A Case Study for Sensitivity-Based Building Energy Optimization

Building design optimization process is associated with uncertainties due to climate change, unpredictable occupant behavior, and physical degradation of building material over time. The inherent uncertainties in the design process reduce the reliability and robustness of the optim3l design solution(s) and affect design decision-making results. This research studies the capabilities of parametric design tools in adopting probabilistic methods to handle uncertainties in building performance optimization. Variance-based methods, e.g., Monte Carlo sensitivity analyses are implemented to identify the most critical parameters in design optimization problems and improve the efficiency of design optimization. The optimal solutions achieved with variance-based methods are satisfying the design objectives more efficiently, also remain robust to changes and uncertainties

UNCERTAINTY AND SENSITIVITY ANALYSIS USING BUILDING INFORMATION MODELING (An Energy Analysis Test Case)

Building design decision-making is associated with uncertainties due to variations over time and unpredictable parameters. There is a growing demand for probabilistic methods, i.e., uncertainty and sensitivity analyses to handle the uncertainties in building design. This research intends to encourage the application of Building Information Modeling (BIM) for addressing design uncertainties affecting building energy performance. The mapping between BIM (Revit and Dynamo) and a customized model-based energy analysis tool in Excel is investigated to translate architectural models to energy models and conduct the probabilistic analyses. The application of this method is demonstrated with a test case of a hypothetical residential unit in College Station, Texas, USA. Input variables in this example are the thermal properties of building elements, and the two simulation outputs are annual heating and cooling energy consumption, and deviation from comfort temperature. The results indicate the probability distribution of simulation outputs and the importance factor of each design input. This method deals with uncertainties and provides a more reliable and robust basis for design decision-making

The Anxiety Disorder Among the Healthcare Providers During The COVID-19 Infection Pandemic: A Systematic Review

Background: The outbreak of the novel coronavirus disease (COVID-19) imposes a considerable psychological burden on the medical staff working in central hospitals for COVID-19. In this systematic review, we will discuss the prevalence and the risk factors of anxiety disorder among the frontline medical staff dealing with COVID-19 patients.Methods: PubMed, Scopus, Embase, Web of Science data bases were systematically searched from December 01, 2019 to April 30, 2020 for related published articles. In all electronic databases, the following search strategy was implemented and these key words (in the title/abstract) were used: “COVID-19” OR “novel Coronavirus” AND “anxiety” OR “psychology” OR “psychiatry” OR “psychological distress” AND “nurses” or “clinicians”. We included only the cross sectional studies.Results: Through the search strategy, we could identify eight related cross sectional articles about anxiety among the healthcare workers in central hospitals for COVID-19 infection. However, the authors scanned the reference lists of the included studies and identified multiple references. According to our findings, the frontline medical staff are at risk developing anxiety disorder which is mainly mild. Additionally, the female nurses are more susceptible to experience anxiety during the COVID-19 pandemic.Conclusion: Regarding to the outbreak of COVID-19 worldwide and the workload of the frontline medical staff dealing with COVID-19 patients, a particular attention should be given on the mental health of the healthcare provides

UNCERTAINTY AND SENSITIVITY ANALYSIS USING BUILDING INFORMATION MODELING (An Energy Analysis Test Case)

Building design decision-making is associated with uncertainties due to variations over time and unpredictable parameters. There is a growing demand for probabilistic methods, i.e., uncertainty and sensitivity analyses to handle the uncertainties in building design. This research intends to encourage the application of Building Information Modeling (BIM) for addressing design uncertainties affecting building energy performance. The mapping between BIM (Revit and Dynamo) and a customized model-based energy analysis tool in Excel is investigated to translate architectural models to energy models and conduct the probabilistic analyses. The application of this method is demonstrated with a test case of a hypothetical residential unit in College Station, Texas, USA. Input variables in this example are the thermal properties of building elements, and the two simulation outputs are annual heating and cooling energy consumption, and deviation from comfort temperature. The results indicate the probability distribution of simulation outputs and the importance factor of each design input. This method deals with uncertainties and provides a more reliable and robust basis for design decision-making

Towards the Application of Uncertainty Analysis in Architectural Design Decision-Making

To this day, proper handling of uncertainties -including unknown variables in primary stages of a design, an actual climate data, occupants` behavior, and degradation of material properties over the time- remains as a primary challenge in an architectural design decision-making process. For many years, conventional methods based on the architects' intuition have been used as a standard approach dealing with uncertainties and estimating the resulting errors. However, with buildings reaching great complexity in both their design and material selections, conventional approaches come short to account for ever-existing but unpredictable uncertainties and prove incapable of meeting the growing demand for precise and reliable predictions. This study aims to develop a probability-based framework and associated prototypes to employ uncertainty analysis and sensitivity analysis in architectural design decision-making. The current research explores an advanced physical model for thermal energy exchange characteristics of a hypothetical building and uses it as a test case to demonstrate the proposed probability-based analysis framework. The proposed framework provides a means to employ uncertainty and sensitivity analysis to improve reliability and effectiveness in a buildings design decision-making process

