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When Dirty Data Leads to Dirty Policing
Get PDFOn May 25th, 2020, George Floyd was tragically killed by police officers in Minneapolis. While George Floyd’s death was the shock that catapulted the Black Lives Matter (“BLM”) movement to the center of international attention, it was also just the tip of the iceberg. Floyd’s death was not the first death of a black person at the hands of the police, nor would it be the last. “A black person is killed by a police officer in America at a rate of more than one [person] every other day.” These repeated incidents across the country have ignited a mass movement centered on police violence against people of color, and predictive policing is at the forefront of the conversation. Yet the timing and casual cruelty of the death of George Floyd, recorded and shared on social media, spurred a national uprising. As people across America protested in the streets, the public seemed to take a greater interest in the history of the American criminal justice system and its roots in racial oppression. Although BLM has existed since 2013, the movement and policy discussion has gained a great deal of attention since the summer of 2020. [..
Disinformation and the Defamation Renaissance: A Misleading Promise of “Truth”
Get PDFToday, defamation litigation is experiencing a renaissance, with progressives and conservatives, public officials and celebrities, corporations and high school students all heading to the courthouse to use libel lawsuits as a social and political fix. Many of these suits reflect a powerful new rhetoric—reframing the goal of defamation law as fighting disinformation. Appeals to the need to combat falsity in public discourse have fueled efforts to reverse the Supreme Court’s press–protective constitutional limits on defamation law under the New York Times v. Sullivan framework. The anti–disinformation frame could tip the scales and generate a majority on the Court to dismantle almost sixty years of constitutionalized defamation law. The new anti–disinformation frame brings with it serious democratic costs without clear corresponding benefits. Defamation lawsuits cannot credibly stem the systemic tide of disinformation or predictably correct reputational harm, but they do threaten powerful chilling effects for the press, super–sized by our current socio-historical context. Especially as claims of disinformation drift away from political speech to economic and social matters, this as a distinct justification increasingly evaporates. Lest progressives too quickly rejoice over the apparent success of their disinformation claims against right–wing media, anti–disinformation defamation litigation presents an equal opportunity invitation—and conservative cases are already on track. The new disinformation frame for defamation suits offers an illusory distraction and further politicizes defamation. Instead, the Article suggests a shift of focus to the audience in order to advance the anti-disinformation project while returning defamation law to its traditional concern with individual reputation
Required Minimum Distribution (RMD) Spreadsheet Calculators Based on the SECURE Act of 2022
Get PDFRequired Minimum Distribution (RMD) Spreadsheet Calculators
Based on the SECURE Act of 2022
The Setting Every Community Up for Retirement Enhancement Act (SECURE Act) of 2022 made a second round of changes (relative to the SECURE Act of 2019) to the required minimum distribution (RMD) schedule for individual retirement accounts (IRAs) and defined contribution retirement plans. Excel spreadsheet calculators are developed to calculate the new annual RMD cash flows throughout retirement for those who are retired and for those who are planning to retire. The spreadsheet calculators also allow savings to accrue with interest if the RMD is in excess of expected annual costs.
KEY TAKEAWAYS:
The spreadsheet calculators require only basic inputs and can be updated and applied at any point in time during the planning period.
The spreadsheet calculators allow for interest to accumulate before and after retirement in the IRA and in a savings account if the RMD is in excess of expected annual costs.
The spreadsheet calculators allow for additional monthly contributions up to retirement
Reacting to the Past as Education for Leadership
Get PDFHow can courses on leadership effectively cultivate students’ leadership skills? This reflective essay explores how one form of role-playing called Reacting to the Past can promote students’ leadership skills and deepen their understanding of leadership. Reacting to the Past is a series of immersive role-playing simulations that are set at key moments in history and that require students to play the part of historical actors over the course of several weeks. I argue that Reacting to the Past encourages students to practice leadership skills in an authentic context, improves students’ understanding of leadership by allowing them to observe and participate in leadership processes firsthand, and has other important benefits for leadership education. Moreover, this essay also provides guidance on how to incorporate Reacting to the Past into courses on leadership and discusses strategies for addressing common problems that instructors confront when using this pedagogy
An Interdisciplinary Approach to the Legal History of Northern Ireland (1921-1948): Methods and Sources
Get PDFApproaches from legal scholarship include primary sources such as statutes and case law, as well as legislative histories which legal scholars rarely consider ‘history’ in the same way as historians. Rather, legal scholars often look to legislative histories to discern the intent of the legislature in enacting laws for the sole purpose of interpreting a statute’s meaning. This study utilises the research tools employed by legal scholars – statutory law, case law, and legislative histories – to examine the establishment of the legal system in Northern Ireland. The study will focus on the early period of devolution (1921 – 1948) and explore how a subordinate Parliament at Stormont used the law and the creation of a legal system to solidify Northern Ireland’s identity as a nation-state
