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Social Capital, Institutional Rules, and Constitutional Amendment Rates
No full textWhy are some constitutions amended more frequently than others? The literature provides few clear answers, as some scholars focus on institutional factors, whereas others emphasize amendment culture. We bridge this divide with new theoretical and empirical insights. Using data from democratic constitutions worldwide and U.S. state constitutions, we examine how social capital reduces the transaction costs imposed by amendment rules. The results indicate that constitutional rigidity decreases amendment frequency, but group membership, civic activism, and political trust can offset the effect of amendment rules. Our findings have important implications for scholars in public law, constitutional and democratic theory, and social movements
Unveiling 4500 years of environmental dynamics and human activity at Songo Mnara, Tanzania
No full textCoastal East Africa has undergone massive transformations through the Late Holocene, with a combination of changes in sea level, increasing human settlement, and ensuing use of coastal resources. A comprehensive multi-proxy analysis, including pollen, phytolith, charcoal, stratigraphy, particle size, and geochemical data from sedimentary cores extracted from mangrove ecosystems combined with soils from archaeological contexts, provided valuable insights into vegetation dynamics, environmental changes, and human interactions within the mangrove ecosystem of Songo Mnara Island, Tanzania over the last 2590 BCE (4540 cal yr BP). The bottommost layers indicate a lack of vegetation, as deduced from the presence of coral rags and high calcium and carbonate content, possibly due to high mid-Holocene sea-level. Evidence of mangrove taxa suggests a decrease in sea level, enabling the establishment of mangroves from around 2590 BCE. A brief period of sea-level rise occurred between 90 BCE and 320 CE before sea-level fell until 1570 CE. Significant evidence of human activity is recorded from around 1400 CE indicated by increased charcoal, crop phytoliths, and evidence of marine resource utilisation. The timing of this human-environment interaction is also linked to the time of lower sea level. However, there was evidence suggesting human abandonment of the island from around 1500 CE. This coincided with a subsequent rise in sea levels and potentially prolonged drought conditions spanning from 1570 to 1700 CE. These factors likely contributed to a shortage of food resources in the area, impacting both agricultural practices due to the scarcity of natural freshwater and the accessibility of marine food resources. From 1700 CE to the present, fluctuations in sea level have been observed, with a signal of recent sea-level rise in tandem with shifts in mangrove, terrestrial herbaceous taxa and fire activity. The low sedimentation rates within mangrove areas suggest that the mangroves on Songo Mnara Island may not keep pace with the current rate of sea-level rise
Oxidized Activated Charcoal Nanozymes: Synthesis, and Optimization for In Vitro and In Vivo Bioactivity for Traumatic Brain Injury
No full textCarbon-based superoxide dismutase (SOD) mimetic nanozymes have recently been employed as promising antioxidant nanotherapeutics due to their distinct properties. The structural features responsible for the efficacy of these nanomaterials as antioxidants are, however, poorly understood. Here, the process–structure–property–performance properties of coconut-derived oxidized activated charcoal (cOAC) nano-SOD mimetics are studied by analyzing how modifications to the nanomaterial's synthesis impact the size, as well as the elemental and electrochemical properties of the particles. These properties are then correlated to the in vitro antioxidant bioactivity of poly(ethylene glycol)-functionalized cOACs (PEG-cOAC). Chemical oxidative treatment methods that afford smaller, more homogeneous cOAC nanoparticles with higher levels of quinone functionalization show enhanced protection against oxidative damage in bEnd.3 murine endothelioma cells. In an in vivo rat model of mild traumatic brain injury (mTBI) and oxidative vascular injury, PEG-cOACs restore cerebral perfusion rapidly to the same extent as the former nanotube-derived PEG-hydrophilic carbon clusters (PEG-HCCs) with a single intravenous injection. These findings provide a deeper understanding of how carbon nanozyme syntheses can be tailored for improved antioxidant bioactivity, and set the stage for translation of medical applications
CrysFormer: Protein structure determination via Patterson maps, deep learning, and partial structure attention
No full textDetermining the atomic-level structure of a protein has been a decades-long challenge. However, recent advances in transformers and related neural network architectures have enabled researchers to significantly improve solutions to this problem. These methods use large datasets of sequence information and corresponding known protein template structures, if available. Yet, such methods only focus on sequence information. Other available prior knowledge could also be utilized, such as constructs derived from x-ray crystallography experiments and the known structures of the most common conformations of amino acid residues, which we refer to as partial structures. To the best of our knowledge, we propose the first transformer-based model that directly utilizes experimental protein crystallographic data and partial structure information to calculate electron density maps of proteins. In particular, we use Patterson maps, which can be directly obtained from x-ray crystallography experimental data, thus bypassing the well-known crystallographic phase problem. We demonstrate that our method, CrysFormer, achieves precise predictions on two synthetic datasets of peptide fragments in crystalline forms, one with two residues per unit cell and the other with fifteen. These predictions can then be used to generate accurate atomic models using established crystallographic refinement programs
Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review
No full textBackground/purpose The use of artificial intelligence (AI) in radiotherapy (RT) is expanding rapidly. However, there exists a notable lack of clinician trust in AI models, underscoring the need for effective uncertainty quantification (UQ) methods. The purpose of this study was to scope existing literature related to UQ in RT, identify areas of improvement, and determine future directions. Methods We followed the PRISMA-ScR scoping review reporting guidelines. We utilized the population (human cancer patients), concept (utilization of AI UQ), context (radiotherapy applications) framework to structure our search and screening process. We conducted a systematic search spanning seven databases, supplemented by manual curation, up to January 2024. Our search yielded a total of 8980 articles for initial review. Manuscript screening and data extraction was performed in Covidence. Data extraction categories included general study characteristics, RT characteristics, AI characteristics, and UQ characteristics. Results We identified 56 articles published from 2015 to 2024. 10 domains of RT applications were represented; most studies evaluated auto-contouring (50 %), followed by image-synthesis (13 %), and multiple applications simultaneously (11 %). 12 disease sites were represented, with head and neck cancer being the most common disease site independent of application space (32 %). Imaging data was used in 91 % of studies, while only 13 % incorporated RT dose information. Most studies focused on failure detection as the main application of UQ (60 %), with Monte Carlo dropout being the most commonly implemented UQ method (32 %) followed by ensembling (16 %). 55 % of studies did not share code or datasets. Conclusion Our review revealed a lack of diversity in UQ for RT applications beyond auto-contouring. Moreover, we identified a clear need to study additional UQ methods, such as conformal prediction. Our results may incentivize the development of guidelines for reporting and implementation of UQ in RT
Exploring Key Reaction and Reactor Parameters of Floating Catalyst Chemical Vapor Deposition (FCCVD) towards High Productivity and Quality of Synthesized CNTs
No full textEMBARGO NOTE: This item is embargoed until 2030-08-01Since the early 1990s, carbon nanotubes (CNTs) have been regarded as promising nanomaterials for diverse applications owing to their outstanding optical, thermal, mechanical, and electrical characteristics. Floating catalyst chemical vapor deposition (FCCVD) stands out as a prevalent technique for CNT synthesis, offering significant potential for achieving high yields and purity of CNTs at minimal production expenses. Despite more than three decades of investigation, there is a shortage of precise data regarding the key factors influencing reaction performance. The complex nature of the processes involved has substantially hampered efforts to scale up CNT production, mainly due to our limited understanding of CNT reaction mechanisms.
Recently, Seung Min Kim’s group at KIST1 reported a remarkable CNT synthesis breakthrough, where they applied a deep injection method to send reactants quickly to the hot zone of the reactor via a narrow-diameter cannula. Taking cues from this methodology, a central focus of my dissertation has been to develop a foundational understanding of the FCCVD reaction performance influenced by critical reaction and reactor parameters. In the experiments performed, methane serves as the primary carbon source, facilitating the production of both CNTs and clean energy hydrogen through CO2 emission-free methane splitting. Moreover, the high-quality CNTs produced demonstrate significant potential to substitute energy-intensive incumbent materials, thereby further reducing CO2 emissions.
