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The work on bridge resilience assessment includes quantitative and qualitative approaches to compare the multiple bridges based on their resilience. But still, the bridge resilience obtained by these assessment approaches is inefficient when prioritising multiple bridges to improve their resilience. Therefore, this study aims to develop a methodology for prioritising the bridges to improve their resilience.

The research methodology follows three sequential phases. In the first phase, criteria importance through intercriteria correlation (CRITIC) technique is used to compute the criteria weights. The criteria considered are age, area, design high flood level, finish road level FRL and resilience index of bridges. While 12 river-crossing bridges maintained by one bridge owner are considered as alternatives. Then, in the second phase, the prioritisation of each bridge is evaluated using five techniques, including technique for order of preference by similarity to ideal solution, VIKOR (in Serbian, Visekriterijumska Optimizacija I Kompromisno Resenje), additive ratio assessment, complex proportional assessment and multi-objective optimisation method by ratio analysis. Finally, in the third phase, the results of all five techniques are integrated using CRITIC and the weighted sum method.

The result of the study enables bridge owners to deal with the particular bridge that requires resilience improvement. The study concluded that it is not enough to consider only the bridge resilience index to improve its resilience. The prioritisation exercise should consider various other criteria that are not preferred during the bridge resilience assessment process.

The proposed methodology is a novel framework based on the existing multi-criteria decision-making (MCDM) techniques for contributing knowledge in the domain of bridge resilience management. It can efficiently overcome the pitfall of decision-making when two bridges have the same resilience index score.

Compares and contrasts the contractual roles of modern waybills against the traditional straight bills of lading in the context of Greek, US and English law. Chronicles the development of international lading bills; identifies the emergence of straight bills and waybills to ameliorate the logistical problems associated with order bills of lading. Discusses the legal status and contractual roles of these lading bills in the context the legislative provisions and associated case law in each of the three countries. Concludes that sea waybills (regulating marine transport of goods) and straight bills of lading have, in essence, the same contractual status, despite the confused and unconsolidated picture of international lading provisions and practices. Recommends measures ‐ involving amendments to English legislation ‐ to consolidate the regulation of international trade.

Refers to the history of the maritime sale of goods which resulted in a bill of lading, representing goods at sea in a ship. Attempts to determine whether or not a bill of lading is a negotiable instrument if it is characterized by such words as to order or to bearer. Compares US, Greek and English law and finds that English law is not in line with US and Greek law. Refers to the English Carriage of Goods by Sea Act (COGSA) 1992. Claims that differences in law may cause some problems for international trade and mentions the European Commission’s project to examine the feasibility of electronic bills of lading.

Looks at the practice of stipulating in international contracts which country’s law should govern any disputes that arise, using a governing‐law clause. Considers the regulations relating to contractual matters of conflict of laws laid down by the 1980 Convention on the Law Applicable to Contractual Obligations, which exclude bills of lading unless they are regarded as non‐negotiable instruments. Outlines the treatment of conflict of laws relating to bills of lading under Greek, US and English law, citing legal cases as examples, and reveals that in all three legal systems the choice of the applicable law, set out in the contract itself, is included in the bill of lading. Uncovers contradictions in the Greek and English approaches to the contractual role of bills of lading, and suggests that a uniform approach must be adopted, following the lead of US legislation, which clearly specifies that the bill of lading is the contract of carriage in which the choice of law is explicitly stated.

Discusses the Bill of Lading and its differences under UK, US and Greek law. Bases the paper on the fact that, under UK and US law, property in the goods sold passes from seller to buyer when the parties intend to pass it (regardless of whether or not delivery actually took place); whereas, under Greek law, ownership of goods passes from seller to buyer only if the intention to pass goods is supported by actual delivery. Asserts that this difference in national law causes problems in international trade. Explores the law in more depth, citing a number of cases and quoting legal precedents. Concludes that the intention of the parties concerned should be taken into consideration.

