Parametric Modelling for Designing Offsite Construction

Increasing population and progressing economies around the world are generating huge demand for built assets. When this demand is dealt with conventional ‘sticks-and-bricks’ approach, it leads to usual delays, wastages, cost overruns, and quality issues, etc. Consequently, the traditional approach results in negative impacts on economic and social scenarios apart from being just unable to deliver required supply level of built assets. On the other hand, offsite construction techniques, when utilized appropriately, can significantly speed up the construction process and improve the quality of deliverables in addition to bringing in improved sustainability and better worker health and safety. But offsite practices are marred with a general perspective of its being cause of rigidity in the design processes and disproportional increment in coordination requirements. To address this perceived problem, the application of Building Information Modelling (BIM) has been conceptualized for the design of a prototype in this research. Simpler ways of modularization and effective optimization of design through parametric modelling has been developed. The methodology coming out of this design exercise, which is of reporting values of parametric variables real-time, is promising in the sense of ensuring the general and flexible usage of offsite practices. Further as experienced during the BIM modelling exercise for the prototype, the design iterations can be accomplished in a more informed manner and optimization run in an automated fashion by using the Application Programming Interface (API) of BIM authoring tool by taking advantage of already defined key parameters. This paper addresses these important issues at the conceptual level and determines a roadmap for further research

Prioritizing BIM Capabilities of an Organization: An Interpretive Structural Modeling Analysis

The Indian Architectural Engineering and Construction sector is grappling with the adoption of BIM as is evident from a relatively low level of adoption. While there have been sufficient number of successful (and unsuccessful) project level implementations of BIM in India, the maturity level of the overall industry and its constituents remains relatively low. One of the challenges faced, especially at the organizational level, is an understanding and development of the organization's BIM capabilities. These capabilities need attention in terms of their effectiveness and hierarchy of implementation in order to overcome the challenges of adoption and increasing maturity levels in BIM usage. The inability to identify crucial BIM capabilities is one of the primary barriers to ineffective BIM implementation and slow adoption in India. The aim of this study is to investigate the dynamics of different BIM capabilities and to understand how these capabilities can be represented as a set of interrelated elements by adopting Interpretive Structure Modeling (ISM) technique Accordingly, a clear understanding regarding the nature of each BIM capability is developed that will help the organizations to plan the strategic implementation of BIM on any project and gain systematic, logical and productive results. Through the three-phased study, it was concluded that BIM capabilities namely visualization, energy and environment analysis, structural analysis, MEP system modelling, constructability analysis, and BIM for as-built were found to be the independent BIM capabilities having strong driving power but weak dependence power. Facilities management is a dependent BIM capability with weak driving power but strong dependence power. This study provides a roadmap to BIM implementers by highlighting the driving and dependence power of each BIM capability which is deemed useful for enhanced delivery of construction projects. Significant theoretical and practical implications are envisioned for both researchers and project managers through the findings of this study

Blimp-1-dependent and -independent natural antibody production by B-1 and B-1-derived plasma cells.

Natural antibodies contribute to tissue homeostasis and protect against infections. They are secreted constitutively without external antigenic stimulation. The differentiation state and regulatory pathways that enable continuous natural antibody production by B-1 cells, the main cellular source in mice, remain incompletely understood. Here we demonstrate that natural IgM-secreting B-1 cells in the spleen and bone marrow are heterogeneous, consisting of (a) terminally differentiated B-1-derived plasma cells expressing the transcriptional regulator of differentiation, Blimp-1, (b) Blimp-1+, and (c) Blimp-1neg phenotypic B-1 cells. Blimp-1neg IgM-secreting B-1 cells are not simply intermediates of cellular differentiation. Instead, they secrete similar amounts of IgM in wild-type and Blimp-1-deficient (PRDM-1ΔEx1A) mice. Blimp-1neg B-1 cells are also a major source of IgG3. Consequently, deletion of Blimp-1 changes neither serum IgG3 levels nor the amount of IgG3 secreted per cell. Thus, the pool of natural antibody-secreting B-1 cells is heterogeneous and contains a distinct subset of cells that do not use Blimp-1 for initiation or maximal antibody secretion

Double Depression is Associated with Greater Risk of Incident Cardiovascular Disease than Major Depression: Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC)

poster abstractEvidence suggests depressive disorders are risk factors for cardiovascular disease (CVD), however, little attention has been given to double depression (major depressive disorder (MDD) superimposed on dysthymia). The current study sought to determine if double depression is a stronger predictor of incident CVD due to greater duration of exposure and severity of depression in adults initially free of CVD. We analyzed data from 29,581 adults (mean age = 45 years, 58% female, 42% non-white) from Waves 1 (2001-2002) and 2 (2004-2005) of the NESARC study. At Wave 1, the Alcohol Use Disorder and Associated Disabilities Interview Schedule was administered to assess lifetime history of DSM-IV MDD and/or dysthymia. A 4-level variable was created for depression: no depression history (n=24,339), lifetime MDD only (n=4,028), lifetime dysthymia only (n=246), lifetime MDD and dysthymia (double depression; n=968). At Wave 2, participants who reported being diagnosed with myocardial infarction, stroke, angina, or arteriosclerosis in the past year were coded as having incident CVD; those diagnosed with myocardial infarction or stroke were coded as having had a hard CVD event. There were 1,380 CVD events and 365 hard CVD events. Logistic regression models adjusted for demographics (age, sex, race-ethnicity, education) and CVD risk factors (hypertension, hypercholesterolemia, diabetes, smoking, BMI) revealed that lifetime double depression (OR=1.72, 95% CI: 1.31-2.25, p.43). Our findings partially support our hypothesis and suggest that persons with double depression may have a stronger connection to an elevated CVD risk in which prevention efforts should be intensified

