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Using a novel measure incorporating stylistic and acoustic data on recorded music from 1967 to 2017, we search for trends in the evolution of musical diversity in 125,340 albums. We find that temporal patterns of diversity differ for stylistic and acoustic data. We also find that the patterns differ dramatically by genre. Some genres, such as blues, jazz, and pop-rock, decrease in diversity over time; most other genres increase in diversity. The causes of these different trends present a puzzle for future research. We also find different patterns for recordings that made the Billboard 200 charts compared to all recordings, suggesting an association between selection processes driven by consumer popularity and diversity. Moreover, associations of diversity and industry structure found in prior research do not hold when we analyze data beyond the smaller sample of the more popular recordings found in Billboard. These findings have implications for many prior studies based exclusively on best-selling recordings

This chapter identifies and analyzes three systemic obstacles to American public policy addressing natural disasters: symbolic obstacles, cognitive obstacles, and structural obstacles. The way we talk about natural disaster, the way we think about the risks of building in hazardous places, and structural aspects of American political institutions all favor development over restraint. These forces have such strength that in the wake of most disasters society automatically and thoughtlessly responds by rebuilding what was damaged or destroyed, even if reconstruction perpetuates disaster vulnerability. Only by addressing each of the obstacles identified are reform efforts likely to succeed.

The aim is to set a state‐of‐the‐art in scientific research towards the development of knee prostheses for transfemoral amputees, by reviewing the literature in the field and by identifying different scientific research lines that have brought out through the years. Also, to provide the information about possible outcomes in the near future, and their links to cybernetics, given the present trends in the field.

Literature related to scientific research carried out up‐to‐date in the field of knee prostheses, is reviewed in scientific articles, books and electronic sources. Then, different research lines are identified from the obtained information, and finally classified as presented in this work.

Three scientific research lines regarding the development of knee prostheses were found, each one dealing with: the design of knee prostheses; the performance assessment of these prostheses; and the creation of control strategies for these prostheses which use electronics to control their performance. Also, two new possible eras of prostheses were encountered: the cybernetic era, and the electromyographic one. Considering both options, it is concluded that the cybernetic era of prostheses is likely to become real soon.

A useful state‐of‐the‐art review for researchers likely to be introduced in the field of development of knee prostheses and prosthetic technology in general.

This literature review not only sets a state‐of‐the‐art of the development of knee prostheses, but also proposes a frame of references which allows to classify the different works done in the field, as well as a better understanding of these through a clear presentation.

Successful bridge management system (BMS) development requires a reliable bridge deterioration model, which is the most crucial component in a BMS. Historical condition ratings obtained from biennial bridge inspections are a major source for predicting future bridge deterioration in BMSs. However, historical condition ratings are very limited in most bridge agencies, thus posing a major barrier for predicting reliable future bridge performance. The purpose of this paper is to present a preliminary study as part of a long‐term research on the development of a reliable bridge deterioration model using advanced Artificial Intelligence (AI) techniques.

This proposed study aims to develop a reliable deterioration model. The development work consists of two major Stages: stage 1 – generating unavailable bridge element condition rating records using the Backward Prediction Model (BPM). This helps to provide sufficient historical deterioration patterns for each element; and stage 2 – predicting long‐term condition ratings based on the outcome of Stage 1 using time delay neural networks (TDNNs).

Long‐term prediction using proposed method can also be expressed in the same form of inspection records – element quantities of each bridge element can be predicted. The proposed AI‐based deterioration model does not ignore critical failure risks in small number of bridge elements in low condition states (CSs). This implies that the risk in long‐term predictions can be reduced.

The proposed methodology aims to utilise limited bridge inspection records over a short period to predict large datasets spanning over a much longer time period for a reliable, accurate and efficient long‐term bridge deterioration model. Typical uncertainty, due to the limitation of overall condition rating (OCR) method, can be minimised in long‐term predictions using limited inspection records.

High performance computing (HPC) is used to solve complex calculations that personal computing devices are unable to handle. HPC offers the potential for small- and medium-size enterprises (SMEs) to engage in product innovation, service improvement and the optimization of resource allocation (Borstnar and Ilijas, 2019). However, the expensive infrastructure, maintenance costs and resource knowledge gaps that accompany the use of HPC can make it inaccessible to SMEs. By moving HPC to the cloud, SMEs can gain access to the infrastructure without the requirement of owning or maintaining it, but they will need to accept the terms and conditions of the cloud contract. This paper aims to improve how SMEs access HPC through the cloud by providing insights into the terms and conditions of HPC cloud contracts.

This paper adopts a systematic literature review by implementing a four-step approach. A comprehensive search was undertaken and results synthesized to enable this paper’s objectives to be met.

This paper proposes that SMEs could gain competitive advantage(s) by understanding their own needs and improving their contract negotiation abilities, service management skills and risk management abilities before accepting the terms and conditions of the cloud contract. Furthermore, a checklist, service-level agreement, easily ignored elements and risk areas are presented as guidance for SMEs when reviewing their HPC cloud contract(s).

While HPC cloud contracts are a niche research topic, it is one of the key factors influencing the ability of SMEs to access HPC through the cloud. It is, however, by no means a level playfield with SMEs at a distinct disadvantage because of not influencing the writing up of the HPC cloud contract. The added value of the paper is that it contributes to our overall understanding of the terms and conditions of HPC cloud contracts.

In Canada, food insecurity is characterized by the consumption of low quantity or low-quality foods, worrying about food supply and/or acquiring foods in socially unacceptable ways, such as begging or scavenging. As of 2012, approximately 15.2% of Ontario, Canada, children are living in food insecure households, a prevalence which has remained steady since 2005. This is particularly concerning when considering that school-aged children are a population whose growth and developing is sensitive to nutritional stress, and the experience of childhood food insecurity is highly associated with the development of adverse physical, mental and learning outcomes. This study aims at establishing the relationship between food insecurity and Education Quality and Accountability Office (EQAO) standardized test scores in order to highlight the incompatibility of the EQAO's reliance on test outcomes in determining Ontarian school's accountability, specifically for those with a high prevalence of food insecurity.