Miracle-dz/UniFAR-FTUs huggingface dataset:
Epistatic effect of C‐reactive protein (CRP) single nucleotide polymorphism (SNP) +1059 and interleukin‐1B SNP +3954 on CRP concentration in healthy male blood donors

Baseline C‐reactive protein (CRP) concentrations are indicative of persons prone to cardiovascular diseases and are about 40–50% heritable. We have previously shown that interleukin (IL)‐1B +3954 allele T is associated with lower CRP concentration. In this study, we aimed to examine the effect of this polymorphism together with the CRP +1059 gene polymorphism on baseline CRP concentrations, and genotyped 336 healthy blood donors for CRP +1059 (G→C) and IL‐1B +3954 (C→T) polymorphisms. In men, the carriers of the CRP +1059 C‐allele had significantly lower CRP values than GG homozygotes (0.66 versus 0.43 mg l−1, up to −35%, P = 0.009). No significant difference was found in women. When the data were stratified for both of these polymorphisms in men, CRP +1059 GG homozygotes had low CRP concentrations only if they were allele‐T carriers of IL‐1B +3954 simultaneously (0.93 versus 0.50 mg l−1, P = 0.013). Genotype CRP +1059 GG/IL‐1B +3954 CC was associated with an almost 3‐fold risk of a higher baseline CRP value [odds ratio (OR) 2.84 (CI 1.03–6.07)]. Thus, both IL‐1B +3954 (C→T) and CRP +1059 (G→C) polymorphisms influence baseline CRP values and act independently of each other in male subjects. These polymorphisms might be predictive markers of persons prone to cardiovascular diseases.
Towards 600 MHz LTE smartphones via tunable magnetodielectric Printed Inverted-F Antennas

The use of magnetodielectric reconfigurable antennas on smartphones was investigated aiming to meet the requirements of the lower bands of current 4G standards and beyond. Since physical dimensions are constrained by the size of the mobile terminal, a reconfigurability mechanism based on partial magnetodielectric substrates and superstrates was studied in order to shift the resonance frequency lower while maintaining low system complexity. A printed inverted-F antenna (PIFA) was used to demonstrate continuous tuning, as opposed to the discrete tuning states of other methods, e.g., aperture tuning by means of switched capacitors. The numerical analysis of the PIFA started with lossy, isotropic ferrites, and then it elevated to gyromagnetic anisotropy. It was found that some of the benefits of tunable magnetodielectric loading are the ability to cover the 600–960 MHz band with just 3–5 sub-bands requiring realistic values of permeability, whereas an adequate radiation efficiency is maintained throughout the band.
Conifer root and butt rot caused by Heterobasidion annosum (Fr.) Bref. s.l.

