scholarly journals Mismatch Between Risk and Response May Amplify Lethal and Non-lethal Effects of Humans on Wild Animal Populations

2021 ◽  
Vol 9 ◽  
Author(s):  
Justine A. Smith ◽  
Kaitlyn M. Gaynor ◽  
Justin P. Suraci
Keyword(s):  
Human Activity ◽  
Human Disturbance ◽  
Stimulus Type ◽  
Scale Up ◽  
Unintended Consequences ◽  
Wild Animal ◽  
Future Research ◽  
Type I ◽  
Lethal Effects ◽  
Animal Populations

Human activity has rapidly transformed the planet, leading to declines of animal populations around the world through a range of direct and indirect pathways. Humans have strong numerical effects on wild animal populations, as highly efficient hunters and through unintentional impacts of human activity and development. Human disturbance also induces costly non-lethal effects by changing the behavior of risk-averse animals. Here, we suggest that the unique strength of these lethal and non-lethal effects is amplified by mismatches between the nature of risk associated with anthropogenic stimuli and the corresponding response by wild animals. We discuss the unique characteristics of cues associated with anthropogenic stimuli in the context of animal ecology and evolutionary history to explore why and when animals fail to appropriately (a) detect, (b) assess, and (c) respond to both benign and lethal stimuli. We then explore the costs of over-response to a benign stimulus (Type I error) and under-response to a lethal stimulus (Type II error), which can scale up to affect individual fitness and ultimately drive population dynamics and shape ecological interactions. Finally, we highlight avenues for future research and discuss conservation measures that can better align animal perception and response with risk to mitigate unintended consequences of human disturbance.

Aviation and the Microbiome

2020 ◽  
Vol 91 (8) ◽  
pp. 651-661
Author(s):  
Joshua T. Davis ◽  
Hilary A. Uyhelji
Keyword(s):  
Psychological Health ◽  
Aviation Safety ◽  
Autism Spectrum ◽  
Unintended Consequences ◽  
Microbial Colonization ◽  
Future Research ◽  
Aerospace Medicine ◽  
Medical Certification ◽  
Physical Disorders ◽  
The Impact

INTRODUCTION: Although the impact of microorganisms on their hosts has been investigated for decades, recent technological advances have permitted high-throughput studies of the collective microbial genomes colonizing a host or habitat, also known as the microbiome. This literature review presents an overview of microbiome research, with an emphasis on topics that have the potential for future applications to aviation safety. In humans, research is beginning to suggest relationships of the microbiome with physical disorders, including type 1 and type 2 diabetes mellitus, cardiovascular disease, and respiratory disease. The microbiome also has been associated with psychological health, including depression, anxiety, and the social complications that arise in autism spectrum disorders. Pharmaceuticals can alter microbiome diversity, and may lead to unintended consequences both short and long-term. As research strengthens understanding of the connections between the microbiota and human health, several potential applications for aerospace medicine and aviation safety emerge. For example, information derived from tests of the microbiota has potential future relevance for medical certification of pilots, accident investigation, and evaluation of fitness for duty in aerospace operations. Moreover, air travel may impact the microbiome of passengers and crew, including potential impacts on the spread of disease nationally and internationally. Construction, maintenance, and cleaning regimens that consider the potential for microbial colonization in airports and cabin environments may promote the health of travelers. Altogether, the mounting knowledge of microbiome effects on health presents several opportunities for future research into how and whether microbiome-based insights could be used to improve aviation safety.Davis JT, Uyhelji HA. Aviation and the microbiome. Aerosp Med Hum Perform. 2020; 91(8):651–661.

