NMS Strikes Back

Detection Transformer (DETR) directly transforms queries to unique objects by using one-to-one bipartite matching during training and enables end-to-end object detection. Recently, these models have surpassed traditional detectors on COCO with undeniable elegance. However, they differ from traditional detectors in multiple designs, including model architecture and training schedules, and thus the effectiveness of one-to-one matching is not fully understood. In this work, we conduct a strict comparison between the one-to-one Hungarian matching in DETRs and the one-to-many label assignments in traditional detectors with non-maximum supervision (NMS). Surprisingly, we observe one-to-many assignments with NMS consistently outperform standard one-to-one matching under the same setting, with a significant gain of up to 2.5 mAP. Our detector that trains Deformable-DETR with traditional IoU-based label assignment achieved 50.2 COCO mAP within 12 epochs (1x schedule) with ResNet50 backbone, outperforming all existing traditional or transformer-based detectors in this setting. On multiple datasets, schedules, and architectures, we consistently show bipartite matching is unnecessary for performant detection transformers. Furthermore, we attribute the success of detection transformers to their expressive transformer architecture. Code is available at https://github.com/jozhang97/DETA.Comment: Code is available at https://github.com/jozhang97/DET

Predicting a Protein's Stability under a Million Mutations

Stabilizing proteins is a foundational step in protein engineering. However, the evolutionary pressure of all extant proteins makes identifying the scarce number of mutations that will improve thermodynamic stability challenging. Deep learning has recently emerged as a powerful tool for identifying promising mutations. Existing approaches, however, are computationally expensive, as the number of model inferences scales with the number of mutations queried. Our main contribution is a simple, parallel decoding algorithm. Our Mutate Everything is capable of predicting the effect of all single and double mutations in one forward pass. It is even versatile enough to predict higher-order mutations with minimal computational overhead. We build Mutate Everything on top of ESM2 and AlphaFold, neither of which were trained to predict thermodynamic stability. We trained on the Mega-Scale cDNA proteolysis dataset and achieved state-of-the-art performance on single and higher-order mutations on S669, ProTherm, and ProteinGym datasets. Code is available at https://github.com/jozhang97/MutateEverythingComment: NeurIPS 2023. Code available at https://github.com/jozhang97/MutateEverythin

Thermodynamics of concentrated solid solution alloys

This paper reviews the three main approaches for predicting the formation of concentrated solid solution alloys (CSSA) and for modeling their thermodynamic properties, in particular, utilizing the methodologies of empirical thermo-physical parameters, CALPHAD method, and first-principles calculations combined with hybrid Monte Carlo/Molecular Dynamics (MC/MD) simulations. In order to speed up CSSA development, a variety of empirical parameters based on Hume-Rothery rules have been developed. Herein, these parameters have been systematically and critically evaluated for their efficiency in predicting solid solution formation. The phase stability of representative CSSA systems is then illustrated from the perspectives of phase diagrams and nucleation driving force plots of the σ phase using CALPHAD method. The temperature-dependent total entropies of the FCC, BCC, HCP, and σ phases in equimolar compositions of various systems are presented next, followed by the thermodynamic properties of mixing of the BCC phase in Al-containing and Ti-containing refractory metal systems. First-principles calculations on model FCC, BCC and HCP CSSA reveal the presence of both positive and negative vibrational entropies of mixing, while the calculated electronic entropies of mixing are negligible. Temperature dependent configurational entropy is determined from the atomic structures obtained from MC/MD simulations. Current status and challenges in using these methodologies as they pertain to thermodynamic property analysis and CSSA design are discussed

Tailoring magnetic behavior of CoFeMnNiX (X = Al, Cr, Ga, and Sn) high entropy alloys by metal doping

Magnetic materials with excellent performances are desired for functional applications. Based on the high-entropy effect, a system of CoFeMnNiX (X = Al, Cr, Ga, and Sn) magnetic alloys are designed and investigated. The dramatic change in phase structures from face-centered-cubic (FCC) to ordered body-centered-cubic (BCC) phases, caused by adding Al, Ga, and Sn in CoFeMnNiX alloys, originates from the potent short-range chemical order in the liquid state predicted by ab initio molecular dynamics (AIMD) simulations. This phase transition leads to the significant enhancement of the saturation magnetization (Ms), e.g., the CoFeMnNiAl alloy has Ms of 147.86 Am2/kg. First-principles density functional theory (DFT) calculations on the electronic and magnetic structures reveal that the anti-ferromagnetism of Mn atoms in CoFeMnNi is suppressed especially in the CoFeMnNiAl HEA because Al changes the Fermi level and itinerant electron-spin coupling that lead to ferromagnetism