UNLABELLED SUMMARY The root and butt rot caused by Heterobasidon annosum is one of the most destructive diseases of conifers in the northern temperate regions of the world, particularly in Europe. Economic losses attributable to Heterobasidion infection in Europe are estimated at 800 million euros annually. The fungus has been classified into three separate European intersterile species P (H. annosum), S (H. parviporum) and F (H. abietinum) based on their main host preferences: pine, spruce and fir, respectively. In North America, two intersterile groups are present, P and S/F, but these have not been given scientific names. The ecology of the disease spread has been intensively studied but the genetics, biochemistry and molecular aspects of pathogen virulence have been relatively little examined. Recent advances in transcript profiling, molecular characterization of pathogenicity factors and establishment of DNA-transformation systems have paved the way for future advances in our understanding of this pathosystem. TAXONOMY Heterobasidion annosum (Fr.) Bref. , H. parviporum Niemelä & Korhonen and H. abietinum Niemelä & Korhonen; kingdom Fungi; class Basidiomycotina; order Aphyllophorales; family Bondarzewiaceae; genus Heterobasidion. IDENTIFICATION presence of the fungus fruit bodies, basidiocarps whitish in the margins, upper surface is tan to dark brown, usually irregular shaped, 3.5 (-7) cm thick and up to 40 cm in diameter; pores 5-19, 7-22 and 13-26 mm(2) for the P, F and S groups, respectively. Small brownish non-sporulating postules develop on the outside of infected roots. Asexual spores (conidiospores) are 3.8-6.6 x 2.8-5.0 microm in size. Mating tests are necessary for identification of intersterility groups. HOST RANGE The fungus attacks many coniferous tree species. In Europe, particularly trees of the genera Pinus and Juniperus (P), Picea (S), Abies (F) and in North America Pinus (P) and Picea, Tsuga and Abies (S/F). To a lesser extent it causes root rot on some decidous trees (Betula and Quercus). Disease symptoms: symptoms (e.g. exhudation of resin, crown deterioration) due to Heterobasidion root rot in living trees are not particularly characteristic and in most cases cannot be distinguished from those caused by other root pathogens. Heterobasidion annosum s.l. is a white rot fungus. Initial growth in wood causes a stain that varies in colour depending on host tree species. Incipient decay is normally pale yellow and it develops into a light brown decay to become a white pocket rot with black flecks in its advanced stage. CONTROL silvicultural methods (e.g. stump removal), chemicals (urea, borates) and biological control agent (Phlebiopsis gigantea, marketed as PG Suspension(R) in the UK, PG IBL(R) in Poland and Rotstop(R) in Fennoscandia) are commonly used approaches for minimizing the disease spread.
One visual search, many memory searches: An eye-tracking investigation of hybrid search

Suppose you go to the supermarket with a shopping list of 10 items held in memory. Your shopping expedition can be seen as a combination of visual search and memory search. This is known as “hybrid search. ” There is a growing interest in understanding how hybrid search tasks are accomplished. We used eye tracking to examine how manipulating the number of possible targets (the memory set size [MSS]) changes how observers (Os) search. We found that dwell time on each distractor increased with MSS, suggesting a memory search was being executed each time a new distractor was fixated. Meanwhile, although the rate of refixation increased with MSS, it was not nearly enough to suggest a strategy that involves repeatedly searching visual space for subgroups of the target set. These data provide a clear demonstration that hybrid search tasks are carried out via a “one visual search, many memory searches” heuristic in which Os examine items in the visual array once with a very low rate of refixations. For each item selected, Os activate a memory search that produces logarithmic response time increases with increased MSS. Furthermore, the percentage of distractors fixated was strongly modulated by the MSS: More items in the MSS led to a higher percentage of fixated distractors. Searching for more potential targets appears to significantly alter how Os approach the task, ultimately resulting in more eye movements and longer response times.
A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training

Systemic property dispossession from minority groups has often been carried out in the name of technological progress. In this paper, we identify evidence that the current paradigm of large language models (LLMs) likely continues this long history. Examining common LLM training datasets, we find that a disproportionate amount of content authored by Jewish Americans is used for training without their consent. The degree of over-representation ranges from around 2x to around 6.5x. Given that LLMs may substitute for the paid labor of those who produced their training data, they have the potential to cause even more substantial and disproportionate economic harm to Jewish Americans in the coming years. This paper focuses on Jewish Americans as a case study, but it is probable that other minority communities (e.g., Asian Americans, Hindu Americans) may be similarly affected and, most importantly, the results should likely be interpreted as a"canary in the coal mine"that highlights deep structural concerns about the current LLM paradigm whose harms could soon affect nearly everyone. We discuss the implications of these results for the policymakers thinking about how to regulate LLMs as well as for those in the AI field who are working to advance LLMs. Our findings stress the importance of working together towards alternative LLM paradigms that avoid both disparate impacts and widespread societal harms.
Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions with Applications

