PMH34: COMPARISON OF OLANZAPINE VERSUS QUETIAPINE IN THE TREATMENT OF HOSPITALIZED PATIENTS WITH SCHIZOPHRENIA

This report highlights ILCA's work in the past, and discusses current activities and future plans with particular reference to mixed crop-livestock systems, market-oriented smallholder dairying, conservation of biodiversity, biological efficiency of livestock, livestock production under trypanosomiasis risk, livestock and resource management policy, and strengthening national research capacities

Use of phosphorus to alleviate stress induced by cadmium and zinc in two submerged macrophytes

The potential mechanism by which P antagonizes the toxicity of Zn and Cd was investigated in Elodea nuttallii and Hydrilla verticillata to understand the interactions between P, Cd and Zn pollutants. The twosubmerged macrophytes were treated with a combination of Cd (0.25 mg L-1) and Zn (1.0 mg L-1) and various concentrations of P (0, 0.05 and 5 mg L-1) for different exposure times (0.5, 1, 2, 4 and 7 days).The toxic effects and oxidative stress caused by the Cd and Zn resulted in a reduction of the total chlorophyll (chlorophyll a and b) and an increase in the content of glutathione (GSH). The activity ofcatalase (CAT) and the contents of malondialdehyde (MDA) both increased in the 1st day, and then reduced during the following 6 days. However, the activity of guaiacol peroxidase (POD) and thecontents of soluble protein both decreased in the first day then increased from the 2nd to 7th days. Each index in the plants treated with Cd and Zn containing P showed similar changing trends to those treated with only Cd and Zn during the 7 days. However, different indices had different response times. At the best response time in each index, the result showed that using P can protect plants from the toxicity and oxidative stress caused by Cd and Zn, which suggested that P can produce an antagonistic response with Cd and Zn to mitigate the oxidative stress to plants. Also, these results suggested that Cd and Zn exerted their toxic effects on the growth of E. nuttallii and H. verticillata, at least in part, by the induction of oxidative stress and inhibition of photosynthesis. Through comparing the response of the two plants to oxidative stress caused by Cd and Zn, it was found that E. nuttallii was more sensitive than H. verticillata. E. nuttallii can be regarded as an indicative plant for Cd and Zn polluted waters

Deep Regionlets for Object Detection

In this paper, we propose a novel object detection framework named "Deep Regionlets" by establishing a bridge between deep neural networks and conventional detection schema for accurate generic object detection. Motivated by the abilities of regionlets for modeling object deformation and multiple aspect ratios, we incorporate regionlets into an end-to-end trainable deep learning framework. The deep regionlets framework consists of a region selection network and a deep regionlet learning module. Specifically, given a detection bounding box proposal, the region selection network provides guidance on where to select regions to learn the features from. The regionlet learning module focuses on local feature selection and transformation to alleviate local variations. To this end, we first realize non-rectangular region selection within the detection framework to accommodate variations in object appearance. Moreover, we design a "gating network" within the regionlet leaning module to enable soft regionlet selection and pooling. The Deep Regionlets framework is trained end-to-end without additional efforts. We perform ablation studies and conduct extensive experiments on the PASCAL VOC and Microsoft COCO datasets. The proposed framework outperforms state-of-the-art algorithms, such as RetinaNet and Mask R-CNN, even without additional segmentation labels.Comment: Accepted to ECCV 201

Treatment of Linear and Nonlinear Dielectric Property of Molecular Monolayer and Submonolayer with Microscopic Dipole Lattice Model: I. Second Harmonic Generation and Sum-Frequency Generation

In the currently accepted models of the nonlinear optics, the nonlinear radiation was treated as the result of an infinitesimally thin polarization sheet layer, and a three layer model was generally employed. The direct consequence of this approach is that an apriori dielectric constant, which still does not have a clear definition, has to be assigned to this polarization layer. Because the Second Harmonic Generation (SHG) and the Sum-Frequency Generation vibrational Spectroscopy (SFG-VS) have been proven as the sensitive probes for interfaces with the submonolayer coverage, the treatment based on the more realistic discrete induced dipole model needs to be developed. Here we show that following the molecular optics theory approach the SHG, as well as the SFG-VS, radiation from the monolayer or submonolayer at an interface can be rigorously treated as the radiation from an induced dipole lattice at the interface. In this approach, the introduction of the polarization sheet is no longer necessary. Therefore, the ambiguity of the unaccounted dielectric constant of the polarization layer is no longer an issue. Moreover, the anisotropic two dimensional microscopic local field factors can be explicitly expressed with the linear polarizability tensors of the interfacial molecules. Based on the planewise dipole sum rule in the molecular monolayer, crucial experimental tests of this microscopic treatment with SHG and SFG-VS are discussed. Many puzzles in the literature of surface SHG and SFG spectroscopy studies can also be understood or resolved in this framework. This new treatment may provide a solid basis for the quantitative analysis in the surface SHG and SFG studies.Comment: 23 pages, 3 figure

An Adaptive Sampling Scheme to Efficiently Train Fully Convolutional Networks for Semantic Segmentation

Deep convolutional neural networks (CNNs) have shown excellent performance in object recognition tasks and dense classification problems such as semantic segmentation. However, training deep neural networks on large and sparse datasets is still challenging and can require large amounts of computation and memory. In this work, we address the task of performing semantic segmentation on large data sets, such as three-dimensional medical images. We propose an adaptive sampling scheme that uses a-posterior error maps, generated throughout training, to focus sampling on difficult regions, resulting in improved learning. Our contribution is threefold: 1) We give a detailed description of the proposed sampling algorithm to speed up and improve learning performance on large images. We propose a deep dual path CNN that captures information at fine and coarse scales, resulting in a network with a large field of view and high resolution outputs. We show that our method is able to attain new state-of-the-art results on the VISCERAL Anatomy benchmark

Spontaneous recovery of hydrogen-degraded TiO₂ ceramic capacitors

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Comparison of interfacial and electrical characteristics of HfO₂and HfAlO high-k dielectrics on compressively strained Si[sub 1−x]Ge[sub x]

Author name used in this publication: P. F. LeeAuthor name used in this publication: J. Y. Dai2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe