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From Cambridge English Corpus
Type 2 logos were drawn in which the height of the nucleotides in the sequence column represented their frequency in proportion to their expected frequency.
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In these chapters of disguise and reversal, acts of rebellion transpire unnoticed within the voice and touch of those representing official society.
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All fiction requires strategies for structuring plot and representing time.
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The symbol is the absolute projected into the order of exteriority, and it is therefore arbitrarily represented.
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Translations of “represent”

替…行動, 作為…的代表(或代理人), 作為…的代言人…

~を代弁する, 代表する, ~を表す…

representar, equivaler a…

يَنوب عَن, يُمَثِّل…

mewakili, melambangkan, menunjukkan…

ทำหน้าที่แทน, เป็นสัญลักษณ์ของ, แสดงให้เห็น…

đại diện, tượng trưng, thể hiện…

stanowić, reprezentować, przedstawiać…

bercakap bagi pihak, melambangkan, sebagai contoh…

anlamına gelmek, ...ile eşit olmak, örneğini oluşturmak…

대표하다, (상징물로) 나타내다, -에 해당하다…

We used commonly activated regions (by masking the overlapping significant voxels) for both somatic and vicarious pain identified by the univariate analyses, namely anterior insula (aINS) and dorsal anterior cingulate cortex (dACC), as regions of interest for local pattern classification (collapsed across body site). We trained the LASSO-PCR classifier within each of these regions for somatic and vicarious pain, cross-validated signature responses withinmodality, and cross-predicted signature responses between modalities.

We found that the local patterns for somatic and vicarious pain were spatially uncorrelated (aINS: r = −0.02; dACC: r = 0.02). The somatic pain pattern in the bilateral aINS showed a linear increase for somatic pain ((27) = 7.05, p<0.0001; accuracy = 89%, p<0.0001), but did not respond to vicarious pain ((27) = −0.51, ; accuracy = 39%, ). On the other hand, the vicarious pain pattern in the bilateral aINS showed neither within-modality classification ((27) = −1.14, ; accuracy = 68%, ), nor cross-modality classification ((27) = 1.56, ; accuracy = 54%, ). The results from the dACC showed within-modality classification for somatic pain ((27) = 4.02, p<0.001; accuracy = 75%, p<0.01), but no cross-modality classification ((27) = −0.07, accuracy = 50%, ). The vicarious pain pattern in the dACC showed neither within-modality classification ((27) = −1.20, ; accuracy = 36%, ), nor cross-modality classification ((27) = −0.14, ; accuracy = 50%, ). Together, these results show that shared representations for somatic and vicarious pain representations in the aINS and dACC cannot be captured by local analyses.

Power and replicability are issues in every study, particularly when making inferences on selective activation patterns. For example, if the NPS responds to vicarious pain, but with weaker intensity [e.g., as in Hutchinson et al., ( Hutchison et al., 1999 )], is our study powered to detect differences? We address this issue in three ways.

First, we used a study design that does not require that the levels of activity for somatic and vicarious pain to be the same in order to detect similarity. Thus, if vicarious pain activated the same patterns as somatic pain, but more weakly, we would identify the representations as overlapping as long as there is some measurable increase in the NPS with high vicarious pain. However, our findings do not indicate such sharing.

Second, we use between-participant multi-system predictive , which do not rely on multiple comparisons correction—which dramatically reduces power and replicability ( Button et al., 2013 ; Yarkoni, 2009 )—for valid tests of the population codes. These analyses also allow for unbiased assessments of power to detect cross-modalitypredictive effects based on the observed strength of the within-modality predictive effects.We performed a formal power analysis for out-of-sample individuals, which indicated that in the NPS, we have 100% power (N needed for 80% power = 4) to detect vicarious pain responses that are as strong as somatic pain responses, and 79.2% power (N needed for 80% power = 29) to detect vicarious pain responses that are only 25% as strong as somatic pain responses. In the VPS, we have 100% power (N needed for 80% power = 4) to detect somatic pain responses that are as strong as vicarious pain responses, and 87.3% power (N needed for 80% power = 24) to detect somatic pain responses that are only 25% as strong as vicarious pain responses.

Third, we demonstrate direct replication in new samples with Study 3, which includes data from a separate sample, scanner, and institution, and show the dissociation of the NPS and VPS responses to somatic and vicarious pain, respectively.