By exploring key parameters categorized into carrier gas, carbon feedstock, catalyst and injector engineering, we found that carrier gas type could influence reaction performance both physically (fluid dynamics varied by gas properties) and chemically (applied to a non-inert carrier, H2). Introducing a trace amount of C2H4 has the potential to augment CNT productivity, a result that could also be attained by optimizing catalyst nanoparticle formation independently. Beyond investigating reaction components, injector engineering is another strategy to boost reaction productivity. Finally, my research investigates potential synergistic effects by combining insights obtained from the examination of individual parameters. Grounded in detail-orientated and quantitative analyses, this dissertation aims to clarify crucial growth mechanisms and suggest optimal practices and innovative reaction designs to advance the development of the FCCVD process for CNT synthesis.
Reference:
(1) Lee, S.-H.; Park, J.; Park, J. H.; Lee, D.-M.; Lee, A.; Moon, S. Y.; Lee, S. Y.; Jeong, H. S.; Kim, S. M. Deep-Injection Floating-Catalyst Chemical Vapor Deposition to Continuously Synthesize Carbon Nanotubes with High Aspect Ratio and High Crystallinity. Carbon 2021, 173, 901–909. https://doi.org/10.1016/j.carbon.2020.11.065
Reversible non-volatile electronic switching in a near-room-temperature van der Waals ferromagnet
Get PDFNon-volatile phase-change memory devices utilize local heating to toggle between crystalline and amorphous states with distinct electrical properties. Expanding on this kind of switching to two topologically distinct phases requires controlled non-volatile switching between two crystalline phases with distinct symmetries. Here, we report the observation of reversible and non-volatile switching between two stable and closely related crystal structures, with remarkably distinct electronic structures, in the near-room-temperature van der Waals ferromagnet Fe5−δGeTe2. We show that the switching is enabled by the ordering and disordering of Fe site vacancies that results in distinct crystalline symmetries of the two phases, which can be controlled by a thermal annealing and quenching method. The two phases are distinguished by the presence of topological nodal lines due to the preserved global inversion symmetry in the site-disordered phase, flat bands resulting from quantum destructive interference on a bipartite lattice, and broken inversion symmetry in the site-ordered phase
Metasurface-in-the-Middle Attacks: Wavefront Manipulation Threats and Countermeasures
No full textTranscending the capabilities of traditional devices, metasurfaces offer nearly limitless control of the EM properties of wireless signals and have recently been shown to facilitate wireless communication with unique designs. However, in this thesis, I explore the security threats posed by malicious metasurfaces and demonstrate that, along with new opportunities, they bring forth unprecedented security challenges. In particular, I expose a new class of “MetaSurface-in-the-Middle” attacks, wherein malicious agent, Eve, can intercept pencil-beam directional links - conventionally believed to be immune from eavesdropping - with an almost imperceptible trace. By exploring the foundation of the attack in WLAN scenarios, I demonstrate that such malicious metasurfaces could be fabricated in under 5 minutes and at the cost of several cents. Furthermore, I study the attack with wireless backhaul links, which are crucial for many functions like low-latency financial trading on Wall Street. I show how Eve designs and employs MetaFly to covertly manipulate the EM wavefront on highly directional backhaul links, secretly inducing eavesdropping diffraction beams. I implement and demonstrate these attacks in both large indoor and outdoor rooftops in a metropolitan area, showcasing how Eve can intercept transmissions with nearly zero bit error rate while maintaining minimal impact on legitimate communication
Catalyst design for water treatment using ab initio simulation
No full textEMBARGO NOTE: This item is embargoed until 2025-12-01Shortage of clean water sources due to climate change, development of industrialization, and population growth is a concerning problem worldwide. Heterogenous catalysis is a promising strategy to reduce the concentration of undesirable substances during water treatment. In this thesis, I apply ab initio simulation to identify key material properties and fundamental reaction mechanisms that dictate catalyst performance for the treatment of two important water contaminants: nitrate and per-fluoroalkyl substances (PFAS). This insight in turn informs design strategies for designing better catalysts for these applications.