Atypical depression and double depression predict new-onset cardiovascular disease in U.S. adults

BACKGROUND: Although depression is a risk factor for cardiovascular disease (CVD), it is unknown whether this risk varies across depressive disorder subtypes. Thus, we investigated atypical major depressive disorder (MDD) and double depression as predictors of new-onset CVD in a nationally representative sample of U.S. adults. METHODS: Prospective data from 28,726 adults initially free of CVD who participated in Wave 1 (2001-2002) and Wave 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) were examined. Lifetime depressive disorder subtypes (Wave 1) and incident CVD (Wave 2) were determined by structured interviews. RESULTS: We identified 1,116 incident CVD cases. In demographics adjusted models, the atypical MDD group had a higher odds of incident CVD than the no depression history (OR = 2.19, 95% CI: 1.71-2.81, P < .001), dysthymic disorder only (OR = 1.61, 95% CI: 1.08-2.39, P = .019), and nonatypical MDD (OR = 1.46, 95% CI: 1.11-1.91, P = .006) groups. Likewise, the double depression group had a higher odds of incident CVD than the no depression history (OR = 2.17, 95% CI: 1.92-2.45, P < .001), dysthymic disorder only (OR = 1.59, 95% CI: 1.16-2.19, P = .004), and MDD only (OR = 1.46, 95% CI: 1.20-1.77, P < .001) groups. Relationships were similar but attenuated after adjustment for CVD risk factors and anxiety disorders. CONCLUSIONS: Adults with atypical MDD or double depression may be subgroups of the depressed population at particularly high risk of new-onset CVD. Thus, these subgroups may (a) be driving the overall depression-CVD relationship and (b) be in need of earlier and/or more intense CVD primary prevention efforts to reduce their excess CVD burden

The intellectual capital of schools: analysing government policy statements on school improvement in light of a new theorization

"Ideology without competence is a dangerous vice. But competence without ideology is a limited virtue." (D. Miliband, Minister of State for School Standards, DfES).Opportunistic attempts have been made by successive governments to establish - some would say impose - sets of criteria against which the effectiveness of not-for-profit organisations like schools can be gauged. Most have been subjective: the extent of staff involvement in decision making, the appropriateness of the leadership shown by senior managers, the percentage of inspected classes regarded as ‘good’, and so on. Lately, UK government rhetoric, using a lexicon borrowed from Business and Economics, suggests a willingness to move to new systems of reportage; centred on improvement rather than blame, on critical friendship more than on confrontation. There appears no longer to be the puritanical tendency among policy-makers to adopt measures that cause pain in the belief that they alone can be right, but do they constitute (as critics like Thrupp suggest) a random collection of well-intentioned but poorly theorised policies, or can they be cogently conceptualised into a whole? Previously, improvement measures judged schooling simply, in terms of external stakeholder outcomes, but failed to capture the essence of what it was to be (or what it took to become) a successful improving school. This paper suggests that current government policy, whether knowingly or not, is essentially describing improvement from a different perspective - an internal perspective of ‘Intellectual Capital’. The paper knits together government policy statements on school improvement with a re-conceptualisation of Intellectual Capital specifically designed for schools, offering an imposed coherence to government policy that could potentially change the way we think about inspection

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.Comment: 9 pages, 5 figures Corrected errors in equation 1

Studies on the Antioxidant Properties of Various extracts of Hippophae rhamnoide

Sea Buckthorn (Hippophae rhamnoides) a spiny shrub native to Ladakh Region of Jammu and Kashmir, have been found to posses so many medicinal properties from times immoral. From this point of view the antioxidant property of the plant fruit extracts have been analysed by DPPH method. Various plant extracts viz, fruit, leaf and root have been analysed for the antioxidant power determination in which fruit extracts showed highest free radical scavenging activity followed by leaf and root extracts. Among the solvents which have been used, more polar solvents showed highest antioxidant activity than the less polar solvent extracts. The IC50 value of various plant extracts as determined have been found to be 40 for DCM extract of fruit, 38 for Methanolic extract of fruit and 30 for the water extract of fruit. Similarly the leaf extracts posses IC50 value as 51, 47 and 37 respectively for DCM, Methanol and Water extracts. The IC50 values of various root extracts have been found to be 53, 50 and 48 respectively for DCM, Methanol and Water

Effectiveness of a Walking Program for Children and Their Families

Please refer to the pdf version of the abstract located adjacent to the title

Exploring the Impact of Evolutionary Computing based Feature Selection in Suicidal Ideation Detection

© 2019 IEEE. The ubiquitous availability of smartphones and the increasing popularity of social media provide a platform for users to express their feelings, including suicidal ideation. Suicide prevention by suicidal ideation detection on social media lights the path to controlling the rapidly increasing suicide rates amongst youth. This paper proposes a diverse set of features and investigates into feature selection using the Firefly algorithm to build an efficient and robust supervised approach to classifying tweets with suicidal ideation. The development of a suicidal language to create three diverse, manually annotated datasets leads to the validation of the proposed model. An in-depth result and error analysis lead to an accurate system for monitoring suicidal ideation on social media along with the discovery of optimal feature subsets and selection methods using a penalty based Firefly algorithm