cssi/SciSciGPT-SciSciNet huggingface dataset:
Neural Systems for Memory-based Value Judgment and Decision-making

Real-life choices often require that we draw inferences about the value of options based on structured, schematic knowledge about their utility for our current goals. Other times, value information may be retrieved directly from a specific prior experience with an option. In an fMRI experiment, we investigated the neural systems involved in retrieving and assessing information from different memory sources to support value-based choice. Participants completed a task in which items could be conferred positive or negative value based on schematic associations (i.e., schema value) or learned directly from experience via deterministic feedback (i.e., experienced value). We found that ventromedial pFC (vmPFC) activity correlated with the influence of both experience- and schema-based values on participants' decisions. Connectivity between the vmPFC and middle temporal cortex also tracked the inferred value of items based on schematic associations on the first presentation of ingredients, before any feedback. In contrast, the striatum responded to participants' willingness to bet on ingredients as a function of the unsigned strength of their memory for those options' values. These results argue that the striatum and vmPFC play distinct roles in memory-based value judgment and decision-making. Specifically, the vmPFC assesses the value of options based on information inferred from schematic knowledge and retrieved from prior direct experience, whereas the striatum controls a decision to act on options based on memory strength.
Network cache design under stationary requests: Exact analysis and Poisson approximation

Abstract The design of caching algorithms to maximize hit probability has been extensively studied. In this paper, we associate each content with a utility, which is a function of either the corresponding content hit rate. We formulate a cache optimization problem to maximize the sum of utilities over all contents under stationary and ergodic request processes. This problem is non-convex in general but we reformulate it as a convex optimization problem when the inter-request time (irt) distribution has a non-increasing hazard rate function. We provide explicit optimal solutions for some irt distributions. We formulate a reverse engineering based dual implementation of LRU under stationary arrivals. We also propose online algorithms that can be implemented using limited information and use a discrete time Lyapunov technique (DTLT) to correctly characterize their stability. Informed by these results, we further propose lightweight Poisson approximate online algorithms that are accurate and efficient in achieving optimal hit rates. We compare the solutions of the hit-rate based (HRB) and hit-probability based (HPB) problems. We find that online algorithms that solve HRB are more robust than online HPB algorithms.
Inert drift system in a viscous fluid: Steady state asymptotics and exponential ergodicity

We analyze a system of stochastic differential equations describing the joint motion of a massive (inert) particle in a viscous fluid in the presence of a gravitational field and a Brownian particle impinging on it from below, which transfers momentum proportional to the local time of collisions. We study the long-time fluctuations of the velocity of the inert particle and the gap between the two particles, and we show convergence in total variation to the stationary distribution is exponentially fast. We also produce matching upper and lower bounds on the tails of the stationary distribution and show how these bounds depend on the system parameters. A renewal structure for the process is established, which is the key technical tool in proving the mentioned results.
Computational fuzzy extractors

Abstract Fuzzy extractors derive strong keys from noisy sources. Their security is usually defined information-theoretically, with gaps between known negative results, existential constructions, and polynomial-time constructions. We ask whether using computational security can close these gaps. We show the following: • Negative result: Noise tolerance in fuzzy extractors is usually achieved using an information reconciliation component called a secure sketch. We show that secure sketches defined using pseudoentropy (Hastad et al., SIAM J. Comput. 1999) instead of information-theoretic security are still subject to upper bounds from coding theory. • Positive result: We show that our negative result can be avoided by constructing and analyzing a computational fuzzy extractor directly. We modify the code-offset construction (Juels and Wattenberg, CCS 1999) to use random linear codes. Security is based on the Learning with Errors problem and holds when the noisy source is uniform or symbol-fixing (that is, each dimension is either uniform or fixed).
Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5-years apart.

