116,688 research outputs found
Bawool Yoo
No full text학위논문(석사)--아주대학교 일반대학원 :분자과학기술학과,2015. 2Ι. Introduction 1
II. Experiments 6
II.1 Chemical Structure 6
II.2 Synthesis 8
II.2.1 Materials 8
II.2.2 Scheme of HMQ-VBS Synthesis 8
II.2.3 Scheme of OHQ-VBS Synthesis 9
II.3 General Characterization 10
II.3.1 1H NMR Analysis 10
II.3.1.1 1H NMR Analysis of intermediates 10
II.3.1.2 1H NMR Analysis of HMQ-VBS and OHQ-VBS 11
III. Results and Discussion 15
III.1 Design and Synthesis 15
III.2 Thermal Analysis 17
III.3 Second Harmonic Generation (SHG) Test 20
III.4 Crystal Growth and Structure 22
IV. Conclusions 34
V. References 35MasterDerivatives of highly nonlinear optical ionic salt organic crystal HMQ-T (2-(4-hydroxy-3-methoxystyryl)-1-methylquinolinium 4-methylbenzenesulfonate) with 2-(4-hydroxy-3-methoxystyryl)-1-methylquinolinium 4-vinylbenzenesulfonate (HMQ-VBS) replacing the 4-methylbenzenesulfonate of HMQ-T have been synthesized and characterized. In addition we synthesized and characterized derivatives of another highly nonlinear optical ionic salt organic crystal OHQ-T (2-(4-hydroxystyryl)-1-methylquinolinium 4-methylbenzenesulfonate) with 2-(4-hydroxystyryl)-1-methylquinolinium 4-vinylbenzenesulfonate (OHQ-VBS) replacing same counteranion. OHQ-VBS crystal exhibits a highly macroscopic nonlinear optical properties with highly second harmonic generation (SHG) efficiency. The cations of OHQ-VBS constitutes strong head-to-tail hydrogen bonds, and they exhibits acentric crystal structure of cations and counteranion layers. Therefore HMQ-VBS crystal exhibits a centrosymmetric crystal structure. X-ray crystallographic analysis revealed that the crystal structure of OHQ-VBS is monoclinic Pn, which is similar to that of OHQ-T, however HMQ-VBS exhibits a centrosymmetric P21/c structure compare to other three molecules
Data for "Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics"
No full textPrediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.
Authors: Kazutaka Kamiya, MD, PhD1, Ik Hee Ryu, MD, MS2, Tae Keun Yoo, MD2, Jung Sub Kim MD2, In Sik Lee, MD, PhD2, Jin Kook Kim MD2, Wakako Ando CO3, Nobuyuki Shoji, MD, PhD3, Tomofusa, Yamauchi, MD, PhD4, Hitoshi Tabuchi, MD, PhD4.
Author Affiliation: 1Visual Physiology, School of Allied Health Sciences, Kitasato University, Kanagawa, Japan, 2B&VIIT Eye Center, Seoul, Korea, 3Department of Ophthalmology, School of Medicine, Kitasato University, Kanagawa, Japan, 4Department of Ophthalmology, Tsukazaki Hospital, Hyogo, Japan.
We hypothesize that machine learning of preoperative biometric data obtained by the As-OCT may be clinically beneficial for predicting the actual ICL vault. Therefore, we built the machine learning model using Random Forest to predict ICL vault after surgery.
This multicenter study comprised one thousand seven hundred forty-five eyes of 1745 consecutive patients (656 men and 1089 women), who underwent EVO ICL implantation (V4c and V5 Visian ICL with KS-AquaPORT) for the correction of moderate to high myopia and myopic astigmatism, and who completed at least a 1-month follow-up, at Kitasato University Hospital (Kanagawa, Japan), or at B&VIIT Eye Center (Seoul, Korea).
This data file (RFR_model(feature=12).mat) is the final trained random forest model for MATLAB 2020a.
