Stand-alone Program Research Articles

Effectiveness of evidence-based medicine on knowledge, attitudes, and practices of family planning providers: a randomized experiment in Jordan.

BackgroundProvider misconceptions and biases about contraceptive methods are major barriers to family planning access for women in low- and middle-income countries, including Jordan. Evidence-Based Medicine (EBM) programs aim to reduce biases and misconceptions by providing doctors with the most up-to-date scientific evidence on contraceptive methods.MethodsWe evaluate the effects of an EBM program conducted in Jordan on private providers’ knowledge, attitudes, and practices. Family planning providers randomly assigned to a treatment group were invited to attend a roundtable seminar on the injectable contraceptive Depot Medroxy Progesterone Acetate (DMPA), and to receive two 15 min one-on-one educational visits that reinforce the messages from the seminar.ResultsThere was low compliance with the EBM program. The study fails to detect an impact on providers’ knowledge of DMPA’s side effects or on reported clinical practices. There is suggestive evidence of a positive impact on providers’ attitudes toward and confidence in prescribing the contraceptive to their patients. There is also evidence of positive selection into program participation.ConclusionsWe conclude that EBM may not be effective as a stand-alone program targeting a family planning method with a high level of provider and consumer bias. Evidence of positive selection into program participation underscores the importance of randomization to avoid overestimating the true effects of interventions.Trial registrationAEA RCT Registry, AEARCTR0000539, 11/3/2014Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-015-1101-z) contains supplementary material, which is available to authorized users.

Ratiocalc: Software for processing data from multicomponent volcanic gas analyzers

Portable gas analyzers have become a powerful tool for the real-time monitoring of volcanic gas composition over the last decade. Gas analyzers make it possible to retrieve in real-time the chemical composition of a fumarole system or a plume in an open-conduit volcano via periodic field-deployments or at permanent stations. The core of a multicomponent volcanic gas analyzer (MultiGAS) consists of spectroscopic and electrochemical sensors that are used to determine the concentrations of the most abundant volcanic gases (H2O, CO2, SO2, H2S, H2, CO and HCl) in a diluted plume and their mutual molar ratios. Processing such data is often difficult due to the high sensitivity of the sensors to environmental conditions such as humidity, gas concentrations, and pressure, with all involving occasional instrumental drift. Analyses require accurate and time-consuming processing by an operator. This paper presents a stand-alone program for the processing of chemical data obtained using the MultiGAS, called Ratiocalc. The Ratiocalc program has a user-friendly interface to enable volcanologists to process large datasets in a simple and rapid manner, thereby reducing the processing time associated with volcano monitoring and surveying.

What do customers get and give in return for loyalty program membership?

A successful loyalty program (LP) represents the firms' investment in long-term relationships with their customers. However, to be effective LPs must be perceived as valuable by customers. The purpose of this study is to examine the different types of value customers derive from LP membership and examine the relationship between program value, loyalty to the program, and loyalty to the brand (firm). Further, we examine the effect of program and brand loyalty on behavioral responses, including share of wallet, share of purchase, word of mouth, and willingness to pay more. The moderating effect of program customization and the duration of the customer's LP membership on the relationship between loyalty to the program and loyalty to the brand is also studied. Using a sample of 628 respondents drawn from the two largest stand-alone retail loyalty programs in Australia we find that LP value consists of six primary constructs which drive loyalty. Specifically, we find that value in the form of reward attractiveness, knowledge benefit, and required effort impacts LP members' perceived experiential benefits, which in turn impact program loyalty; while value derived from group belongingness and disclosure comfort drive brand loyalty. We also find that program loyalty influences brand loyalty; and program and brand loyalty together induce positive customer behaviors. However, program loyalty has a negative impact on a customer's willingness to pay. Our findings highlight the impact of multiple program value elements on customer loyalty, extending the literature by clarifying the relationships among program value, attitudinal loyalty, and behavioral loyalty. Practically, our findings suggest how managers can better design and implement their LPs to build customer loyalty.

PR2ALIGN: a stand-alone software program and a web-server for protein sequence alignment using weighted biochemical properties of amino acids.

