Recent advances in adversarial attacks uncover the intrinsic vulnerability of modern deep neural networks. Since then, extensive efforts have been devoted to enhancing robustness networks via specialized learning algorithms and loss functions. In this work, we take an architectural perspective investigate patterns network architectures that are resilient attacks. To obtain large number needed for study, adopt one-shot architecture search, training a once then finetuning sub-networks sampled...

We measure the stability and folding rate of a mutant enzyme phosphoglycerate kinase (PGK) inside bone tissue cells as function temperature from 38 to 48 °C. To facilitate measurement in individual living cells, we developed rapid laser stepping method capable measuring complete thermal melts kinetic traces about two min. find that this yields improved compared heating sample chamber or microscope stage. By comparing results for six with vitro data, show protein is stabilized by 6 kJ/mole...

Designing an effective loss function plays important role in visual analysis. Most existing designs rely on hand-crafted heuristics that require domain experts to explore the large design space, which is usually sub-optimal and time-consuming. In this paper, we propose AutoML for Loss Function Search (AM-LFS) leverages REINFORCE search functions during training process. The key contribution of work space can guarantee generalization transferability different vision tasks by including a bunch...

When a protein unfolds in the cell, its diffusion coefficient is affected by increased hydrodynamic radius and interactions of exposed hydrophobic residues with cytoplasmic matrix, including chaperones. We characterize photobleaching whole cells at single point, imaging concentration change fluorescent-labeled throughout cell as function time. As folded reference we use green fluorescent protein. The resulting region-dependent anomalous well characterized 2-D or 3-D equations coupled to...

In this paper, we propose an inverse reinforcement learning method for architecture search (IRLAS), which trains agent to learn network structures that are topologically inspired by human-designed network. Most existing approaches totally neglect the topological characteristics of architectures, results in complicated with a high inference latency. Motivated fact networks elegant topology fast speed, mirror stimuli function biological cognition theory extract abstract knowledge expert...

Patch-based methods and deep networks have been employed to tackle image inpainting problem, with their own strengths weaknesses. are capable of restoring a missing region high-quality texture through searching nearest neighbor patches from the unmasked regions. However, these bring problematic contents when recovering large Deep networks, on other hand, show promising results in completing Nonetheless, often lack faithful sharp details that resemble surrounding area. By bringing together...

Abstract Polymers are widely studied materials with diverse properties and applications determined by molecular structures. It is essential to represent these structures clearly explore the full space of achievable chemical designs. However, existing approaches cannot offer comprehensive design models for polymers because their inherent scale structural complexity. Here, a parametric, context‐sensitive grammar designed specifically (PolyGrammar) proposed. Using symbolic hypergraph...

Electron density maps must be accurately estimated to achieve valid dose calculation in MR-only radiotherapy. The goal of this study is assess whether two deep learning models, the conditional generative adversarial network (cGAN) and cycle-consistent (cycleGAN), can generate accurate abdominal synthetic CT (sCT) images from 0.35T MR for liver A retrospective was performed using 12 patients with (n = 8) non-liver 4) cancer. were deformably registered corresponding deformed (dCT) treatment...

In order to study the coupling vibration between a bridge and train under action of crosswind loads, dynamic interaction model wind–train–bridge system is established considering geometric nonlinear factors long-span suspension bridge. A calculation frame composed, corresponding computer program written. highway–railway scheme studied as an example. The linear responses simultaneous both loads wind are compared using self-written program, influence velocity speed on studied. results show...

The attraction and influx of monocytes into the retina has been considered a critical step in development diabetic retinopathy (DR). However, large population studies about association between peripheral blood monocyte levels, an inexpensive easily measurable laboratory index, DR are limited. Thus, we aimed to investigate levels DR.A total 3223 participants out 3277 adults with diabetes were enrolled from seven communities China this cross-sectional survey. Participants underwent several...

