Justice James D. Hopkins: Jurist, Dean, Scholar and Expert on New York Law

It is an appropriate tribute to our late Dean James D. Hopkins that this edition of Pace Law Review be dedicated to a man who many leaders of the bench, bar, and academia believe is one of the twentieth century’s greatest common law appellate jurists. Dean Hopkins, better known as Judge Hopkins, was Pace Law School’s second Dean from 1982 to 1983, an associate justice of the Supreme Court of New York, and a justice of the Appellate Division for the Second Department from 1962 to 1981. He authored hundreds of significant majority, dissenting, and concurring judicial opinions on New York law, many of which continue to be relevant to the development of substantive and procedural law in the Empire State. Hopkins’s opinions have been cited and relied on by courts throughout the nation. He is recognized and praised as a “compleat jurist,” a leading law reformer, and an outstanding scholar

Defeating the Developer\u27s Dilemma: An Online Tool for Individual Consultations

This chapter introduces an online consultation tool that helps resolve the tension that developers often experience in consultations between offering quick fixes and providing in-depth but time-consuming conceptual understanding. The tool that the Eberly Center for Teaching Excellence has developed provides instructors with concrete teaching strategies to address common teaching problems, while also educating them about the pedagogical principles informing those strategies. The tool can be used to enhance traditional face-to-face consultations or, by itself, to reach a wider faculty audience, including adjunct and off site faculty

Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification

Recognition of surgical gesture is crucial for surgical skill assessment and efficient surgery training. Prior works on this task are based on either variant graphical models such as HMMs and CRFs, or deep learning models such as Recurrent Neural Networks and Temporal Convolutional Networks. Most of the current approaches usually suffer from over-segmentation and therefore low segment-level edit scores. In contrast, we present an essentially different methodology by modeling the task as a sequential decision-making process. An intelligent agent is trained using reinforcement learning with hierarchical features from a deep model. Temporal consistency is integrated into our action design and reward mechanism to reduce over-segmentation errors. Experiments on JIGSAWS dataset demonstrate that the proposed method performs better than state-of-the-art methods in terms of the edit score and on par in frame-wise accuracy. Our code will be released later.Comment: 8 pages, 2 figures, accepted for MICCAI 201

Determining Magnetic Nanoparticle Size Distributions from Thermomagnetic Measurements

Thermomagnetic measurements are used to obtain the size distribution and anisotropy of magnetic nanoparticles. An analytical transformation method is described which utilizes temperature-dependent zero-field cooling (ZFC) magnetization data to provide a quantitative measurement of the average diameter and relative abundance of superparamagnetic nanoparticles. Applying this method to self-assembled MnAs nanoparticles in MnAs-GaAs composite films reveals a log-normal size distribution and reduced anisotropy for nanoparticles compared to bulk materials. This analytical technique holds promise for rapid assessment of the size distribution of an ensemble of superparamagnetic nanoparticles.Comment: Correction Appl. Phys. Lett. 98, 216103 (2011

Sonographically Guided Lumbar Puncture in Pediatric Patients

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135581/1/jum201332122191.pd

Aerobic Exercise during Pregnancy and Presence of Fetal-Maternal Heart Rate Synchronization

It has been shown that short-term direct interaction between maternal and fetal heart rates may take place and that this interaction is affected by the rate of maternal respiration. The aim of this study was to determine the effect of maternal aerobic exercise during pregnancy on the occurrence of fetal-maternal heart rate synchronization.In 40 pregnant women at the 36th week of gestation, 21 of whom exercised regularly, we acquired 18 min. RR interval time series obtained simultaneously in the mothers and their fetuses from magnetocardiographic recordings. The time series of the two groups were examined with respect to their heart rate variability, the maternal respiratory rate and the presence of synchronization epochs as determined on the basis of synchrograms. Surrogate data were used to assess whether the occurrence of synchronization was due to chance.In the original data, we found synchronization occurred less often in pregnancies in which the mothers had exercised regularly. These subjects also displayed higher combined fetal-maternal heart rate variability and lower maternal respiratory rates. Analysis of the surrogate data showed shorter epochs of synchronization and a lack of the phase coordination found between maternal and fetal beat timing in the original data.The results suggest that fetal-maternal heart rate coupling is present but generally weak. Maternal exercise has a damping effect on its occurrence, most likely due to an increase in beat-to-beat differences, higher vagal tone and slower breathing rates

Relationship between psychological and biological factors and physical activity and exercise behaviour in Filipino students

The aim of the present study was threefold. Firstly, it investigated whether a general measure or specific measure of motivational orientation was better in describing the relationship between motivation and exercise behaviour. Secondly, it examined the relationship between the four most popular indirect methods of body composition assessment and physical activity and exercise patterns. Thirdly, the interaction between motivation and body composition on physical activity and exercise behaviour was explored in a sample of 275 Filipino male and female students. Males were found to have higher levels of exercise whereas females had higher levels of physical activity. Furthermore, general self-motivation together with body weight and percentage body fat were found to be the best predictor of exercise behaviour whereas the tension/pressure subscale of the ‘Intrinsic Motivation Inventory’ (IMI) was the best predictor of levels of physical activity. However, significant gender differences were observed. That is, for the males only self-motivation and for the females only body weight and BMI predicted exercise behaviour. Also, tension/pressure predicted physical activity levels for the females but not the males. No inverse relationship was found between the four body composition measures and exercise and physical activity behaviour. The results support the notion that the psychobiological approach might be particularly relevant for high intensity exercise situations but also highlights some important gender differences. Finally, the results of this study emphasise the need for more cross-cultural research