Effects of Some Chinese Strains of Peanut Stripe Virus (PStV) on Groundnut Cultivars and Other Plants

Seed transmission frequency and pod losses of groundnuts (Arachis hypogaea) due to peanut stripe virus isolates are reported from China. Five isolates were collected in Wuhan (PStV-W1, W2, N), Guangzhou (PStV-G) and Tansan (PStV-T). These were divided into 3 groups on the basis of symptoms in various groundnut genotypes. Isolates in group 1, which produced mild mottling, were widely distributed. PStV-W1 caused a 1.4-6.4% reduction in plant height, and G, 9.2-16.3%. Losses in pod yields due to these isolates were 20.8-36.6 and 29.8-55%, respectively. PStV-W1 was transmitted to 20.9% and PStV-G to 6.1% of seed of cv Zhonghua No.3. All five isolates were transmitted by Aphis craccivora

Immuno-Therapy with Anti-CTLA4 Antibodies in Tolerized and Non-Tolerized Mouse Tumor Models

Monoclonal antibodies specific for cytotoxic T lymphocyte-associated antigen 4 (anti-CTLA4) are a novel form of cancer immunotherapy. While preclinical studies in mouse tumor models have shown anti-tumor efficacy of anti-CTLA4 injection or expression, anti-CTLA4 treatment in patients with advanced cancers had disappointing therapeutic benefit. These discrepancies have to be addressed in more adequate pre-clinical models. We employed two tumor models. The first model is based on C57Bl/6 mice and syngeneic TC-1 tumors expressing HPV16 E6/E7. In this model, the HPV antigens are neo-antigens, against which no central tolerance exists. The second model involves mice transgenic for the proto-oncogen neu and syngeneic mouse mammary carcinoma (MMC) cells. In this model tolerance to Neu involves both central and peripheral mechanisms. Anti-CTLA4 delivery as a protein or expression from gene-modified tumor cells were therapeutically efficacious in the non-tolerized TC-1 tumor model, but had no effect in the MMC-model. We also used the two tumor models to test an immuno-gene therapy approach for anti-CTLA4. Recently, we used an approach based on hematopoietic stem cells (HSC) to deliver the relaxin gene to tumors and showed that this approach facilitates pre-existing anti-tumor T-cells to control tumor growth in the MMC tumor model. However, unexpectedly, when used for anti-CTLA4 gene delivery in this study, the HSC-based approach was therapeutically detrimental in both the TC-1 and MMC models. Anti-CTLA4 expression in these models resulted in an increase in the number of intratumoral CD1d+ NKT cells and in the expression of TGF-β1. At the same time, levels of pro-inflammatory cytokines and chemokines, which potentially can support anti-tumor T-cell responses, were lower in tumors of mice that received anti-CTLA4-HSC therapy. The differences in outcomes between the tolerized and non-tolerized models also provide a potential explanation for the low efficacy of CTLA4 blockage approaches in cancer immunotherapy trials

Phylogenomic analyses provide insights into primate evolution

Comparative analysis of primate genomes within a phylogenetic context is essential for understanding the evolution of human genetic architecture and primate diversity. We present such a study of 50 primate species spanning 38 genera and 14 families, including 27 genomes first reported here, with many from previously less well represented groups, the New World monkeys and the Strepsirrhini. Our analyses reveal heterogeneous rates of genomic rearrangement and gene evolution across primate lineages. Thousands of genes under positive selection in different lineages play roles in the nervous, skeletal, and digestive systems and may have contributed to primate innovations and adaptations. Our study reveals that many key genomic innovations occurred in the Simiiformes ancestral node and may have had an impact on the adaptive radiation of the Simiiformes and human evolution

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Automated software test data generation using a GA 6/2/94 Automated Software Test Data Generation Using A Genetic Algorithm

Software testing is an important way for improving the quality of software. It accounts approximately half of all software engineering cost. The critical point is to increase the degree of automation of testing and its test data generation. In 80’s most test data generation used symbolic evaluation to drive test data. Since the complexity of the set of predicate equations solving it can not be put into practice. Recent methods use actual program execution and function minimization search method. The local property of these method needs to be improved. In this paper we proposed a new approach-- automated test data generation using a genetic algorithm (GA). Compared with traditional search algorithms the efficiency and efficacy are much better than before. We introduce the new method and apply the new method to a typical sample. The results of the experiment of test data generation using a GA and its analysis is presented in this paper. Further work needs to be extended to dynamic data structure. Key words: software testing, test data generation, path selection, genetic algorithm, fitness

Evaluation of an Aphid-Resistant Groundnut Genotype (EC 36892) in China

An aphid resistant groundnut (Arachis hypogaea) genotype, EC36892, introduced from ICRISAT Asia Centre in 1990, and 3 local cultivars were evaluated in China for resistance to aphids (Aphis craccivora) and peanut stunt cucumovirus (PStV) during 1991 and 1992. Aphid multiplication was much lower on EC36892 than on local cultivars in greenhouse tests, on average 0.6 vs. 6.9 aphids/plant on local variety Huohua 1. In field trials at Wuhan, EC36892 showed higher resistance to aphids in both years. In 1991, there were 4 aphids per 100 plants compared to 60 aphids on Hua 37 and 330 aphids on Huohua 1 at the first aphid multiplication peak. PStV incidence varied during the 2 years of field trials, but EC36892 had lower incidence than the local cultivars. In both years, EC36892 gave higher yields than Huohua 1 but lower than those of Hua 37 and Yihua 1

Multilevel active registration for kinect human body scans: from low quality to high quality

Registration of 3D human body has been a challenging research topic for over decades. Most of the traditional human body registration methods require manual assistance, or other auxiliary information such as texture and markers. The majority of these methods are tailored for high-quality scans from expensive scanners. Following the introduction of the low-quality scans from cost-effective devices such as Kinect, the 3D data capturing of human body becomes more convenient and easier. However, due to the inevitable holes, noises and outliers in the low-quality scan, the registration of human body becomes even more challenging. To address this problem, we propose a fully automatic active registration method which deforms a high-resolution template mesh to match the low-quality human body scans. Our registration method operates on two levels of statistical shape models: (1) the first level is a holistic body shape model that defines the basic figure of human; (2) the second level includes a set of shape models for every body part, aiming at capturing more body details. Our fitting procedure follows a coarse-to-fine approach that is robust and efficient. Experiments show that our method is comparable with the state-of-the-art methods.Comment: 14 pages, the Journal of Multimedia System