Presents the case for the use of computerised Bills of Lading. Outlines the issues of concern with electronic documents, showing that these documents have various roles to play, each of which must be considered when looking at the safeguards built into electronic systems. Considers Digital signatories, legal contractual agreements and various legislative approaches. Covers cross border jurisdiction and digital negotiability before looking at the European Model EDI Agreement. Comments on the Uncitral Model Law on Electronic Commerce and then presents the position held by the banking community. States the arguments for the paper form compared to the electronic form and concludes that there is a need for more understanding and legal clarification within the subject.

The sociology of education has various traditions which examine the connections between education, culture, and inequality. Two of these traditions, symbolic interactionism and critical theory, tend to ignore each other. This paper creates a dialogue between these traditions by applying symbolic interactionist (SI) and radical interactionist (RSI) sensibilities to an important study for resistance theory, Paul Willis’ classic ethnography Learning to Labor (1977). The SI reading of Learning to Labor emphasizes the importance of group interactions and the creation of meaning, while the RSI reading highlights how domination unfolds in social interaction. We argue that SI and RSI have much to offer Learning to Labor, as these readings can avoid some of the critiques commonly leveled on the book regarding the linkage between theory and data, structure and agency, and the book’s conceptualization of culture. Likewise, we argue that the data in Learning to Labor have much to offer SI and RSI, as the material provides grist to further understand the role of symbols in domination while identifying escalating dominance encounters that create a set of patterned interactions that we describe as a “grinding” social order.

Studies on the relationship between migration and health status of individuals most often concentrate on international migrants. In contrast, the purpose of this paper is to examine the relationship between health and internal migration using the first 18 waves of the British Household Survey.

The authors use the 12-version of General Health Questionnaire (GHQ), an indicator of mental health, and physical health indicators as the health variables. This study uses different econometrics estimation methods in modelling the relationship in order to address omitted variable bias as well as unobserved heterogeneity. The econometric estimation methods include Pooled OLS, random effects (RE), fixed effects (FE) and then probit RE. The authors explore the relationship by comparing the health status of movers and non-movers and different types of internal migration such as between local authority districts and between regions.

The results of this research suggest that there is healthy migrant effect on migration within UK on some indicators of physical health like arm/leg, heart and migraine/headache problems, but not on mental health indicator. And the effects are similar for both males and females. It is advised therefore that the department of health should improve the health of those affected by these ailments so that they can have a chance to move perhaps to better their lots.

This study uses different econometrics estimation methods in modelling the relationship in order to address omitted variable bias as well as unobserved heterogeneity. The econometric estimation methods include Pooled OLS, RE, FE and then probit RE.

In this paper, a data mining approach is proposed for monitoring the conditions leading to a rail wheel high impact load. The proposed approach incorporates logical analysis of data (LAD) and ant colony optimization (ACO) algorithms in extracting patterns of high impact loads and normal loads from historical railway records. In addition, the patterns are employed in establishing a classification model used for classifying unseen observations. A case study representing real-world impact load data is presented to illustrate the impact of the proposed approach in improving railway services.

Application of artificial intelligence and machine learning approaches becomes an essential tool in improving the performance of railway transportation systems. By using these approaches, the knowledge extracted from historical data can be employed in railway assets monitoring to maintain the assets in a reliable state and to improve the service provided by the railway network.

Results achieved by the proposed approach provide a prognostic system used for monitoring the conditions surrounding rail wheels. Incorporating this prognostic system in surveilling the rail wheels indeed results in better railway services as trips with no-delay or no-failure can be realized. A comparative study is conducted to evaluate the performance of the proposed approach versus other classification algorithms. In addition to the highly interpretable results obtained by the generated patterns, the comparative study demonstrates that the proposed approach provides classification accuracy higher than other common machine learning classification algorithms.

The methodology followed in this research employs ACO algorithm as an artificial intelligent technique and LDA as a machine learning algorithm in analyzing wheel impact load alarm-collected datasets. This new methodology provided a promising classification model to predict future alarm and a prognostic system to guide the system while avoiding this alarm.