Comparison of hydrologically based instream flow methods using a resampling technique

2007 ◽  
Vol 34 (1) ◽  
pp. 66-74 ◽  
Author(s):  
Daniel Caissie ◽  
Nassir El-Jabi ◽  
Cindie Hébert
Keyword(s):  
Sample Size ◽  
Fish Habitat ◽  
Water Withdrawal ◽  
Instream Flow ◽  
Resources Management ◽  
Instream Flows ◽  
Small Streams ◽  
Wide Range ◽  
Size Variability ◽  
The Impact

The protection of fish habitat against the impact of water extraction in rivers is a recurring problem in water resources management. As such, a wide range of methodologies is available for the calculation of instream flows. This study focuses on historical streamflow methods that rely solely on hydrometric data for instream flow evaluation. The objectives of the study are to compare different historical streamflow methods and use a jackknife resampling technique to assess the variability of instream flow estimates. Results showed that methods based on a percentage of mean annual flow (MAF) generated higher levels of instream flow protection and showed low spatial and sample size variability. Low spatial variability makes the MAF methods more suitable for calculations of instream flows for ungauged basins. The Q50 method provided relatively high levels of instream flow protection; however, spatial and sample size variability were higher than those for the MAF methods. Lastly, the results showed that some methods generated low instream flow protection (namely, the Q90, 7Q2, and 7Q10 methods), especially for small streams, and thus are not recommended for use.Key words: instream flow, aquatic habitat, water withdrawal, impact assessment.

How many particles do we need to measure aerosol mixing state?

2020 ◽  
Author(s):  
Nicole Riemer ◽  
Jessica Gasparik ◽  
Qing Ye ◽  
Matthew West ◽  
Jeff Curtis ◽  
...  
Keyword(s):  
Sample Size ◽  
Single Particle ◽  
Measurement Techniques ◽  
Chemical Species ◽  
Finite Sample ◽  
Mixing State ◽  
Wide Range ◽  
Mixing States ◽  
The Impact ◽  
Aerosol Mixing State

<p>Atmospheric aerosols are evolving mixtures of different chemical species.  The term “aerosol mixing state” is commonly used to describe how different chemical species are distributed throughout a particle population.  A population is “fully internally mixed” if each individual particle consists of same species mixtures, whereas it is fully externally mixed if each particle only contains one species. Mixing state matters for aerosol health impacts and for climate-relevant aerosol properties, such as the particles’ propensity to form cloud droplets or the aerosol optical properties.</p><p>The mixing state metric χ quantifies the degree of internal or external mixing and can be calculated based on the particles’ species mass fractions. Several field studies have used this metric to quantify mixing states for different ambient environments using sophisticated single-particle measurement techniques. Inherent to these methods is a finite number of particles, ranging from a few hundred to several thousand particles, used to estimate the mixing state metric. </p><p>This study evaluates the error that is introduced in calculating χ due to a limited particle sample size.  We used the particle-resolved model PartMC-MOSAIC to generate a scenario library that encompasses a large number of reference particle populations and that represents a wide range of mixing states. We stochastically sub-sampled these particle populations using sample sizes of 10 to 10,000 particles and recalculated χ based on the sub-samples. This procedure mimics the impact of only having a limited sample size as it is common in real-world applications. The finite sample size leads to a consistent overestimation of χ, meaning that the populations appear more internally mixed than they are in reality. These findings are experimentally confirmed using single-particle SP-AMS measurement data from the Pittsburgh area. We also determined confidence intervals of χ for our sub-sampled populations. To determine χ within a range of  +/- 10 percentage points requires a sample size of at least 1000 particles.</p><p> </p>

scholarly journals HUMAN RESOURCES MANAGEMENT OF HEI THROUGH THE FORMATION OF EFFECTIVE HR POLICY

2020 ◽  
Vol 5 (158) ◽  
pp. 58-63
Author(s):  
N. Mushchynska ◽  
N. Matvieieva
Keyword(s):  
Higher Education ◽  
Human Resources ◽  
Teacher Development ◽  
Human Resources Management ◽  
Future Research ◽  
Resources Management ◽  
Wide Range ◽  
Constructive Work ◽  
High Level ◽  
The Impact