Python version:
***************************************************************
from sklearn.model_selection import train_test_split
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import RandomForestRegressor
# connect data in your google drive
from google.colab import auth
auth.authenticate_user()
from google.colab import drive
drive.mount('/content/gdrive')
# Change the path for the custom data
# In this case, we used ICL vault prediction using preop measurement
dataset = pd.read_csv('gdrive/My Drive/ICL/data_icl.csv')
dataset.head()
#optimal features (sorted by importance) :
# 1. ICL size 2. ICL power 3. LV 4. CLR 5. ACD 6. ATA
# 7. MSE 8.Age 9. Pupil size 10. WTW 11. CCT 12. ACW
y = dataset['Vault_1M']
X = dataset.drop(['Vault_1M'], axis = 1)
# Split the dataset to train and test data
# For a simple validation test, we split data to 8:2
train_X, test_X, train_y, test_y = train_test_split(X, y, test_size=0.2, random_state=0)
# Optimal parameter search could be performed in this section
parameters = {'bootstrap': True,
'min_samples_leaf': 3,
'n_estimators': 500,
'criterion': 'mae'
'min_samples_split': 10,
'max_features': 'sqrt',
'max_depth': 6,
'max_leaf_nodes': None}
RF_model = RandomForestRegressor(**parameters)
RF_model.fit(train_X, train_y)
RF_predictions = RF_model.predict(test_X)
importance = RF_model.feature_importances
Thinobius koreanus Lee & Yoo & Ahn 2021, sp. n.
No full text<i>Thinobius koreanus</i> Lee & Yoo sp. n. <p>(Figs. 1B, 4–5)</p> <p> <b>Description.</b> Length 1.60–1.80 mm. Body flattened, surface pubescent; light brown to dark brown, head and abdomen dark brown, pronotum, elytra and antenna brown, mouthparts and legs light brown. <i>Head</i>. Almost as long as wide and slightly narrower than pronotum; widest across eyes; clypeus trapezoidal; eye moderate in size and rounded in lateral aspect, with large eye facet and interfacetal setae; temple well developed, diameter of eye slightly longer than temple; gular suture fused and broadly divergent at posterior part; neck well developed, transversely reticulate sculptures distinct, seta absent (Fig. 4B); antenna slender, moderately elongate, and pubescent; antennomere 1 longest, 3 shortest, 1–11 elongate (Fig. 4A). <i>Mouthparts</i>. Labrum transverse, lateral margin rounded, anterior margin slightly emarginate; mandible triangular, apex bifid with subapical tooth, prostheca and molar tooth well developed; maxillary palpus with four palpomeres, palpomere 1 transverse and small, 2 slightly dilated to apex, 3 largest, 2–3 with many setae, 4 short and slender; apical margin of 3 more than 2.0 times as wide as basal margin of 4; labial palpus with three elongate palpi, palpomere 1 with one long, one short seta and two pores, 2 with one long seta and one pore, 3 with few short sensilla at apex; mentum quadrate with two pairs of long macrosetae and many setae. <i>Thorax</i>. Pronotum transverse, width 0.29–0.30 mm, widest near half of length, surface pubescent with seven pairs of macrosetae and many setae; prosternum with one pair of long setae and a few short setae, apex of prosternal process sharp and elevated (Figs. 4C–D); scutellum an inverted triangle, anterior margin of scutellum emarginate, posterior part reticulate with a few setae and inverted triangle impression, impression about 1.6 times as wide as long, elytron elongate and pubescent; posterior margin with membranous lobe; hind wing present; mesoventral process slightly extended and pointed at apex; metaventral carina absent; metaventrite distinctly reticulate with two pairs of long macrosetae and many setae (Fig. 4E); all tibiae with one long macroseta in middle. <i>Abdomen</i>. Posterior margin of tergite VII with fringe of setae; posterior margin of tergite VIII emarginate; posterior margin of sternite VIII convex. <i>Secondary sexual characteristics</i>. Male tergite IX with ventral structs, struts shorter than other part, female gonocoxites present; female with one ring structure (Fig. 4F). <i>Genitalia</i>. Aedeagus oval (Fig. 5A) with serrated pattern in lateral aspect (Fig. 5B); paramere long and slender; spermatheca as in Fig. 5C.