Digital Commons Network^™

A New Framework For Taxing Cryptocurrencies, Reuven S. Avi-Yonah, Mohanad Salaimi

Articles

This Article explores the tax law challenges associated with the taxation of cryptocurrencies and offers proposals to address such challenges. The Article addresses the proper tax treatment of different cryptocurrency transactions and activities. It examines various aspects associated with the taxation of cryptocurrency through its life cycle, starting from earning cryptocurrency, through its disposal or exchange. The Article also examines the tax treatment of two special crypto events, hard forks and airdrops. Specifically, this Article describes a proposal to tax cryptocurrencies based on their unique features. It argues that various ways of earning or receiving crypto tokens (for example, mining …

How Not To Lie: A Don't-Do-It-Yourself Guide For Litigators, Leonard Niehoff

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Over the past few years, a number of high-profile attorneys have been sanctioned or suspended from the practice of law because they lied. The instance that probably received the greatest media attention came in June of 2021, when the Appellate Division of the Supreme Court of the State of New York ordered the immediate suspension of Rudy Giuliani’s license because he had made demonstrably false statements to the courts, lawmakers, and the public at large concerning the 2020 presidential election. In a 33- page opinion, the court considered the arguments Giuliani raised in his defense but concluded that his pants …

Assessing Visions Of Democracy In Regulatory Policymaking, Shoba Sivaprasad Wadhia, Christopher J. Walker

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Motivated in part by Congress’s failure to legislate, presidents in recent years seem to have turned even more to the regulatory process to make major policy. It is perhaps no coincidence that the feld of administrative law has similarly seen a resurgence of scholarship extolling the virtues of democratic accountability in the modern administrative state. Some scholars have even argued that bureaucracy is as much as if not more democratically legitimate than Congress, either in the aggregative or deliberative sense, or both.

The Failed Federalism Of Affordable Housing: Why States Don't Use Housing Vouchers, Noah Kazis

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This Article uncovers a critical disjuncture in our system of providing affordable rental housing. At the federal level, the oldest, fiercest debate in low-income housing policy is between project-based and tenant-based subsidies: should the government help build new affordable housing projects or help renters afford homes on the private market? But at the state and local levels, it is as if this debate never took place. The federal government (following most experts) employs both strategies, embracing tenant-based assistance as more cost-effective and offering tenants greater choice and mobility. But this Article shows that state and local housing voucher programs are …

Informationalism Beyond Managerialism, Salome Viljoen

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It is now commonplace to observe that digital platforms are both affecting and reshaping markets. The focus of this Article is not the anticompetitive effects of digital platforms upon the markets they enter. It instead focuses on digital platforms themselves as market mechanisms. Information—especially datafied information about people and their behavior—and information technologies have transformed how many markets function in the digital economy. Markets have become market machines: highly engineered and computationally intensive market-like mechanisms that make up a key layer of technological infrastructure within digital platforms.

Cryptic Patent Reform Through The Inflation Reduction Act., Arti K. Rai, Rachel E. Sachs, Price W. Nicholson

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If a statute substantially changes the way patents work in an industry where patents are central, but says almost nothing about patents, is it patent reform? We argue the answer is yes — and it’s not a hypothetical question. The Inflation Reduction Act (“IRA”) does not address patents, but its drug pricing provisions are likely to prompt major changes in how patents work in the pharmaceutical industry. For many years scholars have decried industry’s ever-evolving strategies that use combinations of patents to block competition for as long as possible, widely known as “evergreening,” but legislators have not been receptive to …

The Great Regulatory Dodge, Helen Nissenbaum, Katherine Strandburg, Salome Viljoen

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U.S. privacy law is in a renewed moment of regulatory possibility, with both Congress and the states considering sweeping consumer privacy laws. These new proposals to enact “omnibus” privacy protections could be couched as an antidote to the current U.S. privacy regime: a patchwork of sectoral privacy laws stitched atop the background of FTC consumer contract enforcement. However, this Essay maintains that a one-size-fits-all approach cannot successfully capture both privacy’s value and its variability. Yet, it is clearly the case that the present- day sectoral regime in the United States suffers from significant shortcomings. These shortcomings allow behaviors that seem …

Public Engagement, Equity, And Executive Order 14,094., Nina A. Mendelson

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Executive Order 14,094 ("the Order"), signed by President Biden in April, 2023, breaks ground to make regulatory decisionmaking more equitable and inclusive, continuing a theme the Biden Presidency began with Executive Order 13,985, Advancing Racial Equity and Support for Underserved Communities Through the Federal Government. Agencies must, of course, hear from those who are regulated, but genuinely equitable decisionmaking also requires agencies to hear and engage the concerns of affected individuals and communities, including underserved communities. This recognizes that many Americans have a distinct and substantial interest in the benefits promised by legislatively created regulatory programs, whether those include safe …

