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Syndromic intellectual disability (ID) with accompanying primary microcephaly is a group of rare neurodevelopmental disorders exhibiting extreme genetic and clinical heterogeneity. This layered heterogeneity can partially be resolved by unbiased genetic approaches targeting the genome with next generation sequencing (NGS) technologies, including exome sequencing (ES).This study was performed to dissect the clinical and genetic features in five distinct IDM cases.Singleton or trio ES approach followed by in-depth variant analysis using alternative inheritance models was performed.We have identified biallelic loss of function variants in genes WDR62 and AP4M1 in three families, together with de novo missense variants in genes SOX11 and TRIO in two families. ES based haplotype analysis in two cases upon identification of an identical WDR62 variant in the homozygous state in two cases was suggestive of a small shared haplotype of 0.1 Mb. Additionally, we have shown a paternal origin for the de novo variant in TRIO via a polymorphic tag SNP, which enlightens the mutational mechanism for this variant.In populations with high parental consanguinity, an autosomal recessive inheritance pattern for data analysis is usually the most obvious choice. Therefore, heterozygous variants may be overlooked in standard NGS analyses in consanguineous families. Our findings underlie the importance of using multiple inheritance models in NGS data analysis.

An adaptive traffic-control system (ATCS) is an advanced traffic-signal control system that updates traffic signal timing in an automated way to stabilise and smooth traffic. It is important to examine updated cost and benefits data for the entire life cycle of ATCSs to develop benefit/cost analysis frameworks. The application of a high-level benefit/cost analysis framework is presented in this paper. The framework was first tested on ramp metering systems in a previous study by the authors and its application in ATCSs produced promising results. The framework is composed of four main components: life-cycle cost analysis, benefits achieved through travel time savings, benefits achieved through reductions in energy consumption and benefits achieved through reductions in the number of accidents. A theoretical case study was used to demonstrate the application of the framework. A sensitivity analysis was conducted to determine the effects of higher traffic demand on the benefits achieved. The results showed that ATCSs can be feasible in relieving congestion at junctions. It is anticipated that the proposed framework can improve the higher-level decision-making procedures of transportation agencies concerning the deployment of ATCSs.

PurposePavement deterioration prediction models play a crucial role in determining maintenance strategies and future funding needs. While deterioration prediction models have been studied extensively in the past, applications of these models to local street networks have been limited. This study aims to address this gap by sharing the results of network level deterioration prediction models developed at a local level.Design/methodology/approachNetwork level pavement deterioration prediction models are developed using Markov chains for the local street network in Syracuse, New York, based on pavement condition rating data collected over a 15-year time period. Transition probability matrices are generated by calculating the percentage of street sections that transition from one state to another within one duty cycle. Bootstrap sampling with replacement is used to numerically generate 95% confidence intervals around the transition probability values.FindingsThe overall local street network is divided into three cohorts based on street type (i.e. avenues, streets and roads) and two cohorts based on pavement type. All cohorts demonstrated very similar deterioration trends, indicating the existence of a fast-paced deterioration mechanism for the local street network of Syracuse.Originality/valueThis study contributes to the body of knowledge in deterioration modeling of local street networks, especially in the absence of key predictor variables. Furthermore, this study introduces the use of bootstrap sampling with replacement method in generating confidence intervals for transition probability values.

Connectivity is key in this new era of smart infrastructure. Smart airports utilize new connected technologies to improve end-user experience while ensuring operational feasibility in aeronautical and non-aeronautical segments. The increasing need for digitizing the design-build-operate life cycles of airports can be met by implementing building information modeling (BIM) that enables accessing, managing, utilizing, and connecting physical and operational data in a digital collaborative environment. This study investigates the current state of practice in airport BIM (ABIM) and the use of ABIM processes in digital airport operations and maintenance by connecting existing data sources and integrating smart airport systems. The study proposes a comprehensive and adaptive ABIM management framework that depicts the alignment and connectivity of ABIM processes, resources and stakeholders with airport operational requirements by identifying gaps in the industry and literature, and developing a global understanding in ABIM visions. Research data are collected through literature and industry review, online surveys, and semi-structured interviews with aviation professionals. Mixed methods including non-parametric statistical analysis and qualitative analysis are used to determine the elements of the framework. Model-based systems engineering (MBSE) principles and language are used to generate the framework. For framework validation, a proof of concept (POC) is conducted by development and deployment of a web-based application. The developed ABIM framework is expected to guide major airport stakeholders in their BIM implementation processes to enhance airport operational efficiencies and in strategizing digital initiatives on a connected-BIM platform.

