Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomic Dataflow based Graph-Level Workload Orchestration for Scalable DNN Accelerators

To efficiently deploy state-of-the-art deep neural network (DNN) workloads with growing computational intensity and structural complexity, scalable DNN accelerators have been proposed in recent years, which are featured by multi-tensor engines and distributed on-chip buffers. Such spatial architectures have significantly expanded scheduling space in terms of parallelism and data reuse potentials, which demands for delicate workload orchestration. Previous works on DNN’s hardware mapping problem mainly focus on operator-level loop transformation for single array, which are insufficient for this new challenge. Resource partitioning methods for multi-engines such as CNN-partition and inter-layer pipelining have been studied. However, their intrinsic disadvantages of workload unbalance and pipeline delay still prevent scalable accelerators from releasing full potentials.In this paper, we propose atomic dataflow, a novel graph-level scheduling and mapping approach developed for DNN inference. Instead of partitioning hardware resources into fixed regions and binding each DNN layer to a certain region sequentially, atomic dataflow schedules the DNN computation graph in workload-specific granularity (atoms) to ensure PE-array utilization, supports flexible atom ordering to exploit parallelism, and orchestrates atom-engine mapping to optimize data reuse between spatially connected tensor engines. Firstly, we propose a simulated annealing based atomic tensor generation algorithm to minimize load unbalance. Secondly, we develop a dynamic programming based atomic DAG scheduling algorithm to systematically explore massive ordering potentials. Finally, to facilitate data locality and reduce expensive off-chip memory access, we present mapping and buffering strategies to efficiently utilize distributed on-chip storage. With an automated optimization framework being established, experimental results show significant improvements over baseline approaches in terms of performance, hardware utilization, and energy consumption.
Accelerating Graph Convolutional Networks Using Crossbar-based Processing-In-Memory Architectures

Graph convolutional networks (GCNs) are promising to enable machine learning on graphs. GCNs exhibit mixed computational kernels, involving regular neural-network-like computing and irregular graph-analytics-like processing. Existing GCN accelerators obey a divide-and-conquer philosophy to architect two separate types of hardware to accelerate these two types of GCN kernels, respectively. This hybrid architecture improves intra-kernel efficiency but considers little inter-kernel interactions in a holistic view for improving overall efficiency.In this paper, we present a new GCN accelerator, RE-FLIP, with three key innovations in terms of architecture design, algorithm mappings, and practical implementations. First, ReFlip leverages PIM-featured crossbar architectures to build a unified architecture for supporting the two types of GCN kernels simultaneously. Second, ReFlip adopts novel algorithm mappings that can maximize potential performance gains reaped from the unified architecture by exploiting the massive crossbar-structured parallelism. Third, ReFlip assembles software/hardware co-optimizations to process real-world graphs efficiently. Compared to the state-of-the-art software frameworks running on Intel Xeon E5-2680v4 CPU and NVIDIA Tesla V100 GPU, ReFlip achieves the average speedups of 6,432× and 86.32× and the average energy savings of 9,817× and 302.44×, respectively. In addition, ReFlip also outperforms a state-of-the-art GCN hardware accelerator, AWB-GCN, by achieving an average speedup of 5.06× and an average energy saving of 15.63×.
Terminal differentiation and persistence of effector regulatory T cells essential for the prevention of intestinal inflammation

Regulatory T (Treg) cells represent a specialized CD4+ T cell lineage with essential anti-inflammatory functions. Recent studies of the adaptations of Treg cells to non-lymphoid tissues which enable their specialized immunosuppressive and tissue supportive functions raise questions about the underlying mechanisms of these adaptations and whether they represent stable differentiation or reversible activation states. Using novel genetic tools, we characterized the transcriptional programs of distinct colonic effector Treg cell types. We found that attenuated T cell receptor (TCR) signaling and acquisition of substantial TCR independent functionality appears to facilitate the terminal differentiation of a population of colonic effector Treg cells distinguished by stable expression of immunomodulatory cytokine interleukin-10 (IL-10). Functional studies revealed that this subset of effector Treg cells, but not their expression of IL-10, was indispensable for colonic health. These findings suggest core features of terminal differentiation of effector Treg cells in non-lymphoid tissues and their function therein.
cGAS/STING-DEPENDENT SENSING OF ENDOGENOUS RNA

