Quality improvement in ammonium nitrate production using Six Sigma methodology

Six sigma has been used in different industries to reach operational excellence. However, in the chemical industry, the application of this methodology is limited. This research presents an implementation of the six sigma method for ammonium nitrate (AN) content optimization in condensate production for a fertilizer company in Colombia. The paper aims to determine the levels for input variables in the process, to meet desirable standards for condensate quality in terms of ammonium nitrate content. Based on the DMAIC steps implementation, it was possible to establish the main variables affecting the condensate quality and their optimal levels to reach an ammonium nitrate content below 15,000 ppm. These results demonstrate the impact that a six sigma project may have on operational effectiveness and quality improvement for meeting the customer requirements

The obesity gene, TMEM18, is of ancient origin, found in majority of neuronal cells in all major brain regions and associated with obesity in severely obese children

<p>Abstract</p> <p>Background</p> <p>TMEM18 is a hypothalamic gene that has recently been linked to obesity and BMI in genome wide association studies. However, the functional properties of TMEM18 are obscure.</p> <p>Methods</p> <p>The evolutionary history of TMEM18 was inferred using phylogenetic and bioinformatic methods. The gene's expression profile was investigated with real-time PCR in a panel of rat and mouse tissues and with immunohistochemistry in the mouse brain. Also, gene expression changes were analyzed in three feeding-related mouse models: food deprivation, reward and diet-induced increase in body weight. Finally, we genotyped 502 severely obese and 527 healthy Swedish children for two SNPs near TMEM18 (rs6548238 and rs756131).</p> <p>Results</p> <p>TMEM18 was found to be remarkably conserved and present in species that diverged from the human lineage over 1500 million years ago. The TMEM18 gene was widely expressed and detected in the majority of cells in all major brain regions, but was more abundant in neurons than other cell types. We found no significant changes in the hypothalamic and brainstem expression in the feeding-related mouse models. There was a strong association for two SNPs (rs6548238 and rs756131) of the TMEM18 locus with an increased risk for obesity (p = 0.001 and p = 0.002).</p> <p>Conclusion</p> <p>We conclude that TMEM18 is involved in both adult and childhood obesity. It is one of the most conserved human obesity genes and it is found in the majority of all brain sites, including the hypothalamus and the brain stem, but it is not regulated in these regions in classical energy homeostatic models.</p

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Challenges and Future Direction of Time-Sensitive Software-Defined Networking (TSSDN) in Automation Industry

In Industry 4.0, Cyber physical system (CPS) is suffered from queuing delay during the process of data gathering and feedback generation by which affects the efficiency of providing hard real-time guarantees. Hard real-time cyber physical system requires software and hardware to operate strictly within the deadline. Time-Sensitive Software-Defined Networking (TSSDN) is an architecture which utilizes the centralized network controller in Software-Defined Networking (SDN) to facilitate the operation of software and hardware in CPS globally. Time-sensitive-aware scheduling traffic system in TSSDN is capable to minimize the queuing delay in the network which leads to hard real-time guarantees. Hence, the potential opportunities of TSSDN in automation industry has motivate the further investigate of its current states. This paper will discuss the challenges of TSSDN and suggest its future direction enhancement