B.I.M. Towards design documentation: Experimental application work-flow to match national and proprietary standards

2006 ◽  
Author(s):  
Dianne Davis ◽  
Gordon Tait ◽  
Cindy Bruce-Barrett
Keyword(s):  

2021 ◽  
Author(s):  
Elias Arcondoulis ◽  
Yu Liu ◽  
Pengwei Xu ◽  
Qing Li ◽  
Renke Wei ◽  
...  

Author(s):  
Sweta Pendyala ◽  
Dave Albert ◽  
Katherine Hawkins ◽  
Michael Tenney

Abstract Resistive gate defects are unusual and difficult to detect with conventional techniques [1] especially on advanced devices manufactured with deep submicron SOI technologies. An advanced localization technique such as Scanning Capacitance Imaging is essential for localizing these defects, which can be followed by DC probing, dC/dV, CV (Capacitance-Voltage) measurements to completely characterize the defect. This paper presents a case study demonstrating this work flow of characterization techniques.


2020 ◽  
Author(s):  
Nicholas Mark Stansbury ◽  
Erin Nelson

BACKGROUND Current workflow in GYN triage has medical students interviewing patients after triage by nursing staff. The optimal time to initiate patient contact is unclear. This confusion has led to duplication of questions to patients, interruptions for nurses and fewer patient encounters for students. OBJECTIVE Determine if a restaurant-style buzzer can streamline workflow in gynecology (GYN) triage. METHODS A Plan-Do-Study-Act approach was used. Stakeholders were medical students, nurses, Nurse Practitioners and physicians. Factors contributing to workflow slowdown: students re-asking questions of patients, interruption of nursing staff, confusion about optimal patient flow. The net result was fewer interviews completed by students. The project was introduced during clerkship orientation. Buzzers were provided on weeks 1, 3, 5 of the rotation. Weeks 2, 4, 6 no buzzers were provided as an internal control. After each clerkship, students received a survey assessing key areas of waste and workflow disruption. A focus group with ten nurses was also conducted. RESULTS From February-July 2019, 30/45 surveys were completed (66%) 1. Very difficult/difficult to know when to begin the encounter: 90% without; 21.4% with buzzer p<.001 2. Students re-asking questions: very often/often 96.7% without; 14.8% with buzzer p<.001 3. Nursing staff interruptions: 76.7% very often/often without; 18.5% with buzzer p<.001 4. The odds of interviewing 5 or more patients per shift are ~10X greater using the buzzer χ²=14.2; p<.001 CONCLUSIONS The 10 nurses interviewed unanimously favored the use of the buzzer. Introduction of a simple, low-cost restaurant-style buzzer improved triage work-flow, student and nursing experience.


Author(s):  
Ekaterina Tereshko ◽  
Marina Romanovich ◽  
Irina Rudskaya

The construction industry is high-tech and is one of the key areas for the strategic development of regions in terms of their digitalization. The construction complex provides regions with infrastructure of various levels from design documentation to commissioning, as well as reconstruction and major repairs of buildings. The article adopts an isolated regional approach, which is due to the need to assess specific territories by the level of readiness for digitalization of the construction complex. The purpose of the research is to determine the level of readiness of Russian regions for the digitalization of the construction complex by forming a rating of regions according to the indicator “the level of readiness of the region for digitalization of the construction complex”. To build the rating, the fuzzy sets method was applied using a triangular membership function, which allows to describe the influence of various processes on the formation of digitalization processes in the construction complex of the region. When forming the rating, a scale of fuzzy variable values is set which allows one to classify regions by levels, namely very low, low, medium, high, and very high. The generated rating is illustrated according to the specified scale. Based on the rating, the leading regions and outsider regions are identified by the formed indicator. It was determined that Moscow and Saint Petersburg are highly prepared for the digitalization of their construction complexes, and 53 regions of Russia are potentially prepared. In the future, it will be possible to create a rating of Russian regions on the level of readiness for digitalization of the construction complex with a two-year lag. Then, using the DEA shell analysis method, a quantitative assessment will be carried out that allows you to form performance boundaries and, against the background of four years, adjust the data to identify the most realistic picture. Also, the rating methodology considered by the authors allows us to scale this research to the international level, which will allow us to assess the level of digital development of construction complexes in other countries. The proposed rating algorithm is suitable for other sectors and complexes of the economy. It is enough to determine the main aggregate indicator and select groups of factors.


2021 ◽  
Vol 21 ◽  
pp. 100730
Author(s):  
David Pogorzelski ◽  
Uyen Nguyen ◽  
Paula McKay ◽  
Lehana Thabane ◽  
Megan Camara ◽  
...  
Keyword(s):  

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jiao Chen ◽  
Pansong Zhang ◽  
Haixia Wang ◽  
Yanjing Shi

Abstract Adulteration of beef with cheap chicken has become a growing problem worldwide. In this study, a quick, single primer-triggered isothermal amplification (SAMP) combined with a fast nucleic acid extraction method was employed to detect the chicken meat in adulterated beef. Chicken from adulterated beef was identified using the chicken species-specific primer designed according to the Gallus gallus mitochondrial conserved sequences. Our SAMP method displayed good specificity and sensitivity in detecting chicken and beef meat DNA–the limit of detection (LOD) of SAMP is 0.33 pg/μL of chicken and beef total DNA and 2% w/w chicken meat in beef. The whole work flow from DNA extraction to signal detection can be finished within 1 h, fulfilling the requirement of on-site meat species identification.


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