Stem Cell-Based Therapies: A New Ray of Hope for Diabetic Patients

2019 ◽  
Vol 14 (2) ◽  
pp. 146-151 ◽  
Author(s):  
Junaid Khan ◽  
Amit Alexander ◽  
Mukta Agrawal ◽  
Ajazuddin ◽  
Sunil Kumar Dubey ◽  
...  
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Drug Therapy ◽  
Type I Diabetes ◽  
Embryonic Stem ◽  
Health Concern ◽  
Future Research ◽  
Diabetic Patients ◽  
Successful Implementation ◽  
Type I

Diabetes and its complications are a significant health concern throughout the globe. There are physiological differences in the mechanism of type-I and type-II diabetes and the conventional drug therapy as well as insulin administration seem to be insufficient to address the problem at large successfully. Hypoglycemic swings, frequent dose adjustments and resistance to the drug are major problems associated with drug therapy. Cellular approaches through stem cell based therapeutic interventions offer a promising solution to the problem. The need for pancreatic transplants in case of Type- I diabetes can also be by-passed/reduced due to the formation of insulin producing β cells via stem cells. Embryonic Stem Cells (ESCs) and induced Pluripotent Stem Cells (iPSCs), successfully used for generating insulin producing β cells. Although many experiments have shown promising results with stem cells in vitro, their clinical testing still needs more exploration. The review attempts to bring into light the clinical studies favoring the transplantation of stem cells in diabetic patients with an objective of improving insulin secretion and improving degeneration of different tissues in response to diabetes. It also focuses on the problems associated with successful implementation of the technique and possible directions for future research.

xtgeebcv: A command for bias-corrected sandwich variance estimation for GEE analyses of cluster randomized trials

2020 ◽  
Vol 20 (2) ◽  
pp. 363-381 ◽  
Author(s):  
John A. Gallis ◽  
Fan Li ◽  
Elizabeth L. Turner
Keyword(s):  
Randomized Trials ◽  
Variance Estimation ◽  
Public Health Education ◽  
Standard Errors ◽  
Future Research ◽  
Type I ◽  
Cluster Randomized Trials ◽  
Finite Sample ◽  
Individual Level ◽  
Cluster Randomized

Cluster randomized trials, where clusters (for example, schools or clinics) are randomized to comparison arms but measurements are taken on individuals, are commonly used to evaluate interventions in public health, education, and the social sciences. Analysis is often conducted on individual-level outcomes, and such analysis methods must consider that outcomes for members of the same cluster tend to be more similar than outcomes for members of other clusters. A popular individual-level analysis technique is generalized estimating equations (GEE). However, it is common to randomize a small number of clusters (for example, 30 or fewer), and in this case, the GEE standard errors obtained from the sandwich variance estimator will be biased, leading to inflated type I errors. Some bias-corrected standard errors have been proposed and studied to account for this finite-sample bias, but none has yet been implemented in Stata. In this article, we describe several popular bias corrections to the robust sandwich variance. We then introduce our newly created command, xtgeebcv, which will allow Stata users to easily apply finite-sample corrections to standard errors obtained from GEE models. We then provide examples to demonstrate the use of xtgeebcv. Finally, we discuss suggestions about which finite-sample corrections to use in which situations and consider areas of future research that may improve xtgeebcv.

scholarly journals High-growth firms and scale-ups: a review and research agenda

2019 ◽  
Vol 54 (1) ◽  
pp. 96-111
Author(s):  
Guilherme Fowler A. Monteiro
Keyword(s):  
Research Agenda ◽  
Design Methodology ◽  
Scale Up ◽  
High Growth ◽  
Levels Of Analysis ◽  
Future Research ◽  
Content Type ◽  
Growth Firms ◽  
Different Levels

Purpose This paper aims to conduct an extensive review and advances a framework for the literature of high-growth firms (HGFs) and scale-ups. Design/methodology/approach This paper takes the form of a literature review. Findings The author makes three specific contributions. First, he presents a broad review of high growth in firms, shedding light on the different levels of analysis. Second, he advances a characterization of scale-up companies to enable a better basis for discussion. Finally, he identifies gaps in the existing literature and suggest paths for future research. Originality/value The interest in HGFs and those referred to as scale-ups has increased considerably in recent years. Despite this trend, existing studies still have conceptual divergences and a gap separating theoretical inputs from the actual experiences of entrepreneurs.

scholarly journals Build a Better Bootstrap and the RAWR Shall Beat a Random Path to Your Door: Phylogenetic Support Estimation Revisited

2020 ◽  
Author(s):  
Wei Wang ◽  
Kevin J. Liu
Keyword(s):  
State Of The Art ◽  
Bootstrap Method ◽  
Parametric Method ◽  
Open Data ◽  
Bootstrap Support ◽  
Future Research ◽  
Evolutionary Divergence ◽  
Type I ◽  
Support Estimation ◽  
Non Parametric

