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We examine the stock market reaction to the Tax Cuts and Jobs Act (TCJA) of 2017 during its enactment process, focusing on its international provisions. Consistent with extant evidence, we find lower returns for high-foreign-activity firms, indicating a negative market reaction to the international provisions overall. Considering specific international provisions, we find that the market reaction was more positive (negative) for firms likely most affected by the shift to a quasi-territorial system for taxing foreign earnings (the transition tax on existing unrepatriated earnings, the tax on global intangible low-taxed income, and/or the base erosion and antiabuse tax) than for other firms. Our findings imply that investors are able to disentangle the economic implications of complex and interactive tax law changes.

This chapter honors the opportunity I have had to learn with David Maines over the past 35 years. I connect my research on communication and disability, specifically among individuals who are blind and visually impaired, to Maines' discussion of narratives incorporating Rawlins' exploration of similarity and difference. I discuss narratives of disability as difference using three examples: A short story written by H. G. Wells; the American with Disabilities Act; and interviews conducted with elite blind goalball athletes. I conclude with 10 lessons learned about disability and difference including that the goal of my research is to help us all perceive disability as a difference that matters, but not as a difference that disables.

This case teaches students the importance of maintaining a strong FICO score by illustrating the consequences of paying bills late or not at all. The protagonist is David Molina, a waiter at a struggling Italian restaurant located down the block from where he lives. Money is tight for Molina right now—his limited income means he lives paycheck to paycheck. However, Molina knows things will be looking up for him soon because he recently accepted a job as a bank teller across town—his first desk job.

Molina has been putting off paying two of his bills: a cable bill and his Bank of America credit card bill, both of which are late and have been issued, this time, in the form of threats to impact Molina's credit score if he doesn't pay them. He has just enough money to afford the minimum payments on each overdue bill. But then he receives a phone call from his friend, Jim Lindsey, reminding him about an invitation to go to Myrtle Beach for the upcoming weekend. Molina knows he cannot afford it, but a woman he's attracted to, Jessica, will be there too. Should Molina put off the bills yet again, and if so, how exactly will being late on them hurt his credit score?

The Government of Eswatini (GoE) civil service wage bill has continued to rise in recent years. The personnel budget is still the largest single recurrent expenditure item in the budget in Eswatini. To control the civil service wage bill, the GoE introduced Lean Service Principle through Management Services Division (MSD). The civil service wage bill continues to rise despite the implementation of the Lean Service Principle. So far, there are no tangible outcomes that indicate that the principles applied have been effective in the reduction of the wage bill. Thus, this research aims to examine the question of why the Lean Service Principle failed to effectively slow the rampant growth of the civil service wage bill in the Kingdom of Eswatini. This study used the quantitative research approach to collect data on amounts spent on wages, the percentage increase of the wage bill for the period 2010–2017, and the percentage increase in the number of civil servants as per the Establishment Registers, 2010–2017. The study investigated the wage bill push factors, the shortcomings of the Lean Service Principle, and the Just-In-Time (JIT) Technique in the management and reduction of the GoE civil service wage bill. The study found the MSD has been applying the wrong methodologies in wage bill control, which has been evident in the continued yearly increase of the wage bill. The study recommends that the MSD should consider the utilisation of Human Resources Forecasting and Planning Techniques instead of using the Lean Service Principle and the JIT technique. This study will enable the Cabinet to make an appropriate decision on the mandate and future of the MSD, as there have been growing calls to disband the division due to the failure to reduce and/or control the wage bills as that is the core mandate of the division.

This paper aims to present a methodology for the detection and categorisation of metal powder particles that are partially attached to additively manufactured lattice structures. It proposes a software algorithm to process micro computed tomography (µCT) image data, thereby providing a systematic and formal basis for the design and certification of powder bed fusion lattice structures, as is required for the certification of medical implants.

This paper details the design and development of a software algorithm for the analysis of µCT image data. The algorithm was designed to allow statistical probability of results based on key independent variables. Three data sets with a single unique parameter were input through the algorithm to allow for characterisation and analysis of like data sets.

This paper demonstrates the application of the proposed algorithm with three data sets, presenting a detailed visual rendering derived from the input image data, with the partially attached particles highlighted. Histograms for various geometric attributes are output, and a continuous trend between the three different data sets is highlighted based on the single unique parameter.

