cssi/SciSciGPT-SciSciNet huggingface dataset:
The effect of course shutouts on community college students: Evidence from waitlist cutoffs

Abstract One frequently cited yet understudied channel through which funding levels impact college students is course availability—colleges are often forced to respond to budgetary pressure by reducing course offerings. We provide the first causal evidence on this mechanism at a community college, using administrative course registration data and a novel research design that exploits discontinuities in course admissions created by waitlists. Community colleges enroll about half of U.S. undergraduates and over half of minority students in public colleges. The impacts of course availability in this setting may be especially salient relative to four-year colleges due to open admissions policies, binding class size constraints, and a heavy reliance on state funding. Across a range of bandwidths, we find that students stuck on a waitlist and shut out of a course section were 22–28 percent more likely to take zero courses that term relative to a baseline of about 10 percent. Shutouts also increased transfer rates to nearby, but potentially less-desirable two-year colleges. These results offer some evidence that course availability can disrupt community college students’ educational trajectories.
Assessing Higher Order Language Processing in Long-Term Cochlear Implant Users

Purpose The purpose of this study was to describe and explain individual differences in complex/higher order language processing in long-term cochlear implant (CI) users relative to normal-hearing ...
Jam v. International Finance Corp.

In Jam v. International Finance Corp., the U.S. Supreme Court held that the International Organizations Immunities Act of 1945 (IOIA) affords international organizations (IOs) the same immunity from suit in U.S. courts that foreign governments currently enjoy under the Foreign Sovereign Immunities Act of 1976 (FSIA), which codifies the restrictive theory of foreign sovereign immunity. The International Finance Corporation (IFC) had argued that the IOIA, which grants international organizations the “‘same immunity’ from suit … ‘as is enjoyed by foreign governments’” (p. 15), should be understood to provide international organizations with absolute immunity, which it argued foreign governments enjoyed prior to the United States’ explicit adoption of the restrictive theory in 1952. Under the restrictive theory, a foreign state is immune from suit for its sovereign acts (acta jure imperii), but not for its commercial acts (acta jure gestionis). By interpreting language in the IOIA as granting the “same immunity” to international organizations as foreign governments enjoy at the time the suit is filed, the Supreme Court aligned the regime for IO immunity with that of foreign state immunity, except in cases where the IO's founding charter provides a different rule or where the executive branch has explicitly limited immunity. It remains to be seen what IO activities are deemed “commercial” under this regime and what types of transactions are found to have a sufficient nexus to the United States to fall within the FSIA's commercial-activity exception.
Survey of bacteria associated with western corn rootworm life stages reveals no difference between insects reared in different soils

Western corn rootworm (Diabrotica virgifera virgifera LeConte) is a serious pest of maize (Zea mays L.) in North America and parts of Europe. With most of its life cycle spent in the soil feeding on maize root tissues, this insect is likely to encounter and interact with a wide range of soil and rhizosphere microbes. Our knowledge of the role of microbes in pest management and plant health remains woefully incomplete, yet that knowledge could play an important role in effective pest management strategies. For this study, insects were reared on maize in soils from different locations. Insects from two different laboratory colonies (a diapausing and a non-diapausing colony) were sampled at each life stage to determine the possible core bacteriome. Additionally, soil was sampled at each life stage and resulting bacteria were identified to determine the possible contribution of soil to the rootworm bacteriome, if any. We analyzed the V4 hypervariable region of bacterial 16S rRNA genes with Illumina MiSeq to survey the different species of bacteria associated with the insects and the soils. The bacterial community associated with insects was significantly different from that in the soil. Some differences appear to exist between insects from non-diapausing and diapausing colonies while no significant differences in community composition existed between the insects reared on different soils. Despite differences in the bacteria present in immature stages and in male and female adults, there is a possible core bacteriome of approximately 16 operational taxonomic units (i.e., present across all life stages). This research may provide insights into Bt resistance development, improved nutrition in artificial rearing systems, and new management strategies.
How Acquisitions Affect Firm Behavior and Performance: Evidence from the Dialysis Industry

Many industries have become increasingly concentrated through mergers and acquisitions, which in health care may have important consequences for spending and outcomes. Using a rich panel of Medicare claims data for nearly one million dialysis patients, we advance the literature on the effects of mergers and acquisitions by studying the precise ways providers change their behavior following an acquisition. We base our empirical analysis on more than 1,200 acquisitions of independent dialysis facilities by large chains over a 12-year period and find that chains transfer several prominent strategies to the facilities they acquire. Most notably, acquired facilities converge to the behavior of their new parent companies by increasing patients’ doses of highly reimbursed drugs, replacing high-skill nurses with less-skilled technicians, and waitlisting fewer patients for kidney transplants. We then show that patients fare worse as a result of these changes: outcomes such as hospitalizations and mortality deteriorate, with our long panel allowing us to identify these effects from within-facility or within-patient variation around the acquisitions. Because overall Medicare spending increases at acquired facilities, mostly as a result of higher drug reimbursements, this decline in quality corresponds to a decline in value for payers. We conclude the article by considering the channels through which acquisitions produce such large changes in provider behavior and outcomes, finding that increased market power cannot explain the decline in quality. Rather, the adoption of the acquiring firm’s strategies and practices drives our main results, with greater economies of scale for drug purchasing responsible for more than half of the change in profits following an acquisition.
Highly-Linear Magnet-Free Microelectromechanical Circulators

