Investigating the potential for a user-driven electricity monitoring application to provide useful electricity consumption patterns

Conventional electricity usage monitoring involves complex data collection via costly and intrusive hardware installation. There is a perceived need for a simple and affordable tool that provides users with feedback about their electricity consumption without the hardware installation. This study involves the design and development of a user driven mobile and desktop application that provides users with information on electricity usage patterns and historical trends. The application was designed using Ionic Framework, a tool ideal for the design of hybrid applications that are compatible with both desktop Windows devices and mobile Android devices. The goal of the research will be that the user will track their appliance usage on the application whilst taking electricity meter readings at regular intervals to calculate appliance-specific consumption. The data is added to the mobile or desktop application, which then provides users with a comprehensive display of the electricity usage patterns and trends. The objective is to provide users with the information required so that they can start understanding their electricity consumption better and it is a first step towards empowering the user to make smart decisions at home that will reduce their electricity consumption. The USE (Usefulness, Satisfaction, Ease of Use and Ease of Learning) questionnaire was used to gather user experience feedback from participants about user experience. The USE questionnaire tests the perceived Usefulness, Satisfaction, Ease of Use and Ease of Learnability The 31 individuals who initially volunteered to take part in the study are all residents of the City of Cape Town Municipality, aged between 20 and 80 years old. Not all participants are home owners; some are tenants in their premises. The sample group was selected on a convenience basis, and social media group posts were also used to reach individuals with a potential interest in the study. The two motivating factors that were considered to identify individuals who could potentially have an interest in the study were cost saving and environmental impact. 21 volunteers completed the study and returned the USE questionnaire. The study findings showed that all participants believe that using the application helped them to better understand their electricity consumption

Capability profile of an additively manufacturing machine based on the selective laser melting process

Final year project, 2011ENGLISH ABSTRACT: Additive Manufacturing is a relatively young technology that involves the layer-by-layer addition of material in solid, liquid or powder form to create parts. It is ideally suited for producing complex parts with small production batches. The industrial applications of these techniques as well as the advantages and disadvantages of Additive Manufacturing are explored and an overview of the different Additive Manufacturing techniques is detailed. Selective Laser Melting is one Additive Manufacturing technique that is discussed further and the characteristics of the M2 Laser CUSING machine and the EOSINT M 270 machine are detailed. A capability profile of various Additive Manufacturing machines is ultimately formed and this capability profile is used to identify the applicability of the different machine types to the Tooling, Medical and Aerospace/Motor Industries.AFRIKAANSE OPSOMMING: Toevoegende Vervaardiging is 'n nuwe tegnologie wat behels dat laag-vir-laag toevoeging van materiaal in die vaste-, vloeistof of poeier vorm om produkte te maak. Dit is ideaal geskik vir die vervaardiging van komplekse dele met 'n klein produksie lotte. Die industriële toepassings van hierdie tegnieke asook die voordele en nadele van toevoegende vervaardiging is ondersoek en 'n oorsig van die verskillende toevoeging vervaardiging tegnieke is bespreek. SLM is een Toevoegende Vervaardiging tegniek wat verder bespreek is asook die kenmerke van die M2 Laser CUSING masjien en die EOSINT M 270 masjien. 'n Vermoë profiel van verskeie Toevoeging Vervaardiging masjiene is uiteindelik gevorm en hierdie moontlikheid profiel word gebruik om die toepaslikheid van die verskillende tipes masjien met betrekking tot die Tooling, Mediese en Vlug / Motoriese Sektore

Monogenic variants in dystonia: an exome-wide sequencing study

Background Dystonia is a clinically and genetically heterogeneous condition that occurs in isolation (isolated dystonia), in combination with other movement disorders (combined dystonia), or in the context of multisymptomatic phenotypes (isolated or combined dystonia with other neurological involvement). However, our understanding of its aetiology is still incomplete. We aimed to elucidate the monogenic causes for the major clinical categories of dystonia. Methods For this exome-wide sequencing study, study participants were identified at 33 movement-disorder and neuropaediatric specialty centres in Austria, Czech Republic, France, Germany, Poland, Slovakia, and Switzerland. Each individual with dystonia was diagnosed in accordance with the dystonia consensus definition. Index cases were eligible for this study if they had no previous genetic diagnosis and no indication of an acquired cause of their illness. The second criterion was not applied to a subset of participants with a working clinical diagnosis of dystonic cerebral palsy. Genomic DNA was extracted from blood of participants and whole-exome sequenced. To find causative variants in known disorder-associated genes, all variants were filtered, and unreported variants were classified according to American College of Medical Genetics and Genomics guidelines. All considered variants were reviewed in expert round-table sessions to validate their clinical significance. Variants that survived filtering and interpretation procedures were defined as diagnostic variants. In the cases that went undiagnosed, candidate dystonia-causing genes were prioritised in a stepwise workflow. Findings We sequenced the exomes of 764 individuals with dystonia and 346 healthy parents who were recruited between June 1, 2015, and July 31, 2019. We identified causative or probable causative variants in 135 (19%) of 728 families, involving 78 distinct monogenic disorders. We observed a larger proportion of individuals with diagnostic variants in those with dystonia (either isolated or combined) with coexisting non-movement disorder-related neurological symptoms (100 [45%] of 222; excepting cases with evidence of perinatal brain injury) than in those with combined (19 [19%] of 98) or isolated (16 [4%] of 388) dystonia. Across all categories of dystonia, 104 (65%) of the 160 detected variants affected genes which are associated with neurodevelopmental disorders. We found diagnostic variants in 11 genes not previously linked to dystonia, and propose a predictive clinical score that could guide the implementation of exome sequencing in routine diagnostics. In cases without perinatal sentinel events, genomic alterations contributed substantively to the diagnosis of dystonic cerebral palsy. In 15 families, we delineated 12 candidate genes. These include IMPDH2, encoding a key purine biosynthetic enzyme, for which robust evidence existed for its involvement in a neurodevelopmental disorder with dystonia. We identified six variants in IMPDH2, collected from four independent cohorts, that were predicted to be deleterious de-novo variants and expected to result in deregulation of purine metabolism. Interpretation In this study, we have determined the role of monogenic variants across the range of dystonic disorders, providing guidance for the introduction of personalised care strategies and fostering follow-up pathophysiological explorations