Pioneering studies have shown that individual correlation measures from resting-state functional magnetic resonance imaging studies can identify another scan from that same individual. This method is known as "connectotyping" or functional connectome "fingerprinting." We analyzed a unique dataset of 12-30 years old (N = 140) individuals who had two distinct resting state scans on the same day and again 12-18 months later to assess the sensitivity and specificity of fingerprinting accuracy across different time scales (same day, ~1.5 years apart) and developmental periods (youths, adults). Sensitivity and specificity to identify one's own scan was high (average AUC = 0.94), although it was significantly higher in the same day (average AUC = 0.97) than 1.5-years later (average AUC = 0.91). Accuracy in youths (average AUC = 0.93) was not significantly different from adults (average AUC = 0.96). Multiple statistical methods revealed select connections from the Frontoparietal, Default, and Dorsal Attention networks enhanced the ability to identify an individual. Identification of these features generalized across datasets and improved fingerprinting accuracy in a longitudinal replication data set (N = 208). These results provide a framework for understanding the sensitivity and specificity of fingerprinting accuracy in adolescents and adults at multiple time scales. Importantly, distinct features of one's "fingerprint" contribute to one's uniqueness, suggesting that cognitive and default networks play a primary role in the individualization of one's connectome.
Serre–Tate theory for Shimura varieties of Hodge type

We study the formal neighbourhood of a point in the $$\mu $$ -ordinary locus of an integral model of a Hodge type Shimura variety. We show that this formal neighbourhood has a structure of a “shifted cascade”. Moreover we show that the CM points on the formal neighbourhood are dense and that the identity section of the shifted cascade corresponds to a lift of the abelian variety which has a characterization in terms of its endomorphisms, analogous to the Serre–Tate canonical lift of an ordinary abelian variety.
Some recent developments in cometary physics.

Recent observations and associated theoretical developments bearing on the composition and structure of comets are briefly reviewed. The physical and dynamical processes in cometary atmospheres and ionospheres are discussed, and detailed hydrodynamic models of expanding multiconstituent cometary atmospheres corresponding both to a central nucleus as well as a central nucleus surrounded by a distributed source are presented for comparison with observation. It is argued that observed 'slow' speed for the neutral hydrogen is not incompatible with a purely H2O 'parent' source for that species.
Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning?

The proliferation of smart mobile devices has spurred an explosive growth of mobile crowd-learning services, where service providers rely on the user community to voluntarily collect, report, and share real-time information for a collection of scattered points of interest (PoI). A critical factor affecting the future large-scale adoption of such mobile crowd-learning applications is the freshness of the crowd-learned information, which can be measured by a metric termed “age-of-information” (AoI). However, we show that the AoI of mobile crowd-learning could be arbitrarily bad under selfish users' behaviors if the system is poorly designed. This motivates us to design efficient reward mechanisms to incentivize mobile users to report information in time, with the goal of keeping the AoI and congestion level of each PoI low. Toward this end, we consider a simple linear AoI-based reward mechanism and analyze its AoI and congestion performances in terms of price of anarchy (PoA), which characterizes the degradation of the system efficiency due to selfish behavior of users. Remarkably, we show that the proposed mechanism achieves the optimal AoI performance asymptotically in a deterministic scenario. Further, we prove that the proposed mechanism achieves a bounded PoA in general stochastic cases, and the bound only depends on system parameters. Particularly, when the service rates of PoIs are symmetric in stochastic cases, the achieved PoA is upperbounded by 1/2 asymptotically. Collectively, this work advances our understanding of information freshness in mobile crowd-learning systems.
Maximum Principle Preserving Schemes for Binary Systems with Long-Range Interactions

We study some maximum principle preserving and energy stable schemes for the Allen–Cahn–Ohta–Kawasaki model with fixed volume constraint. With the inclusion of a nonlinear term $$f(\phi )$$ in the Ohta–Kawasaki free energy functional, we show that the Allen–Cahn–Ohta–Kawasaki dynamics is maximum principle preserving. We further design some first order energy stable numerical schemes which inherit the maximum principle preservation in both semi-discrete and fully-discrete levels. Furthermore, we apply the maximum principle preserving schemes to a general framework for binary systems with long-range interactions. We also present some numerical results to support our theoretical findings.
Discovery and predictive modeling of urine microbiome, metabolite and cytokine biomarkers in hospitalized patients with community acquired pneumonia

