Using Geographic Information Systems to Identify Habitat for the Golden-winged Warbler (Vermivora chrysoptera) in Western New York

The Golden-winged Warbler (Vermivora chrysoptera) is a passerine species whose populations have decreased internationally by approximately 66 percent since the 1960s, and by approximately 50 percent in New York. Major causes for declines are from loss of shrubland habitat and through hybridization with the Blue-winged Warbler (Vermivora cyanoptera). This study utilized published data and expert opinion on Golden-winged Warbler (GWWA) habitat requirements to create habitat suitability models within the Western Finger Lakes Region of NY (NYSDEC Region 8) using a geographic information system. This region is an important area for migratory birds and is previously unstudied for GWWA. The concentration of potential GWWA habitat was identified within the central part of the study area, dubbed the “Central Band”, comprising of areas within Livingston, Ontario, Schuyler, Seneca, Steuben, and Yates Counties. Sighting data from the Breeding Bird Survey (BBS) and Cornell Lab of Ornithology’s eBird Program (eBird) were utilized to test for the presence of GWWA within predicted habitat sites. BBS data were useful as an indicator of the model’s effectiveness, with two-thirds of BBS routes containing GWWA sightings intersecting predicted prime habitat sites. Cornell’s eBird sighting data were less effective as an indicator of the model’s accuracy, as available eBird data may contain spatial bias through under-reporting by fewer birders in areas of high habitat concentrations. This study also analyzed proximity of GWWA habitat to public and privately managed lands, offering specific locations where GWWA conservation plans, like NYSDEC’s Young Tree Initiative, could effectively be implemented with a focus on breeding bird habitat. GWWA habitat conservation is significant, as their habitat is also utilized by other species of conservation concern, such as American Woodcock (Scolopax minor) and Ruffed Grouse (Bonasa umbellus), making GWWA a type of umbrella species within early successional habitat

Kilobot: A Robotic Module for Demonstrating Behaviors in a Large Scale (2102^{10} Units) Collective

A collective of robots can together complete a task that is beyond the capabilities of any of its individual robots. One property of a robotic collective that allows it to complete such a task is the shape of the collective. This paper presents Kilobot, a simple modular robot designed to work in a collective to self-assemble and self-heal that collective’s shape. In previous work, an algorithm is given that allows a simulated collective of robots to self-assemble and self-heal a desired shape, keeping the shape sized proportional to the number of robots in the collective. In this abstract, the current work of producing a robotic collective that can demonstrate that algorithm is presented.Engineering and Applied Science

Injuries in the Chinese Arena Football League: American Versus Chinese Players.

Background: Arena football is an indoor version of American football played in indoor arenas on a smaller field with 8 players per team. Only 1 study has evaluated injury rates in arena football, and no study had compared 2 distinct cohorts of players. Purpose/Hypothesis: The purpose of this study was to evaluate and compare injury rates in American versus Chinese athletes in the Chinese Arena Football League. Our hypothesis was that the rate of significant injuries (≥7 days of time lost from play) would be statistically significantly higher in Chinese athletes. Study Design: Cohort study; Level of evidence, 2. Methods: Each of the 6 teams included in this study comprised 11 American and 11 Chinese athletes, for a total of 132 included athletes (66 Chinese, 66 American). All players stayed in the same hotel, trained and played in the same facilities, and were covered by the same medical staff. A total of 18 games were played consecutively in 6 cities from October 1 to November 6, 2016. At least 4 Chinese players had to be on the field for each team at all times during game play. Results: American athletes were significantly older, taller, and heavier than Chinese athletes. The total exposure was 759 athlete-hours, and there were 80 reported injuries, with 74 (92.5%) occurring during games (overall injury rate, 105.4 injuries per 1000 athlete-hours). For American athletes, the exposure was 387 athlete-hours with 38 injuries observed, and the injury rate was 98.2 injuries per 1000 athlete-hours. For Chinese athletes, the exposure was 372 athlete-hours with 42 injuries observed, and the injury rate was 112.9 injuries per 1000 athlete-hours. There was no statistically significant difference in exposure or overall injury rate between American and Chinese athletes. The rate of significant injuries was 30.3 per 1000 athlete-hours; there were 17 such injuries in Chinese athletes compared with 6 such injuries for American athletes. The rate of significant injuries was 45.7 (Chinese) and 15.5 (American) injuries per 1000 athlete-hours, and the relative risk for Chinese versus American athletes for significant injuries was 3.0 (95% CI, 1.2-7.8; Conclusion: The overall risk of injuries was similar between Chinese and American athletes, but Chinese athletes showed statistically higher rates of significant injuries than their American counterparts. Years of experience was the only factor that was associated with severe injuries. As professional sports become more global, medical personnel must take into account the distinct differences and levels of experience between the national and international professional athletes. The results of this study will be used to make recommendations to develop preventive training measures, including techniques to improve tackling

Genocide and the Modern Age: Etiology and Case Studies of Mass Death

https://surface.syr.edu/books/1023/thumbnail.jp

Fall‐Associated Difficulty with Activities of Daily Living in Functionally Independent Individuals Aged 65 to 69 in the United States: A Cohort Study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96257/1/jgs12071.pd

Regenerative Patterning in Swarm Robots: Mutual Benefits of Research in Robotics and Stem Cell Biology

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering