Statistical analysis of machining parameters on burr formation, surface roughness and energy consumption during milling of aluminium alloy Al 6061-T6

Due to the increasing demand for higher production rates in the manufacturing sector, there is a need to manufacture finished or near-finished parts. Burrs and surface roughness are the two most important indicators of the surface quality of any machined parts. In addition to this, there is a constant need to reduce energy consumption during the machining operation in order to reduce the carbon footprint. Milling is one of the most extensively used cutting processes in the manufacturing industry. This research was conducted to investigate the effect of machining parameters on surface roughness, burr width, and specific energy consumption. In the present research, the machining parameters were varied using the Taguchi L9 array design of experiments, and their influence on the response parameters, including specific cutting energy, surface finish, and burr width, was ascertained. The response trends of burr width, energy consumption, and surface roughness with respect to the input parameters were analyzed using the main effect plots. Analysis of variance indicated that the cutting speed has contribution ratios of 55% and 47.98% of the specific cutting energy and burr width on the down-milling side, respectively. On the other hand, the number of inserts was found to be the influential member, with contribution ratios of 68.74% and 35% of the surface roughness and burr width on the up-milling side. The validation of the current design of the experiments was carried out using confirmatory tests in the best and worst conditions of the output parameters.Web of Science1522art. no. 806

COVID 19:Seroprevalence and vaccine responses in UK dental care professionals

Dental care professionals (DCPs) are thought to be at enhanced risk of occupational exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, robust data to support this from large-scale seroepidemiological studies are lacking. We report a longitudinal seroprevalence analysis of antibodies to SARS-CoV-2 spike glycoprotein, with baseline sampling prior to large-scale practice reopening in July 2020 and follow-up postimplementation of new public health guidance on infection prevention control (IPC) and enhanced personal protective equipment (PPE). In total, 1,507 West Midlands DCPs were recruited into this study in June 2020. Baseline seroprevalence was determined using a combined IgGAM enzyme-linked immunosorbent assay and the cohort followed longitudinally for 6 mo until January/February 2021 through the second wave of the coronavirus disease 2019 pandemic in the United Kingdom and vaccination commencement. Baseline seroprevalence was 16.3%, compared to estimates in the regional population of 6% to 7%. Seropositivity was retained in over 70% of participants at 3- and 6-mo follow-up and conferred a 75% reduced risk of infection. Nonwhite ethnicity and living in areas of greater deprivation were associated with increased baseline seroprevalence. During follow-up, no polymerase chain reaction–proven infections occurred in individuals with a baseline anti–SARS-CoV-2 IgG level greater than 147.6 IU/ml with respect to the World Health Organization international standard 20-136. After vaccination, antibody responses were more rapid and of higher magnitude in those individuals who were seropositive at baseline. Natural infection with SARS-CoV-2 prior to enhanced PPE was significantly higher in DCPs than the regional population. Natural infection leads to a serological response that remains detectable in over 70% of individuals 6 mo after initial sampling and 9 mo from the peak of the first wave of the pandemic. This response is associated with protection from future infection. Even if serological responses wane, a single dose of the Pfizer-BioNTech 162b vaccine is associated with an antibody response indicative of immunological memory

Efficacy of learning through play plus intervention to reduce maternal depression in women with malnourished children: A randomized controlled trial from Pakistan

BACKGROUND:The risk factors and adverse outcomes related to maternal depression and child malnutrition are a leading cause of morbidity and mortality in low and middle-income countries (LMIC) including Pakistan. Above 25% of women suffer from maternal depression. Up to 50% children are under-nourished which contributes to 35% of all under-5 deaths in the country. AIM:To determine the efficacy of Learning through Play Plus Thinking Healthy Program (LTP Plus) intervention to reduce maternal depression in mothers with undernourished children. METHODS:In this randomised controlled trial, all eligible mothers presenting to the paediatric departments were invited to participate in the study. Out of the total 256 mothers screened, 107 were included, 54 of those were randomly allocated to LTP Plus group and 53 to treatment as usual (TAU). Edinburgh Postnatal Depression Scale (EPDS) was used to screen for depression. Hamilton Depression Rating Scale (HDRS), Maternal Attachment Inventory (MAI), Social Support Scale (OSLO-3) and the Euro-QoL (EQ-5D) were used to measure the severity of depression, mother-child attachment, level of support and health related quality of life dimensions. Assessments were completed at baseline, end of intervention (3 months from baseline) and at 6 months from baseline. RESULTS:Mothers in the LTP Plus group significantly showed improvements in depression (p<0.001), social support (p = 0.02) and quality of life (p<0.001) at the end of the intervention (LTP Plus), as compared to the TAU group, which were sustained up to 6 months after baseline. CONCLUSION:The outcomes of LTP Plus intervention for mothers of malnourished children show promising results in reducing maternal depression and improving child outcomes. A full trial with longer-term outcomes and cost-effectiveness needs to be conducted

Envisioning a building information model (BIM) integrated building performance visualization (iPViz) interface

The dispersed nature, complexity, and amount of information available in modern buildings with advanced management and control systems, makes it challenging for building operators to holistically understand building performance. One of the reasons is the lack of integration among multiple information sources and tools making it harder to align performance data with user’s experiential model of the physical systems. The goal of this research is to envision an integrated building performance visualization interface that provides contextually relevant, on-demand information to building operators. The research was executed in three sequential phases including an extensive literature review, a detailed case study, and development of a mockup prototype. I conducted an extensive literature review to capture the state-of-the-art in related academic domains and to establish a point-of-departure for the proposed research. The case study focused on a high performance building to understand operation and maintenance practices with an emphasis on building management systems (BMS). The case study involved two phases. In the first phase, I collected qualitative data by conducting interviews, contextual inquiries, and shadowing of building operators. In the second phase, I conducted a survey to collect quantitative data that further expanded upon the initial findings from first phase. The results revealed several overlapping and interrelated challenges that were further analyzed and grouped into two sets of issues: visualization related and system’s interactivity related. I also identified two core problems in the overall use of the BMS: a lack of spatial and informational context, and disconnected monitoring of energy and system performance data. Based on the findings, I developed a BIM Integrated Performance Visualization (iPViz) interface mockup as a proof-of-concept to support the work of building operators. I demonstrated the proposed interface features by using storyboard illustrations based on task-specific scenarios. I designed the scenarios and storyboards to demonstrate the proposed interface’s ability to provide spatially contextual information in response to a building operator’s interactions. The research provides some future directions for the development of BIM-based performance visualization systems. Additional research is required to implement and evaluate the proposed solutions and to analyze their effectiveness in facilitating building management functions.Applied Science, Faculty ofCivil Engineering, Department ofGraduat

Center for Interactive Research on Sustainability (CIRS) : final report

The Centre for Interactive Research on Sustainability (CIRS) located on 2210 West Mall; is one of the greenest buildings in British Columbia at its time of construction - developed primarily in response to the challenge of creating a more sustainable society. The LCA study was completed at the request of UBC Social Ecological Economic Development Studies (SEEDS) to transparently communicate the environmental benefits of University’s first net-zero energy and regenerative building and further pave the ways for similar future ventures. Although first of its kind study of a Green Building in UBC, CIRS LCA study is a part of UBC wide academic building LCA data repository and would contribute to knowledge built up of that database. A formulated approach as per ISO 14044 standard, was adopted to complete the LCA study as comprehensively as possible. The approach was carried off from quantity take-off using different state-of- art software, to preparing as thorough an inventory of building components & assemblies as was possible from the available information, modeling was done with Athena Impact Estimator which has one of the largest life cycle inventory database in North America. Assumptions and limitations of the software as well as the data were document in order to make the process transparent for any future reference or comparisons, this included explicit documentation in the form of input and assumption documents appendix to this report. From the analysis it is evident that CIRS stand up to the test of being sustainable and contributing positively towards its environment. Despite the challenges of whole building LCA study we are confident that this study would be a contribution towards knowledge built up and would encourage further such studies; strengthening the process and providing knowledge based information tool for future policies. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”Applied Science, Faculty ofCivil Engineering, Department ofUnreviewedUndergraduat