Pneumonia is the leading cause of infectious related death costing 12 billion dollars annually in the United States alone. Despite improvements in clinical care, total mortality remains around 4%, with inpatient mortality reaching 5–10%. For unknown reasons, mortality risk remains high even after hospital discharge and there is a need to identify those patients most at risk. Also of importance, clinical symptoms alone do not distinguish viral from bacterial infection which may delay appropriate treatment and may contribute to short-term and long-term mortality. Biomarkers have the potential to provide point of care diagnosis, identify high-risk patients, and increase our understanding of the biology of disease. However, there have been mixed results on the diagnostic performance of many of the analytes tested to date. Urine represents a largely untapped source for biomarker discovery and is highly accessible. To test this hypothesis, we collected urine from hospitalized patients with community-acquired pneumonia (CAP) and performed a comprehensive screen for urinary tract microbiota signatures, metabolite, and cytokine profiles. CAP patients were diagnosed with influenza or bacterial (Streptococcus pneumoniae and Staphylococcus aureus) etiologies and compared with healthy volunteers. Microbiome signatures showed marked shifts in taxonomic levels in patients with bacterial etiology versus influenza and CAP versus normal. Predictive modeling of 291 microbial and metabolite values achieved a + 90% accuracy with LASSO in predicting specific pneumonia etiology. This study demonstrates that urine from patients hospitalized with pneumonia may serve as a reliable and accessible sample to evaluate biomarkers that may diagnose etiology and predict clinical outcomes.
Will colleges survive the storm of declining enrollments? A computational model.

The approaching decline in the U.S. college-age population, sometimes referred to as a "demographic storm," has been identified as an existential threat to the future of American colleges and universities. This article conducts a model-driven analysis of three plausible college-level responses to declining applications. It draws on systems theory to conceptualize a tuition-dependent college as a complex service system and to develop a system dynamics model that captures key causal interrelationships and multiple feedback effects between faculty, facilities, tuition revenue, financials, reputation, and outcomes. Simulations with the college model suggest that common solutions such as reducing faculty or adding campus facilities may improve the college's short-term financial position, but they are insufficient to ensure its long-term viability. This model contributes to the research literature on the economics of higher education, and model-driven academic management and strategy. It also provides useful implications and insights that can inform policy-makers and college leaders.
Recurrent Events Analysis With Data Collected at Informative Clinical Visits in Electronic Health Records.

Although increasingly used as a data resource for assembling cohorts, electronic health records (EHRs) pose many analytic challenges. In particular, a patient’s health status influences when and wh...
Robust Distributed Planar Formation Control for Higher Order Holonomic and Nonholonomic Agents

In this article, we present a distributed formation control strategy for agents with a variety of dynamics to achieve a desired planar formation. Our approach is based on the barycentric-coordinate-based (BCB) control, which is fully distributed, does not require interagent communication or a common sense of orientation, and can be implemented using relative position measurements acquired by agents in their local coordinate frames. This removes the need for global positioning or alignment of local coordinate frames, which are required across several existing strategies. We show how the BCB control for agents with the simplest dynamical model, i.e., the single-integrator dynamics, can be extended to agents with higher order dynamics such as quadrotors, and nonholonomic agents such as unicycles and cars. Specifically, our extension preserves the desired convergence and robustness guarantees of the BCB approach and is provably robust to saturations in the input and unmodeled linear actuator dynamics for unicycle and car agents. We further show that under our proposed BCB control design, the agents can move along a rotated and scaled control direction without affecting the convergence to the desired formation. This observation is used to design a fully distributed collision avoidance strategy, which is often not considered in the formation control literature. We demonstrate the proposed approach in simulations and further present a distributed robotic platform to test the strategy experimentally. Our experimental platform consists of off-the-shelf equipment that can be used to test and validate other multiagent algorithms. The code and implementation instructions for this platform are available online.
Adipose Tissue Segmentation in Unlabeled Abdomen MRI using Cross Modality Domain Adaptation

