Cassidy Silbernagel, Adedeji Aremu and Ian Ashcroft
Metal-based additive manufacturing is a relatively new technology used to fabricate metal objects within an entirely digital workflow. However, only a small number of different…
Abstract
Purpose
Metal-based additive manufacturing is a relatively new technology used to fabricate metal objects within an entirely digital workflow. However, only a small number of different metals are proven for this process. This is partly due to the need to find a new set of parameters which can be used to successfully build an object for every new alloy investigated. There are dozens of variables which contribute to a successful set of parameters and process parameter optimisation is currently a manual process which relies on human judgement.
Design/methodology/approach
Here, the authors demonstrate the application of machine learning as an alternative method to determine this set of process parameters, the subject of this test is the processing of pure copper in a laser powder bed fusion printer. Data in the form of optical images were collected over the course of traditional parameter optimisation. These images were segmented and fed into a convolutional autoencoder and then clustered to find the clusters which best represented a high-quality result. The clusters were manually scored according to their quality and the results applied to the original set of parameters.
Findings
It was found that the machine-learned clustering and subsequent scoring reflected many of the observations which were found in the traditional parameter optimisation process.
Originality/value
This exercise, as well as demonstrating the effectiveness of the ML approach, indicates an opportunity to fully automate the approach to process optimisation by applying labels to the data, hence, an approach that could also potentially be suited for on-the-fly process optimisation.
Graphical abstract
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Ediomo-Ubong Nelson, Ogochukwu Winifred Odeigah and Emeka W. Dumbili
The purpose of this study is to understand the complex interplay between illicit opioids trade and consumption practices and state policies that aim to reduce their misuse.
Abstract
Purpose
The purpose of this study is to understand the complex interplay between illicit opioids trade and consumption practices and state policies that aim to reduce their misuse.
Design/methodology/approach
The study adopted an exploratory design. Data were gathered through in-depth interviews with 31 commercially oriented drug dealers in Uyo, Nigeria. The framework approach was used in data analyses, while “friction” provided the interpretive lens.
Findings
Accounts revealed public concerns over the misuse of tramadol and other opioids among young people and the associated health and social harms. These concerns provided support for enforcement-based approaches to prescription opioids control, including police raids on pharmacy stores. These measures did not curtail opioids supply and consumption. Instead, they constrained access to essential medicines for pain management, encouraged illegal markets and fuelled law enforcement corruption in the form of police complicity in illegal tramadol trade.
Research limitations/implications
The findings reveal the frictions of drug control in Nigeria, wherein enforcement-based approaches gained traction through public concerns about opioids misuse but also faced resistance due to the persistence of non-medical use and illegal supply channels made possible by law enforcement complicity. These indicate a need to prioritize approaches that seek to reduce illegal supply and misuse of opioids while ensuring availability of these medications for health-care needs.
Originality/value
The study is unique in its focus on the creative tension that exists between state control measures and local opioids supply and consumption practices.
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Şerif Canbay and Mustafa Kırca
The study aims to determine whether there is a bidirectional causality relationship between health expenditures and per capita income in Brazil, Russia, India, China, South Africa…
Abstract
Purpose
The study aims to determine whether there is a bidirectional causality relationship between health expenditures and per capita income in Brazil, Russia, India, China, South Africa and Turkey (BRICS+T).
Design/methodology/approach
For that purpose, the 2000–2018 period data of the variables were tested with the Kónya (2006) panel causality test. Additionally, the causality relationships between public and private health expenditures and per capita income were also investigated in the study.
Findings
According to the analysis results, there is no statistically significant causality relationship from total health expenditures and public health expenditures to per capita income in the relevant countries. Besides, there is a unidirectional causality relationship from private health expenditures to per capita income only in Turkey. On the other hand, a unidirectional causality relationship from per capita income to total health expenditures in China, Russia, Turkey and South Africa and from per capita income to public health expenditures in India, Russia, Turkey and South Africa were determined. Consequently, a causality relationship from per capita income to private health expenditures was found out in Russia and Turkey.
Originality/value
The variables are tested for the first time for BRICS+T countries, vis-à-vis the period under consideration and the method used.