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Ascending Arousal Network Connectivity in Disorders of Consciousness: A Diffusion MRI Study
No full textThe human brain gives rise to a great variety of conscious experiences. Patients with disorders of consciousness, a state characterized by the dissociation of awareness and wakefulness, are particularly noteworthy. This study attempts to find key biomarkers of the disorder of consciousness state and discover key regions of the brain that govern consciousness. The focus is on the ascending arousal network—a network of nodes and edges representing connections from the brainstem to subcortical (thalamus, hypothalamus, basal forebrain) nuclei and reaching the cerebral cortex. Previous studies using animal models have demonstrated a high prognostic value of the ascending arousal network in relation to consciousness. This study conducts a diffusion tensor imaging analysis and generates a tract count plot to illustrate differences in connectivity between (N=6) healthy controls and (N=6) patients with chronic disorders of consciousness. Each region of interest was isolated to investigate its specific role and impact on consciousness. A principal component analysis was performed to assess the separability of the two cohorts. The results found each of the regions of interest to be significantly (p<0.05) disrupted in patients with disorders of consciousness. They contributed equally to the linear separability of the two cohorts. This is consistent with previous research and hints at the importance of the ascending arousal network in governing consciousness. These changes are likely associated with the many pathological deteriorations associated with an impaired cognitive state, such as neuronal loss, gliosis, and the degeneration of white matter tracts that connect critical areas of the brain involved in consciousness
A User-Centered Account of Urban Energy Transitions in Kampala, Uganda
No full textThe rapid and complex effects of urbanization are shifting energy production and consumption patterns on the African continent. Energy poverty is manifesting to an increasing degree and in diverse forms in low-income, vulnerable urban populations like informal settlements and/or “slums.” This photo essay shows the lived realities of the urban energy transitions unfolding across Kampala, Uganda’s many informal communities. Though residents are almost universally connected to the grid, 97% of households and businesses rely on expensive and polluting charcoal. Electricity access is precarious and residents develop personalized fuel-stacking strategies to balance the competing demands of affordability, health, convenience, etcetera. Redundancy, hybridity, and improvisation are key features of the strategies that low-income communities use to meet their daily energy needs in the face of an unreliable, unaffordable, or inaccessible grid. This essay contributes to a growing body of research that aims to center users within discussions of urban energy transitions and sustainable development broadly
Toward a Future-Facing Climate Policy
No full textThis Article provides a systems analysis of climate change policy that links together subsystems relating to innovation, energy economics, interest group politics, and government regulation. It is easy but misleading to equate climate policy with emissions regulation. That is too narrow a frame. We urgently need a new energy system because of climate change, but regulating carbon emissions is only one part of a bigger project. We cannot assume that as carbon emissions decline a new energy system will build itself—nor will society be willing to eliminate fossil fuels without confidence in their replacements.
An effective climate policy requires much more than simply restricting fossil fuels and hoping the market will fill the gap. The energy transition requires incentives for energy research, development, and scaling up new energy technologies. For the energy transition to happen, we also need sufficiently large-scale deployment to trigger economies of scale and learning by doing. There is much to be gained, then, from shifting the paradigm from emissions reduction to the energy transition. To make a homely analogy: The reason for a kitchen renovation may be dry rot, and the first step is ripping out rotten wood. But the point of the remodeling is putting in a new kitchen, not just getting rid of the rot
Certifying Legal AI Assistants for Unrepresented Litigants: A Global Survey of Access to Civil Justice, Unauthorized Practice of Law, and AI
No full textThe global integration of artificial intelligence (AI) into legal services has created a critical need for clarity regarding unauthorized practice of law (UPL) rules. Traditionally, UPL rules prohibited unlicensed individuals from engaging in activities legally reserved for qualified attorneys, including, in some jurisdictions, offering legal advice, interpreting laws, representing clients in court, or drafting legal documents. Now that some AI systems can perform functions that practice of law regulating authorities have traditionally reserved for licensed attorneys, a framework is needed to certify the use of legal AI assistants by unrepresented litigants.
