Miracle-dz/UniFAR-FTUs huggingface dataset:
Adversary or Friend? An adversarial Approach to Improving Recommender Systems

Typical recommender systems models are trained to have good average performance across all users or items. In practice, this results in model performance that is good for some users but sub-optimal for many users. In this work, we consider adversarially trained machine learning models and extend them to recommender systems problems. The adversarial models are trained with no additional demographic or other information than already available to the learning algorithm. We show that adversarially reweighted learning models give more emphasis to dense areas of the feature-space that incur high loss during training. We show that a straightforward adversarial model adapted to recommender systems can fail to perform well and that a carefully designed adversarial model can perform much better. The proposed models are trained using a standard gradient descent/ascent approach that can be easily adapted to many recommender problems. We compare our results with an inverse propensity weighting based baseline that also works well in practice. We delve deep into the underlying experimental results and show that, for the users who are under-served by the baseline model, the adversarial models can achieve significantly better results.
MARRS: A Framework for multi-objective risk-aware route recommendation using Multitask-Transformer

One of the most significant map services in navigation applications is route recommendation. However, most route recommendation systems only recommend trips based on time and distance, impacting quality-of-experience and route selection. This paper introduces a novel framework, namely MARRS, a multi-objective route recommendation system based on heterogeneous urban sensing open data (i.e., crime, accident, traffic flow, road network, meteorological, calendar event, and point of interest distributions). We introduce a wide, deep, and multitask-learning (WD-MTL) framework that uses a transformer to extract spatial, temporal, and semantic correlation for predicting crime, accident, and traffic flow of particular road segment. Later, for a particular source and destination, the adaptive epsilon constraint technique is used to optimize route satisfying multiple objective functions. The experimental results demonstrate the feasibility of figuring out the safest and efficient route selection.
Initial Systems Theoretic Metamodel of Verification Artifacts

The last decade has seen an increase in calls for theoretical foundations of systems engineering (SE) along with a transformation to a model‐based and digital paradigm. This transformation is expected to facilitate improved verification. In fact, the literature suggests that the increased complexity of modern engineered systems is challenging the feasibility of traditional verification methods and requires new methods to cope with the change. Furthermore, a review of the SE literature suggests limited focus on verification research. Our research leverages systems theory to characterize the relationships between the verification artifacts. Specifically, we use systems theoretic morphisms to characterize the equivalence preservation between system requirements and verification requirements as well as between a system design and verification models. Although in initial form as provided in this article, our metamodel of verification artifacts is expected to contribute to the theoretical foundations of SE.
Lunar Laser Ranging Test of the Invariance of c

The speed of laser light pulses launched from Earth and returned by a retro-reflector on the Moon was calculated from precision round-trip time-of-flight measurements and modeled distances. The measured speed of light (c) in the moving observers rest frame was found to exceed the canonical value c = 299,792,458 m/s by 200+/-10 m/s, just the speed of the observatory along the line-of-sight due to the rotation of the Earth during the measurements. This is a first-order violation of local Lorentz invariance; the speed of light seems to depend on the motion of the observer after all, as in classical wave theory, and implies that a preferred reference frame exists for the propagation of light. However, the present experiment cannot identify the physical system to which such a reference frame might be tied.
Imperfection Sensitivity of Cylindrical Shells Under Shear Loading

One of the basic load cases relevant for the design of shell structures is torsion, which can occur exemplary in silos and tanks under seismic actions or even under wind loading. To address the stability problem of cylindrical shells under this load case, the relevant design standard EN 1993‐1‐6 and the European Recommendation ECCS EDR5 provide simple approaches for the buckling design of cylindrical shells. In order to improve the current hand calculation rules given in the above documents, this numerical study attempts to include the imperfection sensitivity of cylindrical shells subjected to uniform torsion.
Sirius B and the Measurement of the Gravitational Redshift

