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The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead to rapid deterioration, decreased service life, lower level of service and increased community disruption. Therefore, this paper aims at providing a state-of-the-art review of the literature with respect to deep learning techniques for detecting distress in both pavements and buildings; research advancements per asset/structure type; and future recommendations in deep learning applications for distress detection.

A critical analysis was conducted on 181 papers of deep learning-based cracks detection. A structured analysis was adopted so that major articles were analyzed according to their focus of study, used methods, findings and limitations.

The utilization of deep learning to detect pavement cracks is advanced compared to assess and evaluate the structural health of buildings. There is a need for studies that compare different convolutional neural network models to foster the development of an integrated solution that considers the data collection method. Further research is required to examine the setup, implementation and running costs, frequency of capturing data and deep learning tool. In conclusion, the future of applying deep learning algorithms in lieu of manual inspection for detecting distresses has shown promising results.

The availability of previous research and the required improvements in the proposed computational tools and models (e.g. artificial intelligence, deep learning, etc.) are triggering researchers and practitioners to enhance the distresses’ inspection process and make better use of their limited resources.

A critical and structured analysis of deep learning-based crack detection for pavement and buildings is conducted for the first time to enable novice researchers to highlight the knowledge gap in each article, as well as building a knowledge base from the findings of other research to support developing future workable solutions.

This issue is a selected bibliography covering the subject of leadership.

The purpose of this paper is to deepen our understanding of the philosophical and scientific pedigree of the concept of “common sense”, and explore the implications for managerial decision‐makers.

After examining the management literature on this topic, a brief history of the notion and philosophy of common sense is followed by a review of recent findings in cognitive science and other fields and a discussion of implications for managerial decision‐making.

The notion of common sense has a stable perceptual basis in the makeup of the human mind, as has been shown by philosophers and scientists. Common sense intuitions serve as the basis for making sense of the world: visual perception, scientific reasoning, language, psychology, mathematics, and moral judgments are all rooted in “mental hardware” of common sense. While it is a necessary element of human cognition, common sense can nevertheless lead us astray if we are unaware of its contours and limitations, which are outlined in this paper.

Understanding that the mind comes equipped with a host of common sense mental instincts will have an impact on both one's own decision‐making processes, and how decision‐makers attempt to influence others.

Based on original research as well as literature from a variety of disciplines, this paper provides a comprehensive understanding of the philosophical and scientific pedigree of “common sense” and its implications for decision‐makers.

The aim of this study was to draw on the theory of planned behavior (TPB) and attempt to identify the factors influencing the customer decision to purchase via online auctions, focusing on how managers selling via online auctions can modify product positioning and promotion decisions in order to make their offerings more congruent with these factors.

The study employed a survey instrument to collect data from Yahoo!Kimo website consumers in Taiwan, obtaining 450 samples which were analyzed with structural equation modeling.

Attitude toward online auctions, perceived behavioral control and past related experiences significantly and positively influence the intention to purchase on online auctions, whereas subjective norm does not have such influence. Additionally, past related experiences have a positive effect on perceived behavioral control.

There has been a relative dearth of work on online auction customer behavior. By applying the TPB to online auction research, it was empirically supported that behavioral intention to purchase via online auctions is determined by attitude and perceived behavior control. Past related experiences were further integrated, discovering that they can strengthen perceived behavioral control.

Recommendations are put forward in order to help better align product positioning and promotion decisions in online auctions with customer attitudes, perceived behavioral control, and past related experiences. These constructs may also be capable of explaining employee actions in general managerial contexts, thus extending the contribution of the paper beyond the limited world of online auctions.

This study integrated online auctions, the theory of planned behavior and consumer decision‐making philosophies in order to develop and empirically test a theoretical framework of consumer decision making in online auctions.

The purpose of this paper is to investigate magneto-mechanical coupling occurring in magnetic resonance imaging (MRI) systems. The authors study influence of the strength of the background field on the coupling of mechanically isolated, conductive cylindrical structures and the so-called shields. This coupling has a strong impact on frequency-dependent thermal losses occurring in the shield structures which are of high importance in MRI systems.

In the investigations, numerical methods are applied. First, finite element methods taking into account the full magneto-mechanical coupling are used to investigate the coupled physical phenomena. As these calculations may be time-consuming, several approximate predictive methods are derived. Modal expansion factors and participation factors are based on combinations of structural eigenmode calculations and eddy current calculations using Biot–Savart representations of the dynamic gradient field. In addition, a parallelism factor expressed in terms of the shield vibrations is defined to measure the coupling between the distinct cylinders.

It is found that the strength of the background field strongly influences the coupling of the distinct shields, which strongly increases the parallelism of the shield vibrations. Furthermore, modal expansion and participation factors are significantly influenced, caused by frequency shifts due to magnetic stiffening and increased magnetic coupling.

The current work is limited to the modal expansions of a single shield. This needs to be extended in the future as comparison of modal expansion factors and finite element simulation indicate.

The defined factors estimating parallelism and modal participation in magneto-mechanical coupling are original work and studied for the first time.

Research funded by the Albert Shanker Institute found African-American teachers leaving teaching at higher rates than White counterparts even though the former are recruited in proportionally higher numbers. Thus, while recruitment efforts appear somewhat successful, schools and school systems fail to retain teachers of color. This “revolving door” of African-American teachers portends dire consequences for school communities, creating instability of staffing that potentially upend students’ opportunities for academic success. African-American female (AAF) teachers, considered a backbone of non-White communities, are particularly sensitive to teacher mobility and turnover. Studies, however, indicate that AAF teachers are more satisfied working in urban school contexts than other teachers, suggesting that they prefer racially congruent schools which share sociocultural attributes similar to their own, and view working conditions more favorably in such environments.

