Proper Initialization Research Articles

Improving the Forecast Performance of Hydrological Models Using the Cubature Kalman Filter and Unscented Kalman Filter

AbstractHydrological models are widely used for flood forecasting, and proper initialization of hydrological models is essential. Although the unscented Kalman filter (UKF) has shown promise in the context of operational forecasting, it is limited by its intrinsic instability caused by the loss of positive semidefiniteness of the covariance matrix. Effective methods for tackling this problem have not been seen in the literature. The cubature Kalman filter (CKF) is a powerful nonlinear filter for state estimation, which has received little attention in the hydrologic context. In this paper, to overcome the instability problem of the UKF, a new modified UKF (UKF‐M) is proposed by modifying the default UKF tuning strategy, and a novel nonlinear filter (CKF) is introduced to update the states of hydrological models. The methods are tested using a lumped hydrological model. The results of the stability experiment suggest that both the UKF‐M and CKF can overcome the instability problem, while the original UKF can fail due to the loss of positive semidefiniteness of the covariance matrix. The results of a reforecast experiment in an operational context show that both filters can improve the forecast performance by updating the model state based on the observed discharge, with the UKF‐M achieving better forecast performances. The UKF‐M and CKF can be used to overcome the instability problem of the original UKF and are valuable methods for improving forecast performances of hydrological models by state updating.

Exploring physical and phycological condition of Jahangirnagar University students residing near university area during COVID-19 pandemic

Background: Due of the closure of all educational institute as well as lockdown, the pandemic has affected physical and psychological health of all level students specifically university level students. Although the online based education was started but that brought different challenge to them. Thus, the study aimed to explore the physical and psychological problems faced by Jahangirnagar University students who resides near university area. Methods: Data was collected through an online questionnaire (Google form) from Jahangirnagar University students who reside near the university area using convenient sampling method. To analyse the data, descriptive statistics, Chi-square test and ordinal logistic regression was executed along with graphical representations. Results: The study showed about 92.5% (moderately: 41.2 %, extremely severe: 18%, severe: 24.7%, mild: 8.6%) students were depressed while 94.8% extremely severe: 49.8%, mild: 2.2%, moderate: 15.4% and severe: 27.3%) students were suffering from anxiety problems during pandemic. Chi-square and ordinal logistic suggested “infected by COVID-19”, “sleeping time”, and “time usually spent on physical activity” were the risk factors for depression and anxiety. The study revealed 73.8 percent of respondents have long-term health-related complications where half (52.8%) of the respondents think that the COVID-19 pandemic has had an effect on their physical health. Conclusions: This study shows that throughout the COVID-19 period, a substantial percentage of Jahangirnagar University students experienced physical and psychological health issues. Proper initiatives should be taken by government and policymakers to boost up the mental and physical health condition of students.

DPReLU: Dynamic Parametric Rectified Linear Unit and Its Proper Weight Initialization Method

Activation functions are essential in deep learning, and the rectified linear unit (ReLU) is the most widely used activation function to solve the vanishing gradient problem. However, owing to the dying ReLU problem and bias shift effect, deep learning models using ReLU cannot exploit the potential benefits of negative values. Numerous ReLU variants have been proposed to address this issue. In this study, we propose Dynamic Parametric ReLU (DPReLU), which can dynamically control the overall functional shape of ReLU with four learnable parameters. The parameters of DPReLU are determined by training rather than by humans, thereby making the formulation more suitable and flexible for each model and dataset. Furthermore, we propose an appropriate and robust weight initialization method for DPReLU. To evaluate DPReLU and its weight initialization method, we performed two experiments on various image datasets: one using an autoencoder for image generation and the other using the ResNet50 for image classification. The results show that DPReLU and our weight initialization method provide faster convergence and better accuracy than the original ReLU and the previous ReLU variants.

A Dynamic Control Method for Buck + $LLC$ Cascaded Converter With a Wide Input Voltage Range

DC–DC converters with a wide input voltage range have earned numerous daily applications in the industry. An example is power systems for electric vehicles, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$LLC$</tex-math></inline-formula> converters with remarkable features have also been deployed to provide isolation. It is, therefore, common to find a front buck converter cascaded to a back <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$LLC$</tex-math></inline-formula> converter, where their intermediate bus voltage is set low to accommodate the lowest input voltage to the buck converter. Unfortunately, this causes efficiency to drop at a high input voltage. To avoid the drop, a reconfiguring strategy has been proposed to convert the front buck converter from full bridge to half bridge, as its input voltage rises above a specified threshold. Furthermore, to ensure a smooth and fast reconfiguration, a dynamic control method has been proposed to direct the intermediate bus voltage to track a reference trajectory with a lower current surge. Besides, the method employs pulse-shift modulation to keep a stable output voltage and proper control initialization to prevent oscillation during the transition. These favorable features and an overall higher efficiency have subsequently been verified through experimental testing with a wide input voltage range.

