Miracle-dz/UniFAR-FTUs huggingface dataset:
FP-DETR: Detection Transformer Advanced by Fully Pre-training

Large-scale pre-training has proven to be effective for visual representation learning on downstream tasks, especially for improving robustness and generalization. However, the recently developed detection transformers only employ pre-training on its backbone while leaving the key component, i.e., a 12-layer transformer, being trained from scratch, which prevents the model from above benefits. This separated training paradigm is mainly caused by the discrepancy between the upstream and downstream tasks. To mitigate the issue, we propose FP-DETR, a new method that Fully Pre-Trains an encoder-only transformer and smoothly finetunes it for object detection via a task adapter. Inspired by the success of textual prompts in NLP, we treat query positional embeddings as visual prompts to help the model attend to the target area (prompting) and recognize the object. To this end, we propose the task adapter which leverages self-attention to model the contextual relation between object query embedding. Experiments on the challenging COCO dataset demonstrate that our FP-DETR achieves competitive performance. Moreover, it enjoys better robustness to common corruptions and generalization to small-size datasets than state-of-the-art detection transformers. Code will be made publicly available at https://github.com/encounter1997/FP-DETR.
A Monte Carlo Simulation of Coulomb Collisions and Wave-Particle Interactions in Space Plasma at High Lattitudes

72 Introduction . 73 The Model. 75 Monte Carlo Simulation. 77 Wave Spectral Density. 78 Outflow Characteristics. 79 Finite Larmor Radius Effect. 88 Effect of WPI Level. 96 Summary. 100 References. 101 V · THE EFFECTS OF WAVE PARTICLE INTERACTIONS ON H+ AND o+ OUTFLOW AT HIGH LATITIJDE: A COMPARATIVE STUDY. 105 Abstract. 105 Introduction . 106 The Model. 109 Model Test. 113 Corrected Auroral Ion Outflow. 116 Comparison with the Mean Particle Theory. 121 The Effect of Body Forces. 123 Comparison Between WPI in the Auroral Region and the Polar Wind. 131 Conclusion. 134 References. 135 VI. CONCLUSION. 138 APPENDIX. 143 CURRICULUM VITAE. 147
Modeling Label Space Interactions in Multi-label Classification using Box Embeddings

Multi-label classification is a challenging structured prediction task in which a set of output class labels are predicted for each input. Real-world datasets often have taxonomic relationships between labels which can be explicit, implicit, or partially observed. Most existing multi-label classification methods either ignore the label taxonomy or require the complete specification of the taxonomy at training and inference time to enforce coherence in their predictions. In this work we introduce the multi-label box model (MBM), a multi-label classification method that combines the encoding power of neural networks with the inductive bias of probabilistic box embeddings (Vilnis et al., 2018), which can be understood as trainable Venn-diagrams based on hyper-rectangles. By representing labels as boxes, MBM is able to capture taxonomic relations among labels without them being provided explicitly. Furthermore, since MBM learns the label-label relationships from data and represents them as calibrated conditional probabilities, it provides a high degree of interpretability. This interpretability also facilitates the injection of partial information about label-label relationships into model training, to further improve its consistency. We provide theoretical grounding for our method and show experimentally the model’s ability to learn the true latent taxonomic structure from data. Through extensive empirical evaluations on twelve multi-label classification datasets, we show that MBM can significantly improve taxonomic consistency while maintaining the state-of-the-art predictive performance. 1
On walk-regular graphs and graphs with symmetric hitting times

Aldous [1] asked whether every graph in which the distribution of the return time of random is independent of the starting vertex must be transitive. We remark that this question can be reduced into a purely graph-theoretic one that had already been answered Godsil & McKay [6] and ask some questions motivated by this.
Evolutionary dynamics of genome size and content during the adaptive radiation of Heliconiini butterflies