There is a dearth of research in literature examining how people are managed in higher education institu-tions in Ukraine. This paper explores how universities manage their traditional personnel management system. The problems of formation of HR policy of the institution of higher education (HEI) in the context of its main direc-tions are investigated. In the conditions of critical lack of financial resources, the organizational bases to in-crease the efficiency of application of HRM system in HEI are considered. Our findings reveal some steps to help HEI in their long way to establish a modern HRM system. The basic perspective research directions which will allow implementing modern concepts of HRM in the academic environ-ment are proposed. Among them are rejection of the paradigm student - graduate student - teacher within one HEI and assessment of scientific and pedagogical staff through 3 blocks: effectiveness; competence; potential for teacher development. The need and implications for future research are identified. The most perspective is the role of the positive OCB (Organisational Citizenship Behaviour) as a wide range of individual actions that go beyond assigned tasks because it is associated with constructive work that employees do of their own choice and benefits the company. As an effective motivational tool could be used the perception of the impact of different types of re-search and learning support by different categories of participants in the educational and scientific environment. It is also recommended to pay special attention to the creation of a high level of employee loyalty. The insights from this study would be of value to the management of universities. Keywords: human resources policy (HR policy), human resources management (HRM), institution of higher education (HEI).

scholarly journals Simple study designs in ecology produce inaccurate estimates of biodiversity responses

2019 ◽  
Author(s):  
Alec P. Christie ◽  
Tatsuya Amano ◽  
Philip A. Martin ◽  
Gorm E. Shackelford ◽  
Benno I. Simmons ◽  
...  
Keyword(s):  
Environmental Impact ◽  
Sample Size ◽  
Study Design ◽  
Evidence Synthesis ◽  
List Type ◽  
Robust Designs ◽  
Wide Range ◽  
Randomised Controlled ◽  
Study Designs ◽  
The Impact

AbstractEcologists use a wide range of study designs to estimate the impact of interventions or threats but there are no quantitative comparisons of their accuracy. For example, while it is accepted that simpler designs, such as After (sampling sites post-impact without a control), Before-After (BA) and Control-Impact (CI), are less robust than Randomised Controlled Trials (RCT) and Before-After Control-Impact (BACI) designs, it is not known how much less accurate they are.We simulate a step-change response of a population to an environmental impact using empirically-derived estimates of the major parameters. We use five ecological study designs to estimate the effect of this impact and evaluate each one by determining the percentage of simulations in which they accurately estimate the direction and magnitude of the environmental impact. We also simulate different numbers of replicates and assess several accuracy thresholds.We demonstrate that BACI designs could be 1.1-1.5 times more accurate than RCTs, 2.9-4.1 times more accurate than BA, 3.8-5.6 times more accurate than CI, and 6.8-10.8 times more accurate than After designs, when estimating to within ±30% of the true effect (depending on the sample size). We also found that increasing sample size substantially increases the accuracy of BACI designs but only increases the precision of simpler designs around a biased estimate; only by using more robust designs can accuracy increase. Modestly increasing replication of both control and impact sites also increased the accuracy of BACI designs more than substantially increasing replicates in just one of these groups.We argue that investment into using more robust designs in ecology, where possible, is extremely worthwhile given the inaccuracy of simpler designs, even when using large sample sizes. Based on our results we propose a weighting system that quantitatively ranks the accuracy of studies based on their study design and the number of replicates used. We hope these ‘accuracy weights’ enable researchers to better account for study design in evidence synthesis when assessing the reliability of a range of studies using a variety of designs.

scholarly journals Power and sample size calculation for stepped-wedge designs with discrete outcomes

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Fan Xia ◽  
James P. Hughes ◽  
Emily C. Voldal ◽  
Patrick J. Heagerty
Keyword(s):  
Sample Size ◽  
Health Care Systems ◽  
Sample Size Calculation ◽  
Analytical Formula ◽  
Power Calculation ◽  
Process Of Care ◽  
Stepped Wedge ◽  
Stat Assoc ◽  
Wide Range ◽  
The Impact

