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The Intellectual Origins of the Modern International Tax Regime: Edwin R. A. Seligman, Economic Allegiance, and the League of Nations’ 1923 Report
Full text linkIn March 1923, a group of prominent political economists and tax law experts gathered in Geneva, Switzerland to discuss the post–World War I framework for a new international tax regime. Commissioned by the League of Nations, these experts produced a comprehensive report that gradually became the intellectual foundation of the modern international tax regime. Relying on archival materials and other primary sources, this article contends that the US expert Edwin R. A. Seligman played a vital role in revising the report. While scholars have noted Seligman’s influence over US tax law and policy, his pivotal role in drafting the 1923 report has only recently been acknowledged. This article builds on this recent scholarship by investigating how Seligman’s background, experiences, and ideas—particularly his analysis and advocacy of the concept of “ability to pay” and “economic allegiance”—shaped the 1923 Report, and hence the subsequent development of the modern international tax regime
The QUIC-SP: A Spanish language tool assessing unpredictability in early life is linked to physical and mental health.
Full text linkAccumulating evidence indicates that unpredictable signals in early life represent a unique form of adverse childhood experiences (ACEs) associated with disrupted neurodevelopmental trajectories in children and adolescents. The Questionnaire of Unpredictability in Childhood (QUIC) was developed to assess early life unpredictability [1], encompassing social, emotional, and physical unpredictability in a childs environment, and has been validated in three independent cohorts. However, the importance of identifying ACEs in diverse populations, including non-English speaking groups, necessitates translation of the QUIC. The current study aims to translate and validate a Spanish language version of the QUIC (QUIC-SP) and assess its associations with mental and physical health. Spanish-speaking participants (N = 285) were recruited via the online market crowdsourcing platform, Amazon Mechanical Turk (MTurk), and completed an online survey that included the QUIC-SP and validated Spanish language assessments of physical and mental health. The QUIC-SP demonstrated excellent psychometric properties and similar mean scores, endorsement rates, and internal reliability to the English language version, thus establishing its validity among Spanish-speaking adults. Higher QUIC-SP scores, indicating greater unpredictability in early life, predicted increased symptoms of anxiety, anhedonia, depression, and poorer physical health. Given significant racial and ethnic disparities in health, the QUIC-SP may serve as a valuable tool to address the public health consequences of ACEs among Spanish-speaking populations
What we can learn about Mars from the magnetism of returned samples.
Full text linkThe Red Planet is a magnetic planet. The Martian crust contains strong magnetization from a core dynamo that likely was active during the Noachian period when the surface may have been habitable. The evolution of the dynamo may have played a central role in the evolution of the early atmosphere and the planets transition to the current cold and dry state. However, the nature and history of the dynamo and crustal magnetization are poorly understood given the lack of well-preserved, oriented, ancient samples with geologic context available for laboratory study. Here, we describe how magnetic measurements of returned samples could transform our understanding of six key unknowns about Mars planetary evolution and habitability. Such measurements could i) determine the history of the Martian dynamo fields intensity; ii) determine the history of the Martian dynamo fields direction; iii) test the hypothesis that Mars experienced plate tectonics or true polar wander; iv) constrain the thermal and aqueous alteration history of the samples; v) identify sources of Martian crustal magnetization and vi) characterize sedimentary and magmatic processes on Mars. We discuss how these goals can be achieved using future laboratory analyses of samples acquired by the Perseverance rover
Comparison of a Novel Ultra-Widefield Three-Color Scanning Laser Ophthalmoscope to Other Retinal Imaging Modalities in Chorioretinal Lesion Imaging
Full text linkPurpose: To compare the assessment of clinically relevant retinal and choroidal lesions as well as optic nerve pathologies using a novel three-wavelength ultra-widefield (UWF) scanning laser ophthalmoscope with established retinal imaging techniques for ophthalmoscopic imaging.
Methods: Eighty eyes with a variety of retinal and choroidal lesions were assessed on the same time point using Topcon color fundus photography (CFP) montage, Optos red/green (RG), Heidelberg SPECTRALIS MultiColor 55-color montage (MCI), and novel Optos red/green/blue (RGB). Paired images of the optic nerve, retinal, or choroidal lesions were initially diagnosed based on CFP imaging. The accuracy of the imaging was then evaluated in comparison to CFP using a grading scale ranging from -1 (losing imaging information) to +1 (gaining imaging information).