This paper reports the first demonstration of a magnet-free, high performance microelectromechanical system (MEMS) based circulator. An innovative circuit based on the commutation of MEMS resonators with high quality (Q) factor using RF switches is designed and implemented. Thanks to the high Q factor, a much smaller modulation frequency can be achieved compared to the previous demonstrations, reducing the power consumption and enabling the use of high power-handling switches. Furthermore, the MEMS resonators greatly reduce the required inductance value, guaranteeing much smaller form factor compared to the previous LC demonstrations. The demonstrated circulator shows broad BW (15 dB-IX BW = 34.7 MHz for an operational frequency around 2.5 GHz), low IL (4 dB), high IX (30 dB), high linearity (P1dB = 28 dBm; IIP3 = 40 dBm) and at the same time low power consumption, addressing several of the current limitations hindering the full development of magnet-free circulators.
Scaling computational genomics to millions of individuals with GPUs

Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we show that high efficiency at low cost can be achieved by leveraging general-purpose libraries for computing using graphics processing units (GPUs), such as PyTorch and TensorFlow. We demonstrate > 200-fold decreases in runtime and ~ 5–10-fold reductions in cost relative to CPUs. We anticipate that the accessibility of these libraries will lead to a widespread adoption of GPUs in computational genomics.
New antiretroviral agents for the treatment of HIV infection

Issues, such as complexity, tolerability, and drug resistance and cross-resistance, limit the effectiveness of current antiretroviral regimens and make the continued development of newer agents important, despite the availability of 20 approved drugs for the treatment of HIV infection. Many new compounds are in development in existing classes: nucleoside and nucleotide analogue reverse transcriptase inhibitors (eg, D-d4FC and SPD754), non-nucleoside analogue reverse transcriptase inhibitors (eg, capravirine and TMC125), and protease inhibitors (eg, tipranavir and TMC114). In addition, newer classes of antiretroviral drugs, such as HIV entry inhibitors (eg, TNX-355, SCH 417690, UK-427,857, AMD 11070), that target the first step in the HIV life cycle are under development. Continued improvement in the treatment of HIV infection will result from the availability of convenient, well-tolerated, and affordable drugs with potent and durable antiretroviral activity.
Can Predictive Filters Detect Gradually Ramping False Data Injection Attacks Against PMUs

Intelligently designed false data injection (FDI) attacks have been shown to be able to bypass the χ2-test based bad data detector (BDD), resulting in physical consequences (such as line overloads) in the power system. In this paper, using synthetic PMU measurements and intelligently designed FDI attacks, it is shown that if an attack is suddenly injected into the system, a predictive filter with sufficient accuracy is able to detect it. However, an attacker can gradually increase the magnitude of the attack to avoid detection, and still cause damage to the system.
Assessing method agreement for paired repeated binary measurements administered by multiple raters

Method comparison studies are essential for development in medical and clinical fields. These studies often compare a cheaper, faster, or less invasive measuring method with a widely used one to see if they have sufficient agreement for interchangeable use. Moreover, unlike simply reading measurements from devices, eg, reading body temperature from a thermometer, the response measurement in many clinical and medical assessments is impacted not only by the measuring device but also by the rater. For example, widespread inconsistencies are commonly observed among raters in psychological or cognitive assessment studies due to different characteristics such as rater training and experience, especially in large-scale assessment studies when many raters are employed. This paper proposes a model-based approach to assess agreement of two measuring methods for paired repeated binary measurements under the scenario where the agreement between two measuring methods and the agreement among raters are required to be studied simultaneously. Based upon the generalized linear mixed models (GLMMs), the decision on the adequacy of interchangeable use is made by testing the equality of fixed effects of methods. Approaches for assessing method agreement, such as the Bland-Altman diagram and Cohen's kappa, are also developed for repeated binary measurements based upon the latent variables in GLMMs. We assess our novel model-based approach by simulation studies and a real clinical application, in which patients are evaluated repeatedly for delirium with two validated screening methods. Both the simulation studies and the real data analyses demonstrate that our proposed approach can effectively assess method agreement.
An analog of the Weyl law for the Kohn Laplacian on spheres