BackgroundAlignment of amino acid sequences is the main sequence comparison method used in computational molecular biology. The selection of the amino acid substitution matrix best suitable for a given alignment problem is one of the most important decisions the user has to make. In a conventional amino acid substitution matrix all elements are fixed and their values cannot be easily adjusted. Moreover, most existing amino acid substitution matrices account for the average (dis)similarities between amino acid types and do not distinguish the contribution of a specific biochemical property to these (dis)similarities.FindingsPR2ALIGN is a stand-alone software program and a web-server that provide the functionality for implementing flexible user-specified alignment scoring functions and aligning pairs of amino acid sequences based on the comparison of the profiles of biochemical properties of these sequences. Unlike the conventional sequence alignment methods that use 20x20 fixed amino acid substitution matrices, PR2ALIGN uses a set of weighted biochemical properties of amino acids to measure the distance between pairs of aligned residues and to find an optimal minimal distance global alignment. The user can provide any number of amino acid properties and specify a weight for each property. The higher the weight for a given property, the more this property affects the final alignment. We show that in many cases the approach implemented in PR2ALIGN produces better quality pair-wise alignments than the conventional matrix-based approach.ConclusionsPR2ALIGN will be helpful for researchers who wish to align amino acid sequences by using flexible user-specified alignment scoring functions based on the biochemical properties of amino acids instead of the amino acid substitution matrix. To the best of the authors’ knowledge, there are no existing stand-alone software programs or web-servers analogous to PR2ALIGN. The software is freely available from http://pr2align.rit.albany.edu.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1152-6) contains supplementary material, which is available to authorized users.

Commentary: Continuously cumulating meta-analysis and replicability.

Commentary: Continuously cumulating meta-analysis and replicability.

RSAT 2015: Regulatory Sequence Analysis Tools.

RSAT (Regulatory Sequence Analysis Tools) is a modular software suite for the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations. Nine new programs have been added to the 43 described in the 2011 NAR Web Software Issue, including a tool to extract sequences from a list of coordinates (fetch-sequences from UCSC), novel programs dedicated to the analysis of regulatory variants from GWAS or population genomics (retrieve-variation-seq and variation-scan), a program to cluster motifs and visualize the similarities as trees (matrix-clustering). To deal with the drastic increase of sequenced genomes, RSAT public sites have been reorganized into taxon-specific servers. The suite is well-documented with tutorials and published protocols. The software suite is available through Web sites, SOAP/WSDL Web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

DATA CLASSIFICATION USING DIRICHLET MIXTURES

In the article, we present a method for data classification that is based on the Dirichlet mixture statistics. An important property of the method is its ability to classify data of any type. To test performance of the method, we implemented it as a stand-alone program and tested it on the three different databases of real data. Receiver operating characteristics of the classification was used to compare the method of Dirichlet mixtures to the other classification methods. The classification results and its performance are discussed in the article. The practical value of this study is that the method based on the complex statistics is implemented as a tool and compiled as a library for further development of machine learning environments.

Sensible method for updating motif instances in an increased biological network

A network motif is defined as an over-represented subgraph pattern in a network. Network motif based techniques have been widely applied in analyses of biological networks such as transcription regulation networks (TRNs), protein–protein interaction networks (PPIs), and metabolic networks. The detection of network motifs involves the computationally expensive enumeration of subgraphs, NP-complete graph isomorphism testing, and significance testing through the generation of many random graphs to determine the statistical uniqueness of a given subgraph. These computational obstacles make network motif analysis unfeasible for many real-world applications. We observe that the fast growth of biotechnology has led to the rapid accretion of molecules (vertices) and interactions (edges) to existing biological network databases. Even with a small percentage of additions, revised networks can have a large number of differing motif instances. Currently, no existing algorithms recalculate motif instances in ‘updated’ networks in a practical manner. In this paper, we introduce a sensible method for efficiently recalculating motif instances by performing motif enumeration from only updated vertices and edges. Preliminary experimental results indicate that our method greatly reduces computational time by eliminating the repeated enumeration of overlapped subgraph instances detected in earlier versions of the network. The software program implementing this algorithm, defined as SUNMI (Sensible Update of Network Motif Instances), is currently a stand-alone java program and we plan to upgrade it as a web-interactive program that will be available through http://faculty.washington.edu/kimw6/research.htm in near future. Meanwhile it is recommended to contact authors to obtain the stand-alone SUNMI program.

Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features.

BackgroundProtein-ligand binding site prediction from a 3D protein structure plays a pivotal role in rational drug design and can be helpful in drug side-effects prediction or elucidation of protein function. Embedded within the binding site detection problem is the problem of pocket ranking – how to score and sort candidate pockets so that the best scored predictions correspond to true ligand binding sites. Although there exist multiple pocket detection algorithms, they mostly employ a fairly simple ranking function leading to sub-optimal prediction results.ResultsWe have developed a new pocket scoring approach (named PRANK) that prioritizes putative pockets according to their probability to bind a ligand. The method first carefully selects pocket points and labels them by physico-chemical characteristics of their local neighborhood. Random Forests classifier is subsequently applied to assign a ligandability score to each of the selected pocket point. The ligandability scores are finally merged into the resulting pocket score to be used for prioritization of the putative pockets. With the used of multiple datasets the experimental results demonstrate that the application of our method as a post-processing step greatly increases the quality of the prediction of Fpocket and ConCavity, two state of the art protein-ligand binding site prediction algorithms.ConclusionsThe positive experimental results show that our method can be used to improve the success rate, validity and applicability of existing protein-ligand binding site prediction tools. The method was implemented as a stand-alone program that currently contains support for Fpocket and Concavity out of the box, but is easily extendible to support other tools. PRANK is made freely available at http://siret.ms.mff.cuni.cz/prank.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0059-5) contains supplementary material, which is available to authorized users.

Technology-based interventions for tobacco and other drug use in university and college students: a systematic review and meta-analysis.

BackgroundUniversity students have high levels of tobacco and other drug use, yet they are unlikely to seek traditional care. Technology-based interventions are highly relevant to this population. This paper comprises a systematic review and meta-analysis of published randomized trials of technology-based interventions evaluated in a tertiary (university/college) setting for tobacco and other drug use (excluding alcohol). It extends previous reviews by using a broad definition of technology.MethodsPubMed, PsycInfo, and the Cochrane databases were searched using keywords, phrases, and MeSH terms. Retrieved abstracts (n = 627) were double screened and coded. Included studies met the following criteria: (1) the study was a randomized trial or a randomized controlled trial (RCT); (2) the sample was composed of students attending a tertiary (e.g., university, college) institution; (3) the intervention was either delivered by or accessed using a technological device or process (e.g., computer/internet, telephone, mobile short message services [SMS]); (4) the age range or mean of the sample was between 18 and 25 years; and (5) the intervention was designed to alter a drug use outcome relating to tobacco or other drugs (excluding alcohol).ResultsA total of 12 papers met inclusion criteria for the current review. The majority of included papers examined tobacco use (n = 9; 75%), two studies targeted marijuana use (17%); and one targeted stress, marijuana, alcohol, and tobacco use. A quantitative meta-analysis was conducted on the tobacco use studies using an abstinence outcome measure (n = 6), demonstrating that the interventions increased the rate of abstinence by 1.5 times that of controls (Risk Ratio [RR] = 1.54; 95% Confidence Interval [CI] = 1.20–1.98). Across all 12 studies, a total of 20 technology-based interventions were reviewed. A range of technology was employed in the interventions, including stand-alone computer programs (n = 10), internet (n = 5), telephone (n = 3), and mobile SMS (n = 2).ConclusionsAlthough technological interventions have the potential to reduce drug use in tertiary students, very few trials have been conducted, particularly for substances other than tobacco. However, the improvement shown in abstinence from tobacco use has the potential to impact substantially on morbidity and mortality.Electronic supplementary materialThe online version of this article (doi:10.1186/s13722-015-0027-4) contains supplementary material, which is available to authorized users.

Quantitative visualization of alternative exon expression from RNA-seq data.