Continuing Transformation: Śrī Nāth, His Gurus and His Devotees in a Timeless World

Śrī Nāth is one of the most important images of Krishna being worshipped at the temple of Nathdwara in Rajasthan. His devotees consider him to be a living god, he appears in their dreams, and according to their sayings they are in direct contact with him. Śrī Nāth, originally a local deity, is equated with the major Hindu god Krishna. However, while Krishna may be one of the most important gods in India, he is also ambiguous through his acts and words, if not bluntly unreliable. This double nature of Krishna is reflected in the cult of Śrī Nāth. There is an interesting interaction between Śrī Nāth (implying Krishna himself), the main gurus of his cult, i.e., Vallabha (Vallabhācārya) and the latter’s son and main successor Viṭṭhalnāth and his devoted disciples. At times, Śrī Nāth feels the need to stick to the official Brahmanical cult of the temple rituals, on other occasions, there is no problem in transgressing any given official rule. The same is true for the primary teachers, who are often put on par with Krishna himself or one of the celestials closely connected to him. Additionally, the disciples can apparently do anything in their frenzies. All of this reinforces the idea that this entire cult belongs to another world (alaukik). It is part of the everyday world (laukik) of Hindu India, but meanwhile, each and every rule can be ignored if the supernatural breaks through. Even the distinction between Hinduism and Islam at times simply does not seem to be of importance anymore. Muslims can become addicted to the passionate love for Krishna through the form of Śrī Nāth, so it is sometimes stated. Each and every partaker in the cult may share the visions of the initiated devotee, at times even without proper initiation. This all adds to the experience of the supermundane and supernatural in this particular cult.

EUNNet: Efficient UN-Normalized Convolution Layer for Stable Training of Deep Residual Networks Without Batch Normalization Layer

Batch Normalization (BN) is an essential component of the Deep Neural Networks (DNNs) architectures. It helps improve stability, convergence, and generalization. However, studies are showing that BN might introduce several concerns. Although there are methods for training DNNs without BN using proper weight initialization, they require several learnable scalars or accurate fine-tuning to the training hyperparameters. As a result, in this study, we aim to stabilize the training process of un-normalized networks without using proper weight initialization and to minimize the hyperparameters fine-tuning step. We propose EUNConv, an Efficient UN-normalized Convolutional layer, which helps train un-normalized Deep Residual Networks (ResNets) by using hyperparameters of the normalized networks. Furthermore, we introduce Efficient UN-normalized Neural Network (EUNNet), which replaces all of the conventional convolutional layers of ResNets with our proposed EUNConv. Experimental results show that the proposed EUNNet achieves the same or even better performance than previous methods in various tasks: image recognition, object detection, and segmentation. In particular, EUNNet requires less fine-tuning and less sensitivity to hyperparameters than previous methods.

Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography

We propose a distributed Quantum State Tomography (QST) protocol, named Local Stochastic Factored Gradient Descent (Local SFGD), to learn the low-rank factor of a density matrix over a set of local machines. QST is the canonical procedure to characterize the state of a quantum system, which we formulate as a stochastic non-convex smooth optimization problem. Physically, the estimation of a low-rank density matrix helps characterizing the amount of noise introduced by quantum computation. Theoretically, we prove the local convergence of Local SFGD for a general class of restricted strongly convex/smooth loss functions. Local SFGD converges locally to a small neighborhood of the global optimum at a linear rate with a constant step size, while it locally converges exactly at a sub-linear rate with diminishing step sizes. With a proper initialization, local convergence results imply global convergence. We validate our theoretical findings with numerical simulations of QST on the Greenberger-Horne-Zeilinger (GHZ) state.