Defects in nucleic acid metabolizing enzymes lead to spontaneous but selective activation of either cGAS/STING or RIG-like receptor (RLR) signaling, causing a pathogenic type I interferon response and inflammatory diseases. In these pathophysiological conditions, cGAS-driven IFN production is linked to spontaneous DNA damage. Physiological, or tonic, IFN signaling on the other hand is essential to functionally prime nucleic acid sensing pathways. Here we show that low-level chronic DNA damage in mice lacking the Aicardi-Goutières syndrome gene SAMHD1 reduced tumor-free survival when crossed to a p53-deficient, but not to DNA mismatch repair-deficient background. Increased DNA damage did not result in higher levels of type I interferon. Instead, we found that the chronic interferon response in SAMHD1-deficient mice was driven by the MDA5/MAVS pathway but required functional priming through the cGAS/STING pathway. Our work positions cGAS/STING upstream of tonic IFN signaling and highlights an important role of the pathway in physiological and pathophysiological innate immune priming. Summary Loss of the dNTPase and DNA repair enzyme SAMHD1 is associated with cancer and causes systemic autoimmunity. We show transformation-promoting spontaneous DNA damage and MDA5-driven but cGAS/STING-dependent chronic type I interferon production in SAMHD1-deficient mice.
Sensorimotor decisions rely on the entanglement of evidence and motor accumulation processes

Most contemporary theories of sensorimotor decision-making formalize the process leading up to a decision as a gradual accumulation of noisy stimulus information over time. The resulting evidence signal is thought to be continuously tested against an internal criterion representing the amount of evidence required to make the decision. In the currently prevailing view, the amount of accumulated evidence required for a decision is independent of the amount of sensory evidence presented by the stimulus, and once that level is reached, a choice is categorically communicated to the motor system to execute an overt response. Recent experimental research casts doubts on both of these assumptions. Using a Leaky Integrating Threshold model, we relax these assumptions specifying both an evidence accumulation and a motor accumulation process. The evidence accumulation signal feeds into a leaky motor accumulator, and it is on the level of the motor accumulation that the final decision criterion is set. This adaptation results in a markedly better description of choice-RT data, especially when it comes to urgency manipulations. We show that this alternative theory, which proposes that sensory evidence is doubly integrated before final evaluation, does not only describe the behavioral data better, but its neural correlates can also be readily derived from EEG signatures involving systems of both evidence and motor accumulation.
The time course of categorical and perceptual similarity effects in visual search

During visual search for objects (e.g., an apple), the surrounding distractor objects may share perceptual (tennis ball), categorical (banana), or both (peach) properties with the target. Previous studies showed that the perceptual similarity between target and distractor objects influences visual search. Here, we tested whether categorical target-distractor similarity also influences visual search, and how this influence depends on perceptual similarity. By orthogonally manipulating categorical and perceptual target-distractor similarity, we could investigate how and when the two similarities interactively affect search performance and neural correlates of spatial attention (N2pc) using electroencephalography (EEG). Behavioral results showed that categorical target-distractor similarity interacted with perceptual target-distractor similarity, such that the effect of categorical similarity was strongest when target and distractor objects were perceptually similar. EEG results showed that perceptual similarity influenced the early part of the N2pc (200-250 ms after stimulus onset), while categorical similarity influenced the later part (250-300 ms). Mirroring the behavioral results, categorical similarity interacted with perceptual similarity during this later time window, with categorical effects only observed for perceptually similar target-distractor pairs. Together, these results provide evidence for hierarchical processing in visual search: categorical properties influence spatial attention only when perceptual properties are insufficient to guide attention to the target. Public significance statement Searching for a target object among perceptually similar distractor objects (e.g., looking for an apple among peaches) is relatively difficult. In daily life, target and distractor objects may not only share perceptual but also non-perceptual properties, such as category membership (e.g., fruit). Here, we show that categorical similarity between target and distractor objects influences search performance, particularly when target and distractor objects are perceptually similar. Using electrophysiological recordings, we demonstrate that attentional selection is first influenced by perceptual and then by categorical information. This later categorical influence depended on perceptual similarity, being strongest for perceptually similar objects. These findings provide evidence for hierarchical processing in visual search, with categorical properties extracted after perceptual properties.
The Vibrio cholerae Seventh Pandemic Islands act in tandem to defend against a circulating phage

The current circulating pandemic El Tor biotype of Vibrio cholerae has persisted for over sixty years and is characterized by its acquisition of two unique genomic islands called the Vibrio Seventh Pandemic Islands 1 and 2 (VSP-I and VSP-II). However, the functions of most of the genes on VSP-I and VSP-II are unknown and the advantages realized by El Tor through these two islands are not clear. Recent studies have broadly implicated these two mobile genetic elements with phage defense. Still, protection against phage infection through these islands has not been observed directly in any V. cholerae El Tor biotype. Here we report the isolation of a circulating phage from a cholera patient stool sample and demonstrate that propagation of this phage in its native host is inhibited by elements in both VSP-I and VSP-II, providing direct evidence for the role of these genomic islands in phage defense. Moreover, we show that these defense systems are regulated by quorum sensing and active only at certain cell density. Finally, we have isolated a naturally occurring phage variant that is resistant to the defense conferred by the VSP islands, illustrating the countermeasures used by phages to evade these defense mechanisms. Together, this work demonstrates a functional role for the VSPs in V. cholerae and highlights the key regulatory and mechanistic insights that can be gained by studying anti-phage systems in their native contexts. SIGNIFICANCE (AUTHOR SUMMARY) The current pandemic strain of Vibrio cholerae carries two unique genomic islands. How these two islands confer evolutionary advantage to the pathogen is unknown. We show here the identification of a circulating phage that is sensitive to the defense systems present on these two islands and demonstrate how phage variants can evade these defenses. Our studies provide the first direct evidence showing the importance of these genomic islands in defending against phage in their native environments; and in doing so provide novel insight into the mechanisms of these highly conserved defense elements.
Insights into plastic biodegradation: community composition and functional capabilities of the superworm (Zophobas morio) microbiome in styrofoam feeding trials