Heliconius butterflies, a speciose genus of Müllerian mimics, represent a classic example of an adaptive radiation that includes a range of derived dietary, life history, physiological and neural traits. However, key lineages within the genus, and across the broader Heliconiini tribe, lack genomic resources, limiting our understanding of how adaptive and neutral processes shaped genome evolution during their radiation. We have generated highly contiguous genome assemblies for nine new Heliconiini, 29 additional reference-assembled genomes, and improve 10 existing assemblies. Altogether, we provide a major new dataset of annotated genomes for a total of 63 species, including 58 species within the Heliconiini tribe. We use this extensive dataset to generate a robust and dated heliconiine phylogeny, describe major patterns of introgression, explore the evolution of genome architecture, and the genomic basis of key innovations in this enigmatic group, including an assessment of the evolution of putative regulatory regions at the Heliconius stem. Our work illustrates how the increased resolution provided by such dense genomic sampling improves our power to generate and test gene-phenotype hypotheses, and precisely characterize how genomes evolve.
Lack of Specificity in Geobacter Periplasmic Electron Transfer

Many inner and outer membrane cytochromes used by Geobacter for electron transfer to extracellular acceptors have specific functions. How these are connected by periplasmic carriers remains poorly understood. G. sulfurreducens contains multiple triheme periplasmic cytochromes with unique biochemical properties and expression profiles. ABSTRACT Reduction of extracellular acceptors requires electron transfer across the periplasm. In Geobacter sulfurreducens, three separate cytoplasmic membrane cytochromes are utilized depending on redox potential, and at least five cytochrome conduits span the outer membrane. Because G. sulfurreducens produces 5 structurally similar triheme periplasmic cytochromes (PpcABCDE) that differ in expression level, midpoint potential, and heme biochemistry, many hypotheses propose distinct periplasmic carriers could be used for specific redox potentials, terminal acceptors, or growth conditions. Using a panel of marker-free single, quadruple, and quintuple mutants, little support for these models could be found. Three quadruple mutants containing only one paralog (PpcA, PpcB, and PpcD) reduced Fe(III) citrate and Fe(III) oxide at the same rate and extent, even though PpcB and PpcD were at much lower periplasmic levels than PpcA. Mutants containing only PpcC and PpcE showed defects, but these cytochromes were nearly undetectable in the periplasm. When expressed sufficiently, PpcC and PpcE supported wild-type Fe(III) reduction. PpcA and PpcE from G. metallireducens similarly restored metal respiration in G. sulfurreducens. PgcA, an unrelated extracellular triheme c-type cytochrome, also participated in periplasmic electron transfer. While triheme cytochromes were important for metal reduction, sextuple ΔppcABCDE ΔpgcA mutants grew near wild-type rates with normal cyclic voltammetry profiles when using anodes as electron acceptors. These results reveal broad promiscuity in the periplasmic electron transfer network of metal-reducing Geobacter and suggest that an as-yet-undiscovered periplasmic mechanism supports electron transfer to electrodes. IMPORTANCE Many inner and outer membrane cytochromes used by Geobacter for electron transfer to extracellular acceptors have specific functions. How these are connected by periplasmic carriers remains poorly understood. G. sulfurreducens contains multiple triheme periplasmic cytochromes with unique biochemical properties and expression profiles. It is hypothesized that each could be involved in a different respiratory pathway, depending on redox potential or energy needs. Here, we show that Geobacter periplasmic cytochromes instead show evidence of being highly promiscuous. Any of 6 triheme cytochromes supported similar growth with soluble or insoluble metals, but none were required when cells utilized electrodes. These findings fail to support many models of Geobacter electron transfer, and question why these organisms produce such an array of periplasmic cytochromes.
Cellular and computational models reveal environmental and genetic interactions in MMUT-type methylmalonic aciduria

