Exposure Assessment and Sensitivity Analysis for Chilled Shrimp During Distribution: A Case Study of Home Delivery Services in Taiwan

Abstract Background Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance. Results We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model. Conclusions Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.

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Implementation and effectiveness of drive-through medication pick-up and home delivery services. A patient safety initiative during COVID-19 pandemic

Journal of Patient Safety and Risk Management ◽

10.1177/25160435211009038 ◽

2021 ◽

pp. 251604352110090

Author(s):

Haneen K AlAbbasi ◽

Shabeer A Thorakkattil ◽

Syed I Mohiuddin ◽

Habib S Nemr ◽

Rita Jabbour ◽

...

Keyword(s):

Patient Safety ◽

Implementation Process ◽

Home Delivery ◽

Successful Implementation ◽

Social Distancing ◽

Pharmacy Department ◽

Ensure Patient Safety ◽

Number Of Patients ◽

Delivery Services ◽

Safety Initiative

Introduction With the emergence of the first COVID-19 case in Saudi Arabia, Johns Hopkins Aramco Healthcare has immediately executed the appropriate protocols in response to this severe global crisis. The pharmacy department at Johns Hopkins Aramco Healthcare continues to play an essential role in providing the safest, efficient, and effective service to its eligible patients. In response to the COVID-19 pandemic, the pharmacy department acted by implementing a drive-through pharmacy and home delivery services as new person-centered services to ensure patient safety. These two new services were initiated to protect both the pharmacist and the patient from COVID-19 infections as they ensure social distancing and reduce patients’ visits to the walk-in pharmacies, hence providing valuable and convenient services during this pandemic. Objective This article aims to describe the implementation processes and effectiveness of drive-through medication pick-up and home-delivery services as a patient safety initiative during the COVID-19 pandemic. Method The implementation process of the drive-through and home delivery services are explained in detail. The utilization of these two services is evaluated by measuring the number of patients and prescriptions between April 2020 and August 2020. Result The increased utilization of drive-through medication pick-up and home delivery services in terms of the number of patients and prescriptions ensures patient safety by minimizing infection risk. Conclusion The increase in the utilization of drive-through medication pick-up and home delivery services reflects its successful implementation during the COVID-19 pandemic. Both services meet the pandemic’s social-distancing requirements and minimize risks of infections, which will ensure patient safety during the COVID-19 pandemic.

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Acceptability of remote prescribing and postal delivery services for contraceptive pills and treatment of uncomplicated Chlamydia trachomatis

BMJ Sexual & Reproductive Health ◽

10.1136/bmjsrh-2020-200687 ◽

2020 ◽

pp. bmjsrh-2020-200687

Author(s):

Tom Nadarzynski ◽

Ynez Symonds ◽

Robert Carroll ◽

Jo Gibbs ◽

Sally Kidsley ◽

...

Keyword(s):

Online Survey ◽

Home Delivery ◽

Transmitted Infection ◽

Sexually Transmitted ◽

Sti Testing ◽

Contraceptive Pills ◽

Remote Management ◽

Delivery Services ◽

The Cost ◽

To Receive

ObjectivesThe digitalisation of sexual and reproductive health (SRH) services offers valuable opportunities to deliver contraceptive pills and chlamydia treatment by post. We aimed to examine the acceptability of remote prescribing and ‘medication-by-post’ in SRH.Study designAn online survey assessing attitudes towards remote management was distributed in three UK SRH clinics and via an integrated sexually transmitted infection (STI) postal self-sampling service. Logistic regressions were performed to identify potential correlates.ResultsThere were 1281 participants (74% female and 49% <25 years old). Some 8% of participants reported having received medication via post and 83% were willing to receive chlamydia treatment and contraceptive pills by post. Lower acceptability was observed among participants who were: >45 years old (OR 0.43 (95% CI 0.23–0.81)), screened for STIs less than once annually (OR 0.63 (0.42–0.93)), concerned about confidentiality (OR 0.21 (0.90–0.50)), concerned about absence during delivery (OR 0.09 (0.02–0.32)) or unwilling to provide blood pressure readings (OR 0.22 (0.04–0.97)). Higher acceptability was observed among participants who reported: previously receiving medication by post (OR 4.63 (1.44–14.8)), preference for home delivery over clinic collection (OR 24.1 (11.1–51.9)), preference for home STI testing (OR 10.3 (6.16–17.4)), ability to communicate with health advisors (OR 4.01 (1.03–15.6)) and willingness to: register their real name (OR 3.09 (1.43–10.6)), complete online health questionnaires (OR 3.09 (1.43–10.6)) and use generic contraceptive pills (OR 2.88 (1.21–6.83)).ConclusionsPostal treatment and entering information online to allow remote prescribing were acceptable methods for SRH services and should be considered alongside medication collection in pharmacies. These methods could be particularly useful for patients facing barriers in accessing SRH. The cost-effectiveness and implementation of these novel methods of service delivery should be further investigated.

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Sensitivity Analysis of Fuzzy Activity-Based Life Cycle Costing

MATEC Web of Conferences ◽

10.1051/matecconf/201822505002 ◽

2018 ◽

Vol 225 ◽

pp. 05002

Author(s):

Freselam Mulubrhan ◽

Ainul Akmar Mokhtar ◽

Masdi Muhammad

Keyword(s):

Sensitivity Analysis ◽

Life Cycle ◽

Interest Rate ◽

Life Cycle Costing ◽

High Impact ◽

Final Output ◽

Left And Right ◽

The Interest Rate ◽

Operation Cost

A sensitivity analysis is typically conducted to identify how sensitive the output is to changes in the input. In this paper, the use of sensitivity analysis in the fuzzy activity based life cycle costing (LCC) is shown. LCC is the most frequently used economic model for decision making that considers all costs in the life of a system or equipment. The sensitivity analysis is done by varying the interest rate and time 15% and 45%, respectively, to the left and right, and varying 25% of the maintenance and operation cost. It is found that the operation cost and the interest rate give a high impact on the final output of the LCC. A case study of pumps is used in this study.

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Improving Casthouse Throughput Using Discrete-Event Modelling

Materials Science Forum ◽

10.4028/www.scientific.net/msf.693.3 ◽

2011 ◽

Vol 693 ◽

pp. 3-9 ◽

Cited By ~ 2

Author(s):

Bruce Gunn ◽

Yakov Frayman

Keyword(s):

Sensitivity Analysis ◽

Discrete Event ◽

Casting Machine ◽

Production Data ◽

Model Output ◽

Arrival Times ◽

Event Simulation ◽

Modelling System ◽

Key Parameter

The scheduling of metal to different casters in a casthouse is a complicated problem, attempting to find the balance between pot-line, crucible carrier, furnace and casting machine capacity. In this paper, a description will be given of a casthouse modelling system designed to test different scenarios for casthouse design and operation. Using discrete-event simulation, the casthouse model incorporates variable arrival times of metal carriers, crucible movements, caster operation and furnace conditions. Each part of the system is individually modelled and synchronised using a series of signals or semaphores. In addition, an easy to operate user interface allows for the modification of key parameters, and analysis of model output. Results from the model will be presented for a case study, which highlights the effect different parameters have on overall casthouse performance. The case study uses past production data from a casthouse to validate the model outputs, with the aim to perform a sensitivity analysis on the overall system. Along with metal preparation times and caster strip-down/setup, the temperature evolution within the furnaces is one key parameter in determining casthouse performance.

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