scholarly journals Evaluating the role of deterioration models for condition assessment of sewers

2015 ◽  
Vol 17 (5) ◽  
pp. 789-804 ◽  
Author(s):  
Marius Møller Rokstad ◽  
Rita Maria Ugarelli
Keyword(s):  
Failure Modes ◽  
Structural Condition ◽  
Data Availability ◽  
Limited Data ◽  
Sewer Pipes ◽  
Explanatory Variables ◽  
Deterioration Model ◽  
Sewer Rehabilitation ◽  
Inspection Data

Ensuring reliable structural condition of sewers is an important criterion for sewer rehabilitation decisions. Deterioration models applied to sewer pipes support the rehabilitation planning by means of prioritising pipes according to their current and predicted structural status. There is a benefit in applying such models if sufficient inspection data for calibration, an appropriate deterioration model, and adequate covariates to explain the variability in the conditions are available. In this paper it is discussed up to what level the application of sewer deterioration models can be beneficial under limited data availability. The findings show that the indirect nature of the explanatory covariates which are commonly used in sewer deterioration models makes it difficult to harness any benefit from modelling sewer conditions at a network level, but that the deterioration model application still may be beneficial for prioritising inspection candidates. The prediction power of the current sewer deterioration models is limited by the adequacy of the explanatory variables available, and by the fact that different failure modes are mixed in the aggregated condition class, and not modelled explicitly.

scholarly journals Condition Rating Prediction Using an Interactive Deterioration Model Development Package

2020 ◽  
Vol 10 (24) ◽  
pp. 8946
Author(s):  
Minwoo Chang ◽  
Marc Maguire
Keyword(s):  
Asset Management ◽  
Model Development ◽  
Data Interpretation ◽  
Bridge Inspection ◽  
Explanatory Variables ◽  
Deterioration Model ◽  
Condition Rating ◽  
Initial Dataset ◽  
Stationary Set ◽  
Inspection Data

This paper presents an advanced method to determine explanatory variables required for developing deterioration models without the interference of human bias. Although a stationary set of explanatory variables is ideal for long-term monitoring and asset management, the penalty regression results vary annually due to the innate bias in the inspection data. In this study, weighting factors were introduced to consider the inspection data collected for several years, and the most stationary set was identified. To manage the substantial amount of inspection data effectively, we proposed a software package referred to as the Deterioration Model Development Package (DMDP). The objective of the DMDP is to provide a convenient platform for users to process and investigate bridge inspection data. Using the standardized data interpretation, the user can update an initial dataset for the deterioration model development when new inspection data are archived. The deterministic method and several stochastic approaches were included for the development of the deterioration models. The performances of the investigated methods were evaluated by estimating the error between the predicted and inspected condition ratings; further, this error was used for estimating the most effective number of explanatory variables for a given number of bridges.

Von Willebrand disease and Weibel-Palade bodies

2010 ◽  
Vol 30 (03) ◽  
pp. 150-155 ◽  
Author(s):  
J. W. Wang ◽  
J. Eikenboom
Keyword(s):  
Platelet Adhesion ◽  
Coagulation Factor ◽  
Von Willebrand Disease ◽  
Inflammatory Factors ◽  
Limited Data ◽  
Storage Organelle ◽  
And Function ◽  
Von Willebrand ◽  
Willebrand Factor

SummaryVon Willebrand factor (VWF) is a pivotal haemostatic protein mediating platelet adhesion to injured endothelium and carrying coagulation factor VIII (FVIII) in the circulation to protect it from premature clearance. Apart from the roles in haemostasis, VWF drives the formation of the endothelial cell specific Weibel-Palade bodies (WPBs), which serve as a regulated storage of VWF and other thrombotic and inflammatory factors. Defects in VWF could lead to the bleeding disorder von Willebrand disease (VWD).Extensive studies have shown that several mutations identified in VWD patients cause an intracellular retention of VWF. However, the effects of such mutations on the formation and function of its storage organelle are largely unknown. This review gives an overview on the role of VWF in WPB biogenesis and summarizes the limited data on the WPBs formed by VWD-causing mutant VWF.