A cosmopolitan inversion facilitates seasonal adaptation in overwintering Drosophila
No full textFluctuations in the strength and direction of natural selection through time are a ubiquitous feature of life on Earth. One evolutionary outcome of such fluctuations is adaptive tracking, wherein populations rapidly adapt from standing genetic variation. In certain circumstances, adaptive tracking can lead to the long-term maintenance of functional polymorphism despite allele frequency change due to selection. Although adaptive tracking is likely a common process, we still have a limited understanding of aspects of its genetic architecture and its strength relative to other evolutionary forces such as drift. Drosophila melanogaster living in temperate regions evolve to track seasonal fluctuations and are an excellent system to tackle these gaps in knowledge. By sequencing orchard populations collected across multiple years, we characterized the genomic signal of seasonal demography and identified that the cosmopolitan inversion In(2L)t facilitates seasonal adaptive tracking and shows molecular footprints of selection. A meta-analysis of phenotypic studies shows that seasonal loci within In(2L)t are associated with behavior, life history, physiology, and morphological traits. We identify candidate loci and experimentally link them to phenotype. Our work contributes to our general understanding of fluctuating selection and highlights the evolutionary outcome and dynamics of contemporary selection on inversions
Exploring the disruption of SARS-CoV-2 RBD binding to hACE2
No full textThe COVID-19 pandemic was declared due to the spread of the novel coronavirus, SARS-CoV-2. Viral infection is caused by the interaction between the SARS-CoV-2 receptor binding domain (RBD) and the human ACE2 receptor (hACE2). Previous computational studies have identified repurposed small molecules that target the RBD, but very few have screened drugs in the RBD–hACE2 interface. When studies focus solely on the binding affinity between the drug and the RBD, they ignore the effect of hACE2, resulting in an incomplete analysis. We screened ACE inhibitors and previously identified SARS-CoV-2 inhibitors for binding to the RBD—hACE2 interface, and then conducted 500 ns of unrestrained molecular dynamics (MD) simulations of fosinopril, fosinoprilat, lisinopril, emodin, diquafosol, and physcion bound to the interface to assess the binding characteristics of these ligands. Based on MM-GBSA analysis, all six ligands bind favorably in the interface and inhibit the RBD–hACE2 interaction. However, when we repeat our simulation by first binding the drug to the RBD before interacting with hACE2, we find that fosinopril, fosinoprilat, and lisinopril result in a strongly interacting trimeric complex (RBD-drug-hACE2). Hydrogen bonding and pairwise decomposition analyses further suggest that fosinopril is the best RBD inhibitor. However, when lisinopril is bound, it stabilizes the trimeric complex and, therefore, is not an ideal potential drug candidate. Overall, these results reveal important atomistic interactions critical to the binding of the RBD to hACE2 and highlight the significance of including all protein partners in the evaluation of a potential drug candidate
Nanomaterial-Doped Xerogels for Biosensing Measurements of Xanthine in Clinical and Industrial Applications
No full textFirst-generation amperometric xanthine (XAN) biosensors, assembled via layer-by-layer methodology and featuring xerogels doped with gold nanoparticles (Au-NPs), were the focus of this study and involved both fundamental exploration of the materials as well as demonstrated usage of the biosensor in both clinical (disease diagnosis) and industrial (meat freshness) applications. Voltammetry and amperometry were used to characterize and optimize the functional layers of the biosensor design including a xerogel with and without embedded xanthine oxidase enzyme (XOx) and an outer, semi-permeable blended polyurethane (PU) layer. Specifically, the porosity/hydrophobicity of xerogels formed from silane precursors and different compositions of PU were examined for their impact on the XAN biosensing mechanism. Doping the xerogel layer with different alkanethiol protected Au-NPs was demonstrated as an effective means for enhancing biosensor performance including improved sensitivity, linear range, and response time, as well as stabilizing XAN sensitivity and discrimination against common interferent species (selectivity) over time—all attributes matching or exceeding most other reported XAN sensors. Part of the study focuses on deconvoluting the amperometric signal generated by the biosensor and determining the contribution from all of the possible electroactive species involved in natural purine metabolism (e.g., uric acid, hypoxanthine) as an important part of designing XAN sensors (schemes amenable to miniaturization, portability, or low production cost). Effective XAN sensors remain relevant as potential tools for both early diagnosis of diseases as well as for industrial food monitoring
GVdoc: Graph-based visual document classification
No full textThe robustness of a model for real-world deployment is decided by how well it performs on unseen data and distinguishes between in-domain and out-of-domain samples. Visual document classifiers have shown impressive performance on in-distribution test sets. However, they tend to have a hard time correctly classifying and differentiating out-of-distribution examples. Image-based classifiers lack the text component, whereas multi-modality transformer-based models face the token serialization problem in visual documents due to their diverse layouts. They also require a lot of computing power during inference, making them impractical for many real-world applications. We propose, GVdoc, a graph-based document classification model that addresses both of these challenges. Our approach generates a document graph based on its layout, and then trains a graph neural network to learn node and graph embeddings. Through experiments, we show that our model, even with fewer parameters, outperforms state-of-the-art models on out-of-distribution data while retaining comparable performance on the in-distribution test set