</p> <p> <b>Type material.</b> Holotype, 1 ♂, labeled as follows: ‘ KOREA: Gyeongbuk Prov., Pohang-si, Buk-gu, Cheongha-myeon, Cheongjin-ri, N36°10'38.73" E129°23'37.15" 17 m, 12 VII 2018, IS Yoo, JS Lee, JG Jung, in coarse sand/gravels on seashore, flotation’ ‘ Holotype, <i>Thinobius koreanus</i> Lee and Yoo, Desig. Jae-Seok Lee and In-Seong Yoo, 2021 ’ ‘ Deposited in the Chungnam National University Insect Collection, Korea’. Paratypes, 7 exx., same data as holotype, 5 exx., same data as holotype except for ‘ N36°10ʹ37.8 ʺE129°23ʹ38.0ʺ 9m, 27 VIII 2010, KJ Ahn, TK Kim, YH Kim, IS Yoo, JH Song, SG Lee, JH Jeon, under stones on seashore.’</p> <p> <b>Distribution.</b> Korea.</p> <p> <b>Remarks.</b> This species is similar to <i>T. marinus</i>, but can be distinguished by the shape of antennomeres. Antennomeres 1–11 are elongate in <i>Thinobius koreanus</i> <b>sp. n.</b> (Fig. 4A), but 4–8 transverse in <i>T. marinus</i>. The new species is also similar to <i>T. frizzelli</i> from Canada and USA but can be distinguished by the shape of antennomeres. Antennomeres 4–10 are quadrate and 4–6 are almost same length in the new species (Fig. 4A), but 4–10 rounded form and 5 larger than 4 or 6 in <i>T. frizzelli</i> (Kincaid, 1961). All specimens were collected in the southern part of the Korean peninsula.</p>Published as part of <i>Lee, Jae-Seok, Yoo, In-Seong & Ahn, Kee-Jeong, 2021, Taxonomy of the coastal Thinobius Kiesenwetter (Coleoptera: Staphylinidae Oxytelinae) in Korea, pp. 261-268 in Zootaxa 4985 (2)</i> on pages 264-265, DOI: 10.11646/zootaxa.4985.2.9, <a href="http://zenodo.org/record/4943584">http://zenodo.org/record/4943584</a>
Data for "Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics"
No full textPrediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.
Authors: Kazutaka Kamiya, MD, PhD, Ik Hee Ryu, MD, MS, Tae Keun Yoo, MD, Jung Sub Kim MD, In Sik Lee, MD, PhD, Jin Kook Kim MD, Wakako Ando CO, Nobuyuki Shoji, MD, PhD, Tomofusa, Yamauchi, MD, PhD, Hitoshi Tabuchi, MD, PhD.
We hypothesize that machine learning of preoperative biometric data obtained by the As-OCT may be clinically beneficial for predicting the actual ICL vault. Therefore, we built the machine learning model using Random Forest to predict ICL vault after surgery.
This multicenter study comprised one thousand seven hundred forty-five eyes of 1745 consecutive patients (656 men and 1089 women), who underwent EVO ICL implantation (V4c and V5 Visian ICL with KS-AquaPORT) for the correction of moderate to high myopia and myopic astigmatism, and who completed at least a 1-month follow-up, at Kitasato University Hospital (Kanagawa, Japan), or at B&VIIT Eye Center (Seoul, Korea).
This data file (RFR_model(feature=12).mat) is the final trained random forest model for MATLAB 2020a.
Python version:
***************************************************************
from sklearn.model_selection import train_test_split
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import RandomForestRegressor
# connect data in your google drive
from google.colab import auth
auth.authenticate_user()
from google.colab import drive
drive.mount('/content/gdrive')
# Change the path for the custom data
# In this case, we used ICL vault prediction using preop measurement
dataset = pd.read_csv('gdrive/My Drive/ICL/data_icl.csv')
dataset.head()
#optimal features (sorted by importance) :
# 1. ICL size 2. ICL power 3. LV 4. CLR 5. ACD 6. ATA
# 7. MSE 8.Age 9. Pupil size 10. WTW 11. CCT 12. ACW
y = dataset['Vault_1M']
X = dataset.drop(['Vault_1M'], axis = 1)
# Split the dataset to train and test data, if necessary.
# For example, we can split data to 8:2 as a simple validation test
train_X, test_X, train_y, test_y = train_test_split(X, y, test_size=0.2, random_state=0)
# In our study, we already defined the training (B&VIIT Eye Center, n=1455) and test (Kitasato University, n=290) dataset, this code was not necessary to perform our analysis.