Results: Eighty eyes of 43 patients with 116 retinal or choroidal pathologies, as well as 59 eyes with optic nerve imaging using CFP, MCI, RG, and RGB, were included in this study. Across all subgroups, RGB provided significantly more accurate clinical imaging with CFP as ground truth and compared to other modalities. This was true comparing RGB to both RG (P = 0.0225) and MCI (P < 0.001) overall. Although RGB provided more accurate clinical information overall, it was inferior to RG for melanocytic choroidal lesions (P = 0.011).
Conclusions: RGB can be considered as a useful tool to detect characteristics of central, midperipheral, and peripheral retinal lesions. Regarding melanocytic choroidal lesions, RGB was inferior to RG, and MCI was inferior to both RG and RGB modalities due to color changes.
Translational Relevance: Traditional retinal ultra-widefield imaging uses two wavelengths. Here, we evaluated three wavelengths for ultra-widefield imaging. We examined new optics (basic science) effect on patient imaging (clinical care)
Systematic ocular phenotyping of 8,707 knockout mouse lines identifies genes associated with abnormal corneal phenotypes
Full text linkPurposeCorneal dysmorphologies (CDs) are typically classified as either regressive degenerative corneal dystrophies (CDtrs) or defective growth and differentiation-driven corneal dysplasias (CDyps). Both eye disorders have multifactorial etiologies. While previous work has elucidated many aspects of CDs, such as presenting symptoms, epidemiology, and pathophysiology, the genetic mechanisms remain incompletely understood. The purpose of this study was to analyze phenotype data from 8,707 knockout mouse lines to identify new genes associated with the development of CDs in humans.Methods8,707 knockout mouse lines phenotyped by the International Mouse Phenotyping Consortium were queried for genes associated with statistically significant (P < 0.0001) abnormal cornea morphology to identify candidate CD genes. Corneal abnormalities were investigated by histopathology. A literature search was used to determine the proportion of candidate genes previously associated with CDs in mice and humans. Phenotypes of human orthologues of mouse candidate genes were compared with known human CD genes to identify protein-protein interactions and molecular pathways using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Protein Analysis Through Evolutionary Relationships (PANTHER), and Kyoto Encyclopedia of Genes and Genomes.ResultsAnalysis of data from 8,707 knockout mouse lines identified 213 candidate CD genes. Of these, 37 (17%) genes were previously known to be associated with CD, including 14 in the mouse, 16 in humans, and 7 in both. The remaining 176 (83%) genes have not been previously implicated in CD. We also searched publicly available RNAseq data and found that 131 of the total 213 (61.5%) were expressed in adult human corneal tissue. STRING analysis showed several interactions within and between candidate and established CD proteins. All cellular pathways of the established genes were found in the PANTHER analysis of the candidate genes. Several of the candidate genes were implicated in corneal disease, such as TGF-ß signaling. We also identified other possible underappreciated mechanisms relevant to the human cornea.ConclusionsWe identified 213 mouse genes that resulted in statistically significant abnormal corneal phenotypes in knockout mice, many of which have not previously been implicated in corneal pathology. Bioinformatic analyses implicated candidate genes in several signaling pathways which are potential therapeutic targets
How does negative triangularity mitigate ITG turbulence and transport?
No full textAbstract:
Improved confinement in negative triangularity (NT) experiments is attributed to reduced fluxes driven by micro-turbulence. The physical mechanism of why thermal confinement improves in NT relative to PT is unknown. This study employs gyrokinetic flux tube simulations using the GENE code with local Miller equilibrium to elucidate the physical mechanisms behind the beneficial effects of NT flux surface shapes. The focus is on collisionless ion temperature gradient (ITG) driven turbulence with adiabatic electrons. The kinetic profiles are held fixed across a scan of triangularity values, thus enabling comparisons on a level playing field. The reduced linear growth rates for NT is shown to be due to a reduced eigenmode averaged magnetic drift frequency and a wider, stronger negative local magnetic shear region about the outboard mid-plane. The nonlinear heat flux is lower for NT than that for PT, due to reduced radial correlation length and increased correlation time (
τ
c
) of fluctuations. These, in turn, are due to a comparatively higher level of self-generated zero-frequency E × B zonal shearing rate ω
E
in NT as compared to PT. Though the linear zonal potential residual is lower for NT, the nonlinearly generated E × B zonal shearing rate is higher for NT than for PT. This outcome is linked to the distinctive features of the radial wavenumber spectra of the zonal potential and the zonal shearing rate. The dimensionless parameter
ω
E
τ
c
is suggested as a figure of merit. This is higher for NT than for PT. Thus, the reduced heat diffusivity for NT is linked to increased
ω
E
τ
c
. Self-generated temperature corrugations (i.e. zonal temperature gradients) are much weaker than the background mean temperature gradient. Nevertheless, temperature corrugations are more pronounced in NT than in PT
Weathering the Pain: Ambient Temperatures Role in Chronic Pain Syndromes.
