Suite Of Programs Research Articles

Static detection of uncoalesced accesses in GPU programs

GPU programming has become popular due to the high computational capabilities of GPUs. Obtaining significant performance gains with GPU is however challenging and the programmer needs to be aware of various subtleties of the GPU architecture. One such subtlety lies in accessing GPU memory, where certain access patterns can lead to poor performance. Such access patterns are referred to as uncoalesced global memory accesses. This work presents a light-weight compile-time static analysis to identify such accesses in GPU programs. The analysis relies on a novel abstraction which tracks the access pattern across multiple threads. The abstraction enables quick prediction while providing correctness guarantees. We have implemented the analysis in LLVM and compare it against a dynamic analysis implementation. The static analysis identifies 95 pre-existing uncoalesced accesses in Rodinia, a popular benchmark suite of GPU programs, and finishes within seconds for most programs, in comparison to the dynamic analysis which finds 69 accesses and takes orders of magnitude longer to finish.

Early combination treatment with existing HIV antivirals: an effective treatment for COVID-19?

Since no effective therapy exists, we aimed to test existing HIV antivirals for combination treatment of Coronavirus disease 19 (COVID-19). The crystal structures of SARS-CoV-2 main protein (Mpro) (PDB ID: 6Y2F) and SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) (PDB ID: 7BV2) both available from Protein Data Bank were used in the study. Automated Docking by using blind and standard method both on Mpro and RdRp bound to the modified template-primer RNA was performed with AutoDock 4.2.6 program suite. Lamarckian genetic algorithm (LGA) was used for structures docking. All inhibitors were docked with all bonds completely free to rotate. Our molecular docking findings suggest that lopinavir, ritonavir, darunavir, and atazanavir activated interactions with the key binding sites of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) protease with a better inhibition constant (Ki) for lopinavir, ritonavir, and darunavir. Furthermore, we evidenced the ability of remdesivir, tenofovir, emtricitabine, and lamivudine to be incorporated in SARS-CoV-2 RdRp in the same protein pocket where poses the corresponding natural nucleoside substrates with comparable Ki and activating similar interactions. In principle, the four antiviral nucleotides might be used effectively against SARS-CoV-2. The combination of a protease inhibitor and two nucleoside analogues, drugs widely used to treat HIV infection, could be evaluated in clinical trials for the treatment of COVID-19.

Implementation of the Marchenko multiple elimination algorithm

The Marchenko multiple elimination (MME) and transmission compensation schemes retrieve primary reflections in the two-way traveltime domain without model information or using adaptive subtraction. Both schemes are derived from projected Marchenko equations and are similar to each other, but they use different time-domain truncation operators. The MME scheme retrieves a new data set without internal multiple reflections. The transmission-compensated Marchenko multiple elimination scheme does the same and additionally compensates for transmission losses in the primary reflections. Both schemes can be solved with an iterative algorithm based on a Neumann series. At each iteration, a convolution or correlation between the projected focusing function and the measured reflection response is performed, and, after each convolution or correlation, a truncation in the time domain is applied. After convergence, the resulting projected focusing function is used for retrieving the transmission-compensated primary reflections and the projected Green’s function is used for the physical primary reflections. We have determined that internal multiples are removed by using time-windowed input data that only contain primary reflections. We evaluate both schemes in detail and develop an iterative implementation that reproduces the presented numerical examples. The software is part of our open-source suite of programs and fits into the Seismic Unix software suite of the Colorado School of Mines.

IsoStar Program Suite for Studies of Noncovalent Interactions in Crystals of Chemical Compounds

Both Cambridge Crystallographic Data Centre (CCDC) and Protein Data Bank (PDB) provide unique opportunities for finding information about the structures of chemical and biochemical compounds in the solid state. The IsoStar—a knowledge-based library of intermolecular interactions—is a very powerful tool for automatic analysis of a large amount of data from these databases. The IsoStar program suite could help chemists in understanding of probability of occurrence (frequencies) and spatial characteristics (directionalities) of noncovalent contacts (including hydrogen, halogen, and chalcogen bonds, as well as interactions involving π-systems) between pairs of chemical functional groups; this web application may also be useful for crystal engineers, crystallographers, medicinal chemists, and researchers in fields of computational chemistry and molecular modeling.

A South-to-South Cultural Adaptation of an Evidence-Based Parenting Program for Families in the Philippines.