PurposeThe purpose of this paper is to systematically analyse how building information modelling (BIM) transforms complex infrastructure settings (i.e. airports) around digital technologies by enhancing connectivity and collaboration between major stakeholders and construction technology solutions. The objectives include understanding each project party's perspective for BIM implementation to align their motivations and connectivity along project's supply chain network and how BIM drives construction technology ecosystem uses for a more integrative and collaborative project delivery.Design/methodology/approachThe study adopts qualitative data collection and analysis methods comprising semi-structured interviews, thematic analysis and an explanatory case study of a large-hub airport project.FindingsThe study findings show that enabling BIM implementation leads to streamlining construction technology ecosystem uses that increase connectivity within project parties' processes. Airports – as hosting high-value assets – can fast realize value of synergistic activities throughout project delivery by harnessing significant amount of siloed data created by each major party.Originality/valueThe study provides a structured analysis of how complex project settings leverage construction technology uses through their core BIM processes by highlighting multi-party approaches from an ecosystem perspective. This study also contributes to the body of knowledge and practice by presenting a transferrable and scalable approach for leveraging connected construction technology in a large-scale project involving fragmented processes managed by a large number of stakeholders.

Lafora disease (LD) is a severe form of progressive myoclonus epilepsy inherited in an autosomal recessive fashion. It is associated with biallelic pathogenic variations in EPM2A or NHLRC1, which encode laforin and malin, respectively. The disease usually starts with adolescent onset seizures followed by progressive dementia, refractory status epilepticus and eventually death within 10 years of onset. LD is generally accepted as having a homogenous clinical course with no considerable differences between EPM2A or NHLRC1 associated forms. Nevertheless, late-onset and slow progressing forms of the disease have also been reported. Herein, we have performed clinical and genetic analyses of 14 LD patients from 12 different families and identified 8 distinct biallelic variations in these patients. Five of these variations were novel and/or associated with the LD phenotype for the first time. Interestingly, almost half of the cases were homozygous for the rare rs769301934 (NM_198586.3(NHLRC1): c.436 G A; p.(Asp146Asn)) allele in NHLRC1. A less severe phenotype with an onset at a later age may be the reason for the biased inflation of this variant, which is already present in the human gene pool and can hence arise in the homozygous form in populations with increased parental consanguinity.

Over the last decade, transportation asset management practices have been increasingly enhanced through incorporation of sustainability considerations. Organizational- and network-level gui...

The primary objectives of ramp metering are to reduce congestion on freeways by restricting the total flow entering the freeway and to discourage short-distance travelers from using the freeway. Life-cycle cost analysis of ramp-metering deployments has received attention in particular for identifying the strategy with the lowest cost. However, increasing concerns over the effects of congestion on the environment and increasing rates of accidents are urging decision makers to consider the environmental and social effects of ramp-metering deployments in addition to agency costs. This paper presents a high-level benefit–cost analysis framework for ramp-metering deployments. The framework was constructed in consideration of the triple bottom line of sustainability (i.e., economic, environmental, and social factors). More specifically, the framework is made up of four main components: ( a) life-cycle cost analysis, ( b) analysis of benefits achieved through travel time savings, ( c) analysis of benefits achieved through reductions in energy consumption, and ( d) analysis of benefits achieved through reductions in the number of accidents. A hypothetical case study is used to demonstrate the application of the framework. A sensitivity analysis is conducted to determine the effects of higher traffic demand on the benefits achieved. It is expected that the proposed framework can improve the high-level decision-making procedures of transportation agencies in regard to the deployment of ramp meters.

Sustainable development is one of the most widely studied contemporary issues in the transportation sector. However, few of the existing project-level, sustainability-oriented decision tool...

Approximately a quarter of the bridges in the United States are classified as either functionally obsolete or structurally deficient by the United States Department of Transportation (USDOT). As such, transportation agencies are challenged to handle the increasing need of upgrades with limited resources. Accelerated Bridge Construction (ABC) can reduce the construction duration and can decrease the environmental and socio-economic impacts of repair and upgrade activities by minimizing traffic disruptions. As several states are using accelerated construction techniques, a standard guideline would be highly beneficial for these agencies in developing or improving the ABC decision-making process. As problems are often project specific, a decision tool can assist in determining the viability of ABC over traditional construction methods and in selecting appropriate construction and contracting strategies on a case-by-case basis. This paper presents findings of a recent survey with regards to utilization of ABC strategies by state Departments of Transportation (DOTs), and a decision support framework which consists of three models: (1) Analytical Hierarchy Process (AHP) based ABC vs. traditional construction decision-making model; (2) ABC alternatives selection model; and (3) procurement method and contract selection model. The paper also discusses the use of ABC in New York State and describes a New York State bridge project to validate the AHP model. First published online 02 May 2017

Transportation systems management and operations (TSM&O) strategies such as adaptive traffic control systems (ATCSs) and ramp metering systems (RMSs) can be utilized to exploit existing transporting capacity instead of undertaking costly new construction projects. This paper presents an asset management framework for TSM&O components used in ATCSs and RMSs including signal heads, controllers, detectors, supporting structures, and communication lines to support the decision making processes of transportation agencies. ATCS and RMS overall condition ratings and importance indices are the two parameters that contribute to prioritization of these TSM&O applications. A fuzzy logic approach is used to combine these two major components. Inspection guidelines and published cost databases are primary data sources, while economic (agency), social (traveler), and environmental benefits that would be lost in case of failures are considered in developing procedures to determine the importance indices. This asset management framework allows transportation agencies to identify ATCS and RMS deployments with high risk considering both the condition levels and benefits provided by these deployments, and hence constitutes a highly important step towards development of risk management and mitigation plans featuring appropriate maintenance, repair and rehabilitation (MRR) strategies. Future research can integrate additional TSM&O components into the asset management framework, and the boundary of benefits considered in determining the importance indices can be expanded.