Knowledge attitude and practice regarding “over the counter” prescription of topical eye steroid among the pharmacists/medical shopkeepers

Purpose: Aim of this study is to assess knowledge, attitude, and practice among the pharmacists/medical shopkeepers regarding “over the counter” prescription of topical eye steroid. Method: It is a prospective cross-sectional questionnaire-based observational study, carried out among 60 pharmacists/pharmacy shopkeepers. Result: Out of 60 participants, 40% had been sensitized regarding topical steroid misuse. 16% had seen complications following OTC dispensing, and 83% had never seen complications following OTC dispensing of medications. 50% were of the opinion of banning the OTC dispensing of ocular medications, 41.6% were against it, and 8.33% were of no opinion. Conclusion: Doctors and pharmacists play a crucial role regarding spreading awareness of self-medication. Government should take proper initiative in educating patients to discourage the unethical and irrational dispensing of medicine by pharmacists.

Changes in Mangrove Blue Carbon under Elevated Atmospheric CO 2

While there is consensus that blue carbon ecosystems, such as mangroves, have an important role in mitigating some aspects of global climate change, little is known about mangrove carbon cycling under elevated atmospheric CO 2 concentrations ( e CO 2 ). Here, we review studies in order to identify pathways for how e CO 2 might influence mangrove ecosystem carbon cycling. In general, e CO 2 alters plant productivity, species community composition, carbon fluxes, and carbon deposition in ways that enhance mangrove carbon storage with e CO 2 . As a result, a negative feedback to climate change exists whereby e CO 2 adds to mangrove’s ability to sequester additional carbon, which in turn reduces the rate by which CO 2 builds. Furthermore, e CO 2 affects warming and sea-level rise (SLR) through alternate pathways, which coinfluence the mangrove response in both antagonistic (i.e., warming = greater carbon loss to decomposition) and synergistic (i.e., SLR = greater soil carbon burial) ways. e CO 2 is projected to become a more prominent driver in the future before reaching a steady state. However, given the complexity of the interactions of biological and environmental factors with e CO 2 , long-term field observations and in situ simulation experiments can help to better understand the mechanisms for proper model initialization to predict future changes in mangrove carbon sequestration.

Relações peso-comprimento de peixes de um estuário do Banco dos Abrolhos, Brasil

Abstract: Aim We investigate the length-weight relationship estimates of seventeen species caught using an artisanal purse seine in the Abrolhos Bank, a tropical estuarine complex in eastern Brazil. Methods From February 2012 to November 2013, fish were collected monthly using an artisanal small purse seine with a total of 84 fish landings. The fish were captured in mangrove margins during high tide and retrieved after six hours at depths ranging from 1.2 to 3 meters. Results A total of 4433 fish specimens from 17 species and nine families were sampled. The coefficient of determination ranged from 0.904 for Centropomus parallelus to 0.987 for Lutjanus cyanopterus. Species presented allometric growing, with Caranx latus, Lutjanus cyanopterus and M. curema exhibing negative allometric while all the other species presented positive allometric growing. We present first data in Brazil to L. cyanopterus and first data in the literature to Lutjanus alexandrei. Conclusions Our results provide novel data of biological attributes for 17 species. By understanding the length-weight relationships and growth patterns of these species, data at stock level may subside proper management initiatives such as fishing restrictions in fishing sites or seasons and mesh size limits.

Identifying relationships between disposal behavior, purchase pattern, price, and awareness with the e-waste management systems

E-waste contains toxic materials which require a special treatment for avoiding environmental pollution and accumulation of harmful substances in human body. According to BTRC there are 173.357 million mobile phone subscribers up to February 2021 in Bangladesh. Among all ICT appliances mobile phone has shortest average lifespan of 2 years. Due to increasing availability of e-services in public and private sector, the use of computer and laptop and internet is growing hurriedly during covid-19. Although Bangladesh has policies and instructions to develop ICT, there are no proper instructions and guidelines for management of the waste of technology. If government doesn’t take proper initiatives to control e-waste the toxic substances of these technological appliances spread over everywhere and pollute the environment, the development project of Digital Bangladesh turns into in development hazard. The aim of this paper was to identify the factors influencing towards the e-waste management system in Bangladesh. Through analyzing 250 questionnaires by SmartPLS software, we documented a positive relationship (p 0.05) between price and e-waste management system in Bangladesh.