The Value Of Understandable Consumer Insurance Contracts, Kyle Logue, Daniel Schwarcz, Brenda Cude

Articles

Insurance consumers, the intermediaries who serve them, and the regulators who protect them all would benefit from understandable consumer insurance contracts. This article outlines the benefits of understandable insurance contracts, identifies the regulatory tools that are or can be used to ensure such comprehensibility, and reviews the existing literature about how well consumers comprehend their insurance policies within the context of personal lines insurance in the U.S. The article concludes by proposing an empirical research strategy to study consumers’ understanding of the terms of homeowners insurance policies and, even when they have not read their policies, their expectations about coverage.

All Stick And No Carrot? Reforming Public Offerings, Stephen J. Choi, Adam C. Pritchard

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The SEC heavily regulates the traditional initial public offering (IPO). Those regulatory burdens fuel interest in alternative paths for private companies to go public, “regulatory arbitrage.” The SEC’s response to the emergence of alternatives, most recently SPACs and direct listings, has been to re-assert the regulatory protections in a traditional IPO, including heightened liability under Section 11 of the Securities Act. The SEC’s treatment of the traditional IPO regulatory process as a one-size fits-all regime ignores the weaknesses of this process, in particular the informational inefficiency of the book-building process. In this essay we argue that the agency’s focus in …

Unreasonable Risk: The Failure To Ban Asbestos And The Future Of Toxic Substances Regulation, Rachel Rothschild

Articles

Every day, Americans are exposed to hundreds of chemicals in the air we breathe, the water we drink, and the products we use. The vast majority of these chemicals have never been tested far safety. Many have been shown to cause serious health harms, ranging.from cancer to autoimmune illness to IQ loss. They also have disproportionate effects on some of the most vulnerable populations in our society, such as children, minorities, and industrial workers.

The law that is supposed to protect Americans from dangerous chemical exposures-the Toxic Substances Control Act ("TSCA")-was long considered a dead letter after the Environmental Protection …

Reforming The Exit Tax, Reuven S. Avi-Yonah

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Code Sec. 877A was enacted in 2008 to impose a significant price on U.S. cit-izens who expatriate. But the price is not right. The quarterly data on expatri-ations (published in the Federal Register since 1998) show an increasing trendsince 2008. For example, 3,422 Americans expatriated in 2022, and the averagesince 2013 was 3,239. By comparison, between 1998 and 2012, fewer than1,000 Americans expatriated each year. This paper will discuss why the increasehappened and what Congress can do about it.

When To Be Objectionable… And How Not To Be An Artless Clay-Brained Pignut, Leonard Niehoff

Articles

Having taught evidence for more than 30 years. I've become fairly good at predicting the questions students will ask, especially the questions that are hardest to answer. One of those typically comes after we've discussed how to object to evidence. We've worked through the basics: Stand up, speak up, say that you object, and briefly explain why. At this point a student almost always raises his or her and says something like this: "OK. I understand the how part. But when do I object?"

The New Orleans Transformation: Foster Care As A Rare, Time-Limited Intervention, Josh Gupta-Kagan, Christopher Church, Melissa Carter, Vivek Sankaran, Andrew Barclay

Articles

This Article offers an initial evaluation of one reformed child protection system— New Orleans, Louisiana—and describes how a system that dramatically reduces the number of children in foster care might look. This system shows how a major metropolitan area can shrink its daily population of children in foster care to the low double digits, which would correspond to a reduction of the national daily foster care population by about 360,000. This reduction was mostly due to sending children home—usually to the homes from which they were removed—within days or weeks of removal, raising questions about the necessity of the original …

Individual Mobility And The Corporate Tax, Reuven S. Avi-Yonah

Articles

The COVID-19 pandemic greatly increased the ability of individuals to move to their preferred location on the globe and continue to work remotely. This phenomenon has significant implications for individual income taxation because if they are U.S. citizens, these individuals are subject to two global residence-based tax regimes.