# Optimal parameter search could be performed in this section
parameters = {'bootstrap': True,
'min_samples_leaf': 3,
'n_estimators': 500,
'criterion': 'mae'
'min_samples_split': 10,
'max_features': 'sqrt',
'max_depth': 6,
'max_leaf_nodes': None}
RF_model = RandomForestRegressor(**parameters)
RF_model.fit(train_X, train_y)
RF_predictions = RF_model.predict(test_X)
importance = RF_model.feature_importances
Letter, [Author unclear] to Paulina T. Merritt
No full textHandwritten letter to Paulina Merritt from an unknown author, October 1, 1876.
Thinobius jejuensis Lee & Yoo & Ahn 2021, sp. n.
No full textThinobius jejuensis Lee & Ahn sp. n. (Figs. 1A, 2–3) Description. Length 1.04–1.30 mm. Body flattened, surface pubescent; dark brown. Head. Almost as long as wide and slightly narrower than pronotum; widest across eyes; clypeus trapezoidal; eye moderate in size and rounded in lateral aspect, with large eye facets and interfacetal setae; temple well developed, about 0.8 times as long as eye length in dorsal view; gular suture fused and broadly divergent in anterior and posterior part; neck well developed, distinctly transversely reticulate sculptures with some short setae (Figs. 2B–C); antenna slender, moderately elongate, and pubescent, antennomere 1 longest, 4 and 6 shortest, 1–2 and 7–11 elongate, 3 and 5 slightly elongate, 4 and 6 transverse (Fig. 2A). Mouthparts. Labrum transverse, semicircula; mandible triangle, apex bifid, with one blunt subapical tooth, prostheca and molar tooth well developed; maxillary palpus with four palpomeres, palpomere 1 transverse and small, 2 slightly dilated to apex, 3 largest, 2–3 with dense setae; apical margin of 3 about 3.0 times as wide as basal margin of 4; labial palpus with three elongate palpus, apex of palpomere 1 with two long setae and one pore, apex of 2 with one pore, 3 with few short sensilla at apex; mentum quadrate with one pair of long macrosetae and many setae. Thorax. Pronotum transverse, width 0.24–0.27 mm, widest about anterior third, surface pubescent; prosternum with few setae (Fig. 2D); scutellum an inverted triangle, anterior margin of scutellum emarginate, posterior part reticulate with many setae (Fig. 2E); elytron elongate and pubescent, posterior margin with membranous lobe; hind wing present; mesoventral process slightly extended and blunted at apex; metaventral carinae incomplete; metaventrite with two pairs of long macrosetae and dense setae (Fig. 2F); all tibiae with one long macroseta in middle. Abdomen. Posterior margin of tergite VII with fringe of setae; postero-lateral margin of tergite VIII slightly convex. Secondary sexual characteristics. Male sternite VIII emarginate, female with linear form; male tergite IX with ventral structs, struts as long as remainder, female tergite IX without ventral struts. Male sternite IX elongate, female sternite IX pentagon. Genitalia. Aedeagus oval (Figs. 3A–B); paramere short; spermatheca as in Fig. 3C. Type material. Holotype, 1 ♂, labeled as follows: KOREA: Jeju Prov., Seogwipo-si, Haye-dong, N33°13'54.45" E126°22'19.81" 2 m, 19 X 2014, KJ Ahn, IS Yoo, JS Lee, 10-20 cm deep under/in gravels on seashore. ‘ Holotype, Thinobius jejuensis Lee and Ahn, Desig. Jae-Seok Lee and Kee-Jeong Ahn 2021 ’ ‘ Deposited in the Chungnam National University Insect Collection, Korea’. Paratypes, 3 exx., labeled as same as Holotype (1 on slide; 1 on CNUIC voucher); 30 exx., same data as former except for ‘ N33°13'54.20" E126°22'18.49" 2 m, 05 VIII 2020, JS Lee, JY Park, YJ Kim, flotation’. 