We present an explicit formula for the leading coefficient in the asymptotic expansion of the eigenvalue counting function of the Kohn Laplacian on the unit sphere $${\mathbb {S}}^{2n-1}$$ .
The effects of operating cash flow disclosure on earnings comparability, analysts' forecasts, and firms’ investment decisions during the Pre-IFRS era

Abstract We examine the effects of the availability of operating cash flow (OCF) information disclosed by firms operating in 15 international countries during the pre-IFRS era on: (1) the comparability of these firms' disaggregated earnings to those of U.S. firms for equity valuation purposes, (2) the properties of analysts' earnings forecasts, and (3) the efficiency of firms' investment decisions. We find that the comparability of disaggregated earnings improves after company-disclosed OCF information is available. We also find decreases in analysts' forecast errors and dispersion and a decrease in firms’ tendency to over- or under-invest when they are predisposed to do so.
EARLY FUSION for Goal Directed Robotic Vision

Building perceptual systems for robotics which perform well under tight computational budgets requires novel architectures which rethink the traditional computer vision pipeline. Modern vision architectures require the agent to build a summary representation of the entire scene, even if most of the input is irrelevant to the agent’s current goal. In this work, we flip this paradigm, by introducing EARLYFUSION vision models that condition on a goal to build custom representations for downstream tasks. We show that these goal specific representations can be learned more quickly, are substantially more parameter efficient, and more robust than existing attention mechanisms in our domain. We demonstrate the effectiveness of these methods on a simulated item retrieval problem that is trained in a fully end-to-end manner via imitation learning.
Smoothed Efficient Algorithms and Reductions for Network Coordination Games.

Worst-case hardness results for most equilibrium computation problems have raised the need for beyond-worst-case analysis. To this end, we study the smoothed complexity of finding pure Nash equilibria in Network Coordination Games, a PLS-complete problem in the worst case. This is a potential game where the sequential-better-response algorithm is known to converge to a pure NE, albeit in exponential time. First, we prove polynomial (resp. quasi-polynomial) smoothed complexity when the underlying game graph is a complete (resp. arbitrary) graph, and every player has constantly many strategies. We note that the complete graph case is reminiscent of perturbing all parameters, a common assumption in most known smoothed analysis results. Second, we define a notion of smoothness-preserving reduction among search problems, and obtain reductions from $2$-strategy network coordination games to local-max-cut, and from $k$-strategy games (with arbitrary $k$) to local-max-cut up to two flips. The former together with the recent result of [BCC18] gives an alternate $O(n^8)$-time smoothed algorithm for the $2$-strategy case. This notion of reduction allows for the extension of smoothed efficient algorithms from one problem to another. For the first set of results, we develop techniques to bound the probability that an (adversarial) better-response sequence makes slow improvements on the potential. Our approach combines and generalizes the local-max-cut approaches of [ER14,ABPW17] to handle the multi-strategy case: it requires a careful definition of the matrix which captures the increase in potential, a tighter union bound on adversarial sequences, and balancing it with good enough rank bounds. We believe that the approach and notions developed herein could be of interest in addressing the smoothed complexity of other potential and/or congestion games.
mpfit: a robust method for fitting atomic resolution images with multiple Gaussian peaks

The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit, an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.
Medial entorhinal cortex activates in a traveling wave in the rat

Traveling waves are hypothesized to support the long-range coordination of anatomically distributed circuits. Whether separate strongly interacting circuits exhibit traveling waves remains unknown. The hippocampus exhibits traveling 'theta' waves and interacts strongly with the medial entorhinal cortex (MEC). To determine whether the MEC also activates in a traveling wave, we performed extracellular recordings of local field potentials (LFP) and multi-unit activity along the MEC. These recordings revealed progressive phase shifts in activity, indicating that the MEC also activates in a traveling wave. Variation in theta waveform along the region, generated by gradients in local physiology, contributed to the observed phase shifts. Removing waveform-related phase shifts left significant residual phase shifts. The residual phase shifts covaried with theta frequency in a manner consistent with those generated by weakly coupled oscillators. These results show that the coordination of anatomically distributed circuits could be enabled by traveling waves but reveal heterogeneity in the mechanisms generating those waves.
Computational cannula microscopy of neurons using neural networks

Computational cannula microscopy is a minimally invasive imaging technique that can enable high-resolution imaging deep inside tissue. Here, we apply artificial neural networks to enable real-time, power-efficient image reconstructions that are more efficiently scalable to larger fields of view. Specifically, we demonstrate widefield fluorescence microscopy of cultured neurons and fluorescent beads with a field of view of 200 µm (diameter) and a resolution of less than 10 µm using a cannula of diameter of only 220 µm. In addition, we show that this approach can also be extended to macro-photography.
The Heuristic Dynamic Programming Approach in Boost Converters

