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台灣文學英譯叢刊(No. 46)：台灣當代詩專輯

為了解決Great Red spot的問題，作者 這樣論述：

　　This issue contains the verse of twenty-four poets.   　　From 1924, when Hsieh Chun-mu first published four “Poems in Imitation,” the development of new poetry in Taiwan has a history of almost one hundred years. The roots of new poetry in Taiwan with its “twin flower bulbs,” to use the phr

ase coined by Chen Chien-wu, has now bloomed and borne fruit. It manifests diversified themes, and places great stress on both artistic expression and social concern. It recognizes globalization as the major trend of the times, and maintains a dynamic balance between nativist consciousness and the e

nsibilities of the Chinese cultural diaspora. Taiwan literature and its new poetry written in Chinese should have a place in the Chinese world community,as well as in the history of world literature. Limited by the space allowed for the journal, we could only select works related to “local” and “quo

tidian” writing. Yet we hope to observe through these works the manner in which the unique charm and gracefulness of contemporary poetry from Taiwan has blossomed in the garden of world literature.   　　這一專輯精選具有代表性的詩人二十四家。   　　從1924年謝春木發表「詩的模仿」四首算起，台灣新詩的發展也有將近一百年的歷史。新詩「兩個球根」在台灣已經開花結果，呈現出主題多元，

創作藝術與關懷現實並重，面對全球化的時代趨勢，保持本土意識與文化離散互相呼應和抗衡。台灣文學和以華文創作的新詩，不僅在華人世界，甚至在世界文學的大花園裡，都應該占有一席之地。我們出版這一專輯，收到篇幅的限制，只能以「地方與日常」選錄相關詩作，藉以展現台灣當代詩在世界花園裡一枝獨秀的風姿。

Great Red spot進入發燒排行的影片

Nucleus Near-Infrared (nNIR) Irradiation of Single A549 Cells Induces DNA Damage and Activates EGFR Leading to Mitochondrial Fission

為了解決Great Red spot的問題，作者MOMOH GBETUWA 這樣論述：

Abstract Background: There has been great interest in identifying the biological substrate for light-cell interaction and their relations to cancer treatment. In our study, a single cell nuclear NIR (nNIR) and cytosol exposed NIR has been used to determine for the first-time mitochondria fragmentat

ion count (MFC) to compare NIR effect on subcellular cells. Near infra-red (NIR) possesses less light scattering and absorption in biological tissues it has a biological window that bears a very small photodamage and thus possesses a deep tissue penetration depth. Aim: To evaluate near-infrared (NIR

) laser focused into the nucleus (nNIR) or cytoplasm (cNIR) of a single living cell by a high numerical aperture condenser to dissect the novel role of cell nucleus in mediating NIR effects on mitochondrial dynamics of A549 non-small cell lung cancer cells.Materials and Methods: Cultured 150 single

cell of A549 nucleus and cytosol were incubated with 0.3 μM mitotracker green for 30 min washed with PBS, imaged control cell then treated with 224.02 J/cm2 NIR for 10 s and cells imaged at different time points of 1, 5, 10, 15 and 20 min. A549 cells were treated with conjugated 100 nM FND-EGF and i

ncubated with PD153035, caffeine and cetuximab for 1 h, and imaged cells. Results: Our analysis showed nNIR, but not cNIR, triggered mitochondrial fission in 10 minutes. On the contrast, the fission/fusion balance of mitochondria directly exposed to cNIR does not change. While the same phenomenon is

also triggered by single molecular interactions between epidermal growth factor (EGF) and its receptor EGFR, pharmacological studies with cetuximab, PD153035 and caffeine suggest EGF signaling crosstalk to DNA damaging response to mediate rapid mitochondrial fission as a result of nNIR irradiation.

These results suggest that nuclear DNA integrity is a novel biological target for cellular response to NIR. Conclusions: These results suggest that nuclear DNA integrity is a novel biological target for cellular response to NIR. Keywords: Keywords: near infrared (NIR), epidermal growth factor recep

tor (EGFR), mitochondrial fragmentation count (MFC), mitochondrial dynamic, cetuximab, caffeine.

