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This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The complexity of atmospheric corrosion, further compounded by the effects of climate change, makes existing models inappropriate for corrosion prediction. The commonly used kinetic model and dose-response functions are restricted in their capacity to represent the non-linear behaviour of corrosion phenomena. The application of artificial intelligence (AI)-driven machine learning algorithms to corrosion data can better represent the corrosion mechanism by considering the dynamic behaviour due to changing climatic conditions. Effective use of materials, coating systems and maintenance strategies can then be made with such a corrosivity model. Accurate corrosion prediction will help to improve climate change resilience of the social, economic and energy infrastructure in line with the UN Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure) and 13 (Climate Action). This chapter discusses atmospheric corrosion prediction in relation to the SDGs and the influence of AI in overcoming the challenges.

Using data from the Children of Immigrants Longitudinal Study, this study examines the structural relationships between negative school social relationships, school safety, educational expectation, and academic achievement of Latino immigrant students. Results from multilevel structural equation modeling show that discrimination, unhelpful school social relationships, and experiences of unsafe school environments influence Latino immigrant adolescents’ academic achievement indirectly and directly through their educational expectations. Specifically, this study explores how noncognitive and contextual factors embedded in different structural layers of school organization influence Latino immigrant adolescents’ academic achievement. It draws attention to the impact of negative school factors such as discriminatory and unsupportive school social relationships, and negative and unsafe school structures that undermine school life. Based on our findings, we argue that as Latino immigrant students internalize negative experiences from their school experiences during the critical period of adolescence, such accumulated negative internalization may reinforce negative self-perceptions and inaccurate stereotypes. Not only discrimination but also other negative school features such as the absence of academic supporters, nonacademically oriented friends, and unsafe learning environments inhibit them from navigating positive school opportunities and ultimately, successful school achievement. Implications for the social organization of U.S. public secondary schools with a focus on Latino immigrant adolescents’ academic achievement are discussed.

Extant theory tends to treat Organizational Culture (OC) and fraud-related values as static, characterizing culture as synonymous with potential ethical values − but devoting less attention to how the culture and values arose and where they are headed. Buffer/conduit theory proposes that accountants learn to use a taxonomy containing three dynamic layers: collective fraud orientation, a buffer/conduit layer, and individual fraud orientation. The middle layer contains OC-related internal controls that buffer the orientation layers from spreading fraud-encouraging values, and serve as conduits transmitting fraud-deterring values − or, when controls do not function as intended, transmitting fraud-encouraging values. A factor analysis of 11 indicators of this three-layer taxonomy suggests that older generations of accounting practitioners apply the taxonomy, but millennials do not. Predisposition to commit fraud is especially salient to internally focused millennials, who uniquely perceive recruitment and training as compensating mechanisms and as collective buffers.

The authors use their university and its writing program as a case study to interrogate established wraparound support systems for foster youth and the role that additional, volunteer faculty – led support services can play in retention and graduation rates. This chapter first provides research on college-going foster youth in the United States. Then, it considers the foster youth population and established support programs at the University of California, Riverside. Next, this chapter reviews the benefits of faculty – student mentoring and tutoring, specifically in composition studies, and how those benefits can contribute to a successful college-going experience. The chapter then shifts to offering a model for those interested in establishing a similar program. Using business, communication, composition, education, and psychosocial theory to ground the discussion, the authors provide a detailed account of the proposal, implementation, and ongoing programmatic administration processes, including the rationale undergirding decision-making. Ultimately, they show how equitable supplemental academic support led by composition faculty can bridge the gap between existing foster youth services and outstanding needs, an innovative approach that relies on the natural mentoring relationships which organically evolve from faculty–student interaction.