24 exx., same data as former except for ‘Yeraehaean-Ro, N33.232254, E126.371442, 19 X 2020, KJ Ahn, Under pebbles/gravels by flotation’. Distribution. Korea (Jeju island). Remarks. This species is similar to T. marinus, but can distinguished by the length of temple and the shape of antennomeres. Temple is shorter than the diameter of eye in T. jejuensis Lee & Ahn, sp. n. (Fig. 2B), but longer than the diameter of eye in T. marinus (Cameron, 1917). In addition, antennomeres 5 and 7–8 are elongate in the new species (Fig. 2A), but 4–8 are transverse in T. marinus. All specimens were collected on Jeju-do island, KoreaPublished as part of Lee, Jae-Seok, Yoo, In-Seong & Ahn, Kee-Jeong, 2021, Taxonomy of the coastal Thinobius Kiesenwetter (Coleoptera: Staphylinidae Oxytelinae) in Korea, pp. 261-268 in Zootaxa 4985 (2) on pages 263-264, DOI: 10.11646/zootaxa.4985.2.9, http://zenodo.org/record/494358
Grice’s Maxim in Humor Conversation of Yoo Bro Meme Comic
No full textHumor is funny thing which is made by creativity, interest, and critic to entertain the reader. Through humor violating maxims may occur. This studies concerns on Grice's Maxim in Humor Conversation of Yoo Bro Meme Comic. The main focus of the researcher is to analyze violating maxims use in the conversation of yoo bro meme comic. The purposes of this study are; (1)To identify and classify kinds of maxim are disobeyed in humor conversation of Yoo bro meme comic and (2)To explain how violated maxim generates a sense of humor in Yoo bro meme comic. The design of this study was descriptive qualitative which describes what the data shows. The researcher was the key instrument because she directly involved collecting and analyzing the data in this study. The researcher conducted the study and took the data from website https://me.me/t/yoo-bro. The source of data is 48 conversations. This study used Miles and Huberman’s flow model for analyzing. To identify types of violating maxim and how violating maxim generate sense of humor, researcher applied theory proposed by Grice (1975) as guideline. The result reveals that: (1)There are four types violating maxims found in the conversations of Yoo Bro Meme Comic, namely, violating maxim of quantity, violating maxim of quality, violating maxim of relation, and violating maxim of manner. The most frequent type of violating maxim used by the subject is violating the maxim of quality which occurred 22 times 36.07% of the total violations. The second most common was violating the maxim of relation, this happened 19 times or 31.15% of all occurrences. Violating the maxim of quantity came in third with 22.95% or 14 occurrences. The least frequent type of violating maxims to be used in the conversation of Yoo Bro Meme Comic is violating maxim of manner. It happened 6 times or 9.83% of the total occurrences. (2) To generate sense of humor in yoo bro meme comic, the result showed that behind of violating maxim of quantity the speaker being uninformative, the speaker did not attempt to go truthful behind violating maxim of quality, the speaker being irrelevant behind violating maxim of relation and being unclear behind violating maxim of manne
Carniella coreana Kim & Yoo 2018, sp. nov.