Analysis of RNA sequencing (RNA-Seq) data revealed that the vast majority of human genes express multiple mRNA isoforms, produced by alternative pre-mRNA splicing and other mechanisms, and that most alternative isoforms vary in expression between human tissues. As RNA-Seq datasets grow in size, it remains challenging to visualize isoform expression across multiple samples. To help address this problem, we present Sashimi plots, a quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions. Sashimi plots can be made using the Broad Integrated Genome Viewer or with a stand-alone command line program. Software code and documentation freely available here: http://miso.readthedocs.org/en/fastmiso/sashimi.html

Multi Directional Conductive Metal Detection Robot Control

As technology is growing there is a considerable demand on machine interface to the controlling system. Robotics is an era where mechanical structures are powered by interfacing personal computers with the improved software tools. Hyperlink is a standalone program to interact with the devices remotely interfaced with the personal computers. Wireless communication is also a supporting mechanism to regulate the direction and movement of the robotic machines. This paper aims to direct the conductive metal finding robot in all eight directions. An IR sensor assembly is used to position the robot to move with defined angle. Concentric coil type metal detector is used to pinpoint the targeted metal. Offset Quadrature phase shift keyed modulation stream (OQPSK) with 2.4 G Hz is used for transmitting the information to the remote control section of the robot. The mechanical load calculations are estimated to design the robot. The developed model is best suited on uneven surfaces.

The Place of 'Cultural Competency' in the Toolkit for Immigrant Integration

The purpose of this paper is to trace the evolution of the concept and practice of “cultural competency” and to explore its potential to serve as an organizing principle for policies and programs to integrate immigrants and their children. As some leaders and policy makers look for ways to “mainstream” immigrant integration, i.e. move away from stand-alone immigrant service programs, cultural competency -- understood as an approach to systems reform and quality improvement in workforce education, health care, and human services in general -- may provide an attractive solution.The goal of cultural competency in health and human services emerged in the 1960s as an outgrowth of the Civil Rights Revolution in the United States. The leaders of the cultural competency movement were concerned about inequities in the quality and availability of services and resources for Black and other long-established minorities. They also sought to validate minority cultures and harness the potential of these cultures to build stronger communities and empower people to achieve their potential. Over time, the cultural competency frame has been adapted to meet the needs of the growing immigrant population in the U.S. Several significant milestones along the way include the issuance of executive order 13116 by President Clinton in 1999, which led to the codification of requirements for language access accommodations, and the release of the first standards for Culturally and Linguistically Appropriate Services (CLAS) by the Department of Health and Human services in 2002. More significantly, researchers have struggled to define the meaning of cultural competency and to develop standards for evaluating an organization’s progress on the “cultural competency continuum.” At the same time, there has been a significant shift away from an earlier emphasis on staff training, values clarification, and individual transformation to a new effort to identify the system requirements for cultural competency. Cultural competency offers several advantages as a framework for immigrant integration: first, it encompasses generations beyond the immigrant generation, hence incorporating native-born citizens into its reach; second, it speaks to the needs of long-established minority populations, such as Blacks in the United States; third, it expands outward to include other forms of diversity, including disability, class, and region; and fourth, it speaks to the globalization of contemporary societies and the importance of cultural sensitivity as a way of interacting with diverse populations. The paper will probe each of these advantages, as well as arguments that might be raised against the pursuit of cultural competency by “multicultural skeptics.” In summary, this paper will trace the evolution of the concept of cultural competency, give examples as to how it has proven useful in designing services for immigrant communities, and describe an emerging consensus on system requirements for cultural competency, as reflected in the revised CLAS standards issued in 2013 and in such projects as the “Finding Answers” program of the Robert Wood Johnson Foundation, which funded 33 projects to test interventions to reduce disparities in health care, many of which targeted immigrant populations in the U.S. The paper will also assess the utility of cultural competency as a strategy for mainstreaming immigrant integration.

Optimization and Practical Use of Composition Based Approaches Towards Identification and Collection of Genomic Islands and Their Ontology in Prokaryotes

