This paper reports the isolation from soil of Penicillium strain PY-1 with strong antagonistic activity against plant pathogenic fungi. On the basis of its morphological characteristics and the sequence of the ITS region, strain PY-1 was identified as P. oxalicum. Strain PY-1 produces antifungal substances that suppress the mycelial growth of Sclerotinia sclerotiorum and many other plant pathogenic fungi tested; the highest antagonistic activity was detected at 72 h when cultured in a 250-ml flask containing 80 ml potato dextrose broth. Compared with carbendazim, the relative activity of the antifungal substances produced by strain PY-1 was approximately 4 lg active ingredient (a.i.) per milliliter. The antifungal substances were extracted with ethyl acetate and further separated by high-performance liquid chromatography (HPLC); at least two active components were discovered. The ability to control plant disease with strain PY-1 was confirmed with S. sclerotiorum, a widespread pathogenic fungus that attacks rapeseed (Brassica napus) and other plants. Spores (10 6 or 10 7 ml -1 ) and filtrate (tenfold diluted or undiluted) of strain PY-1 could significantly suppress infection and/or the extent of infection by S. sclerotiorum of plants at seven-true-leaves stage. The potential of strain PY-1 for identifying new antibiotics to control fungal disease and for biological control of plant disease, for example oilseed rape stem rot, is discussed.

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Abstract. Based on the case study and spatial comparison, the analysis of the present situation of the survival and development of colleges and universities in the southwest frontier of China shows that the backward economic development has led to the weakening of higher education. The incompatibility of personnel training and regional development, backward development concept and poor service capacity and other issues are highlighted. Start with the colleges and universities in northwest of Yunnan Province, promote the comprehensive docking of university personnel training and local economy to implement higher education supply-side structural reform, construct school-running mechanism with border characteristics, set up government and enterprise cooperation platform and mechanism, finally realizing transformation and development of border nations regional colleges and universities.

Abstract. The smart grid is one of the important fields of large data applications. The study of power behavior of the user in the big data environment has important significance for the demand side management ,load forecasting and so on . Aiming at the problem of insufficient real-time response capability of massive power data, the introduction of distributed real-time computing platform Storm is used to analyze the user's behavior. In this paper, the k-means algorithm is implemented under the Storm framework. Through the experimental test and comparison analysis, it is verified that the Storm computing system can improve the real-time processing of the data, and can deal with large-scale data.

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