Ensuring the accuracy of information provided by legal AI assistants for unrepresented litigants benefits the entire legal community, including attorneys, by promoting stricter standards and higher acceptance thresholds. We examine the perspectives of several primary stakeholders in certifying legal AI assistants, including unrepresented litigants, practice of law regulating authorities, judiciaries, the legislature, the legal aid community, and the legal tech community.
We conduct a detailed survey of access to justice, AI, and UPL in various international jurisdictions, including Argentina, Australia, Brazil, Canada, China, the European Union, Germany, India, New Zealand, Nigeria, Singapore, the United Kingdom, and the United States. In each of these jurisdictions, we explore how UPL is currently managed in the context of legal AI use by unrepresented litigants. We also include a 50-state and 6-territory survey for the United States on what each Bar Association and Judiciary is doing to regulate legal AI use by unrepresented litigants.
In light of this survey, we propose that practice of law regulating authorities add certified legal AI assistants to their lists of UPL exemptions so that such assistants can provide specific and useful legal information, guidance, and advice to unrepresented litigants. We propose a capability-based framework for certifying legal AI assistants for unrepresented litigants. This is intended as a harmonized global proposal, designed for local implementation by each jurisdiction’s practice of law regulating authority, with the flexibility to address individual jurisdictional nuances.
Unrepresented litigants are already using AI chatbots for help in legal proceedings, sometimes to their detriment. Our proposal aims to allow unrepresented litigants to use legal AI assistants that have been verified for accuracy. This framework addresses the key justification for UPL restrictions—the risk of incorrect legal guidance—by basing the certification of individual capabilities on their accuracy when tested on public benchmark datasets. Legal AI assistants are added to lists of UPL exemptions under this approach if their accuracy meets or exceeds a certification threshold when tested on these public benchmark datasets. The jurisdiction’s practice of law regulating authority would set the certification threshold or, as we suggest, a third-party certifying authority delegated to perform this task. While many public benchmark datasets are required under this framework, the legal AI community is rapidly developing such datasets.
To enable AI to enhance access to justice for unrepresented litigants globally, practice of law regulating authorities in each jurisdiction must choose to exempt certified legal AI systems for unrepresented litigants from unauthorized practice of law regulations
Dynamic Chirality in Perylene Diimide Nanoribbons
No full textHelicenes, a class of polycyclic aromatic hydrocarbons (PAHs), are characterized by their twisted skeletons formed through ortho-annulated aromatic rings, leading to axial chirality and remarkable chiroptical properties. These features make helicenes promising candidates for advanced applications, including chiroptical nonlinear optics, asymmetric catalysis, and chiral switches. Perylene diimide (PDI), an electron-deficient PAH, is known for its exceptional optoelectronic properties and stability. Incorporating PDI units into helicene structures has emerged as an effective strategy for developing non-planar electron acceptors and molecules with enhanced chiroptical properties, making PDI-helicenes valuable for organic electronics and related fields.This thesis investigates the synthesis and chiroptical properties of PDI-[4]helicenes, presenting a method for controlling the dynamic axial chirality in PDI-based twistacenes. Chiral substituents at the imide position induce helicity within the structure, enabling the remote modulation of flexible [4] helicene subunits.
Additionally, a chiral molecular redox switch, chPDI[2], derived from PDI-based twistacenes, is introduced. This material demonstrates reversible multistate chiroptical switching across a broad wavelength range, including ultraviolet, visible, and near-infrared regions. Upon reduction, chPDI[2] shows a significant enhancement in its circular dichroic response, making it a promising candidate for chiroptical switching applications.
Finally, we explore chiral graphene nanoribbons (chGNRs) with acene-based cores, demonstrating helicity control in extended conjugated systems. The longest chGNR[40] exhibits one of the highest recorded chiroptical responses for organic molecules in the visible spectrum, offering new opportunities for chiral optoelectronics and molecular devices
Search for a light charged Higgs boson in → ± decays, with ± → , in collisions at √ = 13 TeV with the ATLAS detector
No full textAbstract
A search for a light charged Higgs boson produced in decays of the top quark, → ± with ± → , is presented. This search targets the production of top-quark pairs ̄ → ±, with → ( = ,), resulting in a lepton-plus-jets final state characterised by an isolated electron or muon and at least four jets. The search exploits b-quark and c-quark identification techniques as well as multivariate methods to suppress the dominant ̄ background.
