• Title/Summary/Keyword: Dissecting

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Mass-rearing Techniques of Anastatus orientalis (Hymenoptera: Eupelmidae), as the Egg-parasitoid of Lycorma delicatula (Hemiptera: Fulgoridae): An Using Method of Antheraea pernyi (Lepidoptera: Saturniidae) and L. delicatula Eggs in Laboratory (꽃매미 알 기생천적인 꽃매미벼룩좀벌의 대량사육기술: 산누에나방과 꽃매미 알 활용 방법)

  • Seo, Meeja;Kim, Jeong Hwan;Seo, Bo Yoon;Park, Changgyu;Choi, Byeong Ryeol;Kim, Kwang Ho;Ji, Chang Woo;Cho, Jum Rae
    • Korean journal of applied entomology
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    • v.57 no.4
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    • pp.243-251
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    • 2018
  • Eggs, immature eggs, and pupae of 8 different insects (Halyomopha halys, Riptortus pedestris, Lymantria dispar, Antheraea yamamai, Verlarifictorus spp, Antheraea pernyi, and Musca domestica) including Lycorma delicatura were used to select the alternative host for laboratory mass rearing of A. orientalis. Except L. delicatula's eggs and immature eggs of A. pernyi, other 7 tested insects were not parasitized by A. orientalis. A. pernyi was reared with oak tree leaves and its cocoons were harvested on mid-July and early October. On 4 or 5 days after emergence, only female adults showing swollen abdomen were collected and stored at $1{\sim}5^{\circ}C$. We could get 150~200 eggs per one female by dissecting the female's abdomen. For examining the possibility for laboratory mass rearing of A. orientalis with A. pernyi's immature eggs, developmental periods from egg to pupa between the two different hosts were compared. Developmental periods were 36.1 days on immature eggs of A. pernyi and 36.8 days on an original host's eggs, respectively. The number of parasitized eggs by A. orientalis' female for 24 h was 3.4 on immature eggs of A. pernyi and 4.2 on an original host's eggs, respectively. However, there were no significant statistical differences in developmental period and parasitization between the two hosts. By supplying honeyed water to newly emerged female parasitoids, it was able to maximize their longevities up to 64.3 days after emergence. Therefore, our results support potential for laboratory mass-rearing of A. orientalis using A. pernyi's immature eggs as an alternative host.

Analysis and Forecast of Venture Capital Investment on Generative AI Startups: Focusing on the U.S. and South Korea (생성 AI 스타트업에 대한 벤처투자 분석과 예측: 미국과 한국을 중심으로)

  • Lee, Seungah;Jung, Taehyun
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.4
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    • pp.21-35
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    • 2023
  • Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.

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