In this study, a heuristic dynamic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during the start-up, the load change, or the input voltage variation is not optimal since the system model changes by varying the operating point. The heuristic dynamic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the HDP is that the neural network-based characteristic of the proposed controller enables boost converters to easily cope with large disturbances. An HDP with a well-trained critic and action networks can perform as an optimal controller for the boost converter. To compare the effectiveness of the traditional PI-based and the HDP boost converter, the simulation results are provided.
A novel MRI-based finite element modeling method for calculation of myocardial ischemia effect in patients with functional mitral regurgitation

Background: Functional Mitral Regurgitation (FMR) associated with coronary artery disease affects nearly 3 million patients in the United States. Both myocardial infarction (MI) and ischemia contribute to FMR development but uncertainty as to which patients will respond to revascularization (REVASC) of ischemia alone prevents rational decision making about FMR therapy. The aim of the study was to create patient-specific cardiac MRI (CMR) informed finite element (FE) models of the left ventricle (LV), calculate regional LV systolic contractility and then use optimized systolic material properties to simulate the effect of revascularization (virtual REVASC). Method: We describe a novel finite element method able to predict the effect of myocardial ischemia on regional left ventricular function. Cardiac MRI (CMR) was obtained in five patients with multi-vessel coronary disease and FMR before and 3 months after percutaneous REVASC and a single healthy volunteer. Patient-specific FE models were created and divided into 17 sectors where the systolic contractility parameter, T_max, of each sector was a function of regional stress perfusion (SP-CMR) and myocardial infarction (LGE-CMR) scores. Sector-specific circumferential and longitudinal end-systolic strain and LV volume from CSPAMM were used in a formal optimization to determine the sector based myocardial contractility, T_max, and ischemia effect, α. Virtual REVASC was simulated by setting α to zero. Results: The FE optimization successfully converged with good agreement between calculated and experimental end-systolic strain and LV volumes. Specifically, the optimized T_max for the healthy myocardium for five patients and the volunteer was 495.1 kPa, 336.8 kPa, 173.5 kPa, 227.9 kPa, 401.4 kPa, and 218.9 kPa. The optimized α was found to be 1.0, 0.44, and 0.08 for Patients 1, 2, and 3, and 0 for Patients 4 and 5. The calculated average of radial strain for the Patients 1, 2, and 3 at baseline and after virtual REVASC was 0.23 and 0.25, respectively. Conclusion: We developed a novel computational method able to predict the effect of myocardial ischemia in patients with FMR. This method can be used to predict the effect of ischemia on the regional myocardium and promises to facilitate better understanding of FMR response to REVASC.
Cooperative Navigation of Micro-Rovers Using Color Segmentation

This paper addresses position estimation of a micro-rover mobile robot (called the “daughter”) as a larger robot (the “mother”) tracks it through large spaces with unstructured lighting. Position estimation is necessary for localization, where the mother extracts the relative position of the daughter for mapping purposes, and for cooperative navigation, where the mother controls the daughter in real-time. The approach taken is to employ the Spherical Coordinate Transform color segmenter developed for medical applications as a low computational and hardware cost solution. Data was collected from 50 images taken in five types of lighting: fluorescent, tungsten, daylight lamp, natural daylight indoors and outdoors. The results show that average pixel error was 1.5, with an average error in distance estimation of 6.3 cm. The size of the error did not vary greatly with the type of lighting. The segmentation and distance tracking have also been implemented as a real-time tracking system. Using this system, the mother robot is able to autonomously control the micro-rover and display a map of the daughter's path in real-time using only a Pentium class processor and no specialized hardware.
Deep Learning for TDD and FDD Massive MIMO: Mapping Channels in Space and Frequency

Can we map the channels at one set of antennas and one frequency band to the channels at another set of antennas— possibly at a different location and a different frequency bandƒ If this channel-to-channel mapping is possible, we can expect dramatic gains for massive MIMO systems. For example, in FDD massive MIMO, the uplink channels can be mapped to the downlink channels or the downlink channels at one subset of antennas can be mapped to the downlink channels at all the other antennas. This can significantly reduce (or even eliminate) the downlink training/feedback overhead. In the context of cell-free/distributed massive MIMO systems, this channel mapping can be leveraged to reduce the fronthaul signaling overheadIn this paper, we introduce the new concept of channel mapping in space and frequency, where the channels at one set of antennas and one frequency band are mapped to the channels at another set of antennas and frequency band. First, we prove that this channel-to-channel mapping function exists under certain conditions. Then, we leverage the powerful learning capabilities of deep neural networks to efficiently learn this non-trivial channel mapping function, which is also confirmed by the simulation results.
Light-Inducible Generation of Membrane Curvature in Live Cells with Engineered BAR Domain Proteins.