AbstractMotivationThe standard bootstrap method is used throughout science and engineering to perform general-purpose non-parametric resampling and re-estimation. Among the most widely cited and widely used such applications is the phylogenetic bootstrap method, which Felsenstein proposed in 1985 as a means to place statistical confidence intervals on an estimated phylogeny (or estimate “phylogenetic support”). A key simplifying assumption of the bootstrap method is that input data are independent and identically distributed (i.i.d.). However, the i.i.d. assumption is an over-simplification for biomolecular sequence analysis, as Felsenstein noted. Special-purpose fully parametric or semi-parametric methods for phylogenetic support estimation have since been introduced, some of which are intended to address this concern.ResultsIn this study, we introduce a new sequence-aware non-parametric resampling technique, which we refer to as RAWR (“RAndom Walk Resampling”). RAWR consists of random walks that synthesize and extend the standard bootstrap method and the “mirrored inputs” idea of Landan and Graur. We apply RAWR to the task of phylogenetic support estimation. RAWR’s performance is compared to the state of the art using synthetic and empirical data that span a range of dataset sizes and evolutionary divergence. We show that RAWR support estimates offer comparable or typically superior type I and type II error compared to phylogenetic bootstrap support as well as GUIDANCE2, a state-of-the-art purpose-built fully parametric method. Additional simulation study experiments help to clarify practical considerations regarding RAWR support estimation. We conclude with thoughts on future research directions and the untapped potential for sequence-aware non-parametric resampling and re-estimation.AvailabilityData and software are publicly available under open-source software and open data licenses at: https://gitlab.msu.edu/liulab/[email protected]

scholarly journals Inclusive education’s promises and trajectories: Critical notes about future research on a venerable idea

2016 ◽  
Vol 24 ◽  
pp. 43 ◽  
Author(s):  
Alfredo J. Artiles ◽  
Elizabeth B. Kozleski
Keyword(s):  
Inclusive Education ◽  
Strategic Alliances ◽  
Multiple Identities ◽  
Research Literature ◽  
Unintended Consequences ◽  
Future Research ◽  
Educational Systems ◽  
Conceptual Clarity ◽  
Education Agenda ◽  
Critical Notes

The purpose of this article is to offer critical notes on inclusive education research in the U.S. We discuss issues germane to conceptual clarity and the ways in which inclusive education interacts with reforms that share equity goals, noting disruptions and unintended consequences that arise at the nexus of these reforms. In addition, we identify enduring challenges and paradoxes in this research literature. These include sampling issues, an emphasis on where students are placed as a proxy for inclusive education vis-à-vis inclusive education as the transformation of educational systems, the ways in which outcome measures have been examined in this research, and the need for and challenges of building strategic alliances that could advance an inclusive education agenda. We conclude with reflections and suggestions for a future research program that include sharpening inclusion’s identity, attending to the fluid nature of ability differences and students’ multiple identities, broadening the unit of analysis to systems of activities, and documenting processes and outcomes.

Digital technologies, online learning and lesson study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rongjin Huang ◽  
Nina Helgevold ◽  
Jean Lang
Keyword(s):  
Online Learning ◽  
Lesson Study ◽  
Teaching And Learning ◽  
Scale Up ◽  
Extended Period ◽  
International Perspective ◽  
Future Research ◽  
Content Type ◽  
Equity Issues ◽  
Positive Effects

PurposeFinding ways in which technology can be used to modify, strengthen, scale up and sustain lesson study (LS) is an emerging field of research. It has become even more important due to a pandemic leading to teacher and student learning being delivered online. The purpose of this paper is to present research findings about experiences of online LS and identify issues for further research.Design/methodology/approachA systematic search of articles from 2010 to 2020 identified 13 relevant papers, and through analysis, some major themes were identified. All papers in the special issue were synthesized from the lens of the identified themes; finally, further directions are discussed.FindingsIn general, various online LS models were found to have features that resulted in positive effects on teaching and learning, but, whilst several characteristics of effective online learning were identified, some studies also highlighted issues.Research limitations/implicationsThere is a need for larger scale projects over an extended period to assess the effectiveness of online LS. Future research focused on carrying out learning study online as well as consideration of equity issues associated with online LS are also suggested.Originality/valueThe studies presented in this issue address the opportunities and challenges of conducting online LS during a pandemic and beyond. Together, the literature review and contributory papers provide an international perspective of using online LS and identify important issues for further research.

