Some aspects of the biology and behaviour of Sesamia nonagrioides botanephaga Tams and Bowden (Lepidoptera: Noctuidae), a major stem borer pest of maize in Southern Ghana

Studies were conducted on the stemborer, Sesamia nonagrioides botanephaga Tams and Bowden (Lepidoptera: Noctuidae), which is a pest of increasing importance on maize in Ghana, to elucidate some aspects of its biology and behaviour in southern Ghana. The pest was more abundant in the minor season than in the major season. The life cycle revealed 10 developmental stages, namely the egg, six larval instars, prepupa and pupa. A female S. n. botanephaga laid eggs within a period of 5 days. The eggs were deposited on the inner side of the leaf sheath fitting tightly onto the maize stem. The mated females laid more eggs per female (330 + 17.7 eggs) than the virgin females (268 + 9.2 eggs). The incubation period of the eggs was 5.23 + 0.03 (5-7) days. The mean larval duration was 29 days and the prepupal period lasted for 1–3 days. The first instar larvae dispersed within 1–3 days after hatching. The third, fourth, fifth, and sixth instar larvae fed actively on maize stalk producing large quantities of frass. The pupal period varied from 6 to 10 days. The life cycle was completed in an average of 35.2 (26-51) days. Adults of S. n. botanephaga lived for between 4–10 days. The adults reared in the laboratory showed a sex ratio of 2:3 (male : female), which was significantly different from the expected ratio (1:1). The implications of these findings are discussed in relation to the effective management of the pest in Ghana

Muppet: MapReduce-Style Processing of Fast Data

MapReduce has emerged as a popular method to process big data. In the past few years, however, not just big data, but fast data has also exploded in volume and availability. Examples of such data include sensor data streams, the Twitter Firehose, and Facebook updates. Numerous applications must process fast data. Can we provide a MapReduce-style framework so that developers can quickly write such applications and execute them over a cluster of machines, to achieve low latency and high scalability? In this paper we report on our investigation of this question, as carried out at Kosmix and WalmartLabs. We describe MapUpdate, a framework like MapReduce, but specifically developed for fast data. We describe Muppet, our implementation of MapUpdate. Throughout the description we highlight the key challenges, argue why MapReduce is not well suited to address them, and briefly describe our current solutions. Finally, we describe our experience and lessons learned with Muppet, which has been used extensively at Kosmix and WalmartLabs to power a broad range of applications in social media and e-commerce.Comment: VLDB201

The role of elective neck dissection during surgical salvage for recurrent nasopharyngeal carcinoma

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Hypoxia in head and neck squamous cell carcinoma

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mTOR pathway and mTOR inhibitors in head and heck cancer

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mTOR pathway and mTOR inhibitors in head and heck cancer

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The diagnostic value of methylated DNA in laryngeal squamous cell carcinoma: meta-analysis

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