‘Dead people don’t claim’: A psychopolitical autopsy of UK austerity suicides

One of the symptoms of post financial crisis austerity in the UK has been an increase in the numbers of suicides, especially by people who have experienced welfare reform. This article develops and utilises an analytic framework of psychopolitical autopsy to explore media coverage of ‘austerity suicide’ and to take seriously the psychic life of austerity (internalisation, shame, anxiety), embedding it in a context of social dis-ease. Drawing on three distinct yet interrelated areas of literature (the politics of affect and psychosocial dynamics of welfare, post and anti-colonial psychopolitics, and critical suicidology), the article aims to better understand how austerity ‘kills’. Key findings include understanding austerity suicides as embedded within an affective economy of the anxiety caused by punitive welfare retrenchment, the stigmatisation of being a recipient of benefits, and the internalisation of market logic that assigns value through ‘productivity’ and conceptualises welfare entitlement as economic ‘burden’. The significance of this approach lies in its ability to widen analytic framing of suicide from an individual and psychocentric focus, to illuminate culpability of government reforms while still retaining the complexity of suicide, and thus to provide relevant policy insights about welfare reform

Comparative analyses on medium optimization using one-factor-at-a-time, response surface methodology, and artificial neural network for lysine–methionine biosynthesis by Pediococcus pentosaceus RF-1

Optimization strategy that encompassed one-factor-at-a-time (OFAT), response surface methodology (RSM), and artificial neural network method was implemented during medium formulation with specific aim for lysine-methionine biosynthesis employing a newly isolated strain of Pediococcus pentosaceus RF-1. OFAT technique was used in the preliminary screening of factors (molasses, nitrogen sources, fish meal, glutamic acid and initial medium pH) before proceeded to optimization study. Implementation of central composite design of experiment subsequently generated 30 experimental runs based on four factors (molasses, fish meal, glutamic acid, and initial medium pH). From RSM analysis, a quadratic polynomial model can be devoted to describing the relationship between various medium components and responses. It also suggested that using molasses (9.86 g/L), fish meal (10.06 g/L), glutamic acid (0.91 g/L), and initial medium pH (5.30) would enhance the biosynthesis of lysine (15.77 g/L) and methionine (4.21 g/L). Alternatively, a three-layer neural network topography at 4-5-2 predicted a further improvement in the biosynthesis of lysine (16.52 g/L) and methionine (4.53 g/L) by using formulation composed of molasses (10.02 g/L), fish meal (18.00 g/L), and glutamic acid (1.17 g/L) with initial medium pH (4.26), respectively