Because of deteriorating condition levels of wastewater networks and financial constraints, sewer agencies are seeking methods to prioritize inspection of sewer pipes on the basis of risk of failure. Risk assessment of sewer pipes requires integration of the probability and consequences-of-failure values in a way that reflects the decision maker’s perception of risk. This paper presents the use of a weighted scoring method to determine criticality of sewer pipelines. The procedure involves identifying important factors, determining the relative importance of the selected factors, and summarizing the overall performance of sewer pipes in terms of these factors. Determination of risk of failure by combining the resultant consequence-of-failure values with the probability-of-failure values using simple multiplication, risk matrices, and fuzzy inference systems is presented. Application of these methods is illustrated by using the sewer network information obtained from a local wastewater agency. The ...

Wastewater utilities are aiming to implement asset management strategies to minimize costly emergency repairs, to justify expenditures, and to optimize future renewal actions. Consequently, development of deterioration models that explain the behavior of wastewater lines and provide predictions regarding potential future condition levels is gaining importance. In this paper, deterioration models are generated to estimate the probability of failure values for sewer sections. A set of variables was obtained by examining the inventory and inspection databases of a sewer network. Three statistical methods (ordinal regression, multinomial logistic regression, and binary logistic regression) were employed in successive steps. Proportionality of odds assumption was tested for ordinal regression models, and suitability of this particular method was discussed. Estimated condition ratings were compared with observed data, and the binary logistic regression model was found to be more suitable for predicting ...

Drainage infrastructure systems and culverts constitute an important portion of highway assets that require routine inspections, maintenance, and timely repair and renewal. Variations in structural characteristics (i.e., material type, shape, and dimension), environmental exposure, and wide geospatial distribution of these infrastructure assets accompanied with strict budget restrictions pose significant challenges for transportation agency officials. Deterioration models constitute one of the most essential components of any infrastructure asset management strategy; these models provide insight on the significant factors that affect infrastructure condition states and expected behavior of infrastructure assets under different conditions. The objectives of this study are to provide a review of previous studies on factors that affect culvert performance and durability and those on culvert asset management, to present current practices of transportation agencies with regard to management of culverts, and, last, to present development of a preliminary deterioration model that will allow decision makers to identify significant factors that affect deterioration of metal culverts and prioritize inspection procedures. The preliminary deterioration model presented in this study is developed by employing binary logistic regression with a forward stepwise variable selection method on data obtained from the Ohio Department of Transportation.

Due to an aging and rapidly deteriorating transportation infrastructure, agencies are facing the challenge of making quick and reliable decisions regarding the repair and renewal of their assets. While comprehensive asset management strategies have been developed for the visible components of the highway system, such as bridges and pavement, culverts and drainage structures are often neglected. The investigators recently completed an MRUTC project in which they have investigated the current culvert asset management practices of transportation agencies and also developed the inventory and inspection protocols necessary for establishing an effective culvert asset management program. This study builds upon the findings of the previous research project and focuses on the application of trenchless technologies for inspection, construction, repair and renewal of culverts. A literature search, a survey of departments of transportation and a survey of technology providers have been conducted to identify and characterize trenchless technology methods used for buried pipes. The limitations of trenchless technologies in terms of applicability to culverts are investigated. Steps of establishing a comprehensive culvert asset management strategy are identified. Based upon the findings a decision support system is developed which will help the decision makers identify the optimum repair/renewal procedures as a function of the condition of the culvert.

The deteriorating highway culvert infrastructure has become a major challenge for the 21 st century. While more importance usually is given to highway embankments, pavements, and bridges, the maintenance of culverts has commonly been neglected. As many culverts reach the end of their design life, the state Departments of Transportation (DOTs) are in need of a model to track the existing culverts and forecast their conditions. Therefore, the main goals of this research is to develop a framework for culvert inventory and inspection by providing protocols and condition rating systems for culvert inventory and inspection, and validate the developed framework by conducting field pilot studies. Performance scores for the culverts are calculated using an analytical hierarchy process (AHP) to determine the magnitude of the deterioration and assist in short and long term planning. This study focuses on concrete, corrugated metal, and plastic culverts spanning less than or equal to 10 feet (3 meters). The developed model contributes to an effective culvert asset management strategy.