Plastics are inexpensive and widely used organic polymers, but their high durability hinders biodegradation. Polystyrene, including extruded polystyrene also known as styrofoam, is among the most commonly produced plastics worldwide and is recalcitrant to microbial degradation. In this study, we assessed changes in the gut microbiome of superworms (Zophobas morio) reared on bran, polystyrene, or under starvation conditions over a three weeks’ time period. Superworms on all diets were able to complete their life cycle to pupae and imago, although superworms reared on polystyrene had minimal weight gains, resulting in lower pupation rates. The change in microbial gut communities from baseline differed considerably between diet groups, with polystyrene and starvation groups characterized by a loss of microbial diversity and the presence of opportunistic pathogens. Inferred microbial functions enriched in the polystyrene group included transposon movements, membrane restructuring, and adaptations to oxidative stress. We detected several encoded enzymes with reported polystyrene and styrene degradation abilities, supporting previous reports of polystyrene degrading bacteria in the superworm gut. By recovering metagenome-assembled genomes (MAGs) we linked phylogeny and functions and identified genera including Pseudomonas, Rhodococcus and Corynebacterium, that possess genes associated with polystyrene degradation. In conclusion, our results provide the first metagenomic insights into the metabolic pathways used by the gut microbiome of superworms to degrade polystyrene. Our results also confirm that superworms can survive on polystyrene feed, however, this diet has considerable negative impacts on host gut microbiome diversity and health. Impact Statement Increasing plastic pollution is a major environmental problem, and a recently proposed way to counteract this trend is to embrace a circular economy, in which used materials are recycled, rather than disposed of. An important step to facilitate this process is to invent new approaches for upcycling of plastic waste to desirable consumer products. Microbial plastic degradation and conversion is likely to play a considerable part in shaping a circular economy, by engineering microbes or their enzymes to bio-upcycle plastic waste. A first step towards actualizing this goal is to identify microbes that can degrade polystyrene and to investigate the enzymes and pathways involved. Our study represents the first metagenomic analysis of an insect gut microbiome on a polystyrene diet. It identifies bacteria with polystyrene and styrene degrading abilities, and infers enzymes and pathways involved in these reactions. Therefore, our results contribute towards understanding microbial polystyrene degradation and will provide a base for future investigations into microbial upcycling of plastic waste.
Detailed investigation on the role of lipid metabolizing enzymes in the pathogenesis of retinopathy of prematurity among preterm infants

Purpose Extremely preterm infants are at risk of developing retinopathy of prematurity (ROP), characterized by an initial insufficient vascular network development in the retina (due to hyperoxia) that progress to neovascularization and neuroinflammation (hypoxic phase) ultimately leading to partial or total vision loss. Lipid metabolism has been shown to be a significant pathway that is involved in the regulation of angiogenesis, inflammation, and apoptosis in oxygen induced retinopathy mouse model, however, it is not explored in human ROP patients. The present study aimed to explore the association of lipid metabolizing, angiogenic and apoptotic genes with altered lipid metabolites in the ROP patients with different severity. Methods The blood, vitreous humor (VH), and fibrovascular membrane (FVM) samples were collected from premature infants diagnosed with ROP and controls. Gene expression of lipid metabolizing enzymes, angiogenesis, and apoptotic genes were performed using semi-quantitative PCR in blood. Lipid metabolites were identified and quantified by LC-MS in VH and were correlated with gene expression. The expression of key lipid metabolizing enzymes in severe stages of ROP was assessed by measuring their expression in FVM by immunohistochemistry. Results Genes coding for the lipid metabolizing enzymes such as CYP1B1, CYP2C8, COX2, and ALOX15 were upregulated while EPHX2 responsible for the conversion of epoxide fatty acids into diol fatty acids was significantly downregulated in ROP cases. The increase in the metabolic intermediates generated from the lipid metabolism pathway further confirmed the role of these enzymes in ROP. except for EPHX2 which did not show any change in its activity. The glial cells in the FVM of ROP infants too showed a lack of EPHX2 expression. A significantly higher expression of genes involved in angiogenesis (VEGF165/189, NOTCH1, and APH1B) and apoptosis (CASP3/8) correlated with altered activity of lipid metabolizing enzymes (based on metabolites levels) among ROP cases. Conclusions Lipid metabolism may play a significant role in ROP development and progression. EPHX2 activity is a key step in the metabolic pathway of arachidonic acid that mediates and regulates inflammation and vascular pathology in preterm infants.
Unique Gut Microbiome Signatures among Adult Patients with Moderate to Severe Atopic Dermatitis in Southern Chinese