Perfluorooctanoic acid (PFOA) is one of the most prevalent PFAS contaminants in surface and ground water. Working with experimentalist collaborators, we reported that hexagonal boron nitride (hBN) is a promising photocatalyst for PFOA degradation under UVC illumination, with an activity ~2x higher than TiO2. In my thesis, I applied density functional theory (DFT) in a grand canonical (GC) formalism (Bhati and Chen et al., J. Phys. Chem. C, 2020, 124, 49, 26625–26639) to determine the photo-catalytic mechanism responsible for PFOA degradation on hBN. (Chen et al. Environ. Sci. Technol., 2022, 56, 12, 8942–8952) I confirmed the favorability of the proposed photo-oxidation step of PFOA on the hBN surface: CnF2n+1COO− + h+ → CnF2n+1ꞏ + CO2. Furthermore, by investigating the electronic properties of hBN, I found that NB substitutional point defect introduces mid-gap states that enable the UVC light absorption and enhance charge carrier separation. Therefore, introducing more NB defects is a promising strategy to enhance the photocatalytic degradation performance of hBN. My work also helped to determine the role of surface hydrophobicity in promoting PFOA degradation, which is attributed both to stronger adsorption of the hydrophobic fluorinated tale of PFOA and the exclusion of water molecules that can scavenge photo-excited holes. (Wang and Chen et al., submitted) Thus, increasing surface hydrophobicity is another strategy for enhancing catalyst performance during PFOA degradation. Using this insight, we are now developing covalent organic framework (COF) catalysts with tunable functionality to tailor hydrophobic and electrostatic interactions, thus maximizing PFOA adsorption.
Besides PFOA, nitrate is another pervasive surface and groundwater contaminant found worldwide. Nitrate anions are highly soluble and mobile, and can cause harmful health effects in humans, including diseases such as blue baby syndrome, cancer, etc. Investigating the reaction network of electrocatalytic nitrate reduction, we found Cu and Pd catalysts can play a synergistic role in nitrate removal. (Lim and Chen et al., ACS Catal. 2023, 13, 1, 87–98) Using DFT, we discerned how the electronic properties of the metal catalyst affect the nitrate reduction reaction mechanism, steering the product selectivity to either N2 or NH3. (Chen and Senftle, submitted) We propose that metals like Pd, with less-occupied and more-delocalized d orbital exhibit higher N2 selectivity due to adsorbate-adsorbate interactions that promote N–N bond formation over N–H bond formation. This insight sets the theoretical basis for the design of better Pd/Cu bimetallic catalysts for the selective disposal of nitrate from water
Bad Roads: Feral Transport Media in American Narrative Art, 1913-1977
No full textIn Bad Roads: Feral Transport Media in American Narrative Art, 1913-1977, I devise the biopolitical and critical regionalist framework of “the bad road” to read for moments of textual ferality in early-to-mid century American literature and film. This framework is based around an understanding of transport media—technologies of mobility, infrastructures, adjacent landscapes—as constructs that mediate and include through exclusion. In what follows, I read for the presence and function of transport media in a diverse array of narratives drawn from the pre and post-interstate eras of twentieth century America. Conducting these analyses demonstrates how both transport media, and the narratives that incorporate them, are uniquely prone to rupture and immunitary failure: moments when a protected inside becomes an outside, or an excised other makes an unheralded return. I refer to this dynamic of containment and rupture as the “bad road.” By applying the “bad road” framework to authors such as Willa Cather, John Steinbeck, Toni Morrison, and N. Scott Momaday, I unpack how the work of narrating mobility in an American colonial context is particularly fraught as the project of modernization is marked by an irrepressible plurality: cultural, geographic, interpersonal, temporal. By setting my project against the backdrop of a crystallizing culture of the “good road” as mobile privatization, I determine that how an author employs, avoids, or is subjected to, the permutations of the bad road, is intimately linked to their cultural positioning. Reading for these differences is crucial to considering the perils and possibilities of mobility in the United States—past, present, and future