Language-Based Image Editing with Recurrent Attentive Models

We investigate the problem of Language-Based Image Editing (LBIE). Given a source image and a natural language description, we want to generate a target image by editing the source image based on the description. We propose a generic modeling framework for two sub-tasks of LBIE: language-based image segmentation and image colorization. The framework uses recurrent attentive models to fuse image and language features. Instead of using a fixed step size, we introduce for each region of the image a termination gate to dynamically determine after each inference step whether to continue extrapolating additional information from the textual description. The effectiveness of the framework is validated on three datasets. First, we introduce a synthetic dataset, called CoSaL, to evaluate the end-to-end performance of our LBIE system. Second, we show that the framework leads to state-of-the-art performance on image segmentation on the ReferIt dataset. Third, we present the first language-based colorization result on the Oxford-102 Flowers dataset.Comment: Accepted to CVPR 2018 as a Spotligh

Med-Tuning: Exploring Parameter-Efficient Transfer Learning for Medical Volumetric Segmentation

Deep learning based medical volumetric segmentation methods either train the model from scratch or follow the standard "pre-training then finetuning" paradigm. Although finetuning a well pre-trained model on downstream tasks can harness its representation power, the standard full finetuning is costly in terms of computation and memory footprint. In this paper, we present the first study on parameter-efficient transfer learning for medical volumetric segmentation and propose a novel framework named Med-Tuning based on intra-stage feature enhancement and inter-stage feature interaction. Given a large-scale pre-trained model on 2D natural images, our method can exploit both the multi-scale spatial feature representations and temporal correlations along image slices, which are crucial for accurate medical volumetric segmentation. Extensive experiments on three benchmark datasets (including CT and MRI) show that our method can achieve better results than previous state-of-the-art parameter-efficient transfer learning methods and full finetuning for the segmentation task, with much less tuned parameter costs. Compared to full finetuning, our method reduces the finetuned model parameters by up to 4x, with even better segmentation performance

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management

An analysis of China's grain production: Looking back and looking forward

Ensuring food security is the foundation of economic development and social stability. China is historically a country that is dominated by agriculture. In the past 60 years, China's total grain output increased by fivefold, from 113 million tons (MT) in 1949 to 571 MT in 2011, a statistic which provides inspiration to producers in other parts of the world. Grain production per capita doubled, from 209 to 425 kg during the same time period. At the national scale, China has succeeded in maintaining a basic self-sufficiency for grain for the past three decades. However, with the increasing population pressure and a growing appetite for animal products, China will need 776 MT grain by 2030 to feed its own people, a net increase of 35.9% from its best year on record. China's drive for future food security is challenged by problems such as low efficiency of resource use and resource limitation, diminishing return in yield response, competition for nonagricultural land uses, and environmental degradation. In this article, we analyze historical, temporal, and spatial variation in total grain production as well as the overall developing trends of current and future grain production, and discussed relevant options to overcome production constraints and further promote agricultural production.</p

Multi-parameter comprehensive early warning of coal pillar rockburst risk based on DNN

A multi-parameter comprehensive early warning method for coal pillar-type rockburst risk based on the deep neural network (DNN) is proposed in this study. By utilizing preprocessed data from the surveillance of coal pillar impact hazards in Yangcheng Coal Mine, this study incorporates training samples derived from three distinct coal pillar-type impact hazard monitoring methodologies: microseismic monitoring, borehole cutting analysis, and real-time stress monitoring. The data characteristics of the monitoring data were extracted, evaluated, classified, and verified by monitoring the data of different working faces. This method was applied to develop the depth of multi-parameter neural network comprehensive early warning software in engineering practice. The results showed that the accuracy of the depth for burst monitoring data processing is improved by 6.89%–16.87% compared to the traditional monitoring methods. This method has a better early warning effect to avoid the occurrence of coal pillar rockburst hazard