Nanoscale membrane curvature is now understood to play an active role in essential cellular processes such as endocytosis, exocytosis and actin dynamics. Previous studies have shown that membrane c...
SuperCRUNCH: A bioinformatics toolkit for creating and manipulating supermatrices and other large phylogenetic datasets

Phylogenies with extensive taxon sampling have become indispensable for many types of ecological and evolutionary studies. Many large-scale trees are based on a "supermatrix" approach, which involves amalgamating thousands of published sequences for a group. Constructing up-to-date supermatrices can be challenging, especially as new sequences may become available almost constantly. However, few tools exist for assembling large-scale, high-quality supermatrices (and other large datasets) for phylogenetic analysis. Here we present SuperCRUNCH, a Python toolkit for assembling large phylogenetic datasets. It can be applied to GenBank sequences, unpublished sequences, or combinations of GenBank and unpublished data. SuperCRUNCH constructs local databases and uses them to conduct rapid searches for user-specified sets of taxa and loci. Sequences are parsed into putative loci and passed through rigorous filtering steps. A post-filtering step allows for selection of one sequence per taxon (i.e. species-level supermatrix) or retention of all sequences per taxon (i.e. population-level dataset). Importantly, SuperCRUNCH can generate "vouchered" population-level datasets, in which voucher information is used to generate multi-locus phylogeographic datasets. Additionally, SuperCRUNCH offers many options for taxonomy resolution, similarity filtering, sequence selection, alignment, and file manipulation. We demonstrate the range of features available in SuperCRUNCH by generating a variety of phylogenetic datasets. We provide examples using GenBank data, and combinations of GenBank and unpublished data. Output datasets include traditional species-level supermatrices, large-scale phylogenomic matrices, and phylogeographic datasets. Finally, we briefly compare the ability of SuperCRUNCH to construct species-level supermatrices to alternative approaches. SuperCRUNCH generated a large-scale supermatrix (1,400 taxa and 66 loci) from 16GB of GenBank data in ~1.5 hours, and generated population-level datasets (
“We're being tracked at all times”: Student perspectives of their privacy in relation to learning analytics in higher education

Abstract Higher education institutions are continuing to develop their capacity for learning analytics (LA), which is a sociotechnical data‐mining and analytic practice. Institutions rarely inform ...
Application of Combined Genomic and Transfer Analyses to Identify Factors Mediating Regional Spread of Antibiotic-resistant Bacterial Lineages

Background Patients entering nursing facilities (NFs) are frequently colonized with antibiotic-resistant organisms (AROs). To understand the determinants of ARO colonization on NF admission, we applied whole-genome sequencing to track the spread of 4 ARO species across regional NFs and evaluated patient-level characteristics and transfer acute care hospitals (ACHs) as risk factors for colonization. Methods Patients from 6 NFs (n = 584) were surveyed for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus faecalis/faecium (VREfc/VREfm), and ciprofloxacin-resistant Escherichia coli (CipREc) colonization. Genomic analysis was performed to quantify ARO spread between NFs and compared to patient-transfer networks. The association between admission colonization and patient-level variables and recent ACH exposures was examined. Results The majority of ARO isolates belonged to major healthcare-associated lineages: MRSA (sequence type [ST] 5); VREfc (ST6); CipREc (ST131), and VREfm (clade A). While the genomic similarity of strains between NF pairs was positively associated with overlap in their feeder ACHs (P 2 for MRSA and VREfc/VREfm) or third-/fourth-generation cephalosporins (aOR, > 2 for MRSA and VREfm). Transfer from specific ACHs was an independent risk factor for only 1 ARO/ACH pair (VREfm/ACH19: aOR, 2.48). Conclusions In this region, healthcare-associated ARO lineages are endemic among connected NFs and ACHs, making patient characteristics more informative of NF admission colonization risk than exposure to specific ACHs.
1-Auslander-Gorenstein algebras which are tilted

Abstract Let Λ be a 1-Auslander-Gorenstein algebra. We give a necessary and sufficient condition for Λ to be a tilted algebra.
Information Flow Optimization in Inference Networks

The problem of maximizing the information flow through a sensor network tasked with an inference objective at the fusion center is considered. The sensor nodes take observations, compress and send them to the fusion center through a network of relays. The network imposes capacity constraints on the rate of transmission in each connection and flow conservation constraints. It is shown that this rate-constrained inference problem can be cast as a Network Utility Maximization problem by suitably defining the utility functions for each sensor, and can be solved using existing techniques. Two practical settings are analyzed: multi-terminal parameter estimation and binary hypothesis testing. It is verified via simulations that using the proposed formulation gives better inference performance than the Max-Flow solution that simply maximizes the total bit-rate to the fusion center.
Sub-Hermitian geometry and the quantitative Newlander-Nirenberg theorem