Teachers’ perceptions of the workplace can be used to gauge risk for occupational stress. Commonly referred to as the transactional model, teachers’ risk for stress can be assessed by the appraising workplace resources vis-à-vis workplace demands. Stress-vulnerable teachers are associated with lower professional commitment and increased occupational burnout. Using data from the National Center for Education Statistics 2007–2008 Schools and Staffing Survey (SASS), this chapter explored the intersections of risk for occupational stress, racial congruence, and professional commitment among AAF teachers. Findings from this chapter suggest interactions between racial congruence and AAF teachers’ perceptions of occupational stress and commitment to teaching. Implications for how these results might inform policy are discussed.

The concept of company culture is now playing an ever‐increasing role in the continuing endeavour to work towards ever better company management, particularly in the industrial field. This monograph reviews the history and development of both national and company cultures, and then goes on to demonstrate the significance of a culture to proper company management. Well‐managed companies will have both a “quality culture” and a “safety culture” as well as a cultural history. However, it has to be recognised that the company culture is subject to change, and effecting this can be very difficult. Of the many national cultures, that of Japan is considered to be the most effective, as is demonstrated by the present dominance of Japan on the industrial scene. Many industrialised nations now seek to emulate the Japanese style of management, but it is not possible to copy or acquire Japan′s cultural heritage. The text is illustrated by a large number of practical examples from real life, illustrating the way in which the company culture works and can be used by management to improve company performance.

Special education in the USA is, in most respects, a 20th century phenomenon and is now governed primarily by federal legislation first enacted in 1975. The federal law in its most recent reauthorization (2004) continues to require a free appropriate public education (FAPE) for all students with disabilities, a full continuum of alternative placements (CAP) ranging from residential or hospital care to inclusion in general education, an individual education plan or program (IEP) for each student identified as needing special education, and placement in the least restrictive environment (LRE) that is thought best for implementing the IEP. Parents must be involved in the special education process. Approximately 14 percent of public school students were identified for special education in 2004–2005, but the number and percentage of students identified in most high-incidence categories as needing special education have declined in recent years (the total for all categories was about 8.5 percent of public school students in 2010). A variety of evidence-based interventions can be used to address the wide range of instructional and behavioral needs of students with disabilities and their families, including transition to further education or work, family services, and teacher education. Special education in the USA may find new sources of support and thrive or may become less common or be abandoned entirely due to criticism and withdrawal of support for social welfare programs of government.

This research analyzes online consumer reviews and ratings to assess e-retail order fulfillment performance. The study aims to (1) identify consumer journey touchpoints in the order fulfillment process and (2) determine their relative importance for the consumer experience.

Text mining and analytics were employed to examine over 100 m online purchase orders, along with associated consumer reviews and ratings from Amazon US. Using natural language processing techniques, the corpus of reviews was structured to pinpoint touchpoints related to order fulfillment. Reviews were then classified according to their stance (either positive or negative) toward these touchpoints. Finally, the classes were correlated with consumer rating, measured by the number of stars, to determine the relative importance of each touchpoint.

The study reveals 12 touchpoints within the order fulfillment process, which are split into three groups: delivery, packaging and returns. These touchpoints significantly influence star ratings: positive experiences elevate them, while negative ones reduce them. The findings provide a quantifiable measure of these effects, articulated in terms of star ratings, which directly reflect the influence of experiences on consumer evaluations.

The dataset utilized in this study is from the US market, which limits the generalizability of the findings to other markets. Moreover, the novel methodology used to map and quantify customer journey touchpoints requires further refinement.

In e-retail and logistics, comprehending touchpoints in the order fulfillment process is pivotal. This understanding helps improve consumer interactions and enhance satisfaction. Such insights not only drive higher conversion rates but also guide informed managerial decisions, particularly in service development.

Drawing upon consumer-generated data, this research identifies a cohesive set of touchpoints within the order fulfillment process and quantitatively evaluates their influence on consumer experience using star ratings as a metric.

The imposition of term limits in bicameral (two‐chamber) state legislatures could produce unforeseen consequences in the policymaking process. Supporters of term limit rules have not considered that their imposition could fundamentally shift the sequence of policymaking in legislatures. This is important given that research on sequential bicameral policymaking suggests qualities of the lower chamber allow it to cultivate policy expertise such that the upper chamber will defer to the lower chamber in policymaking. This project aims to explore whether this proposed policymaking sequence exists in term‐limited states.

A comparison of policy adoptions in states with and without term limits is performed using an original data set on bill adoptions for all US bicameral legislatures that had a regular session between the years 2000 and 2006. Least‐squares regression models evaluate whether basic characteristics of legislatures are as relevant as term limit characteristics in explaining the level of outputs from the lower chamber in term‐limited states.

In states with term limits, the level of policy adoptions initiated by the lower chamber is lower than levels seen in states without term limits. This finding holds when controlling for other relevant variables that can potentially explain lower chamber productivity.

The study analyzes aggregate state‐level data and does not interview individual legislators in states with and without term limits on whether term limits can alter future legislative behavior.

This study is the first to examine whether the policymaking sequence differs between states that possess and do not possess term limit rules.