Rates of child maltreatment are higher in low‐ and middle‐income countries due to risk factors such as social inequities, economic adversity, and sociocultural norms. Given the evidence showing the effectiveness of parenting interventions to prevent child maltreatment, this study embarked on a cultural adaptation of an evidence‐based parenting program with the eventual goal of integrating it within a nationwide conditional cash transfer program for low‐income Filipino parents with children aged 2–6 years. We document the systematic adaptation of the Parenting for Lifelong Health for Young Children program that was developed and tested in South Africa, for low‐resource Filipino families using the heuristic framework for the cultural adaptation of interventions. We underscore the merits of conducting a multistage top‐down and bottom‐up process that uses a participatory approach among cultural insiders and outsiders to develop a parenting intervention that reflects the contextual realities and cultural values of end users. The adapted program, Masayang Pamilya Para sa Batang Pilipino, is the product of a delicate and deliberate effort to balance Filipino childrearing goals and values with the scientific evidence on components of parenting interventions known to promote positive parenting and prevent child maltreatment.

Discovery of Small Molecule Bak Activator for Lung Cancer Therapy.

Rationale: Bak is a major proapoptotic Bcl2 family member and a required molecule for apoptotic cell death. High levels of endogenous Bak were observed in both small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) cell lines. Increased Bak expression was correlated with poor prognosis of NSCLC patients, suggesting that Bak protein is an attractive target for lung cancer therapy. The BH3 domain functions as death domain and is required for Bak to initiate apoptotic cell death. Thus, the BH3 domain is attractive target for discovery of Bak agonist.Methods: The BH3 death domain binding pocket (aa75-88) of Bak was chosen as a docking site for screening of small molecule Bak activators using the UCSF DOCK 6.1 program suite and the NCI chemical library (300,000 small molecules) database. The top 500 compounds determined to have the highest affinity for the BH3 domain were obtained from the NCI and tested for cytotoxicity for further screening. We identified a small molecule Bak activator BKA-073 as the lead compound. The binding affinity of BKA-073 with Bak protein was analyzed by isothermal titration calorimetry (ITC) assay. BKA-073-mediated Bak activation via oligomerization was analyzed by a cross-linking with Bis (maleimido) hexane (BMH). Sensitivity of BKA-073 to lung cancer cells in vitro was evaluated by dynamic BH3 profiling (DBP) and apoptotic cell death assay. The potency of BKA-073 alone or in combination with radiotherapy or Bcl2 inhibitor was evaluated in animal models.Results: We found that BKA-073 binds Bak at BH3 domain with high affinity and selectivity. BKA-073/Bak binding promotes Bak oligomerization and mitochondrial priming that activates its proapoptotic function. BKA-073 potently suppresses tumor growth without significant normal tissue toxicity in small cell lung cancer (SCLC) and NSCLC xenografts, patient-derived xenografts, and genetically engineered mouse models of mutant KRAS-driven cancer. Bak accumulates in radioresistant lung cancer cells and BKA-073 reverses radioresistance. Combination of BKA-073 with Bcl-2 inhibitor venetoclax exhibits strong synergy against lung cancer in vivo.Conclusions: Development of small molecule Bak activator may provide a new class of anticancer agents to treat lung cancer.

Wordsmith Tools as an Enabler for Text Analysis

The process of intellectualization has been characterized as a planned process of accelerating the growth and development of South Africa’s indigenous languages to enhance their effective interface with modern developments, theories and concepts (Finlayson & Madiba, 2002). Corpora are used to develop empirical knowledge about language. A corpus is a collection of naturally occurring texts derived from real life language use in either written or spoken form (cf. Sinclair, 1991). These texts are then processed, stored and accessed by means of computers for use in developing electronic resources of a language. It is thus an important resource in the development of isiZulu Human Language Technologies. Thus, specialized corpora were created for this study and were used as the basis to enquire into the sensitive use of isiZulu with reference to language phenomenon isiHlonipho. Corpus linguistics provides a more objective view of language than introspection, intuition and anecdotes. This study profited from the use of the WordSmith Tools version 6 software program suite, which allowed the researcher to use different programs simultaneously to analyse data.