In this paper, we present a new antithetic multilevel Monte Carlo (MLMC) method for the estimation of expectations with respect to laws of diffusion processes that can be elliptic or hypo-elliptic. In particular, we consider the case where one has to resort to time discretization of the diffusion and numerical simulation of such schemes. Motivated by recent developments, we introduce a new MLMC estimator of expectations, which does not require simulation of intractable L\'evy areas but has a weak error of order 2 and achieves the optimal computational complexity. We then show how this approach can be used in the context of the filtering problem associated to partially observed diffusions with discrete time observations. We illustrate with numerical simulations that our new approaches provide efficiency gains for several problems relative to some existing methods.
Learning from Models and Data for Visual Grounding

We introduce SynGround, a novel framework that combines data-driven learning and knowledge transfer from various large-scale pretrained models to enhance the visual grounding capabilities of a pretrained vision-and-language model. The knowledge transfer from the models initiates the generation of image descriptions through an image description generator. These descriptions serve dual purposes: they act as prompts for synthesizing images through a text-to-image generator, and as queries for synthesizing text, from which phrases are extracted using a large language model. Finally, we leverage an open-vocabulary object detector to generate synthetic bounding boxes for the synthetic images and texts. We finetune a pretrained vision-and-language model on this dataset by optimizing a mask-attention consistency objective that aligns region annotations with gradient-based model explanations. The resulting model improves the grounding capabilities of an off-the-shelf vision-and-language model. Particularly, SynGround improves the pointing game accuracy of ALBEF on the Flickr30k dataset from 79.38% to 87.26%, and on RefCOCO+ Test A from 69.35% to 79.06% and on RefCOCO+ Test B from 53.77% to 63.67%.
Genotoxicity of naturally occurring indole compounds: correlation between covalent DNA binding and other genotoxicity tests

3‐Methylindole (3MI), melatonin (Mel), serotonin (Ser), and tryptamine (Tryp) were evaluated in vitro for their potential to induce DNA adducts, DNA strand breaks, chromosomal aberrations (Abs), inhibition of DNA synthesis, and mutations. All compounds produced DNA adducts in calf thymus DNA in the presence of rat liver S9. In cultured rat hepatocytes, all produced DNA adducts but none induced DNA strand breaks. In Chinese hamster ovary cells, 3MI and Mel produced DNA adducts, Abs, and inhibition of DNA synthesis with and without S9, except that Mel without S9 did not form adducts. Ser formed DNA adducts, was an equivocal Abs inducer, and suppressed DNA synthesis. Tryp induced neither adducts nor Abs, but did suppress DNA synthesis with S9. Ser and Tryp were less cytotoxic than 3MI and Mel. Mel, Ser, and Tryp failed to induce mutations in Salmonella and E. coli strains with or without S9. 3MI and Mel produced DNA adducts but not mutations in Salmonella TA100 with S9. 3MI and its metabolite indole 3‐carbinol also did not induce mutations in a shuttle vector system in human cells. The lack of correlation between DNA adducts and other genotoxicity endpoints for these indole compounds may be due to the higher sensitivity of the 32P‐postlabeling adduct assay or it may indicate that the indole‐DNA adducts per se are not mutagenic and are not able to induce strand breaks or alkali‐labile lesions. The indole‐induced Abs may result from cytotoxicity and suppression of DNA synthesis with minimal if any contribution from DNA adducts. Environ. Mol. Mutagen. 40:1–17, 2002. © 2002 Wiley‐Liss, Inc.
A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms

In this paper, a review is presented for the research on eye gaze estimation techniques and applications, which has progressed in diverse ways over the past two decades. Several generic eye gaze use-cases are identified: desktop, TV, head-mounted, automotive, and handheld devices. Analysis of the literature leads to the identification of several platform specific factors that influence gaze tracking accuracy. A key outcome from this review is the realization of a need to develop standardized methodologies for the performance evaluation of gaze tracking systems and achieve consistency in their specification and comparative evaluation. To address this need, the concept of a methodological framework for practical evaluation of different gaze tracking systems is proposed.
Adversarial Attacks and Defenses in Automated Control Systems: A Comprehensive Benchmark