This paper presents a novel methodology for non-destructive algorithmic detection and categorisation of partially attached metal powder particles, of which no formal methods exist. This material is available to download as a part of a provided GitHub repository.

The purpose of this paper is to evaluate the Dual Use (DU) Option – a crop insurance policy created by the 2018 Farm Bill – relative to other policies available to dual-purpose annual forage producers. The new policy combines existing rainfall-based policies for annual forage crops and multi-peril policies for grain, allowing coverage for multiple crop uses on the same acres during the same growing season.

The paper uses a simulation model to examine crop insurance choices for a typical Texas dual-purpose wheat farm. The certainty equivalent (CE) of wealth is used to rank choices within and between three insurance plans and to analyze the effects of those choices over a range of producer risk aversion levels and for three cases of yield expectations.

The DU Option is more preferred as risk aversion increases, but it is not universally preferred. Therefore, while the policy can be a viable risk management tool, certain restrictions may be limiting its effectiveness.

The findings of this paper can help explain farm-level decision making related to dual-purpose annual forage crop insurance program choices.

This paper contributes to the literature by documenting a new crop insurance program made available in the 2018 Farm Bill and provides insights into producers' possible choices by evaluating extensive scenarios.

Granting ‘sanctuary’ in the United States to those fleeing poverty and violence is rooted in a deep history of hospitality and compassion. As we are witnessing a rise in xenophobia accompanied by policies of exclusion, we also see a rising number of ‘sanctuary jurisdictions’ limiting their cooperation with immigration authorities that many communities consider are using extremely harsh and punitive measures to detain and deport irregular migrants. As this chapter will demonstrate, there has been a dramatic increase through ‘immigration federalism’ of the number of these jurisdictions in cities, states and municipalities since the first practices of ‘sanctuary’ in the 1980s as result of the waves of forced migration due to the civil wars in Central America. The author also proposes that those entities granting ‘sanctuary’ to irregular migrants should also apply practices of ‘compassionate migration’ as described in the chapter to expand their protections further and include them in their communities.

This letter to David R. Maines celebrates our friendship over the last 35 years. I read his voice in emails, handwritten letters, and recollected phone conversations to display the meaningful exchanges of our scholarly friendship. I thank Dave for teaching me how to retire from the academy and grow older with purpose and grace. Highlighting his expert mentoring of my book Friendship Matters (1992), I recall how his suggested revisions for the chapters on aging anticipated a poignant array of our own experiences as friends in our later years. Finally, I appreciate his cultivated interests in drawing, writing poetry, and playing guitar, and thank him for encouraging my music. I am grateful for his dedication to esthetic endeavors, which warmly shaped our friendship during our later years.

Many libraries and archives maintain collections of research documents, such as administrative records, with paper-based formats that limit the documents' access to in-person use. Digitization transforms paper-based collections into more accessible and analyzable formats. As collections are digitized, there is an opportunity to incorporate deep learning techniques, such as Document Image Analysis (DIA), into workflows to increase the usability of information extracted from archival documents. This paper describes the authors' approach using digital scanning, optical character recognition (OCR) and deep learning to create a digital archive of administrative records related to the mortgage guarantee program of the Servicemen's Readjustment Act of 1944, also known as the G.I. Bill.

The authors used a collection of 25,744 semi-structured paper-based records from the administration of G.I. Bill Mortgages from 1946 to 1954 to develop a digitization and processing workflow. These records include the name and city of the mortgagor, the amount of the mortgage, the location of the Reconstruction Finance Corporation agent, one or more identification numbers and the name and location of the bank handling the loan. The authors extracted structured information from these scanned historical records in order to create a tabular data file and link them to other authoritative individual-level data sources.

The authors compared the flexible character accuracy of five OCR methods. The authors then compared the character error rate (CER) of three text extraction approaches (regular expressions, DIA and named entity recognition (NER)). The authors were able to obtain the highest quality structured text output using DIA with the Layout Parser toolkit by post-processing with regular expressions. Through this project, the authors demonstrate how DIA can improve the digitization of administrative records to automatically produce a structured data resource for researchers and the public.

The authors' workflow is readily transferable to other archival digitization projects. Through the use of digital scanning, OCR and DIA processes, the authors created the first digital microdata file of administrative records related to the G.I. Bill mortgage guarantee program available to researchers and the general public. These records offer research insights into the lives of veterans who benefited from loans, the impacts on the communities built by the loans and the institutions that implemented them.