A Randomized Controlled Trial of Three School Meals and Weekend Food Backpacks on Food Security in Virginia

BackgroundFood insecurity is a concern for the health and well-being of low-income children in the United States. School-based nutrition assistance programs aim to reduce food insecurity; however, there is limited evidence of their combined impact on food insecurity among children (FI-C). ObjectiveThis study tested the impact of the Virginia 365 demonstration project on the food security status of children attending low-income schools. DesignA cluster-randomized trial was conducted from 2016 to 2017 with baseline and follow-up surveys. Participants/settingHouseholds with children who attended a treatment (n = 19) or control (n = 19) school in rural and urban Virginia were included. InterventionTreatment schools became food hubs where children had access to free breakfast, lunch, and supper on school days, and a food backpack on weekends and school breaks. Control schools implemented a similar, but less robust set of benefits. Main outcome measuresThe primary outcome was the percentage of children classified as FI-C as measured by the US Department of Agriculture Household Food Security Survey Module. Secondary outcomes included very low food security among children and food security among households and adults. Statistical analysis performedLogistic regression models tested the impact of the demonstration on FI-C and secondary outcomes adjusting for baseline household and individual characteristics. ResultsAt follow-up, 1,393 treatment households and 1,243 control households completed a survey sufficiently to be included in the analysis. The rate of FI-C in treatment households was higher at 25.9% compared with 23.9% in control households, a difference of 2 percentage points (95% CI 0.1 to 3.9). The rate of very low food security among children in treatment households was lower at 3.2% compared with 3.9% in control households, a difference of −0.7 percentage points (95% CI −1.3 to −0.10). ConclusionsAlthough the distinction in nutrition assistance benefits between treatment and control schools was less than planned, providing a suite of school-based nutrition assistance programs targeted broadly to low-income households with children has both positive and negative impacts on child and household food insecurity.

Neural software vulnerability analysis using rich intermediate graph representations of programs

Security vulnerabilities are among the major concerns of modern software engineering. Successful results of machine learning techniques in various challenging applications have led to an emerging field of research to investigate the effectiveness of machine learning, and more recently, deep learning techniques, for the problem of software vulnerability analysis and discovery. In this paper, we explore the utilization of Graph Neural Networks as the latest trend and progress in the field of artificial neural networks. To this end, we propose an original neural vulnerability analysis approach, using customized intermediate graph representations of programs to train graph neural network models. Experimental results on a public suite of vulnerable programs show that the proposed approach is effective at the task of software vulnerability analysis. Additional empirical experiments answer complementary research questions about the proposed approach. In particular, we present experimental results for the challenging task of cross-project vulnerability analysis, with interesting insights on the capabilities of our novel approach. Furthermore, a software utility that was developed in the course of this study is also published as a further contribution to the research community.

The VEGA suite of programs: an versatile platform for cheminformatics and drug design projects.

The VEGA suite of programs and the source code of the VEGA command-line version are available free of charge for non-profit organizations at http://www.vegazz.net.

Quantum chemical study of thiaozole derivatives as corrosion inhibitors based on density functional theory

Quantum chemical and theoretical calculations were carried out in the present study of some thiaozole derivatives. Relationship between electronic parameters of thiaozole derivatives 5-benzylidene-2,4-dioxo tetrahydro1,3-thiazole (5-BDT) 5-(4′-isopropylbenzylidene)-2,4-dioxotetrahydro-1,3-thiazole (5IPBDT), 5-(3′-thenylidene)-2,4-dioxotetrahydro-1,3-thiazole (5-TDT) and 5-(3′,4′dimetoxybenzylidene)-2,4-dioxotetrahydro-1,3-thiazole (5-MBDT) and corrosion inhibition efficiency have been investigated by the Hartree-Fock (HF) and Becke, 3-parameter, Lee-Yang-Parr (B3LYP), M06-2X method with 3-21G, 6-31G, and sdd basis set. All calculations have been performed using the Gaussian 09W suite of programs. The properties most relevant to their potential action as corrosion inhibitors: EHOMO, ELUMO, ΔE (HOMO-LUMO energy gap), electronegativity (χ), chemical potential (μ), chemical hardness (η), electrophilicity (ω), nucleophilicity (ε), global softness (σ) and proton affinity (PA) have been studied.