Long-Term Outcomes in Pockets of Effectiveness

2020 ◽  
pp. 187-201
Author(s):  
Erin Metz McDonnell
Keyword(s):  
Scale Up ◽  
The State ◽  
Future Research ◽  
Long Term Outcomes ◽  
Organizational Reform ◽  
Future Outcomes

This chapter describes what happened to the positive cases in this study over the longer term. By examining the outcomes observed in the selected cases, the chapter sheds some speculative light on whether the bureaucratic ethos can survive the departure of the niche founder, and sketches a range of possible outcomes for whether niches can scale up or possibly even diffuse more broadly. However, because the cases studied so far in this work have been selected instead of being randomly sampled, they cannot definitively show what will happen or even what is likely to happen as pockets of effectiveness within the state mature. They do however, sketch a range of future outcomes that are possible, laying a foundation for future research to analyze the conditions under which particular long-term outcomes do or do not emerge. The cases collectively illuminate some of the promise and pitfalls of interstitiality as a force for organizational reform more broadly throughout the state.

Alignment for Advanced Machine Learning Systems

2020 ◽  
pp. 342-382
Author(s):  
Jessica Taylor ◽  
Eliezer Yudkowsky ◽  
Patrick LaVictoire ◽  
Andrew Critch
Keyword(s):  
Machine Learning ◽  
Side Effects ◽  
Objective Function ◽  
Unintended Consequences ◽  
Learning Systems ◽  
Large Impact ◽  
Future Research ◽  
Objective Functions ◽  
Research Areas ◽  
The Right

This chapter surveys eight research areas organized around one question: As learning systems become increasingly intelligent and autonomous, what design principles can best ensure that their behavior is aligned with the interests of the operators? The chapter focuses on two major technical obstacles to AI alignment: the challenge of specifying the right kind of objective functions and the challenge of designing AI systems that avoid unintended consequences and undesirable behavior even in cases where the objective function does not line up perfectly with the intentions of the designers. The questions surveyed include the following: How can we train reinforcement learners to take actions that are more amenable to meaningful assessment by intelligent overseers? What kinds of objective functions incentivize a system to “not have an overly large impact” or “not have many side effects”? The chapter discusses these questions, related work, and potential directions for future research, with the goal of highlighting relevant research topics in machine learning that appear tractable today.

The emergence of tolerance of human disturbance in Neotropical birds

2019 ◽  
Vol 36 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Piotr Tryjanowski ◽  
Jakub Z. Kosicki ◽  
Martin Hromada ◽  
Peter Mikula
Keyword(s):  
North America ◽  
Human Disturbance ◽  
Escape Response ◽  
Bird Species ◽  
Small Scale ◽  
Behavioural Plasticity ◽  
Mato Grosso ◽  
Animal Populations ◽  
History Of ◽  
Rapid Emergence

AbstractAnimals living close to human settlements more often experience disturbance, but also reduced predation risk. Because an escape response is costly, behavioural adjustments of animals in terms of increased tolerance of humans occurs and is often reported in the literature. However, most such studies have been conducted in and around long-existing cities in Europe and North America, on well-established animal populations. Here, we investigate the degree of tolerance of human disturbance across 132 bird species occurring in disturbed (small farms) and undisturbed (intact wetlands and grasslands) areas in Pantanal, Mato Grosso (Brazil), a region with only a very recent history of human-induced disturbance. We found a clear across-species trend toward higher tolerance of human disturbance in birds near farms when compared with birds in wild areas. Such a flexible and perhaps also rapid emergence of tolerance when facing small-scale and very recent human disturbance presumably involves learning and might be attributed to behavioural plasticity. The ability of birds to modify their degree of tolerance of human disturbance may play a key role in the facilitation of wildlife–human coexistence.

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