During much of the twentieth century, Albert Einstein’s General Theory of Relativity was widely regarded as resting on three basic astronomical observational verifications: the deflection of starlight during a solar eclipse; the explanation for the anomalous perihelion advance of Mercury’s orbit; and the gravitational redshift, first ‘observed’ in the white dwarf Sirius B. The first of these verifications was reported by the 1919 British solar eclipse expedition led by Arthur Eddington. The second involved a small (43 arc second per century) advance in the apsidal motion of Mercury’s perihelion, which was first discovered by U. J. J. Le Verrier in 1859, and which could not be explained by Newtonian gravity without hypothesizing perturbing ‘planets’ or massive ‘rings’ interior to Mercury’s orbit. The third verification, the measurement of a non-Doppler redshift in the spectral lines of the white dwarf Sirius B, was reported in 1925 by the eminent spectroscopist Walter S. Adams. This observation grew out of an extended correspondence between Adams and Arthur Eddington in 1924. Unlike the deflection of starlight and the perihelion advance of Mercury, the original Sirius B gravitational redshift measurement has not withstood the test of time. The redshift phenomenon is real enough but the original Adams measurement was too small by nearly a factor of four. Had this been apparent at the time, the Sirius B result surely would have been used as strong evidence against General Relativity rather than in support of it. As it was, the faulty redshift measurements of Sirius B also remained for many decades an impediment to a fuller understanding of white dwarf interiors and radii. It is ironic that the original observational measurement of the Sirius B redshift and the theoretical prediction that prompted it were both in error, and that the errors were such that they conspired to produce astonishingly good agreement. Previous papers in this series have reviewed the circumstances surrounding the discovery of Sirius B and the events leading to the realization of the existence of white dwarfs in general. The latter investigation involves both Eddington and Adams as major participants in the discovery of degenerate stars. In this paper I review the particular circumstances surrounding the measurements of the gravitational redshift in Sirius B. At the time of its announcement, and for some decades after that, Adams’s redshift measurement was regarded as both a triumphal verification of Einstein’s prediction of the gravitational redshift, and simultaneously as an empirical demonstration of Eddington’s ideas of the extraordinarily small radii and high densities of degenerate stars. Later, when better observations and more reliable theories of the structure of degenerate stars were available, questions began to be raised about JHA, xli (2010)
Ductile Fracture Simulation of Stainless Steel Coupons Under Monotonic Tensile Forces

Stainless steel alloys exhibit a nonlinear stress‐strain behaviour which can be precisely described by the Ramberg‐Osgood material model up to the ultimate stress. However, there is no consensus on the ductile fracture model under monotonic loading, which affects the post‐necking stress‐strain behaviour, to be adopted for stainless steels, even though the fracture model may have clear applications in structural design, such as in predicting joint failure in direct design approaches. This study presents the calibration of the fracture parameters for two of the most common ductile fracture models: the modified critical stress model and the Lee and Wierzbicki model. The calibrations are based on experimental results from tensile coupons tests on austenitic, ferritic and duplex stainless steel, extracted from cold‐formed tubes and sheet material, and on advanced finite element simulations. The calibrated values show a low dispersion for each of the analysed materials, indicating that the fracture parameters are an inherent property of the material, and which have been found to be slightly higher for the more ductile alloys. Average values of the fracture parameters for different stainless steels are also preliminarily proposed for their direct application in finite element simulations.
Trajectory Classification Method for Anchored Molecular Motor-Biopolymer Interactions in the C. elegans first Mitosis

During zygotic mitosis, forces generated at the cell cortex are required for the separation and migration of paternally provided centrosomes, pronuclear migration, proper segregation of genetic material, and successful cell division. Identification of individual cortical force generating units in vivo is necessary to study the regulation of microtubule dependent force generation throughout the cell cycle, to further understanding of asymmetric cell division, and to identify the molecular mechanism of force generation. Here we present a method to determine both the location and relative number of microtubule dependent cortical force generating units using single molecule imaging of fluorescently labelled dynein. Dynein behavior is modeled to differentiate and categorize trajectories that correspond to that which is cortically bound and interacting with a microtubule, and is cortically bound and not interacting with a microtubule. The categorization strategy recapitulates well known force asymmetries in the first mitosis of the C. elegans embryo. To evaluate the robustness of categorization, we RNAi depleted the microtubule subunit TBA-2 resulting in reduction of the number of trajectories categorized as engaged with a microtubule. This technique will be a valuable tool to provide new insight to the molecular mechanisms of dynein cortical force generation and its regulation as well as other instances wherein anchored motors interact with biopolymers (eg. Actin, tubulin, DNA).
RoboEM: automated 3D flight tracing for synaptic-resolution connectomics