Full text linkPURPOSE OF REVIEW: Chronic pain is highly prevalent and involves a complex interaction of sensory, emotional, and cognitive processes, significantly influenced by ambient temperature. Despite advances in pain management, many patients continue to experience inadequate pain relief. This review aims to consolidate and critically evaluate the current evidence on the impact of ambient temperature on chronic pain conditions such as fibromyalgia (FM), multiple sclerosis (MS), complex regional pain syndrome (CRPS), and osteoarthritis (OA). RECENT FINDINGS: Patients with FM often report pain exacerbations due to temperature changes, with studies showing lower thresholds for heat and cold-induced pain compared to healthy controls. In MS, the Uhthoff phenomenon, characterized by temperature-induced neurological deterioration, underscores the significance of ambient temperature in pain management. CRPS patients exhibit heightened pain sensitivity to temperature changes, with both warm and cold stimuli potentially aggravating symptoms. OA patients frequently report increased pain and rigidity associated with lower temperatures and higher humidity. Understanding the mechanisms through which temperature influences pain can enhance pain management strategies. This review highlights the need for further research to elucidate these mechanisms and develop targeted interventions, ultimately improving the quality of life for individuals with chronic pain conditions
Task relevant autoencoding enhances machine learning for human neuroscience.
Full text linkIn human neuroscience, machine learning can help reveal lower-dimensional neural representations relevant to subjects behavior. However, state-of-the-art models typically require large datasets to train, and so are prone to overfitting on human neuroimaging data that often possess few samples but many input dimensions. Here, we capitalized on the fact that the features we seek in human neuroscience are precisely those relevant to subjects behavior rather than noise or other irrelevant factors. We thus developed a Task-Relevant Autoencoder via Classifier Enhancement (TRACE) designed to identify behaviorally-relevant target neural patterns. We benchmarked TRACE against a standard autoencoder and other models for two severely truncated machine learning datasets (to match the data typically available in functional magnetic resonance imaging [fMRI] data for an individual subject), then evaluated all models on fMRI data from 59 subjects who observed animals and objects. TRACE outperformed alternative models nearly unilaterally, showing up to 12% increased classification accuracy and up to 56% improvement in discovering cleaner, task-relevant representations. These results showcase TRACEs potential for a wide variety of data related to human behavior
BetaAlign: a deep learning approach for multiple sequence alignment.
Full text linkMOTIVATION: Multiple sequence alignments are extensively used in biology, from phylogenetic reconstruction to structure and function prediction. Here, we suggest an out-of-the-box approach for the inference of multiple sequence alignments, which relies on algorithms developed for processing natural languages. We show that our AI-based methodology can be trained to align sequences by processing alignments that are generated via simulations, and thus different aligners can be easily generated for datasets with specific evolutionary dynamics attributes. We expect that natural-language processing solutions will replace or augment classic solutions for computing alignments, and more generally, challenging inference tasks in phylogenomics. RESULTS: The multiple sequence alignment (MSA) problem is a fundamental pillar in bioinformatics, comparative genomics, and phylogenetics. Here we characterize and improve BetaAlign, the first deep learning aligner, which substantially deviates from conventional algorithms of alignment computation. BetaAlign draws on natural language processing (NLP) techniques and trains transformers to map a set of unaligned biological sequences to an MSA. We show that our approach is highly accurate, comparable and sometimes better than state-of-the-art alignment tools. We characterize the performance of BetaAlign and the effect of various aspects on accuracy; for example, the size of the training data, the effect of different transformer architectures, and the effect of learning on a subspace of indel-model parameters (subspace learning). We also introduce a new technique that leads to improved performance compared to our previous approach. Our findings further uncover the potential of NLP-based methods for sequence alignment, highlighting that AI-based algorithms can substantially challenge classic approaches in phylogenomics and bioinformatics. AVAILABILITY: Datasets used in this work are available on HuggingFace (Wolf et al., 2020) at: https://huggingface.co/dotan1111. Source code is available at: https://github.com/idotan286/SimulateAlignments. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online