Relationship between Pregnancy-induced Hypertension with Neonatal and Maternal Complications

Background Prevalence of hypertension has a relatively high prevalence especially in developing countries. In order to prevent and control the disease, it is important to know the extent of the complications. The aim of this study was to investigate the relationship between pregnancy-induced hypertension with neonatal and maternal complications.   Materials and Methods This prospective, descriptive study was conducted on 230 overweight women, with hypertension (n=115) and normal blood pressure (n=115) during pregnancy, referring to Hamedan hospitals. Researcher-made questionnaire including demographic characteristics and maternal and neonatal complications were used to collect required data. Data analysis was performed using Chi-square, t-test and ANOVA based on the difference between the data at a level of error less than 5%. Results: There was no significant difference between the two groups in terms of demographic characteristics, smoking history, and mean weight, number of pregnancies, number of births, history of abortion and the reception of care during pregnancy (P > 0.05). Significant relationship was observed between pregnancy and maternal outcomes, such as cesarean section, infection, bleeding, hydramnios, diabetes, proteinuria, edema, headache and hospitalization time, as well as neonatal outcomes such as low birth weight, preterm delivery, Apgar, and longer hospitalization (

Towards the Application of Uncertainty Analysis in Architectural Design Decision-Making

To this day, proper handling of uncertainties -including unknown variables in primary stages of a design, an actual climate data, occupants` behavior, and degradation of material properties over the time- remains as a primary challenge in an architectural design decision-making process. For many years, conventional methods based on the architects' intuition have been used as a standard approach dealing with uncertainties and estimating the resulting errors. However, with buildings reaching great complexity in both their design and material selections, conventional approaches come short to account for ever-existing but unpredictable uncertainties and prove incapable of meeting the growing demand for precise and reliable predictions. This study aims to develop a probability-based framework and associated prototypes to employ uncertainty analysis and sensitivity analysis in architectural design decision-making. The current research explores an advanced physical model for thermal energy exchange characteristics of a hypothetical building and uses it as a test case to demonstrate the proposed probability-based analysis framework. The proposed framework provides a means to employ uncertainty and sensitivity analysis to improve reliability and effectiveness in a buildings design decision-making process

The Effect of Percutaneous Laser Disc Decompression on Reducing Pain and Disability in Patients With Lumbar Disc Herniation

Introduction: As low back pain incidence is increasing, noninvasive modalities are gaining attention for their ability to achieve the best possible outcome with the least complications. Percutaneous laser disc decompression (PLDD) is currently popular for this purpose. This study aims to evaluate the effect of PLDD on disability and pain reduction in patients with lumbar disc herniation.Methods: Thirty patients were enrolled in this study. Spinal nerve blocks were conducted by laser discectomy single stage injection of a needle into the disc space. The nucleus pulposus of herniated discs were irradiated with laser in order to vaporize a small part of the nucleus pulposus of the intervertebral discs and reduce the voluminosity of diseased discs. Patients were treated with 1000 J of 980 nm diode laser with 5 W energy. In order to measure the severity of pain, visual analog scale (VAS) and also ODI (Oswestry Disability Index) were used. Data were analyzed using SPSS version 12.Results: Thirty patients participated in this trial including 11 men and 19 women with a mean age (SD) of 40.8 (10.8) years. The mean patients VAS score and ODI level before and after discectomy showed statistically significant differences. The mean VAS and ODI scores showed no statistical difference between males and females (P < 0.05) and percutaneous laser discectomy decreased the VAS and ODI at both groups of patients similarly.Conclusion: We found the use of PLDD reduces pain and disability in patients as a noninvasive procedure

An Investigation of Three types of Tooth Implant Supported Fixed Prosthesis Designs with 3D Finite Element Analysis

Objective: Tooth/implant supported fixed prostheses may present biomechanical design problems, as the implant is rigidly anchored within the alveolus, whereas the tooth is attached by the periodontal ligament to the bone allowing movement. Many clinicians prefer tooth/implant supported fixed prosthesis designs with rigid connectors. However, there are some doubts about the effect of attachment placement in different prosthesis designs. The purpose of this study was to examine the stresses accumulated around the implant and natural teeth under occlusal forces using three dimensional finite element analysis (3D FEA).Materials and Methods: In this study, different connection designs of tooth/implant fixed prosthesis in distal extension situations were investigated by 3D FEA. Three models with various connection designs were studied; in the first model an implant rigidly connected to an abutment, in the second and third models an implant connected to abutment tooth with nonrigid connector in the distal part of the tooth and mesial part of the implant. In each model, a screw type implant (5×11mm) and a mandibular second premolar were used. The stress values of these models loaded with vertical forces (250N) were analyzed.Results: There was no difference in stress distribution around the bone support of the implant. Maximum stress values were observed at the crestal bone of the implant. In all models, tooth movement was higher than implant movement.Conclusion: There is no difference in using a rigid connector, non rigid connector in the distal surface of the tooth or in the mesial surface of an implant