Improvement of a Memory Profiling Tool, MALT

Project Specification This project focuses on improving the web-based user interface for the MALT memory profiling tool. In particular, it introduces a new and improved source code viewer which shows annotations for memory statistics on memory allocating lines on the source code. Also, it adds a new call-tree viewer to the interface which allows the user to browse through the function calls in the profiled program to see where memory is being allocated and freed and exactly how much. Abstract MALT is a memory profiling tool designed for profiling programs on the Linux platform. MALT generated profile data can be viewed in the MALT GUI which is a web-based program for visualizing data and exploring code. To further the development of MALT GUI, we improved its Source Code Viewer by redesigning the page and replacing the code editor. We compare several syntax highlighters and code editors and describe why we used Prism.js library for syntax highlighting plus its advantages such as being faster, leaner and easier to extend. We also discuss the performance gains and reduction in page load time gained by these changes. Also, we discuss the addition of a new feature to the MALT GUI called a Call Tree Viewer to generate and view Call Graphs with memory statistics. We compare several graphing libraries for their suitability to make a call graph and why we selected Graphviz for MALT GUI. We discuss the implementation of call tree for transforming and filtering the data before it is rendered and shown to the user

Statistical Analysis of Machining Parameters on Burr Formation, Surface Roughness and Energy Consumption during Milling of Aluminium Alloy Al 6061-T6

Due to the increasing demand for higher production rates in the manufacturing sector, there is a need to manufacture finished or near-finished parts. Burrs and surface roughness are the two most important indicators of the surface quality of any machined parts. In addition to this, there is a constant need to reduce energy consumption during the machining operation in order to reduce the carbon footprint. Milling is one of the most extensively used cutting processes in the manufacturing industry. This research was conducted to investigate the effect of machining parameters on surface roughness, burr width, and specific energy consumption. In the present research, the machining parameters were varied using the Taguchi L9 array design of experiments, and their influence on the response parameters, including specific cutting energy, surface finish, and burr width, was ascertained. The response trends of burr width, energy consumption, and surface roughness with respect to the input parameters were analyzed using the main effect plots. Analysis of variance indicated that the cutting speed has contribution ratios of 55% and 47.98% of the specific cutting energy and burr width on the down-milling side, respectively. On the other hand, the number of inserts was found to be the influential member, with contribution ratios of 68.74% and 35% of the surface roughness and burr width on the up-milling side. The validation of the current design of the experiments was carried out using confirmatory tests in the best and worst conditions of the output parameters

Design and Modeling of a Fuel Cell System Using Biomass Feedstock as a Biofuel

This paper aims to model ceramic fuel cell system based on low-temperature planar solid oxide fuel cell (SOFC) different biogases fuels from multiple biomasses, that is, animal waste, redwood, rice husk and sugar cane. Biomass is a better choice for the generation of energy globally. Therefore, there is a focus on the most available biomass resources in the country that can be used as clean energy sources. This developed model is designed by thermodynamic analysis and electrochemical calculations using MATLAB. The designed model is a lumped parameter model based on the steady-state one-dimensional flow. In this model, all calculated power and flow rate values were kept as positive values. Also, the system is considered to be free of leaks, and heat loss is neglected. The operating temperature and pressure are assumed to be 500–700 \ub0C and the partial pressure is set at three different pressures; P1 (1 bar), P2 (2 bar), and P3 (3 bar), respectively, and fuel utilization factor is 80%. It is observed that the best performance is obtained with animal-waste based biogas at 700 \ub0C and P3 (3 bar)