigation site through a Food Frequency Questionnaire (FFQ)  10  , adapted for diet reporting of the past month. FFQ outputs were converted in daily amounts of nutrient intake using software developed by the German Institute of Human Nutrition (DIFE), Potsdam. Subject alcohol consumption was reported weekly at all visits and converted to the average number of alcohol units per week (one unit= 10 grams of pure alcohol). In a personal e-diary, through electronic Patient Reported Outcomes (ePRO) software (Patient Cloud, Medidata), subjects daily reported their compliance with the Hp eradication therapy, with the study product consumption and with the dietary restrictions, in the corresponding periods, as well as any adverse event, concomitant medication and nutritional supplement intake from V2 to V7.
and Additional file 1: methods. Additional stools were collected at the first day and after the end of each AAD episode. The study was performed in accordance with the Declaration of Helsinki and Good Clinical Practice (International Conference on Harmonisation E6) and approved by the Ethics Committee of Charité -Campus Mitte (Application Number EA1/297/15) of the Charité -Universitätsmedizin Berlin, Germany. All volunteers provided a signed informed consent form (ICF). The trial was registered on clinicaltrials. gov (registration number: NCT02900196). Subject selection Screening lasted from September 16 th 2016 (first inclusion [ICF signature]) to May 31 st 2017 (Last inclusion), and the study experimental phase from October 07th 2016 (first randomization) to August 10 th 2017 (last visit).
Mixed Reality Framework Unity (Unity Technologies, San Francisco, CA, United States) was selected as the development platform because it allows easy interaction with visual elements (both 2D or 3D) and integrates different plugins and libraries that greatly facilitate the implementation, allowing for the porting of applications to most extended platforms. Each application considered one or more scenes, which in turn were made up of objects structured in the form of a parent-child hierarchy. Each of the objects had a "Transform" component, a script that controls its position, rotation, and scale, fostering the possibility of adding many other different components even in the form of userprogrammed scripts. Microsoft Visual Studio was adopted as the programming environment, with C# as the programming language, to deploy the applications on the device.
Additionally, voice commands were available to show or hide the different tools by saying "show/ hide" followed by "preoperative study/three-dimensional model/clinical history/medical illustration/surgical video". As a first step, the application loaded preoperative imaging studies (following the DICOM standard) from a local or remote file location. Each image view (axial, coronal, and sagittal) was displayed on an individual panel (Figure  2A ), which allowed the user to navigate (forward or backward) within the set of available slices. These preoperative imaging studies have also been used to create 3D anatomical models. For this purpose, 3D Slicer (www. slicer. org), an open-source software package for medical image analysis, was used. The user can adjust position, rotation, and scale of the 3D model to facilitate its visualisation.
Regarding the module for generating the 3D model from the preoperative imaging study, it allowed the scaling, rotation, and positioning of the model to the user's preference for a better perception of the patient's anatomy. The generation of this content involved a certain computational cost depending on the model; therefore, caution should be exercised when segmenting the anatomical areas of interest, as well as in the subsequent reduction of polygons of the resulting mesh. In the cases described in this study, it was not necessary to reduce the mesh of the 3D model obtained. However, it is suggested to use standard materials provided by Microsoft's Mixed Reality ToolKit framework. For the visualisation of reference surgical videos, it would be possible to temporarily label them and separate their content into chapters, thus allowing easier access to the different steps involved in the surgery.
The surgeon also had access to reference surgical videos, as well as different documents with the patient's clinical history and reference anatomical illustrations. The surgeon's vision, together with the information in the form of holograms, was shared on the screens of the OR via streaming. It should be noted that this video streaming suffered a slight time delay of approximately one second during the entire retransmission using the Microsoft Windows Device Portal software. The streaming option of our tool allowed all personnel inside and outside the OR to directly see what the surgeon saw. This feature was also reported by  Gregory et al. during surgery for the implantation of a shoulder prosthesis  (Gregory et al. , 2018). This tool can also be used in videoconferences during live surgeries as a method of immersion in the surgery.