Abstract Motivation Horizontally transferred genomic islands (islands, GIs) have been referred to as important factors which contribute towards bacterial evolution in general and particularly towards the emergences of pathogens and outbreak instances. The development of tools for identification of such elements and retracing their distribution will help to understand how such cases arise. Sequence composition has been used to identify GIs, infer their phylogeny; and determine their relative time of insertion. Collection of metadata on known GIs will enhance insight into horizontal gene transfer ontology and flow. Results This paper introduces the merger of SeqWord Genomic Islands Sniffer (SWGIS), which utilizes composition based approaches for identification of GIs in bacterial genomic sequences, and the Predicted Genomic Islands (Pre_GI) database, which houses 26,744 islands found in 2,407 bacterial plasmids and chromosomes. SWGIS is a standalone program that detects GIs using a set of optimized parametric measures with estimates of acceptable false positive and false negative rates. Pre_GI is a novel repository that includes island ontology and flux. This study furthermore illustrates the need for parametric optimization towards the prediction of GIs to minimize false negative and false positive predictions. In addition Pre_GI emphasizes the practicality of the compounded knowledge that the database affords in detection and visualization of ontological links between GIs. Availability SWGIS is freely available on the web at http://www.bi.up.ac.za/SeqWord/sniffer/index.html , and Pre_GI is freely accessible at http://pregi.bi.up.ac.za/index.php.

ProGeRF: proteome and genome repeat finder utilizing a fast parallel hash function.

Repetitive element sequences are adjacent, repeating patterns, also called motifs, and can be of different lengths; repetitions can involve their exact or approximate copies. They have been widely used as molecular markers in population biology. Given the sizes of sequenced genomes, various bioinformatics tools have been developed for the extraction of repetitive elements from DNA sequences. However, currently available tools do not provide options for identifying repetitive elements in the genome or proteome, displaying a user-friendly web interface, and performing-exhaustive searches. ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences. It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results. ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool. It was developed using the hash table approach to extract perfect and imperfect repetitive regions in a (multi)FASTA file, while allowing a linear time complexity.

Thirty years of standalone percutaneous coronary interventions: A 23,261 case experience from a Canadian tertiary referral centre

Background: When percutaneous coronary intervention (PCI) was first performed >35 years ago, on-site cardiac surgery backup for PCI failure was deemed essential. As techniques improved and primary PCI became the preferred reperfusion strategy for acute myocardial infarction, many standalone PCI programs originally established to facilitate access to primary PCI started to perform elective PCI, which remains a Class IIb recommendation in American College of Cardiology Foundation/American Heart Association/Society for Cardiac Angiography and Interventions guidelines. Two recent United States studies showed that outcomes of elective PCI in standalone centres were noninferior to those with on-site cardiac surgery. The Royal Alexandra Hospital in Edmonton (Alberta) performed the first standalone PCI in Canada in 1981. Objectives: The authors describe their first 30 years’ experience with PCI – the largest single-centre standalone experience reported to date. Methods: Patient and procedural data have been collected since the first standalone PCI in 1981, evolving from paper records to a computer database and, in 1995, a provincial database. Quality assurance and peer review in collaboration with the regional cardiac surgery program was established from the outset. Results: The success, emergency coronary bypass and death rates for 23,261 standalone PCIs performed between 1981 and 2011 were 96.0%, 0.2% and 0.5%, respectively. For 9068 PCIs performed between 2007 and 2011 (a period that most reflects contemporary practice), the rates were 96.5%, 0.04% and 0.6%, respectively. These results compare favourably with PCI results reported in literature, irrespective of the presence or absence of on-site cardiac surgery. Conclusions: With high volumes and an experienced team, standalone PCIs can be performed safely with excellent success and low complication rates.

SUMAC: Constructing Phylogenetic Supermatrices and Assessing Partially Decisive Taxon Coverage.

The amount of phylogenetically informative sequence data in GenBank is growing at an exponential rate, and large phylogenetic trees are increasingly used in research. Tools are needed to construct phylogenetic sequence matrices from GenBank data and evaluate the effect of missing data. Supermatrix Constructor (SUMAC) is a tool to data-mine GenBank, construct phylogenetic supermatrices, and assess the phylogenetic decisiveness of a matrix given the pattern of missing sequence data. SUMAC calculates a novel metric, Missing Sequence Decisiveness Scores (MSDS), which measures how much each individual missing sequence contributes to the decisiveness of the matrix. MSDS can be used to compare supermatrices and prioritize the acquisition of new sequence data. SUMAC constructs supermatrices either through an exploratory clustering of all GenBank sequences within a taxonomic group or by using guide sequences to build homologous clusters in a more targeted manner. SUMAC assembles supermatrices for any taxonomic group recognized in GenBank and is optimized to run on multicore computer systems by parallelizing multiple stages of operation. SUMAC is implemented as a Python package that can run as a stand-alone command-line program, or its modules and objects can be incorporated within other programs. SUMAC is released under the open source GPLv3 license and is available at https://github.com/wf8/sumac.

