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Institution

University at Buffalo

EducationBuffalo, New York, United States
About: University at Buffalo is a education organization based out in Buffalo, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 33773 authors who have published 63840 publications receiving 2278954 citations. The organization is also known as: UB & State University of New York at Buffalo.


Papers
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Journal ArticleDOI
TL;DR: Based on these four full-scale WWTPs evaluated, the apparent removal of organic micropollutants in wastewater is dependent on a combination of biological and physico-chemical treatment processes and operating conditions of the treatment system.

495 citations

Journal ArticleDOI
TL;DR: Children who have FASD are more prevalent among first graders in this Midwestern city than predicted by previous, popular estimates.
Abstract: OBJECTIVES: To determine the prevalence and characteristics of fetal alcohol spectrum disorders (FASD) among first grade students (6- to 7-year-olds) in a representative Midwestern US community. METHODS: From a consented sample of 70.5% of all first graders enrolled in public and private schools, an oversample of small children (≤25th percentile on height, weight, and head circumference) and randomly selected control candidates were examined for physical growth, development, dysmorphology, cognition, and behavior. The children’s mothers were interviewed for maternal risk. RESULTS: Total dysmorphology scores differentiate significantly fetal alcohol syndrome (FAS) and partial FAS (PFAS) from one another and from unexposed controls. Alcohol-related neurodevelopmental disorder (ARND) is not as clearly differentiated from controls. Children who had FASD performed, on average, significantly worse on 7 cognitive and behavioral tests and measures. The most predictive maternal risk variables in this community are late recognition of pregnancy, quantity of alcoholic drinks consumed 3 months before pregnancy, and quantity of drinking reported for the index child’s father. From the final multidisciplinary case findings, 3 techniques were used to estimate prevalence. FAS in this community likely ranges from 6 to 9 per 1000 children (midpoint, 7.5), PFAS from 11 to 17 per 1000 children (midpoint, 14), and the total rate of FASD is estimated at 24 to 48 per 1000 children, or 2.4% to 4.8% (midpoint, 3.6%). CONCLUSIONS: Children who have FASD are more prevalent among first graders in this Midwestern city than predicted by previous, popular estimates.

495 citations

Journal ArticleDOI
TL;DR: Increased relative risks for total CVA and nonhemorrhagic stroke associated with periodontitis were also seen in white men, white women, and African Americans.
Abstract: Background Periodontal disease has been found to be a potential risk factor for coronary heart disease. However, its association with cerebrovascular accidents (CVAs) is much less studied. Methods This study examines the association between periodontal disease and CVA. The study cohort comprises 9962 adults aged 25 to 74 years who participated in the First National Health and Nutrition Examination Survey and its follow-up study. Baseline periodontal status was categorized into (1) no periodontal disease, (2) gingivitis, (3) periodontitis, and (4) edentulousness. All CVAs (International Classification of Diseases, Ninth Revision [ICD-9], codes 430-438) were ascertained by hospital records for nonfatal events and death certificates for fatal events. The first CVA, nonfatal or fatal, was used to define incidence. Relative risks were estimated by hazard ratios from the Cox proportional hazard model with adjustment for several demographic variables and well-established cardiovascular risk factors. Weights were used to generate risk estimates. Results Periodontitis is a significant risk factor for total CVA and, in particular, nonhemorrhagic stroke (ICD-9, 433-434 and 436-438). Compared with no periodontal disease, the relative risks (95% confidence intervals) for incident nonhemorrhagic stroke were 1.24 (0.74-2.08) for gingivitis, 2.11 (1.30-3.42) for periodontitis, and 1.41 (0.96-2.06) for edentulousness. For total CVA, the results were 1.02 (0.70-1.48) for gingivitis, 1.66 (1.15-2.39) for periodontitis, and 1.23 (0.91-1.66) for edentulousness. Increased relative risks for total CVA and nonhemorrhagic stroke associated with periodontitis were also seen in white men, white women, and African Americans. Similar results were found for fatal CVA. Conclusion Periodontal disease is an important risk factor for total CVA and, in particular, nonhemorrhagic stroke.

494 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide additional evidence on the positive theory of accounting policy choice by combining individual accounting principles into firm income strategies, using a probit analysis where the independent variables were size, management compensation, industry concentration ratio, systematic risk, capital intensity and the total debt to total asset ratio.

494 citations

Journal ArticleDOI
TL;DR: A user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS) automatically detects frontal faces in the video stream and coded each frame with respect to 20 Action units.
Abstract: Spontaneous facial expressions differ from posed expressions in both which muscles are moved, and in the dynamics of the movement. Advances in the field of automatic facial expression measurement will require development and assessment on spontaneous behavior. Here we present preliminary results on a task of facial action detection in spontaneous facial expressions. We employ a user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS). The system automatically detects frontal faces in the video stream and coded each frame with respect to 20 Action units. The approach applies machine learning methods such as support vector machines and AdaBoost, to texture-based image representations. The output margin for the learned classifiers predicts action unit intensity. Frame-by-frame intensity measurements will enable investigations into facial expression dynamics which were previously intractable by human coding.

494 citations


Authors

Showing all 34002 results

NameH-indexPapersCitations
Rakesh K. Jain2001467177727
Julie E. Buring186950132967
Anil K. Jain1831016192151
Donald G. Truhlar1651518157965
Roger A. Nicoll16539784121
Bruce L. Miller1631153115975
David R. Holmes1611624114187
Suvadeep Bose154960129071
Ashok Kumar1515654164086
Philip S. Yu1481914107374
Hugh A. Sampson14781676492
Aaron Dominguez1471968113224
Gregory R Snow1471704115677
J. S. Keller14498198249
C. Ronald Kahn14452579809
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202388
2022363
20212,772
20202,695
20192,527
20182,500