External Investigators' Follow-Up Intentions When Whistleblowers Report Healthcare Fraud: The Effects of Report Anonymity and Previous Confrontation

2020 ◽  
Vol 32 (2) ◽  
pp. 91-101
Author(s):  
Steven E. Kaplan ◽  
Danny Lanier ◽  
Kelly R. Pope ◽  
Janet A. Samuels
Keyword(s):  
Experimental Study ◽  
Early Detection ◽  
Data Availability ◽  
Medical Provider ◽  
Perceived Credibility ◽  
The Relationship ◽  
Critical Investigation

ABSTRACT Whistleblowing reports, if properly investigated, facilitate the early detection of fraud. Although critical, investigation-related decisions represent a relatively underexplored component of the whistleblowing process. Investigators are responsible for initially deciding whether to follow-up on reports alleging fraud. We report the results of an experimental study examining the follow-up intentions of highly experienced healthcare investigators. Participants, in the role of an insurance investigator, are asked to review a whistleblowing report alleging billing fraud occurring at a medical provider. Thus, participants are serving as external investigators. In a between-participant design, we manipulate the report type and whether the caller previously confronted the wrongdoer. We find that compared to an anonymous report, a non-anonymous report is perceived as more credible and follow-up intentions stronger. We also find that perceived credibility fully mediates the relationship between report type and follow-up intentions. Previous confrontation is not significantly associated with either perceived credibility or follow-up intentions. Data Availability: Data are available upon request.

scholarly journals Investment Portfolio, Democratic Accountability, Poverty and Income Inequality Nexus in Pakistan: A Way to Social Sustainability

2021 ◽  
Vol 13 (11) ◽  
pp. 6411
Author(s):  
Muhammad Shahid Hassan ◽  
Haider Mahmood ◽  
Muhammad Ibrahim Saeed ◽  
Tarek Tawfik Yousef Alkhateeb ◽  
Noman Arshed ◽  
...  
Keyword(s):  
Income Inequality ◽  
Social Sustainability ◽  
Data Availability ◽  
Democratic Accountability ◽  
Investment Portfolio ◽  
Economic Activities ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Short Run

Institutions help to streamline the economic activity-related procedures, where government intervention might be involved. Institutions also play a significant role in social sustainability. The findings using the Autoregressive Distributed Lag approach to cointegration for the period from 1984–2019 reveal that investment portfolio and democratic accountability reduce poverty in Pakistan both in the long and short run. Moreover, democratic accountability helps to reduce income inequality, but the investment portfolio’s role is not significant. The literacy rate helps to reduce income inequality, and inflation increases poverty and income inequality. The remittances increase income inequality, and urbanization increases poverty. To eradicate poverty and income inequality, the governments should be accountable for their actions to the general public while they remain in power. If they do not deliver as per their manifestoes, they will not be reelected in the next election. Moreover, there is a dire need to redefine the role of an investment portfolio to reduce the risk of investment. So, investments would increase economic activities and could reduce poverty and income inequality. This study contributes to the literature by inquiring about the role of the investment portfolio and democratic accountability in social sustainability by reducing poverty and income inequality. This study only considers Pakistan’s economy due to limitations of poverty data availability in other countries. The scope could further be broadened by accessing data for a wider Asia region to test the role of the investment portfolio and democratic accountability to reduce poverty and income inequality.

Life Course Socioeconomic Position, Intergenerational Social Mobility, and Hypertension Incidence in ELSA-Brasil

2021 ◽  
Author(s):  
José Aparecido Soares Lopes ◽  
Luana Giatti ◽  
Rosane Harter Griep ◽  
Antonio Alberto da Silva Lopes ◽  
Sheila Maria Alvim Matos ◽  
...  
Keyword(s):  
Life Course ◽  
Social Mobility ◽  
Socioeconomic Position ◽  
Linear Models ◽  
Sociodemographic Factors ◽  
Incidence Rates ◽  
Explanatory Variables ◽  
Rate Ratios

Abstract Background Life course epidemiology is a powerful framework to unravel the role of socioeconomic position (SEP) disparities in hypertension (HTN). This study investigated whether life course SEP is associated with HTN incidence. Specifically, to test whether cumulative low SEP throughout life and unfavorable intergenerational social mobility increased HTN incidence. METHODS Longitudinal analysis of 8,754 ELSA-Brasil participants without HTN or cardiovascular in visit 1 (2008–2010). The response variable was the incidence of HTN between visits 1 and 2 (2012–2014). The explanatory variables were childhood, youth, and adulthood SEP, cumulative low SEP, and intergenerational social mobility. Associations were estimated by incidence rate ratios (IRRs) obtained by generalized linear models, with Poisson distribution and logarithmic link function, after adjustment for sociodemographic, behavioral, and health factors. RESULTS The incidence of HTN was 43.2/1,000 person-years, being higher in males, elderly (70–74 years), self-declared black, and low SEP individuals. After considering sociodemographic factors, low SEP in childhood, youth, and adulthood remained statistically associated with increased HTN incidence. Individuals in the third (IRR: 1.26; 95% confidence interval (CI): 1.11–1.44) and fourth top quartiles (IRR: 1.29; 95% CI: 1.11–1.49) of cumulative low SEP, vs. first, as well as those with low stable intergenerational trajectory (IRR: 1.29; 95% CI: 1.16–1.43), vs. high stable, also had increased HTN incidence rates. Conclusions Socioeconomic disparities at all phases of the life cycle appear to raise HTN incidence rates, being the individuals with greater accumulation of exposure to low SEP and with more unfavorable intergenerational mobility at greatest risk, even in a short follow-up time.

scholarly journals Heparin-induced thrombocytopenia: research and clinical updates

Hematology ◽  
2016 ◽  
Vol 2016 (1) ◽  
pp. 262-268 ◽  
Author(s):  
Oluwatoyosi Onwuemene ◽  
Gowthami M. Arepally
Keyword(s):  
Limited Data ◽  
Platelet Factor ◽  
Heparin Induced Thrombocytopenia ◽  
Diagnostic Strategies ◽  
Immune Mediated ◽  
Emerging Therapies ◽  
Current Perspective ◽  
Clinical Advances ◽  
A Current

Abstract Heparin-induced thrombocytopenia (HIT) remains an important diagnosis to consider in hospitalized patients developing thrombocytopenia. HIT is an immune-mediated prothrombotic disorder caused by antibodies to platelet factor 4 (PF4) and heparin. Recent basic scientific studies have advanced our understanding of disease pathogenesis through studies of the PF4/heparin structure, immune mechanisms, and cellular basis of thrombosis. Clinical advances have also occurred in areas of HIT prevention, description of disease variants, and diagnostic strategies. Emerging anticoagulants with the potential to change HIT treatment are evolving, although with limited data. This review will provide a current perspective on HIT pathogenesis, disease features, diagnostic strategies, and role of emerging therapies for the management of HIT.

The Role of Offshore Monitoring in an Effective Deepwater Riser Integrity Management Program

2007 ◽  
Author(s):  
Brittany Goldsmith ◽  
Elizabeth Foyt ◽  
Madhu Hariharan
Keyword(s):  
Failure Modes ◽  
Human Life ◽  
Management Program ◽  
Measured Data ◽  
Operating Conditions ◽  
Environmental Damage ◽  
Positioning Systems ◽  
Integrity Management ◽  
Deepwater Riser

As offshore field developments move into deeper water, one of the greatest challenges is in designing riser systems capable of overcoming the added risks of more severe environments, complicated well requirements and uncertainty of operating conditions. The failure of a primary riser component could lead to unacceptable consequences, including environmental damage, lost production and possible injury or loss of human life. Identification of the risks facing riser systems and management of these risks are essential to ensure that riser systems operate without failure. Operators have recognized the importance of installing instrumentation such as global positioning systems (GPS), vessel motion measurement packages, wind and wave sensors and Acoustic Doppler Current Profiler (ADCP) units to monitor vessel motions and environmental conditions. Additionally, high precision monitoring equipment has been developed for capturing riser response. Measured data from these instruments allow an operator to determine when the limits of acceptable response, predicted by analysis or determined by physical limitations of the riser components, have been exceeded. Regular processing of measured data through automated routines ensures that integrity can be quickly assessed. This is particularly important following extreme events, such as a hurricane or loop current. High and medium alert levels are set for each parameter, based on design analysis and operating data. Measured data is compared with these alert levels, and when an alert level is reached, further response evaluation or inspection of the components in question is recommended. This paper will describe the role of offshore monitoring in an integrity management program and discuss the development of alert levels based on potential failure modes of the riser systems. The paper will further demonstrate how this process is key for an effective integrity management program for deepwater riser systems.

scholarly journals The Determinants of Access to Sanitation: The Role of Human Rights and the Challenges of Measurement

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1676
Author(s):  
Rebecca Schiel ◽  
Bruce M. Wilson ◽  
Malcolm Langford
Keyword(s):  
Sustainable Development ◽  
Human Rights ◽  
Field Data ◽  
Data Availability ◽  
Regression Analyses ◽  
Human Right ◽  
Sustainable Development Goal ◽  
Development Goal ◽  
The Sustainable Development

Ten years after the United Nation’s recognition of the human right to water and sanitation (HRtWS), little is understood about how these right impacts access to sanitation. There is limited identification of the mechanisms responsible for improvements in sanitation, including the international and constitutional recognition of rights to sanitation and water. We examine a core reason for the lack of progress in this field: data quality. Examining data availability and quality on measures of access to sanitation, we arrive at three findings: (1) where data are widely available, measures are not in line with the Sustainable Development Goal (SDG) targets, revealing little about changes in sanitation access; (2) data concerning safe sanitation are missing in more country-year observations than not; and (3) data are missing in the largest proportions from the poorest states and those most in need of progress on sanitation. Nonetheless, we present two regression analyses to determine what effect rights recognition has on improvements in sanitation access. First, the available data are too limited to analyze progress toward meeting SDGs related to sanitation globally, and especially in regions most urgently needing improvements. Second, utilizing more widely available data, we find that rights seem to have little impact on access.

AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

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