The data analysed correspond to 140 fb⁻¹ of collisions at √ = 13 TeV recorded with the ATLAS detector at the LHC between 2015 and 2018. Observed (expected) 95% confidence-level upper limits on the branching fraction ( → ±) , assuming ( → ) + ( → ± ( → )) = 1.0 , are set between 0.066% (0.077%) and 3.6% (2.3%) for a charged Higgs boson with a mass between 60 and 168 GeV
Cross-Sector Collaboration: The New York Green Bank (NYGB), The New York City Panel on Climate Change
Get PDFThis case study examines the role of cross-sector collaboration in enhancing climate resilience in New York City, focusing on partnerships between the New York Green Bank (NYGB), the New York City Panel on Climate Change (NPCC), and venture capital firms. These collaborations help overcome market barriers and drive clean energy investments, as seen in projects like the Hudson contract and distributed energy resources. The study highlights the importance of financial solutions in urban sustainability and advocates for the city to engage with venture capital firms to attract investment, driving the clean energy transition and building a more resilient future for NYC
Symmetries of vanishing nonlinear Love numbers of Schwarzschild black holes
Get PDFThe tidal Love numbers parametrize the conservative induced tidal response of self-gravitating objects. It is well established that asymptotically-flat black holes in four-dimensional general relativity have vanishing Love numbers. In linear perturbation theory, this result was shown to be a consequence of ladder symmetries acting on black hole perturbations.
In this work, we show that a black hole’s tidal response induced by a static, parity-even tidal field vanishes for all multipoles to all orders in perturbation theory. Our strategy is to focus on static and axisymmetric spacetimes for which the dimensional reduction to the fully nonlinear Weyl solution is well-known. We define the nonlinear Love numbers using the point-particle effective field theory, matching with the Weyl solution to show that an infinite subset of the static, parity-even Love number couplings vanish, to all orders in perturbation theory. This conclusion holds even if the tidal field deviates from axisymmetry.
Lastly, we discuss the symmetries underlying the vanishing of the nonlinear Love numbers. An (2, ℝ) algebra acting on a covariantly-defined potential furnishes ladder symmetries analogous to those in linear theory. This is because the dynamics of the potential are isomorphic to those of a static, massless scalar on a Schwarzschild background. We comment on the connection between the ladder symmetries and the Geroch group that is well-known to arise from dimensional reduction
Platform Operations: From Models to Methods
No full textOnline platforms – from on-demand home-services and e-commerce fulfillment networks to content streamers – thrive on their ability to match demand with supply. Doing so well requires algorithms that cope with uncertainty, high-dimensional type spaces, mis-aligned and multiple objectives, and informational frictions. This dissertation develops models and methods that illuminate these challenges and propose simple, and often near-optimal solutions. The dissertation is organized into five self-contained but thematically linked chapters – the first three chapters are related to problems in online matching, dynamic resource allocation and multi-objective optimization in order fulfillment problems, while, the last two chapters deal with design and optimization of recommendation systems.
First, we tackle algorithm design questions that arise in online matching and dynamic resource allocation problems. How should a centralized matching platform dynamically match heterogeneous service providers with heterogeneous customers? What are the fundamental drivers of algorithmic performance in these dynamic resource allocation platforms? Is there a unifying algorithmic principle which can solve large class of dynamic resource allocation problems? How to make resource allocation decisions with multiple and often competing objectives?
