EVMP: enhancing machine learning models for synthetic promoter strength prediction by Extended Vision Mutant Priority framework

IntroductionIn metabolic engineering and synthetic biology applications, promoters with appropriate strengths are critical. However, it is time-consuming and laborious to annotate promoter strength by experiments. Nowadays, constructing mutation-based synthetic promoter libraries that span multiple orders of magnitude of promoter strength is receiving increasing attention. A number of machine learning (ML) methods are applied to synthetic promoter strength prediction, but existing models are limited by the excessive proximity between synthetic promoters.MethodsIn order to enhance ML models to better predict the synthetic promoter strength, we propose EVMP(Extended Vision Mutant Priority), a universal framework which utilize mutation information more effectively. In EVMP, synthetic promoters are equivalently transformed into base promoter and corresponding k-mer mutations, which are input into BaseEncoder and VarEncoder, respectively. EVMP also provides optional data augmentation, which generates multiple copies of the data by selecting different base promoters for the same synthetic promoter.ResultsIn Trc synthetic promoter library, EVMP was applied to multiple ML models and the model effect was enhanced to varying extents, up to 61.30% (MAE), while the SOTA(state-of-the-art) record was improved by 15.25% (MAE) and 4.03% (R2). Data augmentation based on multiple base promoters further improved the model performance by 17.95% (MAE) and 7.25% (R2) compared with non-EVMP SOTA record.DiscussionIn further study, extended vision (or k-mer) is shown to be essential for EVMP. We also found that EVMP can alleviate the over-smoothing phenomenon, which may contributes to its effectiveness. Our work suggests that EVMP can highlight the mutation information of synthetic promoters and significantly improve the prediction accuracy of strength. The source code is publicly available on GitHub: https://github.com/Tiny-Snow/EVMP

On-Policy Pixel-Level Grasping Across the Gap Between Simulation and Reality

Grasp detection in cluttered scenes is a very challenging task for robots. Generating synthetic grasping data is a popular way to train and test grasp methods, as is Dex-net and GraspNet; yet, these methods generate training grasps on 3D synthetic object models, but evaluate at images or point clouds with different distributions, which reduces performance on real scenes due to sparse grasp labels and covariate shift. To solve existing problems, we propose a novel on-policy grasp detection method, which can train and test on the same distribution with dense pixel-level grasp labels generated on RGB-D images. A Parallel-Depth Grasp Generation (PDG-Generation) method is proposed to generate a parallel depth image through a new imaging model of projecting points in parallel; then this method generates multiple candidate grasps for each pixel and obtains robust grasps through flatness detection, force-closure metric and collision detection. Then, a large comprehensive Pixel-Level Grasp Pose Dataset (PLGP-Dataset) is constructed and released; distinguished with previous datasets with off-policy data and sparse grasp samples, this dataset is the first pixel-level grasp dataset, with the on-policy distribution where grasps are generated based on depth images. Lastly, we build and test a series of pixel-level grasp detection networks with a data augmentation process for imbalance training, which learn grasp poses in a decoupled manner on the input RGB-D images. Extensive experiments show that our on-policy grasp method can largely overcome the gap between simulation and reality, and achieves the state-of-the-art performance. Code and data are provided at https://github.com/liuchunsense/PLGP-Dataset

4D Human Body Capture from Egocentric Video via 3D Scene Grounding

We introduce a novel task of reconstructing a time series of second-person 3D human body meshes from monocular egocentric videos. The unique viewpoint and rapid embodied camera motion of egocentric videos raise additional technical barriers for human body capture. To address those challenges, we propose a simple yet effective optimization-based approach that leverages 2D observations of the entire video sequence and human-scene interaction constraint to estimate second-person human poses, shapes, and global motion that are grounded on the 3D environment captured from the egocentric view. We conduct detailed ablation studies to validate our design choice. Moreover, we compare our method with the previous state-of-the-art method on human motion capture from monocular video, and show that our method estimates more accurate human-body poses and shapes under the challenging egocentric setting. In addition, we demonstrate that our approach produces more realistic human-scene interaction

Severe nausea and vomiting in pregnancy: psychiatric and cognitive problems and brain structure in children

Background: Two studies have suggested that severe prolonged nausea and vomiting during pregnancy is associated with emotional and behavioral problems in offspring, with smaller sample size and short-term follow-up. Moreover, little information is available on the role of the brain structure in the associations. Methods: In a US-based cohort, the association was investigated between severe prolonged nausea and vomiting in pregnancy (extending after the second trimester and termed SNVP), psychiatric and cognitive problems, and brain morphology, from the Adolescent Brain Cognitive Development (ABCD) study, from 10,710 children aged 9–11 years. We validated the emotional including psychiatric findings using the Danish National Cohort Study with 2,092,897 participants. Results: SNVP was significantly associated with emotional and psychiatric problems (t = 8.89, Cohen’s d = 0.172, p = 6.9 × 10−19) and reduced global cognitive performance (t = − 4.34, d = − 0.085, p = 1.4 × 10−5) in children. SNVP was associated with low cortical area and volume, especially in the cingulate cortex, precuneus, and superior medial prefrontal cortex. These lower cortical areas and volumes significantly mediated the relation between SNVP and the psychiatric and cognitive problems in children. In the Danish National Cohort, severe nausea and vomiting in pregnancy were significantly associated with increased risks of behavioral and emotional disorders in children (hazard ratio, 1.24; 95% confidence interval, 1.16–1.33). Conclusions: SNVP is strongly associated with psychiatric and cognitive problems in children, with mediation by brain structure. These associations highlight the clinical importance and potential benefits of the treatment of SNVP, which could reduce the risk of psychiatric disorder in the next generation