Strabismus And Amblyopia In Africa – A Systematic Review And Meta-Analysis, Prince Kwaku Akowuah, Samuel Adade, Andrews Nartey, Ebenezer Owusu, Richard Donkor, Stephen Ankamah-Lomotey

Articles

The objective of this review was to estimate the prevalence of strabismus and amblyopia in Africa. A systematic online literature search was conducted for articles on strabismus and amblyopia in Africa. Meta-analysis was performed, using the Freeman-Tukey double arcsine transformation, to estimate the prevalence of strabismus and amblyopia in Africa. Subgroup analyses were conducted according to age, gender, study year, and type of amblyopia. Meta-regression was used to evaluate the influence of predetermined factors on the prevalence of amblyopia. 8 (1 population-based & 7 school-based) and 21 (3 population-based & 18 school-based) studies on strabismus and amblyopia with sample sizes …

Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Articles

The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart sound signals need to be captured using a signal acquisition device. However, it is almost impossible to capture noise-free heart sound signals due to the presence of internal and external noises in most situations. Such noises and degradations in heart sound signals can potentially reduce the accuracy of data-driven classification models. Although different techniques have been proposed in the literature to address the noise issue, how and to what extent different noise …

Comparing Poor And Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy In Acute Ischemic Stroke, Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Mohlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Beendszus, Dietmar Frey

Articles

Outcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disability and mortality (mRS 5 and 6) might be of equal importance for clinical decision-making.

Understanding And Predicting Cognitive Improvement Of Young Adults In Ischemic Stroke Rehabilitation Therapy, Helard Becerra Martinez, Katryna Cisek, Alejandro Garcia-Rudolph, John Kelleher, Andrew Hines

Articles

Accurate early predictions of a patient's likely cognitive improvement as a result of a stroke rehabilitation programme can assist clinicians in assembling more effective therapeutic programs. In addition, sufficient levels of explainability, which can justify these predictions, are a crucial requirement, as reported by clinicians. This article presents a machine learning (ML) prediction model targeting cognitive improvement after therapy for stroke surviving patients. The prediction model relies on electronic health records from 201 ischemic stroke surviving patients containing demographic information, cognitive assessments at admission from 24 different standardized neuropsychology tests (e.g., TMT, WAIS-III, Stroop, RAVLT, etc.), and therapy information collected …

Towards Automated Weed Detection Through Two-Stage Semantic Segmentation Of Tobacco And Weed Pixels In Aerial Imagery, S. Imran Moazzam, Umar S. Khan, Waqar Qureshi, Tahir Nawaz, Faraz Kunwar

Articles

In precision farming, weed detection is required for precise weedicide application, and the detection of tobacco crops is necessary for pesticide application on tobacco leaves. Automated accurate detection of tobacco and weeds through aerial visual cues holds promise. Precise weed detection in crop field imagery can be treated as a semantic segmentation problem. Many image processing, classical machine learning, and deep learning-based approaches have been devised in the past, out of which deep learning-based techniques promise better accuracies for semantic segmentation, i.e., pixel-level classification. We present a new method that improves the precision of pixel-level inter-class classification of the crop …

A Big Data Smart Agricultural System: Recommending Optimum Fertilisers For Crops, Vuong Ngo, Thuy-Van T. Duong, Nguyen Nguyen, Cach N. Dang, Owen Conlan

Articles

Nutrients are important to promote plant growth and nutrient deficiency is the primary factor limiting crop production. However, excess fertilisers can also have a negative impact on crop quality and yield, cause an increase in pollution and decrease producer profit. Hence, determining the suitable quantities of fertiliser for every crop is very useful. Currently, the agricultural systems with internet of things make very large data volumes. Exploiting agricultural Big Data will help to extract valuable information. However, designing and implementing a large scale agricultural data warehouse are very challenging. The data warehouse is a key module to build a smart …

Towards Sweetness Classification Of Orange Cultivars Using Short‑Wave Nir Spectroscopy, Ayesha Zeb, Waqar Shahid Qureshi, Abdul Ghafoor, Amanullah Malik, Muhammad Imran, Alina Mirza, Mohsin Islam Tiwana, Eisa Alanazi

Articles

The global orange industry constantly faces new technical challenges to meet consumer demands for quality fruits. Instead of traditional subjective fruit quality assessment methods, the interest in the horticulture industry has increased in objective, quantitative, and non-destructive assessment methods. Oranges have a thick peel which makes their non-destructive quality assessment challenging. This paper evaluates the potential of short-wave NIR spectroscopy and direct sweetness classification approach for Pakistani cultivars of orange, i.e., Red-Blood, Mosambi, and Succari. The correlation between quality indices, i.e., Brix, titratable acidity (TA), Brix: TA and BrimA (Brix minus acids), sensory assessment of the fruit, and short-wave NIR …

Discovering Child Sexual Abuse Material Creators’ Behaviors And Preferences On The Dark Web, Vuong Ngo, Rahul Gajula, Christina Thorpe, Susan Mckeever

Articles

Background: Producing, distributing or discussing child sexual abuse materials (CSAM) is often committed through the dark web in order to remain hidden from search engines and regular users. Additionally, on the dark web, the CSAM creators employ various techniques to avoid detection and conceal their activities. The large volume of CSAM on the dark web presents a global social problem and poses a significant challenge for helplines, hotlines and law enforcement agencies.