39 Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs

Abstract The aim of this study was to investigate different inclusion rates of purebred (PB) and CB phenotypes and genotypes in genetic evaluations. Assuming PB and CB traits with moderate heritabilities (h2 = 0.4), a three-way swine crossbreeding scheme was simulated, and selection was practiced for 6 generations. The goal was to increase the CB phenotype. Phenotypes, genotypes and pedigrees for three purebred breeds (each consisting of 25 males and 175 females), F1 crosses (400 females) and terminal cross progeny (2500) were simulated using AlphaSimR. The genome consisted of 18 chromosomes with 1,800 QTL and 59.4k SNP markers. Selection was performed using EBV produced by the BLUPf90 suite of programs for each phenotyping/genotyping strategy. Strategies investigated were 1) increasing the proportion of CB with genotypes, phenotypes and sire pedigree information, 2) decreasing the proportion of PB phenotypes and genotypes, and 3) altering the genetic correlation between PB and CB traits (rpc). Each strategy was replicated 15 times. Results showed that including CB performance improved the CB phenotype regardless of rpc or phenotyping/genotyping strategy. Compared to using only PB information, including 10% of possible CB animals per generation with sire pedigrees and phenotypes increased the response in CB phenotype when rpc was 0.1, 0.3, 0.5, 0.7, and 0.9 by 192, 64, 41, 25 and 21%, respectively. Including CB genotypes dramatically improved the previously mentioned increases in response. Minimal change was observed in the CB phenotype when PB phenotypes were included or removed, if CB phenotypes, genotypes and sire pedigrees were included. PB genotypes were more informative than phenotypes in enabling prediction for CB traits. In practice, the inclusion rates of CB and PB data depends upon the degree of connectedness between CB animals and PB selection candidates and the cost-benefit ratio of increased CB performance and genotyping/phenotyping costs.

PSV-13 Genetic parameters and quantitative trait loci for heat stress related traits in sheep

Abstract Greater selection emphasis has been placed on efficiency than on fitness in livestock populations over the last several decades. Heat stress is a concern in production systems due to the negative effects on production, reproduction, and immunity. The objective of the study was to estimate variance components and identify quantitative trait loci (QTL) for heat stress related traits in sheep. A total of 125 Dorper, Katahdin, and St. Croix ewes originating from four regions of the United States were selected for the experiment. Animals were separated into four trials due to facility limitations. Data were collected for each trial over four consecutive two-week periods in an environmentally controlled facility with targeted heat load index (HLI) for daytime/nighttime of 70/70, 85/77, 90/77, and 95/81. Body weight was collected three times per week and rectal temperature was collected weekly. Black globe temperature and humidity were measured every 15 minutes. Animals were genotyped using the Illumina OvineSNP50 BeadChip. After quality control, 49,396 effective single nucleotide polymorphisms were included in the univariate analysis performed with the BLUPF90 suite of programs. Fixed effects in the models included region of origin, breed, trial, and age as a covariate. Traits analyzed included rectal temperature at 95 HLI (RT95), feed intake at 95 HLI (FI95), and average daily gain for the period for HLI between 90 and 95 (ADG). Heritabilities for RT95, FI95, and ADG were 0.35, 0.10, and 0.10, respectively. Largest effect QTL were identified on chromosomes 23, 9, and 6 for RT95, chromosomes 9, 2, and 20 for FI95, and chromosomes 6, 1, and 5 for ADG. Many of the regions identified have also been associated with weight and carcass traits in other studies, but few had obvious connections to the heat stress related response. In conclusion, results suggest selection could improve heat tolerance in sheep.

Tree2C: A Flexible Tool for Enabling Model Deployment with Special Focus on Cheminformatics Applications

Despite the increasing role played by artificial intelligence methods (AI) in pharmaceutical sciences, model deployment remains an issue, which only can be addressed with great difficulty. This leads to a marked discrepancy between the number of published predictive studies based on AI methods and the models, which can be used for new predictions by everyone. On these grounds, the present paper describes the Tree2C tool which automatically translates a tree-based predictive model into a source code with a view to easily generating applications which can run as a standalone software or can be inserted into an online web service. Moreover, the Tree2C tool is implemented within the VEGA environment and the generated program can include the source code to calculate the required attributes/descriptors. Tree2C supports various programming languages (i.e., C/C++, Fortran 90, Java, JavaScript, JScript, Lua, PHP, Python, REBOL and VBScript and C-Script). Along with a detailed description of the major features of this tool, the paper also describes two examples which are aimed to predict the blood–brain barrier (BBB) permeation as well as the mutagenicity. They permit a clear evaluation of the potentials of Tree2C and of its related features as implemented by the VEGA suite of programs. The Tree2C tool is available for free.