Integrating machine learning into Automated Control Systems (ACS) enhances decision-making in industrial process management. One of the limitations to the widespread adoption of these technologies in industry is the vulnerability of neural networks to adversarial attacks. This study explores the threats in deploying deep learning models for fault diagnosis in ACS using the Tennessee Eastman Process dataset. By evaluating three neural networks with different architectures, we subject them to six types of adversarial attacks and explore five different defense methods. Our results highlight the strong vulnerability of models to adversarial samples and the varying effectiveness of defense strategies. We also propose a novel protection approach by combining multiple defense methods and demonstrate it's efficacy. This research contributes several insights into securing machine learning within ACS, ensuring robust fault diagnosis in industrial processes.
Performance of the New Aptima HCV Quant Dx Assay in Comparison to the Cobas TaqMan HCV2 Test for Use with the High Pure System in Detection and Quantification of Hepatitis C Virus RNA in Plasma or Serum

ABSTRACT Quantitating the level of hepatitis C virus (HCV) RNA is the standard of care for monitoring HCV-infected patients during treatment. The performances of commercially available assays differ for precision, limit of detection, and limit of quantitation (LOQ). Here, we compare the performance of the Hologic Aptima HCV Quant Dx assay (Aptima) to that of the Roche Cobas TaqMan HCV test, version 2.0, using the High Pure system (HPS/CTM), considered a reference assay since it has been used in trials defining clinical decision points in patient care. The assays' performance characteristics were assessed using HCV RNA reference panels and plasma/serum from chronically HCV-infected patients. The agreement between the assays for the 3 reference panels was good, with a difference in quantitation values of <0.5 log. High concordance was demonstrated between the assays for 245 clinical samples (kappa = 0.80; 95% confidence interval [CI], 0.720 to 0.881); however, Aptima detected and/or quantitated 20 samples that HPS/CTM did not detect, while Aptima did not detect 1 sample that was quantitated by HPS/CTM. For the 165 samples quantitated by both assays, the values were highly correlated (R = 0.98; P < 0.0001). The linearity of quantitation from concentrations of 1.4 to 6 log was excellent for both assays for all HCV genotypes (GT) tested (GT 1a, 1b, 2b, and 3a) (R 2 > 0.99). The assays had similar levels of total and intra-assay variability across all genotypes at concentrations from 1,000 to 25 IU/ml. Aptima had a greater analytical sensitivity, quantitating more than 50% of replicates at 25-IU/ml target. Aptima showed performance characteristics comparable to those of HPS/CTM and increased sensitivity, making it suitable for use as a clinical diagnostic tool on the fully automated Panther platform.
Differential modulation for two-way wireless communications: a perspective of differential network coding at the physical layer

This work considers two-way relay channels (TWRC), where two terminals transmit simultaneously to each other with the help of a relay node. For single antenna systems, we propose several new transmission schemes for both amplify-and-forward (AF) protocol and decode-and-forward (DF) protocol where the channel state information is not required. These new schemes are the counterpart of the traditional noncoherent detection or differential detection in point-to-point communications. Differential modulation design for TWRC is challenging because the received signal is a mixture of the signals from both source terminals. We derive maximum likelihood (ML) detectors for both AF and DF protocols, where the latter can be considered as performing differential network coding at the physical layer. As the exact ML detector is prohibitively complex, we propose several suboptimal alternatives including decision feedback detectors and prediction-based detectors. All these strategies work well as evidenced by the simulation results. The proposed protocols are especially useful when the required average data rate is high. In addition, we extend the protocols to the multiple-antenna case and provide the design criterion of the differential unitary space time modulation (DUSTM) for TWRC.
On Pretraining Data Diversity for Self-Supervised Learning