Quantitative assessment of retinal microvascular remodeling in eyes that underwent idiopathic epiretinal membrane surgery

Purpose: To explore the surgical outcomes of the macular microvasculature and visual function in eyes with idiopathic epiretinal membrane (iERM) using spectral-domain optical coherence tomography angiography (SD-OCTA).Methods: This observational, cross-sectional study included 41 participants who underwent iERM surgery with a 3-month (3M) follow-up. Forty-one healthy eyes formed the control group. The assessments included best-corrected visual acuity (BCVA) and mean sensitivity (MS) by microperimetry and SD-OCTA assessment of vessel tortuosity (VT), vessel density (VD), foveal avascular zone, and retinal thickness (RT).Results: The findings showed statistically significant differences in VT, foveal avascular zone parameters, RT, BCVA, and MS between the iERM and control groups (p &lt; 0.05). After iERM surgery, the macular VT, SCP VD, and RT decreased significantly (p &lt; 0.01) while the DCP VD increased (p = 0.029). The BCVA improved significantly (p &lt; 0.001) and was associated with the MS (rs = −0.377, p = 0.015). MS was associated with the SCP VD and RT at 3M (SCP VD rs = 0.511, p = 0.001; RT rs = 0.456, p = 0.003). In the superior quadrant, the MS improved significantly (p &lt; 0.001) and the improvement of MS was associated with the reduction of VT (β = −0.330, p = 0.034).Conclusion: Microcirculatory remodeling and perfusion recovery were observed within 3 months after iERM surgery. VT was a novel index for evaluating the morphology of the retinal microvasculature in eyes with iERM and was associated with MS in the superior quadrant

Fecal Microbiota Dynamics Reveal the Feasibility of Early Weaning of Yak Calves under Conventional Grazing System

Background: The gut microbiota plays an important role in the health and production of animals. However, little information is available on the dynamic variations and comparison of intestinal microbiota in post-weaning yak calves living on the QTP. Methods: We explored the fecal bacterial microbiota succession of yak calves at different months after early weaning (60 d) compared with cattle calves by 16S rRNA gene amplicon sequencing and functional composition prediction. Results: We found no significant difference in blood biochemical parameters related to glucose and lipid metabolism between yaks and calves in different months after weaning. The core fecal bacterial microbiota from both species of calves was dominated by Ruminococcaceae, Rikenellaceae, and Bacteroidaceae. The fecal microbial community has a great alteration within the time after weaning in both cattle and yak calves, but cattle showed a larger change. After five months, the microbiota achieves a stable and concentrated state. This is also similar to the functional profile. Conclusions: Based on the exploration of dynamic changes in the fecal microbiota at an early stage of life, our results illustrated that there were no negative effects of intestinal microbiota succession on yak calves when early weaning was employed

Stomatal and growth responses to hydraulic and chemical changes induced by progressive soil drying.

A better understanding of physiological responses of crops to drought stress is important for ensuring sustained crop productivity under climate change. Here we studied the effect on 15 d-old maize (Zea mays L.) plants of a 6-d non-lethal period of soil drying (soil water potential (SWP) decreased from –0.20 to –0.81 MPa). Root growth was initially stimulated during drying (when SWP decreased from –0.31 to –0.38 MPa, c.f. –0.29 MPa in well-watered pots), followed by inhibition during Days 5–6 (SWP from –0.63 to –0.81 MPa). Abscisic acid (ABA) in the root began to accumulate as the root water potential declined during Days 2–3. Leaf elongation was inhibited from Day 4 (SWP < –0.51 MPa), just after leaf ABA content began to increase, but coinciding with a decline in leaf water potential. The stomatal conductance was restricted earlier in the younger leaf (4th) (on Day 3) than in the older leaf (3rd). The ethylene content of leaves and roots decreased during drying, but after the respective increase in ABA contents. This work identified critical timing of hydraulic and chemical changes at the onset of soil drying, which can be important in initiating early stomatal and growth responses to drought