Vine Spread for Superpixel Segmentation.

Superpixel is the over-segmentation region of an image, whose basic units "pixels" have similar properties. Although many popular seeds-based algorithms have been proposed to improve the segmentation quality of superpixels, they still suffer from the seeds initialization problem and the pixel assignment problem. In this paper, we propose Vine Spread for Superpixel Segmentation (VSSS) to form superpixel with high quality.

Explored Normalized Cut With Random Walk Refining Term for Image Segmentation.

The Normalized Cut (NCut) model is a popular graph-based model for image segmentation. But it suffers from the excessive normalization problem and weakens the small object and twig segmentation. In this paper, we propose an Explored Normalized Cut (ENCut) model that establishes a balance graph model by adopting a meaningful-loop and a k-step random walk, which reduces the energy of small salient region, so as to enhance the small object segmentation.

Atom surface fragment contribution method for predicting the toxicity of ionic liquids.

In this study, a novel method-atom surface fragment contribution (ASFC)-was proposed for assessing the properties of compounds. We developed a predictive model using the ASFC method based on the sigma surface areas (S) of fragments/groups for estimating the toxicity of ILs. A toxicity dataset of 140 ILs towards leukemia rat cell line (ICP-81) was gathered and employed to train and validate models.

The fate of anaerobic syntrophy in anaerobic digestion facing propionate and acetate accumulation.

How the acetate and propionate accumulation impact anaerobic syntrophy during methane formation is not well understood. To investigate such effect, continuous acetate (35 g/L), propionate (11.25 g/L) and bicarbonate (30 g/L) supplementation were used during mesophilic anaerobic digestion.

A QSPR model for estimating Henry's law constant of H2S in ionic liquids by ELM algorithm.

Ionic liquids (ILs) as green solvents have been studied in the application of gas sweetening. However, it is a huge challenge to obtain all the experimental values because of the high costs and generated chemical wastes. This study pioneered a quantitative structure-property relationship (QSPR) model for estimating Henry's law constant (HLC) of HS in ILs.

Effects of Akt/mTOR/p70S6K Signaling Pathway Regulation on Neuron Remodeling Caused by Translocation Repair.

Peripheral nerve injury repair has been considered a difficult problem in the field of trauma for a long time. Conventional surgical methods are not applicable in some special types of nerve injury, prompting scholars to seek to develop more effective nerve translocation repair technologies. The purpose of this study was to explore the functional state of neurons in injured lower limbs after translocation repair, with a view to preliminarily clarify the molecular mechanisms underlying this process.

Prediction of ammonia absorption in ionic liquids based on extreme learning machine modelling and a novel molecular descriptor S.

The large amounts of ammonia emissions generated from industrial production have caused serious environmental pollution problems, such as soil acidification, eutrophication, the formation of fine particles and changes in the global greenhouse balance, and also greatly endanger human health. At present, effectively reducing ammonia emissions or recovering ammonia is still a huge challenge. Ionic liquids (ILs) as a new class of green solvent have been introduced for ammonia absorption with great potential, but a huge number on combination systems of ILs lead to the difficulty of measuring the ammonia solubility in all ILs by experiments (e.

Assessing the ecotoxicity of ionic liquids on Vibrio fischeri using electrostatic potential descriptors.

Ionic liquids (ILs) have attracted increasing attention both in the scientific community and the industry in the past two decades. Their risk of being inevitable released to ecosystem lights up the urgent research on their toxicity to the environment. To reduce the time and capital consumption on testing tremendous ILs ecotoxicity experimentally, it is essential to construct predictive models for estimating their toxicity.

Dynamic Random Walk for Superpixel Segmentation.

In this paper, we propose a novel random walk model, called Dynamic Random Walk (DRW), which adds a new type of dynamic node to the original RW model and reduces redundant calculation by limiting the walk range. To solve the seed-lacking problem of the proposed DRW, we redefine the energy function of the original RW and use the first arrival probability among each node pair to avoid the interference for each partition. Relaxation of our DRW is performed with the help of a greedy strategy and the Weighted Random Walk Entropy(WRWE) that uses the gradient feature to approximate the stationary distribution.

Predicting the Toxicity of Ionic Liquids toward Acetylcholinesterase Enzymes Using Novel QSAR Models.

Limited information on the potential toxicity of ionic liquids (ILs) becomes the bottleneck that creates a barrier in their large-scale application. In this work, two quantitative structure-activity relationships (QSAR) models were used to evaluate the toxicity of ILs toward the acetylcholinesterase enzyme using multiple linear regression (MLR) and extreme learning machine (ELM) algorithms. The structures of 57 cations and 21 anions were optimized using quantum chemistry calculations.

Accumulation of Ca3.2 T-type Calcium Channels in the Uninjured Sural Nerve Contributes to Neuropathic Pain in Rats with Spared Nerve Injury.

Injuries to peripheral nerve fibers induce neuropathic pain. But the involvement of adjacent uninjured fibers to pain is not fully understood. The present study aims to investigate the possible contribution of Ca3.

Sensitization of neurons in the central nucleus of the amygdala via the decreased GABAergic inhibition contributes to the development of neuropathic pain-related anxiety-like behaviors in rats.

Background: Despite high prevalence of anxiety accompanying with chronic pain, the mechanisms underlying pain-related anxiety are largely unknown. With its well-documented role in pain and emotion processing, the amygdala may act as a key player in pathogenesis of neuropathic pain-related anxiety. Pain-related plasticity and sensitization of CeA (central nucleus of the amygdala) neurons have been shown in several models of chronic pain.