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept

INTEnsive ambulance-delivered blood pressure Reduction in hyper-ACute stroke Trial (INTERACT4) : study protocol for a randomized controlled trial

Background: Early pre-hospital initiation of blood pressure (BP) lowering could improve outcomes for patients with acute stroke, by reducing hematoma expansion in intracerebral hemorrhage (ICH), and time to reperfusion treatment and risk of intracranial hemorrhage in ischemic stroke (IS). We present the design of the fourth INTEnsive ambulance-delivered blood pressure Reduction in hyper-ACute stroke Trial (INTERACT4). Methods: A multi-center, ambulance-delivered, prospective, randomized, open-label, blinded endpoint (PROBE) assessed trial of pre-hospital BP lowering in 3116 hypertensive patients with suspected acute stroke at 50+ sites in China. Patients are randomized through a mobile phone digital system to intensive BP lowering to a target systolic BP of < 140 mmHg within 30 min, or guideline-recommended BP management according to local protocols. After the collection of in-hospital clinical and management data and 7-day outcomes, trained blinded assessors conduct telephone or face-to-face assessments of physical function and health-related quality of life in participants at 90 days. The primary outcome is the physical function on the modified Rankin scale at 90 days, analyzed as an ordinal outcome with 7 categories. The sample size was estimated to provide 90% power (α = 0.05) to detect a 22% reduction in the odds of a worse functional outcome using ordinal logistic regression. Discussion: INTERACT4 is a pragmatic clinical trial to provide reliable evidence on the effectiveness and safety of ambulance-delivered hyperacute BP lowering in patients with suspected acute stroke. Trial registration: ClinicalTrials.gov NCT03790800. Registered on 2 January 2019; Chinese Trial Registry ChiCTR1900020534. Registered on 7 January 2019. All items can be found in this protocol paper

Critical role of Bcl11b in suppressor function of T regulatory cells and prevention of inflammatory bowel disease

Bcl11b is required for optimal FoxP3 expression and suppressor function by regulatory T cells and for the generation of inducible regulatory T cells

Controlling the stereochemistry and regularity of butanethiol self-assembled monolayers on Au(111)

© 2014 American Chemical Society. The rich stereochemistry of the self-assembled monolayers (SAMs) of four butanethiols on Au(111) is described, the SAMs containing up to 12 individual C, S, or Au chiral centers per surface unit cell. This is facilitated by synthesis of enantiomerically pure 2-butanethiol (the smallest unsubstituted chiral alkanethiol), followed by in situ scanning tunneling microscopy (STM) imaging combined with density functional theory molecular dynamics STM image simulations. Even though butanethiol SAMs manifest strong headgroup interactions, steric interactions are shown to dominate SAM structure and chirality. Indeed, steric interactions are shown to dictate the nature of the headgroup itself, whether it takes on the adatom-bound motif RS•Au(0)S•R or involves direct binding of RS• to face-centered-cubic or hexagonal-close-packed sites. Binding as RS• produces large, organizationally chiral domains even when R is achiral, while adatom binding leads to rectangular plane groups that suppress long-range expression of chirality. Binding as RS• also inhibits the pitting intrinsically associated with adatom binding, desirably producing more regularly structured SAMs

Detailed Analysis of a Contiguous 22-Mb Region of the Maize Genome

Most of our understanding of plant genome structure and evolution has come from the careful annotation of small (e.g., 100 kb) sequenced genomic regions or from automated annotation of complete genome sequences. Here, we sequenced and carefully annotated a contiguous 22 Mb region of maize chromosome 4 using an improved pseudomolecule for annotation. The sequence segment was comprehensively ordered, oriented, and confirmed using the maize optical map. Nearly 84% of the sequence is composed of transposable elements (TEs) that are mostly nested within each other, of which most families are low-copy. We identified 544 gene models using multiple levels of evidence, as well as five miRNA genes. Gene fragments, many captured by TEs, are prevalent within this region. Elimination of gene redundancy from a tetraploid maize ancestor that originated a few million years ago is responsible in this region for most disruptions of synteny with sorghum and rice. Consistent with other sub-genomic analyses in maize, small RNA mapping showed that many small RNAs match TEs and that most TEs match small RNAs. These results, performed on ∼1% of the maize genome, demonstrate the feasibility of refining the B73 RefGen_v1 genome assembly by incorporating optical map, high-resolution genetic map, and comparative genomic data sets. Such improvements, along with those of gene and repeat annotation, will serve to promote future functional genomic and phylogenomic research in maize and other grasses