Spending for success: identifying ‘what works?’ for Indigenous student outcomes in Australian Universities

Abstract Despite the continued investment in Indigenous support networks and dedicated education units within universities, levels of key performance indicators for Indigenous students—access, participation, success and completion (attainment)—remain below that of the overall domestic student population in most institutions. It remains important to determine what works to achieve Indigenous student success in higher education. This paper proposes that such methods have an integral role to play in providing a holistic view of Indigenous participation and success at university, and are particularly useful in the development and evaluation of strategies and programs. This project found no quantitative correlation between financial investment and success rate for Indigenous students. A negative correlation between access rate and success rate suggests that factors other than those that encourage participation are important in supporting successful outcomes. Those universities that have high success rates have a suite of programs to support Indigenous students, but it is not immediately clear which of these strategies and programs may be most effective to facilitate Indigenous student success rates. In this discussion, we suggest that a multi-layered determinants model is a useful way to conceptualise the many factors that may impact on student success, and how they might intersect.

Automated and optimally FRET-assisted structural modeling

FRET experiments can provide state-specific structural information of complex dynamic biomolecular assemblies. However, to overcome the sparsity of FRET experiments, they need to be combined with computer simulations. We introduce a program suite with (i) an automated design tool for FRET experiments, which determines how many and which FRET pairs should be used to minimize the uncertainty and maximize the accuracy of an integrative structure, (ii) an efficient approach for FRET-assisted coarse-grained structural modeling, and all-atom molecular dynamics simulations-based refinement, and (iii) a quantitative quality estimate for judging the accuracy of FRET-derived structures as opposed to precision. We benchmark our tools against simulated and experimental data of proteins with multiple conformational states and demonstrate an accuracy of ~3 Å RMSDCα against X-ray structures for sets of 15 to 23 FRET pairs. Free and open-source software for the introduced workflow is available at https://github.com/Fluorescence-Tools. A web server for FRET-assisted structural modeling of proteins is available at http://nmsim.de.

Co-60 MR Guided Adaptive Radiation Treatment Improves Target Coverage and Organs-At-Risk Sparing: Dosimetric Analysis of 1185 Adaptive Fractions and 5 Years’ Experience

Early data indicate MRI guided online adaptive radiotherapy (MRGRT) spares organs-at-risk (OARs) when inter-fractional motion of tumor targets and critical GI organs is significant. However, these studies were limited in patient numbers. This study systematically assesses all previously adapted treatment fractions of the MR imaging system Co-60 machine at the authors’ institution. The dosimetry metrics on patients’ treatment day anatomy between the adapted plans vs the un-adapted plans are compared. The aims are to determine the reasons (and corresponding rates) necessitating plan adaptations and quantifying improvement in target coverage. All abdominal cancer patients (N = 137) previously treated with MRGRT on the VR Co-60 machine from 2015 to 2019 are included. Treatment sites were pancreas (98), adrenal (11) and not otherwise specified abdomen (28). A total 961 (81.1%) out of 1185 fractions were adapted. Plan adaptation conditions were 1) the target was edited, or 2) any critical OAR constraints were violated, or 3) target coverage was significantly worse (V95%Rx reduction >10% for PTV-PRV) than the one achieved with the previous plan. For each adapted fraction, dose was calculated using a Monte Carlo dose calculation engine previously developed by authors for both 1) the plan before adaptation and 2) the adapted new plan. A suite of computer algorithm programs were developed to 1) process the treatment plan data files exported from TPS, 2) recognize the case-specific target structure and critical OARs, 3) compute treatment-day DVH metrics (V95%Rx and D95% for the targets, and V>constraint for OARs) on the calculated dose volumes, and 4) analyze the results arithmetically and statistically. Data of 961 adapted treatment fractions were processed and analyzed. The analysis shows that 1) critical OARs were edited for 100% cases, 2) tumor targets were edited for 90 (9.4%) cases, 3) critical OAR constraints were violated for 870 (90.5%) cases by the un-adapted plans, 4) plan optimization objectives were edited for 33 (3.4%) cases and 5) all critical OAR constraints were met in all (100%) adapted plans, 6) target coverages were improved for 888 (92.4%) cases with the adapted plans compared to un-adapted plans that were normalized to meet OAR constraints. After more than 5 years and 1100 fractions of experience, results continue to confirm that adapted plans provided significantly better target coverage while preventing violation of critical OAR constraints. Future work is necessary to establish the clinical significance of these data and validate these findings in the VR MRI Linac.