The Pacific Northwest Seafood Cookbook: Salmon, Crab, Oysters, and More

為了解決Great Red spot的問題，作者Tomky, Naomi 這樣論述：

For thousands of years, the abundance of fish and shellfish in the Pacific Northwest created a seafood paradise for the Indigenous peoples hunting and gathering along the region's pristine waterways, and, later, for the Chinese, Scandinavian, Filipino, and Japanese immigrants (along with many others

), who have made this region home. Drawing on these diverse influences, the region fostered a cuisine that is as varied as its people, yet which remains specifically Northwestern.Here, food writer Naomi Tomky leads readers through an exploration of this cuisine. She starts with the basics of buying

great-tasting and sustainable seafood, surveys the variety of seafood on offer--from stars like halibut and oysters to unsung heroes like lingcod and smelt--and shares 75 delicious recipes reflecting the people who live in the region today, including Red Curry Mussels, IPA-Battered Cod, Dungeness Cr

ab Deviled Eggs, and Pink Scallop Ceviche.From the first cut of salmon, prized for its rich flavor and versatility, to the last crack of the sweet Dungeness crab, Tomky covers grilling, curing, and baking, and shares secrets for tricky tasks like removing pin bones and mussel beards. She explains ho

w flavor-packed spot prawns put other shrimp to shame and why the region's razor clams are unparalleled. For curious seafood rookies in search of the perfect fool-proof salmon and barnacled fish-cooking veterans looking for a new way to enjoy their favorite catch, The Pacific Northwest Seafood Cookb

ook is a must-have guide to cooking, and eating, the region.Including recipes from Tom Douglas, Shiro Kashiba, Bonnie Morales, Mutsuko Soma, Ethan Stowell, Jason Stratton, John Sundstrom, and more.

以深度學習偵測植物病害之研究－以稻熱病為例

為了解決Great Red spot的問題，作者曾信維 這樣論述：

稻熱病作為水稻之主要病害之一，目前防治稻熱病之主要方法為抗病品種之栽培以及殺菌劑之施用，雖然前者具有較低之生產成本，且對於環境所造成之負擔也較低，然而過度依賴單一品種或是不當的施肥管理，將使其抗病性逐年下降。而殺菌劑之施用雖然較為有效，則需要注意施藥之劑量以及範圍，避免過度施藥所增加之生產成本及環境衝擊。傳統在執行稻熱病害的偵測時多以人力進行地面調查，無論是時間上或是金錢上都需要花費大量成本，對於病徵判斷之精確度亦有限。隨著機器學習技術之發展，如深度學習這類具有高學習力及高辨識力之技術，可以提供使用者一次性進行大量資料的訓練，且其”end-to-end”之特性使資料不須進行預處理，可以節省大

量時間成本，因此本研究欲使用深度學習之技術開發一套稻熱病病徵之影像辨識系統，先針對田野調查所拍攝之影像進行專家判釋，建立病害病徵之影像資料庫，並用其進行深度學習，建立稻熱病辨識之卷積神經網路模型。同時，本研究使用經紅外線改機之相機影像進行深度學習，探討此類資料對於稻熱病之判釋能力。本研究根據所蒐集之資料，將影像分為健康、稻熱病及胡麻葉枯病三個分類，並將可見光及紅外光影像分別進行深度學習之模型訓練。模型進行遷移學習以提升訓練效率，並使用DenseNet121作為模型架構。模型完成訓練後進行測試資料之預測，並以混淆矩陣進行辨識成果的展示，同時計算相關指標以進行成果精度評估。結果顯示利用可見光影像進

行訓練之分類模型精度可達0.98，紅外線影像之分類模型精度達0.94，可見光影像在病徵辨識上較有優勢，而透過紅外線改機所獲得之紅外線影像亦能取得不錯的辨識精度，顯示此類影像應用於病徵辨識之潛力。