No full textCarniella coreana sp. nov. ḎĘLj꼬ŔHḍ ( ljḓ ) (Fig. 1 A-K) Type materials. Holotype: ♂ from Jangheung-ri, Jangheung-eup, Cheorwon-gun, Gangwon-do, Korea (127°15 ʹ 30.5 ʺ E, 38°11 ʹ 59.8 ʺ N), 20 May 2017, S. T. Kim and S.Y. Lee. Paratype: 2♂♂, same data as holotype; 1♂, same data as holotype, 30 May 2017, S. T. Kim and S.Y. Lee. Etymology. The specific epithet is a noun in apposition derived from the Korea where the types were collected. Diagnosis. The male of newly described species is most similar to C. tsurui Ono, 2007 in the general shape of its palp, but can be easily distinguished by winding structure of embolus and broad tipped and twisted embolic apophysis. Measurements. Total length 1.10 (habitus). Carapace 0.52 long, 0.40 wide. Eye; ALE 0.04, AME 0.02, PLE 0.03, PME 0.03; AME-AME 0.02, AME-ALE 0.03, AME-PME 0.03, PME-PME 0.06, PME-PLE 0.03, ALE-PLE contiguous; AER 0.22, PER 0.23. Chelicera 0.19 long, 0.09 wide. Endite 0.08 long, 0.14 wide. Labium 0.05 long, 0.04 wide. Sternum 0.27 long, 0.30 wide. Legs; I, 1.05 (0.32, 0.36, 0.20, 0.17); II, 0.96 (0.32, 0.32, 0.14, 0.18); III, 0.79 (0.24, 0.26, 0.12, 0.17); IV, 1.04 (0.31, 0.37, 0.16, 0.20). Abdomen 0.60 long, 0.52 wide. Description. Male (holotype). Carapace: dark yellowish brown, oval, lustrous, several long setae at middle, longer than wide; head region flat, thoracic region with black marginal stripes slope gently; cervical furrow and radial furrow distinct, fovea indistinct, slightly depressed (Fig. 1A, B); clypeal outgrowth round, small warts with a short hair dorsally (Fig. 1 A-D). Eyes: ALE largest, interdistance between PME-PME farthest; PER slighly longer than AER; AER almost straight and PER recurved from front, AER recurved and PER almost straight from above. Chelicera: weak, dark yellowish brown; two promarginal teeth, lower tooth larger with small projection (Fig. 1E). Endite and labium: dark yellowish brown, endite wider than long (Fig. 1F). Sternum: dark yellowish brown, round, slightly convex, wider than long; covered densely with small warts bearing a short hair; not protrude between fourth coxae (Fig. 1F). Legs: short and thick, yellowish brown, semi-transparent, hairy without spines, no annuli; I≒ IV-II-III. Abdomen: grayish brown, globular, hairy, no particular pattern with two pairs of muscle impressions, longer than wide (Fig. 1A, B); venter grayish brown. Spinnerets: pale grayish brown, anterior spinnerets largest and posterior ones poorly developed; colulus small with a pair of setae (Fig. 1G). Male palp (Fig. H-J): tibia short and simple without spines and trichobothria; cymbium slender and semi-transparent with long transparent setae, distally modified with a finger-shaped process; embolus filate and winding with a twisted and broad tipped embolic apophysis (Fig. 1K). Ecological remarks. Present species was collected by pitfall traps at levees around traditional rice ecosystem. Distribution. Korea (new record).Published as part of Kim, Seung Tae & Yoo, Jung Sun, 2018, Carniella coreana sp. nov., a new comb-footed spider (Araneae: Theridiidae) from Korea, pp. 248-250 in Journal of Species Research 7 (3) on page 250, DOI: 10.12651/JSR.2018.7.3.248, http://zenodo.org/record/813899
Handwritten biographical information on Paulina T. McClung Merritt
No full textA handwritten biography of Paulina T. McClung Merritt by an unknown author, 1892.
Heterogeneous and tissue-specific regulation of effector T cell responses by IFN-gamma during Plasmodium berghei ANKA infection.
No full textIFN-γ and T cells are both required for the development of experimental cerebral malaria during Plasmodium berghei ANKA infection. Surprisingly, however, the role of IFN-γ in shaping the effector CD4(+) and CD8(+) T cell response during this infection has not been examined in detail. To address this, we have compared the effector T cell responses in wild-type and IFN-γ(-/-) mice during P. berghei ANKA infection. The expansion of splenic CD4(+) and CD8(+) T cells during P. berghei ANKA infection was unaffected by the absence of IFN-γ, but the contraction phase of the T cell response was significantly attenuated. Splenic T cell activation and effector function were essentially normal in IFN-γ(-/-) mice; however, the migration to, and accumulation of, effector CD4(+) and CD8(+) T cells in the lung, liver, and brain was altered in IFN-γ(-/-) mice. Interestingly, activation and accumulation of T cells in various nonlymphoid organs was differently affected by lack of IFN-γ, suggesting that IFN-γ influences T cell effector function to varying levels in different anatomical locations. Importantly, control of splenic T cell numbers during P. berghei ANKA infection depended on active IFN-γ-dependent environmental signals--leading to T cell apoptosis--rather than upon intrinsic alterations in T cell programming. To our knowledge, this is the first study to fully investigate the role of IFN-γ in modulating T cell function during P. berghei ANKA infection and reveals that IFN-γ is required for efficient contraction of the pool of activated T cells
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