Imbalance of the immune system caused by alterations of gut microbiome is considered to be a critical factor in the pathogenesis of infant eczema but the exact role of the gut microbiome in adult atopic dermatitis (AD) patients remains to be clarified. To investigate the differences of the gut microbiome between adult AD patients and healthy individuals, stool samples of 234 adults, containing 104 AD patients and 130 healthy subjects were collected for amplicon sequencing. Altered structure and metabolic dysfunctions of the gut microbiome were identified in adult AD patients. Our results illustrated that the adult AD patients were more likely to have allergies, particularly non-food allergies. And the gut microbiome composition of the AD and normal groups were considerably different. Besides, Romboutsia and Clostridium_sensu_stricto_1 was enriched in the normal group, whereas Blautia, Butyricicoccus, Lachnoclostridium, Eubacterium_hallii_group, Erysipelatoclostridium, Megasphaera, Oscillibacter, Flavonifractor were dominated in the AD group. Moreover, purine nucleotide degradation pathways were significantly enriched in the AD group and the enrichment of proteinogenic amino acid biosynthesis pathways was found in the normal group. This study provides insights into new therapeutic strategies targeting the gut microbiome for AD and evidence for the involvement of gut-skin axis in AD patients.
Channel-independent function of UNC-9/Innexin in spatial arrangement of GABAergic synapses in C. elegans

Precise synaptic connection of neurons with their targets is essential for the proper functioning of the nervous system. A plethora of signaling pathways act in concert to mediate the precise spatial arrangement of synaptic connections. Here we show a novel role for a gap junction protein in controlling tiled synaptic arrangement in the GABAergic motor neurons in C. elegans, in which their axons and synapses overlap minimally with their neighboring neurons within the same class. We found that while EGL-20/Wnt controls axonal tiling, their presynaptic tiling is mediated by a gap junction protein UNC-9/Innexin, that is localized at the presynaptic tiling border between neighboring DD neurons. Strikingly, the gap junction channel activity of UNC-9 is dispensable for its function in controlling tiled presynaptic patterning. While gap junctions are crucial for the proper functioning of the nervous system as channels, our finding uncovered the novel channel-independent role of UNC-9 in synapse patterning.
An improved lattice structure design optimization framework considering additive manufacturing constraints

Purpose Methods to optimize lattice structure design, such as ground structure optimization, have been shown to be useful when generating efficient design concepts with complex truss-like cellular structures. Unfortunately, designs suggested by lattice structure optimization methods are often infeasible because the obtained cross-sectional parameter values cannot be fabricated by additive manufacturing (AM) processes, and it is often very difficult to transform a design proposal into one that can be additively designed. This paper aims to propose an improved, two-phase lattice structure optimization framework that considers manufacturing constraints for the AM process. Design/methodology/approach The proposed framework uses a conventional ground structure optimization method in the first phase. In the second phase, the results from the ground structure optimization are modified according to the pre-determined manufacturing constraints using a second optimization procedure. To decrease the computational cost of the optimization process, an efficient gradient-based optimization algorithm, namely, the method of feasible directions (MFDs), is integrated into this framework. The developed framework is applied to three different design examples. The efficacy of the framework is compared to that of existing lattice structure optimization methods. Findings The proposed optimization framework provided designs more efficiently and with better performance than the existing optimization methods. Practical implications The proposed framework can be used effectively for optimizing complex lattice-based structures. Originality/value An improved optimization framework that efficiently considers the AM constraints was reported for the design of lattice-based structures.
Decoding individual differences in mental information from human brain response predicted by convolutional neural networks

Recent advantages in brain decoding with functional magnetic resonance imaging (fMRI) have enabled us to estimate individual differences in mental information from brain responses to natural stimuli. However, the physical constraints and costs of fMRI measurements prevent brain decoding from achieving real-world applications. We address this issue by building a novel framework to decode individual differences in mental information under natural situations from brain responses predicted using convolutional neural networks (CNNs). Once the CNN-based prediction model is trained using measured response, mental information can be decoded from the predicted responses of individual brains with no need for additional fMRI measurements. The model was found to capture individual-difference patterns consistent with conventional decoding using measured responses in 81/87 items to be decoded. Our framework has great potential to decode personal mental information with low dependence on fMRI measurements, which could help substantially expand the applicability of brain decoding in daily life.