MMUT-type methylmalonic aciduria is a rare inherited metabolic disease caused by the loss of function of the methylmalonyl-CoA mutase (MMUT) enzyme. Patients develop symptoms resembling those of primary mitochondrial disorders, but the underlying causes of mitochondrial dysfunction remain unclear. Here, we examined environmental and genetic interactions in MMUT deficiency using a combination of computational modeling and cellular models to decipher pathways interacting with MMUT. Immortalized fibroblast (hTERT BJ5ta) MMUT-KO (MUTKO) clones displayed a mild mitochondrial impairment in standard glucose-based medium, but they did not to show increased reliance on respiratory metabolism nor reduced growth or viability. Consistently, our modeling predicted MUTKO specific growth phenotypes only for lower extracellular glutamine concentrations. Indeed, two of three MMUT-deficient BJ5ta cell lines showed a reduced viability in glutamine-free medium. Further, growth on 183 different carbon and nitrogen substrates identified increased NADH (nicotinamide adenine dinucleotide) metabolism of BJ5ta and HEK293 MUTKO cells compared to controls on purine- and glutamine-based substrates. With this knowledge, our modeling predicted 13 reactions interacting with MMUT that potentiate an effect on growth, primarily those of secondary oxidation of propionyl-CoA, oxidative phosphorylation and oxygen diffusion. Of these, we validated 3-hydroxyisobutytyl-CoA hydrolase (HIBCH) in the secondary propionyl-CoA oxidation pathway. Altogether, these results suggest compensation for the loss of MMUT function by increasing anaplerosis through glutamine or by diverting flux away from MMUT through the secondary propionyl-CoA oxidation pathway, which may have therapeutic relevance. 1 sentence take-home message By perturbing metabolic pathways through genetic and environmental interventions in cellular and computational models of MMUT-type methylmalonic aciduria, we identified glutamine and secondary oxidative propionyl-CoA oxidation pathways as being important in the disease.
Spatiotemporal summation of perimetric stimuli in healthy observers

Spatial summation of perimetric stimuli has been used to derive conclusions about the spatial extent of retinal-cortical convergence, mostly from the size of the critical area of summation (Ricco’s area, RA) and critical number of Retinal Ganglion Cells (RGCs). However, spatial summation is known to change dynamically with stimulus duration. Conversely, temporal summation and critical duration also vary with stimulus size. Such an important and often neglected spatio-temporal interaction has important implications for modelling perimetric sensitivity in healthy observers and for formulating hypotheses for changes measured in disease. In this work, we performed experiments on visually heathy observers confirming the interaction of stimulus size and duration in determining summation responses in photopic conditions. We then propose a simplified computational model that captures these aspects of perimetric sensitivity by modelling the total retinal input, the combined effect of stimulus size, duration and retinal cones-to-RGC ratio. We additionally show that, in the macula, the enlargement of RA with eccentricity might not correspond to a constant critical number of RGCs, as often reported, but to a constant critical total retinal input. We finally compare our results with previous literature and show possible implications for modelling disease, especially glaucoma.
EEG-based Motor Imagery Decoding via Graph Signal Processing on Smooth Learned Graphs

 Abstract — Objective: This paper presents a graph signal processing (GSP)-based approach for decoding two-class motor imagery EEG data via deriving task-specific discriminative features. Methods: First, a graph learning (GL) method is used to learn subject-specific graphs from EEG signals. Second, by diagonalizing the normalized Laplacian matrix of each subject’s graph, an orthonormal basis is obtained using which the graph Fourier transform (GFT) of the EEG signals is computed. Third, the GFT coefficients are mapped into a discriminative subspace for differentiating two class data using a projection matrix obtained by the Fukunaga-Koontz transform (FKT). Finally, an SVM classifier is trained and tested on the variance of the resulting features to differentiate motor imagery classes. Results: The proposed method is evaluated on Dataset IVa of the BCI Competition III and its performance is compared to i) using features extracted on a graph constructed by Pearson correlation coefficients and ii) three state-of-the-art alternative methods. Conclusion: Experimental results indicate the superiority of the proposed method over alternative methods, reflecting the added benefit of integrating elements from GL, GSP and FKT. Significance: The proposed method and results underpin the importance of integrating spatial and temporal characteristics of EEG signals in extracting features that can more powerfully differentiate motor imagery classes.
lncRNA HOTAIRM1 Coordinates with RNA Processing Factors in DNA Damage Repair

