Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers

Fast Coordinated Control of DFIG Wind Turbine Generators for Low and High Voltage Ride-Through

This paper presents a fast coordinated control scheme of the rotor side converter (RSC), the Direct Current (DC) chopper and the grid side converter (GSC) of doubly fed induction generator (DFIG) wind turbine generators (WTGs) to improve the low voltage ride through (LVRT) and high voltage ride through (HVRT) capability of the DFIG WTGs. The characteristics of DFIG WTGs under voltage sags and swells were studied focusing on the DFIG WTG stator flux and rotor voltages during the transient periods of grid voltage changes. The protection schemes of the rotor crowbar circuit and the DC chopper circuit were proposed considering the characteristics of the DFIG WTGs during voltage changes. The fast coordinated control of RSC and GSC were developed based on the characteristic analysis in order to realize efficient LVRT and HVRT of the DFIG WTGs. The proposed fast coordinated control schemes were verified by time domain simulations using Matlab-Simulink

An Edge-Preserved Image Denoising Algorithm Based on Local Adaptive Regularization

Image denoising methods are often based on the minimization of an appropriately defined energy function. Many gradient dependent energy functions, such as Potts model and total variation denoising, regard image as piecewise constant function. In these methods, some important information such as edge sharpness and location is well preserved, but some detailed image feature like texture is often compromised in the process of denoising. For this reason, an image denoising method based on local adaptive regularization is proposed in this paper, which can adaptively adjust denoising degree of noisy image by adding spatial variable fidelity term, so as to better preserve fine scale features of image. Experimental results show that the proposed denoising method can achieve state-of-the-art subjective visual effect, and the signal-noise-ratio (SNR) is also objectively improved by 0.3–0.6 dB

GeoSegNet: Point Cloud Semantic Segmentation via Geometric Encoder-Decoder Modeling

Semantic segmentation of point clouds, aiming to assign each point a semantic category, is critical to 3D scene understanding.Despite of significant advances in recent years, most of existing methods still suffer from either the object-level misclassification or the boundary-level ambiguity. In this paper, we present a robust semantic segmentation network by deeply exploring the geometry of point clouds, dubbed GeoSegNet. Our GeoSegNet consists of a multi-geometry based encoder and a boundary-guided decoder. In the encoder, we develop a new residual geometry module from multi-geometry perspectives to extract object-level features. In the decoder, we introduce a contrastive boundary learning module to enhance the geometric representation of boundary points. Benefiting from the geometric encoder-decoder modeling, our GeoSegNet can infer the segmentation of objects effectively while making the intersections (boundaries) of two or more objects clear. Experiments show obvious improvements of our method over its competitors in terms of the overall segmentation accuracy and object boundary clearness. Code is available at https://github.com/Chen-yuiyui/GeoSegNet

High expression of nucleophosmin is closely related to the grade and invasion of colorectal cancer

420-426This study explores the differential protein expression in the colorectal cancer (CRC) patients to validate a new biomarker for tumor progression. CRC tissues and their adjacent non-cancerous tissues were analyzed by two-dimensional LC/MS/MS. Nucleophosmin 1 (NPM1) was selected and confirmed its differential expression by Western blot. Immunohistological staining of NPM1 in tissues was performed to validate its correlation with clinicopathologic parameters of CRC patients. There were 39 candidates with significant difference between cancerous tissues and their adjacent non-cancerous tissues, which included 19 increased proteins and 20 decreased proteins in CRC samples. Especially, NPM1 was correlated with poor differentiation, and lymph node metastasis according to the analysis of patients’ clinicopathologic parameters. Increased expression of NPM1 can be as a critical biomarker for clinical diagnosis of tumor progression of CRC patients

High expression of nucleophosmin is closely related to the grade and invasion of colorectal cancer