Abstract Given a finite collection of C 1 complex vector fields on a C 2 manifold M such that they and their complex conjugates span the complexified tangent space at every point, the classical Newlander-Nirenberg theorem gives conditions on the vector fields so that there is a complex structure on M with respect to which the vector fields are T 0 , 1 . In this paper, we give intrinsic, diffeomorphic invariant, necessary and sufficient conditions on the vector fields so that they have a desired level of regularity with respect to this complex structure (i.e., smooth, real analytic, or have Zygmund regularity of some finite order). By addressing this in a quantitative way we obtain a holomorphic analog of the quantitative theory of sub-Riemannian geometry initiated by Nagel, Stein, and Wainger. We call this sub-Hermitian geometry. Moreover, we proceed more generally and obtain similar results for manifolds which have an associated formally integrable elliptic structure. This allows us to introduce a setting which generalizes both the real and complex theories.
Viscous transport in eroding porous media

Transport of viscous fluid through porous media is a direct consequence of the pore structure. Here we investigate transport through a specific class of two-dimensional porous geometries, namely those formed by fluid-mechanical erosion. We investigate the tortuosity and dispersion by analyzing the first two statistical moments of tracer trajectories. For most initial configurations, tortuosity decreases in time as a result of erosion increasing the porosity. However, we find that tortuosity can also increase transiently in certain cases. The porosity-tortuosity relationships that result from our simulations are compared with models available in the literature. Asymptotic dispersion rates are also strongly affected by the erosion process, as well as by the number and distribution of the eroding bodies. Finally, we analyze the pore size distribution of an eroding geometry. The simulations are performed by combining a boundary integral equation solver for the fluid equations, a second-order stable time-stepping method to simulate erosion, and high-order numerical methods to stably and accurately resolve nearly touching eroded bodies and particle trajectories near the eroding bodies.
Chapter 2 – Development of Airway Epithelium

Tracheobronchial airway development begins prenatally and continues for an extended period of postnatal life. In adults, the organization of tracheobronchial airway epithelium is highly complex and variable both within the airway tree of a single species and in the same airway generation in different species, including the composition of the cell populations, their secrectory products, and their metabolic capabilities. When the same differentiated cell phenotypes are present in many different airway generations, their relative abundance varies widely. Differentiation during pre- and postnatal development is a proximal and distal phenomenon, with each phenotype differentiating over a different period of time depending on the airway microenvironment in which it is differentiating. This developmental process balances between the active proliferation necessary for airway growth and the differentiated functions required for healthy airway function in neonates. All of these processes are highly susceptible to disruption by toxicants that target the respiratory system.
LC2: A Language for Conversational Computing

The purpose of time-sharing is twofold: to increase the efficiency of the computer system and, while attaining this increase, to permit efficient communication between a programmer and his programs. This communication we may call conversation. Prevailing programming languages like FORTRAN, PL/1, ALGOL, COBOL, etc., are poorly designed for such interactive programming. However, languages like JOSS [1], APL [2], and the to be described LC2 are much more suited to this task.
Global broadcasting of local fractal fluctuations in a bodywide distributed system supports perception via effortful touch

Abstract A long history of research has pointed to the importance of fractal fluctuations in physiology, but so far, the physiological evidence of fractal fluctuations has been piecemeal and without clues to bodywide integration. What remains unknown is how fractal fluctuations might interact across the body and how those interactions might support the coordination of goal-directed behaviors. We demonstrate that a complex interplay of fractality in mechanical fluctuations across the body supports a more accurate perception of heaviness and length of occluded handheld objects via effortful touch in blindfolded individuals. For a given participant, the flow of fractal fluctuation through the body indexes the flow of perceptual information used to derive perceptual judgments. Effortful touch depends on compression of high-dimensional flux of mechanotransduction into low-dimensional perceptual information specifying properties of hefted occluded objects. These patterns in the waxing and waning of fluctuations across disparate anatomical locations provide novel insights into the form of this compression.
Ceftriaxone and mGlu2/3 interactions in the nucleus accumbens core affect the reinstatement of cocaine-seeking in male and female rats.