The eukaryotic RNA processing factor Y14 participates in double-strand break (DSB) repair via its RNA-dependent interaction with the non-homologous end-joining (NHEJ) complex. We identified the long non-coding RNA HOTAIRM1 as a candidate that mediates this interaction. HOTAIRM1 localized to DNA damage sites induced by ionizing radiation. Depletion of HOTAIRM1 delayed the recruitment of DNA damage response and repair factors to DNA lesions and reduced DNA repair efficiency. Identification of the HOTAIRM1 interactome revealed a large set of RNA processing factors including mRNA surveillance factors. The surveillance factors Upf1 and SMG6 localized to DNA damage sites in a HOTAIRM1-dependent manner. Depletion of Upf1 or SMG6 increased the level of DSB-induced non-coding transcripts at damaged sites, indicating a pivotal role for Upf1/SMG6-mediated RNA degradation in DNA repair. We conclude that HOTAIRM1 serves as an assembly scaffold for both DNA repair and RNA processing factors that act in concert to repair DSBs.
Human Satellite 1 (HSAT1) analysis provides novel evidence of pericentromeric transcription

Pericentromeric regions of human chromosomes are composed of tandem-repeated and highly organized sequences named satellite DNAs. Although being known for a long time as the most AT-rich fraction of the human genome, classical satellite HSAT1 has been disregarded in genomic and transcriptional studies, falling behind other human satellites in terms of knowledge. The path followed herein trails with HSAT1 isolation and cloning, followed by in silico analysis. Monomer copy number and expression data was obtained in a wide variety of human cell lines, with greatly varying profiles in tumoral/non-tumoral samples. HSAT1 was mapped in human chromosomes and applied in in situ transcriptional assays. Additionally, it was possible to observe the nuclear organization of HSAT1 transcripts and further characterize them by 3’ RACE-Seq. Size-varying polyadenylated HSAT1 transcripts were detected, which possibly accounts for the intricate regulation of alternative polyadenylation. As far as we know, this work pioneers HSAT1 transcription studies. With the emergence of new human genome assemblies, acrocentric pericentromeres are becoming relevant characters in disease and other biological contexts. HSAT1 sequences and associated noncoding RNAs will most certainly prove significant in the future of HSAT research.
Improved model quality assessment using sequence and structural information by enhanced deep neural networks

Protein model quality assessment plays an important role in protein structure prediction, protein design, and drug discovery. In this work, DeepUMQA2, a substantially improved version of DeepUMQA for protein model quality assessment, is proposed. First, sequence features containing protein co-evolution information and structural features reflecting family information are extracted to complement model-dependent features. Second, a novel backbone network based on triangular multiplication update and axial attention mechanism is designed to enhance information exchange between inter-residue pairs. On CASP13 and CASP14 datasets, the performance of DeepUMQA2 increases by 20.5% and 20.4% compared with DeepUMQA, respectively (measured by top 1 loss). Moreover, on the three-month CAMEO dataset (March 11 to June 04, 2022), DeepUMQA2 outperforms DeepUMQA by 15.5% (measured by local AUC0,0.2) and ranks first among all competing server methods in CAMEO blind test. Experimental results show that DeepUMQA2 outperforms state-of-the-art model quality assessment methods, such as ProQ3D-LDDT, ModFOLD8, DeepAccNet, Atom_ProteinQA, and QMEAN3.
Apolipoprotein E genotype modulates longitudinal atrophy at the temporal lobe after mild traumatic brain injury

Backgrounds Moderate or severe traumatic brain injury (TBI) is one of the strongest environmental risks for late-life dementia, especially Alzheimer’s disease (AD). However, the interaction between genetic factors and environmental exposure to mild TBI triggering neurodegenerative processes is still unclear. We used longitudinal imaging to differentiate spatial patterns of progressive brain volume loss in individual patients with and without carrying apolipoprotein E (APOE) ε4 carriers. Methods For 59 patients with acute mild TBI (mTBI, age: 36.92 ± 11.91 years; 14 APOE ε4 carriers) and 48 matched healthy controls (HCs, age: 37.92 ± 11.72 years; 10 APOE ε4 carriers), longitudinal (6-12 months follow-up) brain structure was assessed using voxel-based morphometry on T1-weighted scans. Longitudinal volume changes in the temporal lobe were characterized by the Jacobian determinant (JD) metric, reflecting spatial warping between the baseline and follow-up scans. JD values were regionally calculated and correlated with neuropsychological measures. Results MTBI patients lost a mean of 0.27% (SD = 0.43) of GM and 0.27% (SD = 0.50) of WM volume in the temporal lobe over the 6-12 month follow-up. Patients with a high genetic risk for AD (APOE ε4 allele carries) were associated with severer atrophy in the left superior temporal gyrus and middle temporal gyrus regions than the controls (P < 0.05). Furthermore, atrophy in these regions of gray matter could predict the performance change ratio of the language fluency in mTBI APOE ε4 carriers (β = 0.570, P < 0.05). While, compared with HC APOE ε4 non-carriers, mTBI non-carriers exhibited volume loss in the medial temporal lobe. Conclusions This prospective study provided evidence that the APOE ε4 allele interacting with mTBI increased the risk of AD phenotype development with language dysfunction. Graphic Abstract
IL-12/18/21 pre-activation enhances the anti-tumor efficacy of expanded γδT cells and overcomes resistance to anti-PD-L1 treatment