In Chapter 1, we study dynamic two-sided matching with heterogeneous demand and supply modeled as highly dimensional weight and feature vectors respectively. We show that simple myopic policies such as Greedy which are practically prevalent can impact be highly sub-optimal. We develop a forward-looking supply aware policy dubbed Simulate-Optimize-Assign-Repeat (SOAR). We prove that SOAR achieves the optimal regret scaling under different assumptions on the demand and supply distributions. In Chapter 2, we broaden the scope to general online resource allocation problems. We identify a novel driver of algorithmic performance – the spatial distribution of demand types. We develop a unifying algorithm dubbed Repeatedly Act using Multiple Simulations (RAMS) which is a generalization of SOAR studied in Chapter 1. In Chapter 3, we turn to multi-objective optimization in the context of order fulfillment problems. We develop a principled framework for weight generation to enable the weighted objective approach.
Next, we take the viewpoint of a system designer and tackle platform design questions in the context of recommendation systems. By optimizing for measurable proxies, are recommendation systems at risk of significantly under-delivering on utility? If so, how can one improve utility which is seldom measured? Different information provisioning tools exists, such as public rankings and personalized recommendations, but when do these tools work and when do they not? What is the role of the market setting in the driving the efficacy of these different information provisioning tools?
In Chapter 4, we study a stylized model of repeated user consumption. We demonstrate that optimizing for measurable proxies like engagement can lead to significant utility losses. Instead, we propose a utility-aware policy that initially recommends diverse set of options. As the platform becomes more forward-looking, our utility-aware policy achieves the best of both worlds: near-optimal utility and near-optimal engagement simultaneously. Our study elucidates an important feature of recommendation systems; given the ability to suggest multiple items, one can perform significant exploration without incurring significant reductions in engagement. By recommending high-risk, high-reward items alongside popular items, systems can enhance discovery of high utility items without significantly affecting engagement.
In Chapter 5, we ask when personalized recommendations are worth their added complexity relative to public rankings. In unconstrained supply settings, both public rankings and personalized recommendations improve welfare, with their relative value determined by the degree of preference heterogeneity. In contrast, in supply-constrained settings, revealing just the common term of the utility, as done by public rankings, provides limited benefit since the total common value available is limited by capacity constraints, whereas personalized recommendations, by revealing both common and idiosyncratic terms, significantly enhance welfare by enabling agents to match with items they idiosyncratically value highly
Phylogeography, diversification, and conservation of temperate mountain flora
No full textOver the past two decades, multiple hypotheses and datasets have emerged to describe the impacts of mountain uplift, Quaternary glacial cycles, and climatic transitions on plant diversification in mountain systems across the world. While many studies have documented these large-scale dynamics for species in mountains generally, few have used population genomics to identify specific geographic barriers and quantify their impacts on population divergence and gene flow. My research uses phylogeographic and population genomic approaches to describe how these evolutionary processes and landscape features have influenced each other to drive diversification across two temperate mountain regions - the Hengduan Mountains of China and the North American Cordillera.
Chapter 1 focuses on the phylogeographic histories of twelve widespread Pedicularis species in the Hengduan Mountains Region (HMR). It is common to find many species of Pedicularis flowering in sympatry in this region, and an outstanding question is whether such species have experienced parallel phylogeographic histories as their populations have diverged across the HMR. This chapter outlines the phylogenetic and population genetic approaches I used to determine the population structure and migration potential for each species, highlighting areas of the landscape that appear to function as barriers to gene flow.
In Chapter 2, I characterize population structure and historical patterns of gene flow within the Pedicularis cranolopha species complex. Additionally, I use a dataset of historical-contemporary samples to develop a novel temporal genomics framework that allows us to test whether gene flow has increased in recent time due to human impacts across the HMR landscape. Since the Pedicularis cranolopha genome was recently assembled, I was able to use whole-genome sequencing (WGS) to assemble a more robust dataset for investigating genomic changes over time.
Chapter 3 begins to clarify the phylogenetic relationships of Delphinium sect. Diedropetala across the North American Cordillera. This clade includes 60 species which have rapidly diversified across mountain regions of western North America in the last 3-5 million years. In collaboration with researchers from the USDA Agricultural Research Service, I used RADseq data from 34 species to infer the first phylogeny of Delphinium species endemic to North America based on genome-wide data