We ran additional cross-classification analyses to predict stimulation site (upper versus lower limb), restricting training to only the primary somatosensory cortex. We used a support vector machine (SVM) classifierwith data that weremasked for SI SII regions [obtained from the SPM Anatomy Toolbox ( Eickhoff et al., 2005 )] and previously cited regions implicated for somatotopy for somatic pain ( Baumgärtner et al., 2010 ). The results revealed strong somatotopy for somatic pain (upper versus lower limb: 96% accuracy, p<0. 0001) and weak somatotopy for vicarious pain (79% accuracy, p<0. 01). Critically, however, cross-classification was at chance for both patterns, and the patterns themselves were spatially uncorrelated (r = 0.022), indicating that vicarious pain does not share somatotopic representations with somatic pain in the somatosensory cortex.

In the present study, somatic pain was administered to the volar surface of the left forearm and the dorsal surface of the left foot, whereas the visual stimuli for the vicarious pain session showed pictures of injury about the occur to the right hand and right foot. Importantly, the weights in contralateral hemispheres for somatic pain (right) and vicarious pain (left) were spatially uncorrelated (r=0.07). In order to further account for the difference in laterality between the two modalities, we flipped the contrast images along the x -axis for the testing set from left to right and found that the weights obtained from classifying the body sites in one modality still performed below chance on the other modality (see New casual shoes custom hand printed women canvas shoes Largest Supplier Cheap Online Grly4yR
). Together, these results reveal that somatosensory regions do not show somatotopy for vicarious pain, irrespective of the laterality of stimulation site (right for vicarious pain and left for somatic pain). However, it will be important for future research to examine the somatotopy question with greater precision using more carefully matched designs.

Meyers KE. Evaluation of hematuria in children. . 2004 Aug. 31(3):559-73, x. .

Roy S 3rd. Hematuria. . 1998 Jun. 19(6):209-12; quiz 213. .

Samuel S, Bitzan M, Zappitelli M, et al. Canadian Society of Nephrology Commentary on the 2012 KDIGO clinical practice guideline for glomerulonephritis: management of nephrotic syndrome in children. . 2014 Mar. 63(3):354-62. .

Sargent JD, Stukel TA, Kresel J, Klein RZ. Normal values for random urinary calcium to creatinine ratios in infancy. . 1993 Sep. 123(3):393-7. .

Seigel M, Lee ML. Hematuria. . 1974. 3:1.

Ward JF, Kaplan GW, Mevorach R, et al. Refined microscopic urinalysis for red blood cell morphology in the evaluation of asymptomatic microscopic hematuria in a pediatric population. . 1998 Oct. 160(4):1492-5. .

Yadin O. Hematuria in children. . 1994 Sep. 23(9):474-8, 481-5. .

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Approach to hematuria.
Nonglomerular hematuria.
Microscopy of urinary sediment. Typical appearance in non-glomerular hematuria: RBCs are uniform in size and shape but show two populations of cells because a small number have lost their hemoglobin pigment.
Microscopy of urinary sediment. Typical appearance of RBCs in glomerular hematuria: RBCs are small and vary in size, shape, and hemoglobin content.
Microscopy of urinary sediment. A cast containing numerous erythrocytes, indicating glomerulonephritis.
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Contributor Information and Disclosures
Author

Sanjeev Gulati, MD, MBBS, DNB(Peds), DM, DNB(Neph), FIPN(Australia), FICN, FRCPC(Canada) Additional Professor, Department of Nephrology, Sanjay Gandhi Post Graduate Institute of Medical Sciences; Senior Consultant in Pediatric Nephrology and Additional Director, Department of Nephrology and Transplant Medicine, Fortis Institute of Renal Sciences Transplantation, India Sanjeev Gulati, MD, MBBS, DNB(Peds), DM, DNB(Neph), FIPN(Australia), FICN, FRCPC(Canada) is a member of the following medical societies: American Society of Pediatric Nephrology , International Society of Nephrology , Royal College of Physicians and Surgeons of Canada , Indian Academy of Pediatrics Disclosure: Nothing to disclose.

Sanjeev Gulati, MD, MBBS, DNB(Peds), DM, DNB(Neph), FIPN(Australia), FICN, FRCPC(Canada)
Coauthor(s)

Deogracias Pena, MD Medical Director of Dialysis, Medical Director of Pediatric Nephrology and Transplantation, Cook Children's Medical Center; Clinical Associate Professor, Texas Tech University Health Sciences Center, Paul L Foster School of Medicine; Medical Director of Pediatric Nephrology, Florida Hospital for Children Deogracias Pena, MD is a member of the following medical societies: American Academy of Pediatrics , monroo black and beige bind long sleeve dress Discount Footlocker Finishline Outlet Recommend Buy Cheap Supply Get To Buy Online 6C6Tld
, American Society of Pediatric Nephrology Disclosure: Nothing to disclose.

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