Michigan State University

About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.

Synthesizing standardized mean‐change measures

Abstract: A new approach is presented for the meta-analysis of data from pre-test-post-test designs. With this approach, data from studies using different designs may be compared directly and studies without control groups need not be omitted. The approach is based on a ‘standardized mean-change’ measure, computed for each sample within a study, and involves analysis of the standardized mean changes and differences in the standardized mean changes. Analyses are illustrated using results of studies of the effectiveness of mental practice on motor-skill development.

Face Spoof Detection With Image Distortion Analysis

Abstract: Automatic face recognition is now widely used in applications ranging from deduplication of identity to authentication of mobile payment. This popularity of face recognition has raised concerns about face spoof attacks (also known as biometric sensor presentation attacks), where a photo or video of an authorized person’s face could be used to gain access to facilities or services. While a number of face spoof detection techniques have been proposed, their generalization ability has not been adequately addressed. We propose an efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA). Four different features (specular reflection, blurriness, chromatic moment, and color diversity) are extracted to form the IDA feature vector. An ensemble classifier, consisting of multiple SVM classifiers trained for different face spoof attacks (e.g., printed photo and replayed video), is used to distinguish between genuine (live) and spoof faces. The proposed approach is extended to multiframe face spoof detection in videos using a voting-based scheme. We also collect a face spoof database, MSU mobile face spoofing database (MSU MFSD), using two mobile devices (Google Nexus 5 and MacBook Air) with three types of spoof attacks (printed photo, replayed video with iPhone 5S, and replayed video with iPad Air). Experimental results on two public-domain face spoof databases (Idiap REPLAY-ATTACK and CASIA FASD), and the MSU MFSD database show that the proposed approach outperforms the state-of-the-art methods in spoof detection. Our results also highlight the difficulty in separating genuine and spoof faces, especially in cross-database and cross-device scenarios.

Measuring stress in wildlife: techniques for quantifying glucocorticoids

Abstract: Stress responses play a key role in allowing animals to cope with change and challenge in the face of both environmental certainty and uncertainty. Measurement of glucocorticoid levels, key elements in the neuroendocrine stress axis, can give insight into an animal’s well-being and can aid understanding ecological and evolutionary processes as well as conservation and management issues. We give an overview of the four main biological samples that have been utilized [blood, saliva, excreta (feces and urine), and integumentary structures (hair and feathers)], their advantages and disadvantages for use with wildlife, and some of the background and pitfalls that users must consider in interpreting their results. The matrix of choice will depend on the nature of the study and of the species, on whether one is examining the impact of acute versus chronic stressors, and on the degree of invasiveness that is possible or desirable. In some cases, more than one matrix can be measured to achieve the same ends. All require a significant degree of expertise, sometimes in obtaining the sample and always in extracting and analyzing the glucocorticoid or its metabolites. Glucocorticoid measurement is proving to be a powerful integrator of environmental stressors and of an animal’s condition.

The role of functional traits and trade‐offs in structuring phytoplankton communities: scaling from cellular to ecosystem level

Abstract: Trait-based approaches to community structure are increasingly used in terrestrial ecology. We show that such an approach, augmented by a mechanistic analysis of trade-offs among functional traits, can be successfully used to explain community composition of marine phytoplankton along environmental gradients. Our analysis of literature on major functional traits in phytoplankton, such as parameters of nutrient-dependent growth and uptake, reveals physiological trade-offs in species abilities to acquire and utilize resources. These trade-offs, arising from fundamental relations such as cellular scaling laws and enzyme kinetics, define contrasting ecological strategies of nutrient acquisition. Major groups of marine eukaryotic phytoplankton have adopted distinct strategies with associated traits. These diverse strategies of nutrient utilization can explain the distribution patterns of major functional groups and size classes along nutrient availability gradients.

What Are We Weighting For

Abstract: :When estimating population descriptive statistics, weighting is called for if needed to make the analysis sample representative of the target population. With regard to research directed instead at estimating causal effects, we discuss three distinct weighting motives: (1) to achieve precise estimates by correcting for heteroskedasticity; (2) to achieve consistent estimates by correcting for endogenous sampling; and (3) to identify average partial effects in the presence of unmodeled heterogeneity of effects. In each case, we find that the motive sometimes does not apply in situations where practitioners often assume it does.