γδT cells are promising candidates for cellular immunotherapy due to their immune regulation through cytokine production and MHC-independent direct cytotoxicity against a broad spectrum of tumors. However, current γδT cell-based cancer immunotherapy has limited efficacies and novel strategies are needed to improve its clinical outcomes. Here, we report that cytokine pre-treatment with IL-12/18, IL-12/15/18, IL-12/18/21 and IL-12/15/18/21 could effectively enhance the activation and cytotoxicity of in vitro expanded murine and human γδT cells. However, only adoptive transfer of IL-12/18/21 pre-activated γδT cells significantly inhibited tumor growth in a murine melanoma model and a hepatocellular carcinoma model. Both IL-12/18/21 pre-activated antibody-expanded and zoledronate-expanded human γδT cells effectively controlled tumor growth in a humanized mouse model. IL-12/18/21 pre-activation promoted γδT cell proliferation and cytokine production in vivo and enhanced IFN-γ and TNF-α production, as well as granzyme B expression by endogenous CD8+ T cells in a cell-cell contact dependent manner. Furthermore, the adoptive transfer of IL-12/18/21 pre-activated γδT cells could overcome the resistance to anti-PD-L1 therapy, and the combination therapy had a synergistic effect on the therapeutic outcomes. Moreover, the enhanced anti-tumor function of adoptively transferred IL-12/18/21 pre-activated γδT cells was largely diminished in the absent of endogenous CD8+T cells when administered alone or in combination with anti-PD-L1, suggesting a CD8+T cell-dependent mechanism. Taken together, IL-12/18/21 pre-activation could promote γδT cell anti-tumor function and overcome the resistance to checkpoint blockade therapy, indicating an effective combinational cancer immunotherapeutic strategy. Synopsis IL-12/18/21 pre-activation enhances the anti-tumor efficacy of adoptively transferred γδT cells by promoting its proliferation, activation, and cytotoxicity, as well as activating endogenous CD8+ T cells. Adoptive transfer of IL-12/18/21 pre-activated γδT cells could overcome the resistance to anti-PD-L1 therapy, indicating an effective combinational cancer immunotherapeutic strategy.
Initial Evaluation of the Intelligent Multi-UxV Planner with Adaptive Collaborative/Control Technologies (IMPACT)

Abstract : This report covers the first year of research and development for the Intelligent Multi-UxV Planner with Adaptive Collaborative/Control Technologies (IMPACT) program. The goal of IMPACT is to integrate autonomous technologies like cooperative control algorithms, intelligent agents, and autonomics frameworks with human-autonomy interfaces to support effective supervisory control of multiple heterogeneous unmanned vehicles (UxVs) in dynamic operating environments. With IMPACT, the human-autonomy team controls multiple UxVs by utilizing high level commands called plays. To evaluate the year one IMPACT system, seven participants were asked to use IMPACT to manage six UxVs in the context of a base defense mission. Participants rated both the overall IMPACT system and system subcomponents (play calling, autonomy, feedback, and test bed) positively. Objective data was also collected on the modality (mouse/keyboard, touchscreen, speech recognition) participants used to call plays. Participants not only used the mouse/keyboard more frequently, but also were faster and more accurate with the mouse/keyboard as compared to the touchscreen and speech recognition. Participant feedback has directly led to planned enhancements for the Spiral 2 IMPACT system.