Mapping neuronal networks from 3-dimensional electron microscopy data still poses substantial reconstruction challenges, in particular for thin axons. Currently available automated image segmentation methods, while substantially progressed, still require human proof reading for many types of connectomic analyses. RoboEM, an AI-based self-steering 3D flight system trained to navigate along neurites using only EM data as input, substantially improves automated state-of-the-art segmentations and replaces human proof reading for more complex connectomic analysis problems, yielding computational annotation cost for cortical connectomes about 400-fold lower than the cost of manual error correction.
LIS1, a glyco-humanized swine polyclonal anti-lymphocyte globulin, as a novel induction treatment in solid organ transplantation

Anti-thymocyte/lymphocyte globulins (ATGs/ALGs) are immunosuppressive drugs used in induction therapies to prevent acute rejection in solid organ transplantation. Because of animal origin, ATGs/ALGs contain highly immunogenic carbohydrate xenoantigens eliciting antibodies that are associated with subclinical inflammatory events possibly impacting long-term graft survival. Their strong and long-lasting lymphodepleting activity also increases the risk for infections. To circumvent these drawbacks, LIS1 has been engineered as a glyco-humanized polyclonal antibody obtained by immunizing genetically modified pigs knocked out for major xeno-antigens αGal and Neu5Gc. It is Fc-silenced in humans and differs from other ATGs/ALGs by its mechanism of action excluding antibody-dependent cell-mediated cytotoxicity and being restricted to complement and phagocyte-mediated cytotoxicity, apoptosis and antigen masking, resulting in profound inhibition of T-cell alloreactivity in mixed-leucocyte-reactions. Preclinical evaluation in macaques showed that LIS1 impacted CD4+, CD8+ effector T cells but not T-reg, B cells or myeloid cells. Compared with rabbit ATG, LIS1 induced transient depletion of target T cells in the peripheral blood but was equivalent in preventing allograft rejection in a skin allograft model. The novel therapeutic modality of LIS1 might present advantages in induction treatment after organ transplantation by shortening the T-cell depletion period while maintaining adequate immunosuppression and reducing immunogenicity.
How enhancers regulate wavelike gene expression patterns

A key problem in development is to understand how genes turn on or off at the right place and right time during embryogenesis. Such decisions are made by non-coding sequences called ‘enhancers’. Much of our models of how enhancers work rely on the assumption that genes are activated de novo as stable domains across embryonic tissues. Such view has been strengthened by the intensive landmark studies of the early patterning of the anterior-posterior (AP) axis of the Drosophila embryo, where indeed gene expression domains seem to arise more or less stably. However, careful analysis of gene expressions in other model systems (including the AP patterning in vertebrates and short-germ insects like the beetle Tribolium castaneum) painted a different, very dynamic view of gene regulation, where genes are oftentimes expressed in a wavelike fashion. How such gene expression waves are mediated at the enhancer level is so far unclear. Here we establish the AP patterning of the short-germ beetle Tribolium as a model system to study dynamic and temporal pattern formation at the enhancer level. To that end, we established an enhancer prediction system in Tribolium based on time- and tissue-specific ATAC-seq and an enhancer live reporter system based on MS2 tagging. Using this experimental framework, we discovered several Tribolium enhancers, and assessed the spatiotemporal activities of some of them in live embryos. We found our data consistent with a model in which the timing of gene expression during embryonic pattern formation is mediated by a balancing act between enhancers that induce rapid changes in gene expressions (that we call ‘dynamic enhancers’) and enhancers that stabilizes gene expressions (that we call ‘static enhancers’).
Grasshopper genome reveals long-term conservation of the X chromosome and temporal variation in X chromosome evolution