To explore the differential protein expression in the colorectal cancer (CRC) patients to validate a new biomarker for tumor progression. CRC tissues and their adjacent non-cancerous tissues were analyzed by two-dimensional LC/MS/MS. Nucleophosmin 1 (NPM1) was selected and confirmed its differential expression by Western blot. Immunohistological staining of NPM1 in tissues was performed to validate its correlation with clinicopathologic parameters of CRC patients. There were 39 candidates with significant difference between cancerous tissues and their adjacent non-cancerous tissues, which included 19 increased proteins and 20 decreased proteins in CRC samples. Especially, NPM1 was correlated with poor differentiation, and lymph node metastasis according to the analysis of patients’ clinicopathologic parameters. Increased expression of NPM1 can be as a critical biomarker for clinical diagnosis of tumor progression of CRC patients

Abnormal hubs in global network as neuroimaging biomarker in right temporal lobe epilepsy at rest

While abnormal neuroimaging features have been reported in patients suffering from right temporal lobe epilepsy (rTLE), the value of altered degree centrality (DC) as a diagnostic biomarker for rTLE has yet to be established. As such, the present study was designed to examine DC abnormalities in rTLE patients in order to gauge the diagnostic utility of these neuroimaging features. In total, 68 patients with rTLE and 73 healthy controls (HCs) participated in this study. Imaging data were analyzed using DC and receiver operating characteristic (ROC) methods. Ultimately, rTLE patients were found to exhibit reduced right caudate DC and increased left middle temporal gyrus, superior parietal gyrus, superior frontal gyrus, right precuneus, frontal gyrus Inferior gyrus, middle-superior frontal gyrus, and inferior parietal gyrus DC relative to HC. ROC analyses indicated that DC values in the right caudate nucleus could be used to differentiate between rTLE patients and HCs with a high degree of sensitivity and specificity. Together, these results thus suggest that rTLE is associated with abnormal DC values in the right caudate nucleus, underscoring the relevance of further studies of the underlying pathophysiology of this debilitating condition

Postnatal onset of retinal degeneration by loss of embryonic Ezh2 repression of Six1

Some adult-onset disorders may be linked to dysregulated embryonic development, yet the mechanisms underlying this association remain poorly understood. Congenital retinal degenerative diseases are blinding disorders characterized by postnatal degeneration of photoreceptors, and affect nearly 2 million individuals worldwide, but ∼50% do not have a known mutation, implicating contributions of epigenetic factors. We found that embryonic deletion of the histone methyltransferase (HMT) Ezh2 from all retinal progenitors resulted in progressive photoreceptor degeneration throughout postnatal life, via derepression of fetal expression of Six1 and its targets. Forced expression of Six1 in the postnatal retina was sufficient to induce photoreceptor degeneration. Ezh2, although enriched in the embryonic retina, was not present in the mature retina; these data reveal an Ezh2-mediated feed-forward pathway that is required for maintaining photoreceptor homeostasis in the adult and suggest novel targets for retinal degeneration therapy

IGFBPL1 Regulates Axon Growth through IGF-1-mediated Signaling Cascades

Activation of axonal growth program is a critical step in successful optic nerve regeneration following injury. Yet the molecular mechanisms that orchestrate this developmental transition are not fully understood. Here we identified a novel regulator, insulin-like growth factor binding protein-like 1 (IGFBPL1), for the growth of retinal ganglion cell (RGC) axons. Expression of IGFBPL1 correlates with RGC axon growth in development, and acute knockdown of IGFBPL1 with shRNA or IGFBPL1 knockout in vivo impaired RGC axon growth. In contrast, administration of IGFBPL1 promoted axon growth. Moreover, IGFBPL1 bound to insulin-like growth factor 1 (IGF-1) and subsequently induced calcium signaling and mammalian target of rapamycin (mTOR) phosphorylation to stimulate axon elongation. Blockage of IGF-1 signaling abolished IGFBPL1-mediated axon growth, and vice versa, IGF-1 required the presence of IGFBPL1 to promote RGC axon growth. These data reveal a novel element in the control of RGC axon growth and suggest an unknown signaling loop in the regulation of the pleiotropic functions of IGF-1. They suggest new therapeutic target for promoting optic nerve and axon regeneration and repair of the central nervous system