Practical initialization of the Nelder–Mead method for computationally expensive optimization problems

Black-box optimization (BBO) algorithms are widely employed by practitioners to address computationally expensive real-world problems such as automatic tuning of machine learning models and evacuation route planning. The Nelder–Mead (NM) method is a well-known local search heuristic for BBO that has been applied to solve many real-world problems from way back because of its promising performance. However, this method has a strong dependence on initialization due to its local search tendency. Nevertheless, a discussion on the proper initialization of the NM method is limited to the recent study by Wessing (Optim Lett 13(4):847–856, 2019), which is solely based on an analysis using the simple sphere function. In this study, we take a further step to improve Wessing’s result by massively investigating how the initialization affects the search performance in views of the initial simplex size and shape and a constraint handling method that is employed on 24 BBO benchmarking problems. Based on the numerical results, we present the empirical best practice for the initialization of the NM method for cases involving a limited evaluation budget.

The landscape of the proximal point method for nonconvex–nonconcave minimax optimization

Minimax optimization has become a central tool in machine learning with applications in robust optimization, reinforcement learning, GANs, etc. These applications are often nonconvex–nonconcave, but the existing theory is unable to identify and deal with the fundamental difficulties this poses. In this paper, we study the classic proximal point method (PPM) applied to nonconvex–nonconcave minimax problems. We find that a classic generalization of the Moreau envelope by Attouch and Wets provides key insights. Critically, we show this envelope not only smooths the objective but can convexify and concavify it based on the level of interaction present between the minimizing and maximizing variables. From this, we identify three distinct regions of nonconvex–nonconcave problems. When interaction is sufficiently strong, we derive global linear convergence guarantees. Conversely when the interaction is fairly weak, we derive local linear convergence guarantees with a proper initialization. Between these two settings, we show that PPM may diverge or converge to a limit cycle.

Trends and Spatial Heterogeneity of Climate Extremes in the Southwestern Region of Bangladesh

This study attempts to investigate the climatic variability in the southwestern area of Bangladesh focusing on temperature and precipitation extremes. Long-term daily records of temperature and precipitation from six weather stations spread over the study area were analyzed. A total of 20 yearly indices were calculated and testified for the trends with the Mann–Kendal test and Sen’s estimator of slope at a 95% confidence interval. Moreover, one-way ANOVA and Tukey–Kramer post-hoc tests were applied to verify the spatial heterogeneity of the climatic indices among the meteorological stations. Findings revealed that Khulna is the worst affected area with significant changes in 12 climatic indices. Jessore and Faridpur followed Khulna with significant changes in 10 and 9 indices, respectively. Among the indices, significant changes in TN10p (frequencies of daily minimum temperature event that falls below the 10th percentile value), TX10p (frequencies of daily maximum temperature event that falls beyond the 10th percentile value), CSDI (cold spell duration indicator), and CDD (consecutive dry day) are the most common phenomenon in the studied region. Five out of six stations have been experiencing significant increasing trends for TN10p. That indicates an overall increase of extreme cold day frequencies in the area. Khulna station showed shreds of evidence of extreme cold temperature instances with a statistically significant fall in the minimum value of the yearly minimum temperatures (TNn). Besides, Khulna also experienced a statistically significant fall in the minimum value of the yearly maximum temperatures. Consistently, the area showed a significant trend of wider cold spells. Similarly, the extremely warm day frequencies have also been increasing significantly for the Khulna, Jessore, and Faridpur areas. Therefore, it is evident that the studied area has been experiencing temperature extremes. On the other hand, precipitation extremes are apparent for only Khulna and Jessore. Both these stations showed increasing trends in heavy precipitation events and wet spells (consecutive precipitation days). ANOVA outcome suggests that the study area has significant spatial heterogeneity in climatic indices. Precipitation indices show high spatial heterogeneity than those of temperature. Among the meteorological stations, Mongla and Ishwardi show the maximum departure than those of others. This study may help policy-makers, researchers, and academicians to take proper initiatives to reduce the impacts of changing climatic parameters in the coastal areas of Bangladesh.

Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent

AbstractThis paper studies early-stopped mirror descent applied to noisy sparse phase retrieval, which is the problem of recovering a $k$-sparse signal $\textbf{x}^\star \in{\mathbb{R}}^n$ from a set of quadratic Gaussian measurements corrupted by sub-exponential noise. We consider the (non-convex) unregularized empirical risk minimization problem and show that early-stopped mirror descent, when equipped with the hypentropy mirror map and proper initialization, achieves a nearly minimax-optimal rate of convergence, provided the sample size is at least of order $k^2$ (modulo logarithmic term) and the minimum (in modulus) non-zero entry of the signal is on the order of $\|\textbf{x}^\star \|_2/\sqrt{k}$. Our theory leads to a simple algorithm that does not rely on explicit regularization or thresholding steps to promote sparsity. More generally, our results establish a connection between mirror descent and sparsity in the non-convex problem of noisy sparse phase retrieval, adding to the literature on early stopping that has mostly focused on non-sparse, Euclidean and convex settings via gradient descent. Our proof combines a potential-based analysis of mirror descent with a quantitative control on a variational coherence property that we establish along the path of mirror descent, up to a prescribed stopping time.