We present the first chromosome-level genome assembly of the grasshopper, Locusta migratoria, one of the largest insect genomes. We use coverage differences between females (XX) and males (X0) to identify the X chromosome gene content, and find that the X chromosome shows both complete dosage compensation in somatic tissues and an underrepresentation of testes-expressed genes. Remarkably, X-linked gene content from L. migratoria is highly conserved across four insect orders, namely Orthoptera, Hemiptera, Coleoptera and Diptera, and the 800 Mb grasshopper X chromosome is homologous to the fly ancestral X chromosome despite 400 million years of divergence, suggesting either repeated origin of sex chromosomes with highly similar gene content, or long-term conservation of the X chromosome. We use this broad conservation of the X chromosome to test for temporal dynamics to Fast-X evolution, and find evidence of a recent burst evolution for new X-linked genes in contrast to slow evolution of X-conserved genes. Additionally, our results reveal the X chromosome represents a hotspot for adaptive protein evolution related migration and the locust swarming phenotype. Overall, our results reveal a remarkable case of conservation and adaptation on the X chromosome.
A multiplexed plant-animal SNP array for selective breeding and species conservation applications

Reliable and high-throughput genotyping platforms are of immense importance for identifying and dissecting genomic regions controlling important phenotypes, supporting selection processes in breeding programmes, and managing wild populations and germplasm collections. Amongst available genotyping tools, SNP arrays have been shown to be comparatively easy to use and generate highly accurate genotypic data. Single species arrays are the most commonly used type so far; however, some multi-species arrays have been developed for closely related species that share SNP markers, exploiting inter-species cross-amplification. In this study, the suitability of a multiplexed plant-animal SNP array, including both closely and distantly related species, was explored. The performance of the SNP array across species for diverse applications, ranging from intra-species diversity assessments to parentage analysis, was assessed. Moreover, the value of genotyping pooled DNA of distantly related species on the SNP array as a technique to further reduce costs was evaluated. SNP performance was generally high, and species-specific SNPs proved suitable for diverse applications. The multi-species SNP-array approach reported here could be transferred to other species to achieve cost savings resulting from the increased throughput when several projects use the same array, and the pooling technique adds another highly promising advancement to additionally decrease genotyping costs by half.
Quantifying the bioavailable energy in an ancient hydrothermal vent on Mars and a modern Earth-based analogue

Putative alkaline hydrothermal systems on Noachian Mars were potentially habitable environments for microorganisms. However, the types of reactions that could have fueled microbial life in such systems and the amount of energy available from them have not been quantitatively constrained. In this study, we use thermodynamic modeling to calculate which catabolic reactions could have supported ancient life in a saponite-precipitating hydrothermal vent system in the Eridania basin on Mars. To further evaluate what this could mean for microbial life, we evaluated the energy potential of an analogue site in Iceland, the Strytan Hydrothermal Field (SHF). Results show that out of the 85 relevant redox reactions that were considered, the highest energy-yielding reactions in the Eridania hydrothermal system were dominated by methane formation. By contrast, Gibbs energy calculations carried out for Strytan indicate that the most energetically favorable reactions are CO2 and O2 reduction coupled to H2 oxidation. In particular, our calculations indicate that an ancient hydrothermal system within the Eridania basin could have been a habitable environment for methanogens using NH4+ as an electron acceptor. Differences in Gibbs energies between the two systems were largely determined by oxygen – its presence on Earth and absence on Mars. However, Strytan can serve as a useful analogue for Eridania when studying methane producing reactions that do not involve O2.
Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning

Given the prevalence of dementia and the development of pathology-specific disease modifying therapies, high-value biomarker strategies to inform medical decision making are critical. In-vivo tau positron emission tomography (PET) is an ideal target as a biomarker for Alzheimer’s disease diagnosis and treatment outcome measure. However, tau PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that impute tau PET images from more widely-available cross-modality imaging inputs. Participants (n=1,192) with brain MRI, fluorodeoxyglucose (FDG) PET, amyloid PET, and tau PET were included. We found that a CNN model can impute tau PET images with high accuracy, the highest being for the FDG-based model followed by amyloid PET and MRI. In testing implications of AI-imputed tau PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and MRI-based models utilized the non-local input from physically remote ROIs to estimate the tau PET, but this was not the case for the PiB-based model. This implies that the model can learn the distinct biological relationship between FDG PET, MRI, and tau PET from the relationship between amyloid PET and tau PET. Our study suggests that extending neuroimaging’s use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.