Characterization of cellulase production by carbon sources in two Bacillus species

The induction of cellulase production in two Bacillus spp. was studied by means of measuring cellulase activities under the condition of different carbon sources. The results indicate that cellulase could not be induced by cellulose material as a sole carbon source. Instead, they could be induced by monosaccharide or disaccharide with reducing group. Moreover, the expression of cellulase components was synergistic. When cell wall/envelope enzyme and endoenzyme from two Bacillus spp. acted on these inducers, analysis of reaction products by high performance liquid chromatography (HPLC) revealed that cell wall/envelope enzyme and endoenzyme from two Bacillus spp. were inactive on these inducers. It also indicated that these inducers entered cells directly and served function of induction.Keywords: Bacillus, cellulase, induction, carbon source

Germanium-lead perovskite light-emitting diodes.

Reducing environmental impact is a key challenge for perovskite optoelectronics, as most high-performance devices are based on potentially toxic lead-halide perovskites. For photovoltaic solar cells, tin-lead (Sn-Pb) perovskite materials provide a promising solution for reducing toxicity. However, Sn-Pb perovskites typically exhibit low luminescence efficiencies, and are not ideal for light-emitting applications. Here we demonstrate highly luminescent germanium-lead (Ge-Pb) perovskite films with photoluminescence quantum efficiencies (PLQEs) of up to ~71%, showing a considerable relative improvement of ~34% over similarly prepared Ge-free, Pb-based perovskite films. In our initial demonstration of Ge-Pb perovskite LEDs, we achieve external quantum efficiencies (EQEs) of up to ~13.1% at high brightness (~1900 cd m-2), a step forward for reduced-toxicity perovskite LEDs. Our findings offer a new solution for developing eco-friendly light-emitting technologies based on perovskite semiconductors

Magnetoelastic coupling behavior at the ferromagnetic transition in the partially disordered double perovskite La2NiMnO6

The magnetocapacitance and magnetoresistance properties near room temperature of partially disordered double perovskite L a 2 NiMn O 6 are related, at least in part, to coupled ferroelastic and magnetic instabilities that are responsible for a ferromagnetic phase transition near 280 K. A systematic analysis of this coupling from the perspectives of strain and elasticity has revealed a system with biquadratic coupling among three order parameters belonging to irreducible representations of X + 3 , Γ + 4 and m Γ + 4 of the parent space group F m ¯ 3 m . Classical octahedral tilting drives the structural transitions at high temperatures and strong acoustic attenuation through the temperature interval ∼300–500 K, observed by resonant ultrasound spectroscopy from a polycrystalline sample, is consistent with pinning of ferroelastic twin walls by point defects. Below room temperature, stiffening of the shear modulus by up to ∼40% can be understood in terms of biquadratic coupling of the ferromagnetic order parameter with strain. Acoustic attenuation with Debye-like patterns of loss in the temperature interval ∼150–280 K yielded activation energies and relaxation times which match up with AC magnetic and dielectric spectroscopy data reported previously in the literature. The dynamic loss mechanism, perhaps related to hopping of electrons between N i 2 + and M n 4 + , is potentially multiferroic, therefore. In addition to the possibilities for tailoring the intrinsic properties of L a 2 NiMn O 6 by controlling oxygen content, B -site order or by choice of substrate for imposing a strain on thin films, it should be possible also to engineer extrinsic properties which would respond to applied electric, magnetic, and stress fields

Remaining useful life prognostics of lithium-ion batteries based on a coordinate reconfiguration of degradation trajectory and multiple linear regression

Lithium battery has been widely applied as new energy to cope with pressures in both form environment and energy. The remaining useful life (RUL) prognostics of lithium-ion batteries have become more critical. Convenient battery life prediction allows early detection of performance deficiencies to help maintain the battery system promptly. This paper proposes a RUL prognostics model of lithium-ion batteries based on a coordinate reconfiguration of degradation trajectory and multiple linear regression. First, a new sampling rule is used to reconfigure the coordinates of degradation data of new batteries and truncated similar batteries. Then, the relationship between similar and new lithium-ion batteries is established by using the reconfiguration data. Moreover, a new RUL prognostics model based on a coordinate reconfiguration of degradation trajectory and multiple linear regression is established by considering the influence of time-varying factors, which can improve prediction accuracy with small sample data and significantly reduce product development time and cost

Strain coupling and acoustic attenuation associated with glassy magnetic phase transitions in the disordered double perovskite La2FeMnO6

Elastic and anelastic anomalies in a ceramic sample of La2FeMnO6 have been characterized by resonant ultrasound spectroscopy in order to understand the strength and form of magnetoelastic coupling that accompanies the glassy magnetic transitions of a double perovskite with no long-range order of the B-site cations. The first transition, to a cluster glass below ∼280K, does not appear to involve any significant coupling with strain. The second glassy transition, near 55 K, appears to conform to Vogel-Fulcher dynamics in which magnetic dissipation and acoustic loss peaks arise from freezing driven by interactions between ferromagnetic clusters, with an activation energy of ∼0.03eV and time constant τo∼10−9s. The magnetoelastic coupling mechanism appears to involve local spin states with strain relaxation enhanced by changes in local electronic structure. Mediation of the coupling via strain also ensures that local heterogeneity in the strain state, such as at ferroelastic twin walls, will contribute to the magnetic heterogeneity of these materials