The beta-lactam antibiotic ceftriaxone reliably attenuates the reinstatement of cocaine seeking. While the restoration of nucleus accumbens core (NA core) GLT-1 expression is necessary for ceftriaxone to attenuate reinstatement, AAV-mediated GLT-1 overexpression is not sufficient to attenuate reinstatement and does not prevent glutamate efflux during reinstatement. Here, we test the hypothesis that ceftriaxone attenuates reinstatement through interactions with glutamate autoreceptors mGlu2 and mGlu3 in the NA core. Male and female rats self-administered cocaine for 12 days followed by 2–3 weeks of extinction training. During the last 6–10 days of extinction, rats received ceftriaxone (200 mg/kg IP) or vehicle. In experiment 1, rats were killed, and NA core tissue was biotinylated for assessment of total and surface expression of mGlu2 and mGlu3 via western blotting. In experiment 2, we tested the hypothesis that mGlu2/3 signaling is necessary for ceftriaxone to attenuate cue- and cocaine-primed reinstatement by administering bilateral intra-NA core infusion of mGlu2/3 antagonist LY341495 or vehicle immediately prior to reinstatement testing. mGlu2 expression was reduced by cocaine and restored by ceftriaxone. There were no effects of cocaine or ceftriaxone on mGlu3 expression. We observed no effects of estrus on expression of either protein. The antagonism of mGlu2/3 in the NA core during both cue- and cocaine-primed reinstatement tests prevented ceftriaxone from attenuating reinstatement. These results indicate that ceftriaxone’s effects depend on mGlu2/3 function and possibly mGlu2 receptor expression. Future work will test this hypothesis by manipulating mGlu2 expression in pathways that project to the NA core.
Chapter 6 – MATLAB Programs

MATLAB Programs covers more on scripts and user-defined functions. User-defined functions that return more than one value and also user-defined functions that do not return anything are introduced. The concept of a program in MATLAB, which consists of a script that calls user-defined functions, is demonstrated with examples. Modular programming is emphasized, and a longer menu-driven program is shown as a reference. Subfunctions and scope of variables are also introduced, as are some debugging techniques. The use of the new Live Editor to create live scripts is introduced. Live scripts can embed equations, images, and hyperlinks in addition to formatted text.
Unique transcriptional signatures of sleep loss across independently evolved cavefish populations.

Animals respond to sleep loss with compensatory rebound sleep, and this is thought to be critical for the maintenance of physiological homeostasis. Sleep duration varies dramatically across animal species, but it is not known whether evolutionary differences in sleep duration are associated with differences in sleep homeostasis. The Mexican cavefish, Astyanax mexicanus, has emerged as a powerful model for studying the evolution of sleep. While eyed surface populations of A. mexicanus sleep approximately 8 hr each day, multiple blind cavefish populations have converged on sleep patterns that total as little as 2 hr each day, providing the opportunity to examine whether the evolution of sleep loss is accompanied by changes in sleep homeostasis. Here, we examine the behavioral and molecular response to sleep deprivation across four independent populations of A. mexicanus. Our behavioral analysis indicates that surface fish and all three cavefish populations display robust recovery sleep during the day following nighttime sleep deprivation, suggesting sleep homeostasis remains intact in cavefish. We profiled transcriptome-wide changes associated with sleep deprivation in surface fish and cavefish. While the total number of differentially expressed genes was not greater for the surface population, the surface population exhibited the highest number of uniquely differentially expressed genes than any other population. Strikingly, a majority of the differentially expressed genes are unique to individual cave populations, suggesting unique expression responses are exhibited across independently evolved cavefish populations. Together, these findings suggest sleep homeostasis is intact in cavefish despite a dramatic reduction in overall sleep duration.
U.S. industry-level returns and oil prices

Abstract This paper empirically investigates and provides further support for the oil price effect documented in Driesprong et al. (2008) in the U.S. industry-level returns. We find that oil price predictability is concentrated in a relatively small number of industry-level returns, the relevant measure for a study of the oil effect is percentage change in oil spot prices, and changes in oil futures prices have virtually no prediction power for industry-level returns. With percentage changes in oil spot prices as the predictor, approximately one fifth of industry returns are oil-predictable. We detect a two trading weeks delay in reaction to oil price changes which is consistent with the Hong and Stein (1996) underreaction hypothesis. These results are robust to various alternative specifications, and are shown to be unrelated to time-varying risk premia. Moreover, we demonstrate that trading strategies based on the oil effect generate superior gains in comparison with buy-and-hold strategy in the presence of reasonable trading costs.
Topological Boundaries of Unitary Representations

We introduce and study a generalization of the notion of the Furstenberg boundary of a discrete group $\Gamma$ to the setting of a general unitary representation $\pi: \Gamma \to B(\mathcal H_\pi)$. This space, which we call the "Furstenberg-Hamana boundary" of the pair $(\Gamma, \pi)$, is a $\Gamma$-invariant subspace of $B(\mathcal H_\pi)$ that carries a canonical $C^*$-algebra structure. In many natural cases, including when $\pi$ is a quasi-regular representation, the Furstenberg-Hamana boundary of $\pi$ is commutative, but can be non-commutative in general. We study various properties of this boundary, and give some applications.
The full holonomy group under the Ricci flow

We give a short, direct proof that the full holonomy group of a solution to the Ricci flow is invariant up to isomorphism using the invariance of the reduced holonomy under the flow.
Enabling Language Models to Fill in the Blanks.