We explore the impact of training with more diverse datasets, characterized by the number of unique samples, on the performance of self-supervised learning (SSL) under a fixed computational budget. Our findings consistently demonstrate that increasing pretraining data diversity enhances SSL performance, albeit only when the distribution distance to the downstream data is minimal. Notably, even with an exceptionally large pretraining data diversity achieved through methods like web crawling or diffusion-generated data, among other ways, the distribution shift remains a challenge. Our experiments are comprehensive with seven SSL methods using large-scale datasets such as ImageNet and YFCC100M amounting to over 200 GPU days. Code and trained models will be available at https://github.com/hammoudhasan/DiversitySSL .
The optimal shape of cells of a superconducting accelerating section

The shape of TESLA accelerating structure can be improved to decrease maximal surface magnetic field by sacrificing and increasing maximal surface electric field. This sacrifice may be necessary because the magnetic field is a hard limit but electric field emission can be decreased by processing. For the case of superconducting cavities RF magnetic strength should be of a more concern.
What makes a small-world network? Leveraging machine learning for the robust prediction and classification of networks

The ability to simulate realistic networks based on empirical data is an important task across scientific disciplines, from epidemiology to computer science. Often simulation approaches involve selecting a suitable network generative model such as Erd\"os-R\'enyi or small-world. However, few tools are available to quantify if a particular generative model is suitable for capturing a given network structure or organization. We utilize advances in interpretable machine learning to classify simulated networks by our generative models based on various network attributes, using both primary features and their interactions. Our study underscores the significance of specific network features and their interactions in distinguishing generative models, comprehending complex network structures, and forming real-world networks
Wav2Gloss: Generating Interlinear Glossed Text from Speech

Thousands of the world's languages are in danger of extinction--a tremendous threat to cultural identities and human language diversity. Interlinear Glossed Text (IGT) is a form of linguistic annotation that can support documentation and resource creation for these languages' communities. IGT typically consists of (1) transcriptions, (2) morphological segmentation, (3) glosses, and (4) free translations to a majority language. We propose Wav2Gloss: a task to extract these four annotation components automatically from speech, and introduce the first dataset to this end, Fieldwork: a corpus of speech with all these annotations covering 37 languages with standard formatting and train/dev/test splits. We compare end-to-end and cascaded Wav2Gloss methods, with analysis suggesting that pre-trained decoders assist with translation and glossing, that multi-task and multilingual approaches are underperformant, and that end-to-end systems perform better than cascaded systems, despite the text-only systems' advantages. We provide benchmarks to lay the ground work for future research on IGT generation from speech.
Does Differentially Private Synthetic Data Lead to Synthetic Discoveries?

Background: Synthetic data has been proposed as a solution for sharing anonymized versions of sensitive biomedical datasets. Ideally, synthetic data should preserve the structure and statistical properties of the original data, while protecting the privacy of the individual subjects. Differential privacy (DP) is currently considered the gold standard approach for balancing this trade-off. Objectives: The aim of this study is to evaluate the Mann-Whitney U test on DP-synthetic biomedical data in terms of Type I and Type II errors, in order to establish whether statistical hypothesis testing performed on privacy preserving synthetic data is likely to lead to loss of test's validity or decreased power. Methods: We evaluate the Mann-Whitney U test on DP-synthetic data generated from real-world data, including a prostate cancer dataset (n=500) and a cardiovascular dataset (n=70 000), as well as on data drawn from two Gaussian distributions. Five different DP-synthetic data generation methods are evaluated, including two basic DP histogram release methods and MWEM, Private-PGM, and DP GAN algorithms. Conclusion: Most of the tested DP-synthetic data generation methods showed inflated Type I error, especially at privacy budget levels of $\epsilon\leq 1$. This result calls for caution when releasing and analyzing DP-synthetic data: low p-values may be obtained in statistical tests simply as a byproduct of the noise added to protect privacy. A DP smoothed histogram-based synthetic data generation method was shown to produce valid Type I error for all privacy levels tested but required a large original dataset size and a modest privacy budget ($\epsilon\geq 5$) in order to have reasonable Type II error levels.