Objective: Identifying CSAM discussions on the dark web and uncovering associated metadata insights into characteristics, behaviours and motivation of CSAM creators.

Participants and Setting: We have conducted an …

Toward Inclusive Online Environments: Counterfactual-Inspired Xai For Detecting And Interpreting Hateful And Offensive Tweets, Muhammad Deedahwar Mazhar Qureshi, Muhammad Atif Qureshi, Wael Rashwan

Articles

The prevalence of hate speech and offensive language on social media platforms such as Twitter has significant consequences, ranging from psychological harm to the polarization of societies. Consequently, social media companies have implemented content moderation measures to curb harmful or discriminatory language. However, a lack of consistency and transparency hinders their ability to achieve desired outcomes. This article evaluates various ML models, including an ensemble, Explainable Boosting Machine (EBM), and Linear Support Vector Classifier (SVC), on a public dataset of 24,792 tweets by T. Davidson, categorizing tweets into three classes: hate, offensive, and neither. The top-performing model achieves a weighted …

Biogeography Based Optimization With Salp Swarm Optimizer Inspired Operator For Solving Non-Linear Continuous Optimization Problems, Vanita Garg, Kusum Deep, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

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In this paper, a novel attempt is made to incorporate the two effective algorithm strategies, where BBO has a strong exploration and Salp Swarm Algorithm (SSA) is used for exploitation of the search space. The proposed algorithm is tested on IEEE CEC 2014 and statistical, convergence graphs are given. The proposed algorithm is also applied to 10 real life problems and compared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms.

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

Articles

In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

Learnings From A National Cyberattack Digital Disaster During The Sars-Cov-2 Pandemic In A Pediatric Emergency Medicine Department, Fiona Leonard, Hugh O'Reilly, Carol Blackburn, Laura Melody, Dani Hall, Eleanor Ryan, Kate Bruton, Pamela Doyle, Bridget Conway, Michael Barrett

Articles

Objective: The primary objective was to analyze the impact of the national cyberattack in May 2021 on patient flow and data quality in the Paediatric Emergency Department (ED), amid the SARS-CoV-2 (COVID-19) pandemic. Methods: A single site retrospective time series analysis was conducted of three 6-week periods: before, during, and after the cyberattack outage. Initial emergent workflows are described. Analysis includes diagnoses, demographic context, key performance indicators, and the gradual return of information technology capability on ED performance. Data quality was compared using 10 data quality dimensions. Results: Patient visits totaled 13 390. During the system outage, patient experience times …

New Fxlmat-Based Algorithms For Active Control Of Impulsive Noise, Alina Mirza, Farkhanda Afzal, Ayesha Zeb, Abdul Wakeel, Waqar Shahid Qureshi, Ali Akgul

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In the presence of non-Gaussian impulsive noise (IN) with a heavy tail, active noise control (ANC) algorithms often encounter stability problems. While adaptive filters based on the higher-order error power principle have shown improved filtering capability compared to the least mean square family algorithms for IN, however, the performance of the filtered-x least mean absolute third (FxLMAT) algorithm tends to degrade under high impulses. To address this issue, this paper proposes three modifications to enhance the performance of the FxLMAT algorithm for IN. To improve stability, the first alteration i.e. variable step size FxLMAT (VSSFxLMAT)algorithm is suggested that incorporates the …

Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand

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Rapid growth in the utilization of the inverter-interfaced distributed energy resources (IIDERs) in microgrids has brought new challenges in the network protection area. Microgrid protection specifically becomes a concern during operation in the islanded mode. There is a considerable reduction in fault current levels in this mode compared to when the microgrid is connected to the grid, which makes conventional algorithms operate with significant delay or, in many cases, not even pick up the fault. This paper proposes a protection algorithm based on the rate of change of direct-axis current component ( id ) to protect inverter-based microgrids (IBMGs). The …

A Comparison Of Feature Selection Methodologies And Learning Algorithms In The Development Of A Dna Methylation-Based Telomere Length Estimator, Trevor Doherty, Emma Dempster, Eilis Hannon, Jonathan Mill, Richie Poulton, David Corcoran, Karen Sugden, Ben Williams, Avshalom Caspi, Terrie E. Moffitt, Sarah Jane Delany, Therese Murphy Dr

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The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine–guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based …