PUMAA: A Platform for Accessible Microbiome Analysis in the Undergraduate Classroom.

Improvements in high-throughput sequencing makes targeted amplicon analysis an ideal method for the study of human and environmental microbiomes by undergraduates. Multiple bioinformatics programs are available to process and interpret raw microbial diversity datasets, and the choice of programs to use in curricula is largely determined by student learning goals. Many of the most commonly used microbiome bioinformatics platforms offer end-to-end data processing and data analysis using a command line interface (CLI), but the downside for novice microbiome researchers is the steep learning curve often required. Alternatively, some sequencing providers include processing of raw data and taxonomy assignments as part of their pipelines. This, when coupled with available web-based or graphical user interface (GUI) analysis and visualization tools, eliminates the need for students or instructors to have extensive CLI experience. However, lack of universal data formats can make integration of these tools challenging. For example, tools for upstream and downstream analyses frequently use multiple different data formats which then require writing custom scripts or hours of manual work to make the files compatible. Here, we describe a microbial ecology bioinformatics curriculum that focuses on data analysis, visualization, and statistical reasoning by taking advantage of existing web-based and GUI tools. We created the Program for Unifying Microbiome Analysis Applications (PUMAA), which solves the problem of inconsistent files by formatting the output files from several raw data processing programs to seamlessly transition to a suite of GUI programs for analysis and visualization of microbiome taxonomic and inferred functional profiles. Additionally, we created a series of tutorials to accompany each of the microbiome analysis curricular modules. From pre- and post-course surveys, students in this curriculum self-reported conceptual and confidence gains in bioinformatics and data analysis skills. Students also demonstrated gains in biologically relevant statistical reasoning based on rubric-guided evaluations of open-ended survey questions and the Statistical Reasoning in Biology Concept Inventory. The PUMAA program and associated analysis tutorials enable students and researchers with no computational experience to effectively analyze real microbiome datasets to investigate real-world research questions.

Helping Babies Survive: Lessons Learned From Global Trainers.

The Helping Babies Survive (HBS) suite of programs was launched in 2010 as an evidence-based educational package to train health care workers in low- and middle-income countries in neonatal resuscitation, immediate newborn care, and complications of prematurity. To date, there has been no purposeful examination of lessons learned from HBS trainers. Our intent with this study is to gather that data from the field. To estimate the total global reach of the HBS program, we obtained equipment distribution data from Laerdal and HBS material download data from the HBS Web site as of March 2020. To understand the lessons learned from HBS trainers, we examined comments from trainers who recorded their trainings on the HBS Web site, and other first-hand accounts. More than 1 million pieces of equipment (simulators, flip charts, provider guides, and action plans) have been distributed worldwide. HBS materials have been downloaded from the Web site >130 000 times and have now been translated into 27 languages. HBS equipment and training has reached an estimated 850 000 providers in 158 countries. Qualitative analysis revealed 3 major themes critical to building successful and sustainable HBS programs: support, planning and local context, and subthemes for each. Lessons learned from experienced trainers represent a vital distillation of first-hand experience into widely applicable knowledge to be used to reduce potential failures and achieve desired outcomes. Findings from this study offer further guidance on best practices for implementing and sustaining HBS programs and provide insight into challenges and successes experienced by HBS trainers.

Helping Babies Survive Programs as an Impetus for Quality Improvement.

Achieving the ambitious reduction in global neonatal mortality targeted in the Sustainable Development Goals and Every Newborn Action Plan will require reducing geographic disparities in newborn deaths through targeted implementation of evidence-based practices. Helping Babies Survive, a suite of educational programs targeting the 3 leading causes of neonatal mortality, has been commonly used to educate providers in evidence-based practices in low-resource settings. Quality improvement (QI) can play a pivotal role in translating this education into improved care. Measurement of key process and outcome indicators, derived from the algorithms ("Action Plans") central to these training programs, can assist health care providers in understanding the baseline quality of their care, identifying gaps, and assessing improvement. Helping Babies Survive has been the focus of QI programs in Kenya, Nepal, Honduras, and Ethiopia, with critical lessons learned regarding the challenge of measurement, necessity of facility-based QI mentorship and multidisciplinary teams, and importance of systemic commitment to improvement in promoting a culture of QI. Complementing education with QI strategies to identify and close remaining gaps in newborn care will be essential to achieving the Sustainable Development Goals and Every Newborn Action Plan targets in the coming decade.