We present a simple approach for text infilling, the task of predicting missing spans of text at any position in a document. While infilling could enable rich functionality especially for writing assistance tools, more attention has been devoted to language modeling—a special case of infilling where text is predicted at the end of a document. In this paper, we aim to extend the capabilities of language models (LMs) to the more general task of infilling. To this end, we train (or fine tune) off-the-shelf LMs on sequences containing the concatenation of artificially-masked text and the text which was masked. We show that this approach, which we call infilling by language modeling, can enable LMs to infill entire sentences effectively on three different domains: short stories, scientific abstracts, and lyrics. Furthermore, we show that humans have difficulty identifying sentences infilled by our approach as machine-generated in the domain of short stories.
Computing unit groups of curves

Abstract The group of units modulo constants of an affine variety over an algebraically closed field is free abelian of finite rank. Computing this group is difficult but of fundamental importance in tropical geometry, where it is necessary in order to realize intrinsic tropicalizations. We present practical algorithms for computing unit groups of smooth curves of low genus. Our approach is rooted in divisor theory, based on interpolation in the case of rational curves and on methods from algebraic number theory in the case of elliptic curves.
Association between inflammatory bowel disease and prostate cancer: A large-scale, prospective, population-based study.

Inflammatory bowel disease (IBD) is an established risk factor for colorectal cancer. Recent reports suggesting IBD is also a risk factor for prostate cancer (PC) require further investigation. We studied 218 084 men in the population-based UK Biobank cohort, aged 40 to 69 at study entry between 2006 and 2010, with follow-up through mid-2015. We assessed the association between IBD and subsequent PC using multivariable Cox regression analyses, adjusting for age at assessment, ethnic group, UK region, smoking status, alcohol drinking frequency, body mass index, Townsend Deprivation Index, family history of PC and previous prostate-specific antigen testing. Mean age at study entry was 56 years, 94% of the men were white, and 1.1% (n = 2311) had a diagnosis of IBD. After a median follow-up of 78 months, men with IBD had an increased risk of PC (adjusted hazard ratio [aHR] = 1.31, 95% confidence interval [CI] = 1.03-1.67, P = .029). The association with PC was only among men with the ulcerative colitis (UC; aHR = 1.47, 95% CI = 1.11-1.95, P = .0070), and not Crohn's disease (aHR 1.06, 95% CI = 0.63-1.80, P = .82). Results are limited by lack of data on frequency of health care interactions. In a large-scale, prospective cohort study, we detected an association between IBD, and UC specifically, with incident PC diagnosis.
Epitaxial Chemical Deposition of ZnO Nanocolumns from NaOH Solutions

A new method of depositing epitaxial ZnO nanocolumns on sputter-coated ZnO substrates is described that utilizes supersaturated zincate species in sodium hydroxide solutions and requires no complexing agents. Uniform arrays of columns are grown reproducibly over entire substrates in 10 to 50 min. Columns are 50 to 2000 nm long and 50 to 100 nm wide. Strict substrate cleaning and/or preparations are not necessary with this method, in contrast to many other techniques. Films grow only on substrates pre-coated with ZnO, not on bare glass or ITO-or SnO2-coated glass. Factors affecting the column growth are elucidated and experimental observations are correlated with crystal growth theory.
The Uruguay Round and Welfare in Some Distorted Agricultural Economies

Abstract The Uruguay Round's induced changes in world agricultural prices will affect the welfare of developing countries. The standard terms of trade effect calculation can mislead, since the `distortion effect' operates alongside `the terms of trade effect'. This study of the Uruguay Round's impact on nine agricultural economies reveals distortion effects which are many times larger than terms of trade effects. In three of nine cases, the distortion effect reverses the impact of the terms of trade effect. In two other cases, the distortion effect raises trivial terms of trade effect up to around 1% of national income.
Continued fractions and orderings on the Markov numbers

Abstract Markov numbers are integers that appear in the solution triples of the Diophantine equation, x 2 + y 2 + z 2 = 3 x y z , called the Markov equation. A classical topic in number theory, these numbers are related to many areas of mathematics such as combinatorics, hyperbolic geometry, approximation theory and cluster algebras. There is a natural map from the rational numbers between zero and one to the Markov numbers. In this paper, we prove a conjecture seen in Martin Aigner's book, Markov's theorem and 100 years of the uniqueness conjecture, that determine an ordering on subsets of the Markov numbers based on their corresponding rational. The proof relies on a relationship between Markov numbers and continuant polynomials which originates in Frobenius' 1913 paper.