System level approaches for mainstreaming tobacco control into existing health programs in India: Perspectives from the field.

Introduction:India is the second largest consumer of tobacco in the world, and varieties of both smoked and smokeless tobacco products are widely available. The national program for tobacco control is run like a vertical stand-alone program. There is a lack of understanding of existing opportunities and barriers within the health programs that influence the integration of tobacco control messages into them. The present formative research identifies such opportunities and barriers.Methods:We conducted a multi-step, mixed methodological study of primary care personnel and policy-makers in two Indian states of Andhra Pradesh and Gujarat. The primary purpose of our study was to investigate health worker and policy-maker perceptions on the integration of tobacco control intervention. We systematically collected data in three steps: In Step I, we conducted in-depth interviews (IDIs) and focus group discussions with primary care health personnel, Step II consists of a quantitative survey among health care providers (n = 1457) to test knowledge, attitudes and practices in tobacco control and Step III we conducted 75 IDIs with program heads and policy-makers to evaluate the relative congruence of their views on integration of the tobacco control program.Results:Majority of the health care providers recognized tobacco use as a major health problem. There was a general consensus for the need of training for effective dissemination of information from health care providers to patients. Almost 92% of the respondents opined that integration of tobacco control with other health programs will be highly effective to downscale the tobacco epidemic.Conclusions:Our findings suggest the need for integration of tobacco control program into existing health programs. Integration of tobacco control strategies into the health care system within primary and secondary care will be more effective and counseling for tobacco cessation should be available for population at large.

Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis

Abstract We present cna , a package for performing Coincidence Analysis (CNA). CNA is a config-urational comparative method for the identification of complex causal dependencies—in particular,causal chains and common cause structures—in configurational data. After a brief introduction to themethod’s theoretical background and main algorithmic ideas, we demonstrate the use of the packageby means of an artificial and a real-life data set. Moreover, we outline planned enhancements of thepackage that will further increase its applicability. Introduction Configurational comparative methods (CCMs) subsume techniques for the identification of complexcausal dependencies in configurational data using the theoretical framework of Boolean algebra andits various extensions (Rihoux and Ragin,2009). For example, Qualitative Comparative Analysis(QCA;Ragin,1987,2000,2008)—hitherto the most prominent representative of CCMs—has beenapplied in areas as diverse as business administration (e.g.,Chung,2001), environmental science(van Vliet et al.,2013), evaluation (Cragun et al.,2014), political science (Thiem,2011), public health(Longest and Thoits,2012) and sociology (Crowley,2013). Besides three stand-alone programs basedon graphical user interfaces, three R packages for QCA are currently available, each with a differentscope of functionality:

MotionMeerkat: integrating motion video detection and ecological monitoring

Summary Human observation is expensive and limits the breadth of data collection. For this reason, remotely placed video cameras are increasingly used to monitor animals. One drawback of field‐based video recordings is extensive review time. Computer vision can mitigate this cost and enhance data collection by extracting biological information from images with minimal time investment. MotionMeerkat is a new standalone program that identifies motion events from a video stream. After running a video, the user reviews a folder of candidate motion frames for the target organism. This tool reduces the time needed to review videos and accommodates a variety of inputs. I tested MotionMeerkat using hummingbird–plant videos recorded in a tropical montane forest. To validate the optimal parameter set for finding motion events, I counted hummingbirds observed from direct video review compared to events found in images returned from MotionMeerkat. To show the generality of the approach, MotionMeerkat was tested on a set of terrestrial and underwater videos. To assess the performance of the background subtraction for further image analysis, I hand counted the number of frames with target organisms and compared them to the MotionMeerkat output. MotionMeerkat was highly successful in finding motion events and often reduced the number of frames needed to capture hummingbird visitation by over 90%. Both background approaches effectively found a variety of organisms in ecological videos. I provide general recommendations for parameter settings and extending this approach in the future.