Current knowledge, attitude, and practice (KAP) towards physical activity (PA) and its impact on obesity management in Bangladesh: A cross-sectional study.

The purpose of this study was to evaluate the Bangladeshi people's current knowledge, attitude, and practice (KAP) on obesity and physical activity (PA), as well as the associated factors. The KAP was evaluated using a standard questionnaire among 429 individuals, of whom 75.5% were men and had a mean age (±SD) of 28.9 ± 7.9 years. Using a mobile-based KoBo toolbox v.25.0 program, information was gathered from respondents who resided in various districts. A Chi-square test and a linear regression test were performed to determine the relationship between the variables, and a one-way analysis of variance (ANOVA) was conducted to the determine differences in means. The study showed that more than 95% of participants had good knowledge level, although the attitude and practice levels were low. Based on ANOVA test, the mean knowledge score was significantly different (p < 0.05) with age, marital status, and education; attitude levels with education and body mass index (BMI); and practice levels with education, residence, marital status, and BMI. Linear regression analysis exhibited: the level of knowledge was associated with age (β = -5.34), BMI (β = 3.67), and attitude (β = 0.46) while the level of attitude was associated with education (β = 2.26), BMI (β = -2.42), knowledge (β = 0.2) and practice levels (β = 0.18); and finally, the level of practice was associated with education (β = -3.29), BMI (β = -4.5) and attitude (β = 0.35). The increased prevalence of obesity among the Bangladeshi population was indicated by optimal levels of knowledge but inadequate levels of attitude and practice toward PA. So, proper initiatives should be taken to educate people on the importance of regular PA to manage obesity by policymakers and the government.

Management of patients with bleeding disorders and educational needs regarding hemophilia a in 23 italian emergency departments - Results from a survey conducted in Piedmont.

Haemophilia and von Willebrand disease are the bleeding disorders most frequently encountered in the emergency department (ED), that are often the first point of contact for patients. Evidence suggests that management in the ED is currently suboptimal, mainly because the physicians have few opportunities to deal with this kind of patients. We carried out a survey to investigate the management of patients with haemophilia A in Emergency Departments (EDs), and to understand the training needs of the involved physicians. Overall, in Piedmont Region there are 32 EDs, and considering that our survey was conducted on 21 physicians working in 23 Emergency Departments (EDs), this number is representative of the Region's reality. The interviews were conducted through face-to-face meetings, including general aspects regarding the clinical characteristics and the management of patients, and self-evaluation of knowledge and interest in receiving information about the disease. In 2019, 131 patients with haemophilia A were admitted (108 adults, 23 paediatric). The best-known and most widely available and used treatments were plasma derivatives, followed by first- and second-generation recombinant FVIII. More recent recombinant and bypassing agents were less known. Half of the interviewees considered their -knowledge of bleeding disorders in general and haemophilia in particular to be "basic", and only one third defined it as "good"; however, 86% expressed great interest in receiving information about the topic. The survey confirms the needs related to the clinical management of rare inherited clotting disorders in EDs. The physicians involved are keen to overcome this lack of knowledge, and proper initiatives should be implemented.

Competency mapping building a competent workforce through human resource information system

Purpose: The paper focuses especially on competence mapping, a probable method for enhancing the performance of employees in a corporation by the use of the Human useful resource facts gadget (HRIS). Theoretical framework: Competency mapping is the technique of figuring out key abilities for a company or manner and incorporating those capabilities into diverse approaches such as technique evaluation, schooling, and organizational recruitment. Over the years, highly professional and knowledge based jobs are growing, whilst low-professional jobs are cutting (Mathur & Rawat, 2020). This calls for future skill mapping by proper human resource management initiatives. Methodology: Primary data is used for the study. However secondary data has also been used. Data on employee competence have been accrued from organization information, private interactions with employees, their supervisors, colleagues and employees of different departments. For this motive, several parameters of attributes, capabilities and expertise were compiled in accordance with HR suggestions and process roles that have been authorized by using HRIS of HR department. Later we have performed some statistical analysis by various statistical tools. Findings: In our study, we have found that attributes, skills and knowledge which are related to competency mapping can be increased by Human Resource Information System if it is properly managed.