We propose a new method to super-resolve images captured by hybrid light field system that consists of standard camera and high-resolution camera. The image is taken as reference help with super-resolving the low-resolution images. Our combines an exemplar-based algorithm state of-the-art single super-resolution approach draws on strengths both. Both quantitative qualitative experiments show our proposed substantially outperforms existing methods datasets in challenging large parallax setting.

In this paper, we propose an end-to-end reasoning-decision networks (RDN) approach for robust face alignment via policy gradient. Unlike the conventional coarse-to-fine approaches which likely lead to bias prediction due poor initialization, our aims learn a by leveraging raw pixels reason subset of shape candidates, sequentially making plausible decisions remove outliers initialization. To achieve this, formulate as Markov decision process defining agent, typically interacts with trajectory...

The problem of molecular generation has received significant attention recently. Existing methods are typically based on deep neural networks and require training large datasets with tens thousands samples. In practice, however, the size class-specific chemical is usually limited (e.g., dozens samples) due to labor-intensive experimentation data collection. This presents a considerable challenge for learning generative models comprehensively describe design space. Another major generate only...

Abstract The gene encoding beta2-adrenergic receptor (β2-AR), adrenoceptor beta 2 ( ADRB2 ), has been reported to closely associated with various cancers. However, its role in lung adenocarcinoma (LUAD) remains controversial. This research shed light on the prognostic value of LUAD and further explored association immune cell infiltration. was significantly decreased LUAD. expression correlated gender, smoking status, T classification, pathologic stage. Patients low group presented poorer...

Purpose To develop and evaluate a method of reconstructing patient‐ treatment day‐ specific volumetric image motion model from free‐breathing cone‐beam projections respiratory surrogate measurements. This Motion‐Compensated Simultaneous Algebraic Reconstruction Technique (MC‐SART) generates uses derived directly the projections, without requiring prior measurements 4DCT, can compensate for both inter‐ intrabin deformations. The be used to generate images at arbitrary breathing points, which...

Recent advances in adversarial attacks uncover the intrinsic vulnerability of modern deep neural networks. Since then, extensive efforts have been devoted to enhancing robustness networks via specialized learning algorithms and loss functions. In this work, we take an architectural perspective investigate patterns network architectures that are resilient attacks. To obtain large number needed for study, adopt one-shot architecture search, training a once then finetuning sub-networks sampled...

The double burden of malnutrition (DBM), undernutrition in early life and an obesogenic environment later on, influences risk chronic disorders. Great Famine China from 1959 to1962 remarkable economic development the 1980s provided such a for large number people their 60s.We aimed to analyze effect status on association between famine exposure hyperuricemia adulthood.Participants numbering 12 666 were enrolled based Survey Prevalence East Metabolic Diseases Risk Factors (SPECT-China) Study...

Recent works have shown that interval bound propagation (IBP) can be used to train verifiably robust neural networks. Reseachers observe an intriguing phenomenon on these IBP trained networks: CROWN, a bounding method based tight linear relaxation, often gives very loose bounds We also most neurons become dead during the training process, which could hurt representation capability of network. In this paper, we study relationship between and prove CROWN is always tighter than when choosing...

Ensuring the high efficiency and stable operation of a supersonic through-flow fan (STFF) in wide range inlet Mach numbers is vital importance. The influence number (M) ranging from 0.3 to 2.36 on aerodynamic performance flow structure STFF cascade studied. results indicate that at design incidence, transonic inflow condition has greater loss, lower static pressure ratio, larger turning than non-transonic condition. evolution shock with increasing as follows: shock-free → passage...

Designing an effective loss function plays important role in visual analysis. Most existing designs rely on hand-crafted heuristics that require domain experts to explore the large design space, which is usually sub-optimal and time-consuming. In this paper, we propose AutoML for Loss Function Search (AM-LFS) leverages REINFORCE search functions during training process. The key contribution of work space can guarantee generalization transferability different vision tasks by including a bunch...