Abstract Background Stepped-wedge designs (SWD) are increasingly used to evaluate the impact of changes to the process of care within health care systems. However, to generate definitive evidence, a correct sample size calculation is crucial to ensure such studies are properly powered. The seminal work of Hussey and Hughes (Contemp Clin Trials 28(2):182–91, 2004) provides an analytical formula for power calculations with normal outcomes using a linear model and simple random effects. However, minimal development and evaluation have been done for power calculation with non-normal outcomes on their natural scale (e.g., logit, log). For example, binary endpoints are common, and logistic regression is the natural multilevel model for such clustered data. Methods We propose a power calculation formula for SWD with either normal or non-normal outcomes in the context of generalized linear mixed models by adopting the Laplace approximation detailed in Breslow and Clayton (J Am Stat Assoc 88(421):9–25, 1993) to obtain the covariance matrix of the estimated parameters. Results We compare the performance of our proposed method with simulation-based sample size calculation and demonstrate its use on a study of patient-delivered partner therapy for STI treatment and a study that assesses the impact of providing additional benchmark prevalence information in a radiologic imaging report. To facilitate adoption of our methods we also provide a function embedded in the R package “swCRTdesign” for sample size and power calculation for multilevel stepped-wedge designs. Conclusions Our method requires minimal computational power. Therefore, the proposed procedure facilitates rapid dynamic updates of sample size calculations and can be used to explore a wide range of design options or assumptions.

THE IMPACT OF LEADERSHIP PRACTICES TO TEAM MEMBERS’ SATISFACTION

2009 ◽  
Vol 8 (1) ◽  
Author(s):  
Chalimah .
Keyword(s):  
Conflict Resolution ◽  
Leadership Practices ◽  
Hotel Industry ◽  
Leader Behavior ◽  
Team Leader ◽  
Shop Floor ◽  
Team Members ◽  
Top Executives ◽  
Wide Range ◽  
The Impact

eamwork is becoming increasingly important to wide range of operations. It applies to all levels of the company. It is just as important for top executives as it is to middle management, supervisors and shop floor workers. Poor teamwork at any level or between levels can seriously damage organizational effectiveness. The focus of this paper was therefore to examine whether leadership practices consist of team leader behavior, conflict resolution style and openness in communication significantly influenced the team member’s satisfaction in hotel industry. Result indicates that team leader behavior and the conflict resolution style significantly influenced team member satisfaction. It was surprising that openness in communication did not affect significantly to the team members’ satisfaction.

Stress, anxiety, depression and burnout in frontline health care workers during COVID-19 pandemic: a brief systematic review and new data from Russia

2021 ◽  
Author(s):  
Ekaterina Mosolova ◽  
Dmitry Sosin ◽  
Sergey Mosolov
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Female Gender ◽  
Assessment Tools ◽  
Care Workers ◽  
Younger Age ◽  
Wide Range ◽  
Associated Risk Factors ◽  
Anxiety Depression ◽  
The Impact

During the COVID-19 pandemic, healthcare workers (HCWs) have been subject to increased workload while also exposed to many psychosocial stressors. In a systematic review we analyze the impact that the pandemic has had on HCWs mental state and associated risk factors. Most studies reported high levels of depression and anxiety among HCWs worldwide, however, due to a wide range of assessment tools, cut-off scores, and number of frontline participants in the studies, results were difficult to compare. Our study is based on two online surveys of 2195 HCWs from different regions of Russia during spring and autumn epidemic outbreaks revealed the rates of anxiety, stress, depression, emotional exhaustion and depersonalization and perceived stress as 32.3%, 31.1%, 45.5%, 74.2%, 37.7% ,67.8%, respectively. Moreover, 2.4% of HCWs reported suicidal thoughts. The most common risk factors include: female gender, nurse as an occupation, younger age, working for over 6 months, chronic diseases, smoking, high working demands, lack of personal protective equipment, low salary, lack of social support, isolation from families, the fear of relatives getting infected. These results demonstrate the need for urgent supportive programs for HCWs fighting COVID-19 that fall into higher risk factors groups.

A MODELING SYSTEM FOR CLIMATE CHANGE RISK ASSESSMENT, MANAGEMENT AND HEDGING IN COASTAL AREAS

2017 ◽  
Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Coastal Areas ◽  
Mitigation Strategies ◽  
System Structure ◽  
The Arctic ◽  
Risk Modeling ◽  
Wide Range ◽  
Adverse Weather ◽  
The Impact

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.

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