Mitral regurgitation increases readmission due to heart failure after percutaneous coronary intervention among patients with ST-elevation myocardial infarction: a retrospective data review

Abstract Introduction Post-ST elevation myocardial infarction (STEMI) course can be complicated with mitral regurgitation (MR) which has significant impact on in-patient outcomes and post-discharge course. MR in the setting of STEMI can be due to left ventricular dilatation, papillary muscle rupture or chordal rupture. Purpose In this retrospective study, we aimed to evaluate the impact of MR on readmission within one year after percutaneous coronary intervention (PCI) in STEMI patients. Methods We conducted a single-center retrospective observation cohort study. We included all patients admitted to the hospital with diagnosis of STEMI, underwent PCI during the same admission (index admission) and discharged alive in the period between Jan 1st, 2016 and Sep 30th, 2018. Factors associated with readmission due to heart failure within 1 year of discharge were evaluated using multivariate logistic regression and results were reported as odds ratio (OR) with p-value &amp;lt;0.05 indicating statistical significance. Results A total of 1257 patients were included in our retrospective analysis. The mean age of the study population was 51±10 years. Around 16% (n=206) of the study population had mitral regurgitation (MR) during their admission for STEMI. Among them, 195 patients had newly discovered MR. MR severity was mild in 196 (95%) patients with MR. Unplanned readmission due to cardiac reasons within 1 year of discharge occurred in 103 (8.2%) patients. Among them, 37 (3%) were readmitted due to heart failure. MR was found to increase the likelihood of readmission due to heart failure within one year after PCI among patients with STEMI by three times (aOR=3.13, 95% CI 1.39–7.03; p-value 0.006). As demonstrated in table 1, other positive predictors for readmission due to heart failure were female gender (aOR=3.80, 95% CI 1.22–11.86; p-value 0.021), chronic kidney disease (aOR=4.56, 95% CI 1.22–17.03; p-value 0.024), and clinical heart failure during the index admission (aOR=4.82, 95% CI 1.53–15.15; p-value 0.007). Interestingly, reduced left ventricular ejection fraction was not a significant predictor of heart failure readmission. Conclusion Mitral regurgitation is relatively common in STEMI and most frequently presents with mild severity. In our study, MR was found to be a strong predictor for readmission due to heart failure within one year after PCI among patients with STEMI, which may warrant frequent follow-up for these patients and proper initiation of and titration of guideline-directed medical therapy (GDMT). Funding Acknowledgement Type of funding sources: None.

Creation of standard work for the management of outpatient oral antineoplastic therapy.

369 Background: Recently, there has been a dramatic increase in the use of oral antineoplastics for the treatment of various malignancies. The development of these agents has been so rapid that the infrastructure needed for their appropriate supervision has trailed their availability. Previously at Virginia Mason, there was no standard work established for the management of patients starting these agents and consequently there were defects noted, including delays in the medications’ delivery to the patient, lack of appropriate teaching regarding potential medication toxicities and even delayed provider follow-up. The goal of this project was to create standard work around the treatment initiation and follow-up of all patients starting outpatient oral antineoplastic therapy. Methods: A multi-disciplinary team of providers, nurses, and pharmacists held a flow mapping session to identify defects and waste points in the process between the prescription being written until the first provider follow-up visit after medication delivery. The team focused on decreasing the amount of time between prescription initiation and first clinic follow up, as well as increasing the percentage of RN teaching sessions performed and documented. This involved the creation of a dedicated inbox in the Electronic Medical Record (EMR) to which pharmacy and care manager nurses had exclusive access to facilitate rapid communication between team members. The work also resulted in the creation of an antineoplastics teaching template which was used to document teaching on potential treatment toxicities. Results: Standard work was created for the outpatient oral antineoplastic administration process and teaching documentation. Using the new tools, lead time was improved by 21.7% and teaching documentation was improved by 185% at the 30-day mark. These metrics were monitored over a 3 month period, and at the end of 90 days the lead time improvement was maintained at 21.2% and teaching documentation improvement at 110% (Table). Conclusions: The rapid development of oral antineoplastic medications has required Oncology practices to develop more robust workflow infrastructure to administer these medications properly and safely. We created standard work for the proper initiation and follow-up of oral antineoplastic therapy. In doing so we identified specific defects and instances of waste and were able to improve the workflow process to address these issues, resulting in measurable quality improvements and overall better patient care.[Table: see text]