Abdominal fat quantification is critical since multiple vital organs are located within this region. Although computed tomography (CT) is a highly sensitive modality to segment body fat, it involves ionizing radiations which makes magnetic resonance imaging (MRI) a preferable alternative for this purpose. Additionally, the superior soft tissue contrast in MRI could lead to more accurate results. Yet, it is highly labor intensive to segment fat in MRI scans. In this study, we propose an algorithm based on deep learning technique(s) to automatically quantify fat tissue from MR images through a cross modality adaptation. Our method does not require supervised labeling of MR scans, instead, we utilize a cycle generative adversarial network (C-GAN) to construct a pipeline that transforms the existing MR scans into their equivalent synthetic CT (s-CT) images where fat segmentation is relatively easier due to the descriptive nature of HU (hounsfield unit) in CT images. The fat segmentation results for MRI scans were evaluated by expert radiologist. Qualitative evaluation of our segmentation results shows average success score of 3.80/5 and 4.54/5 for visceral and subcutaneous fat segmentation in MR images*.
Comparative genome-wide DNA methylation analysis in myocardial tissue from donors with and without Down syndrome.

Abstract Down syndrome (DS, trisomy 21) is the most common major chromosomal aneuploidy compatible with life. The additional whole or partial copy of chromosome 21 results in genome-wide imbalances that drive the complex pathobiology of DS. Differential DNA methylation in the context of trisomy 21 may contribute to the variable architecture of the DS phenotype. The goal of this study was to examine the genomic DNA methylation landscape in myocardial tissue from non-fetal individuals with DS. >480,000 unique CpG sites were interrogated in myocardial DNA samples from individuals with (n = 12) and without DS (n = 12) using DNA methylation arrays. A total of 93 highly differentially methylated CpG sites and 16 differentially methylated regions were identified in myocardial DNA from subjects with DS. There were 18 differentially methylated CpG sites in chromosome 21, including 5 highly differentially methylated sites. A CpG site in the RUNX1 locus was differentially methylated in DS myocardium, and linear regression suggests that donors’ age, gender, DS status, and RUNX1 methylation may contribute up to ~51% of the variability in RUNX1 mRNA expression. In DS myocardium, only 58% of the genes overlapping with differentially methylated regions codify for proteins with known functions and 24% are non-coding RNAs. This study provides an initial snapshot on the extent of genome-wide differential methylation in myocardial tissue from persons with DS.
Depressive symptoms in child caregivers of very old Mexican Americans

To study the effects of disability, cognitive impairment, and neuropsychiatric disturbance among older Mexican Americans on depressive symptoms in their children caregivers. This study utilizes dat...
Hundreds of new periodic signals detected in the first year of TESS with the weirddetector

We apply the ${\tt weirddetector}$, a nonparametric signal detection algorithm based on phase dispersion minimization, in a search for low duty-cycle periodic signals in the Transiting Exoplanet Survey Satellite (${\it TESS}$) photometry. Our approach, in contrast to commonly used model-based approaches specifically for flagging transits, eclipsing binaries, or other similarly periodic events, makes minimal assumptions about the shape of a periodic signal, with the goal of finding "weird" signals of unexpected or arbitrary shape. In total, 248,301 ${\it TESS}$ sources from the first-year Southern sky survey are run through the ${\tt weirddetector}$, of which we manually inspect the top 21,500 for periodicity. To minimize false-positives, we here only report on the upper decile in terms of signal score, a sample for which we obtain 97% recall of ${\it TESS}$ eclipsing binaries and 62% of the TOIs. In our sample, we find 377 previously unreported periodic signals, for which we make a first-pass assignment that 26 are ultra-short periods ($<0.3$ d), 313 are likely eclipsing binaries, 28 appear planet-like, and 10 are miscellaneous signals.
Power Analysis for Stepped Wedge Trials with Two Treatments

Abstract Stepped wedge designs (SWDs) are designs for cluster randomized trials that feature staggered, unidirectional cross-over, typically from a control to a treatment condition. Existing literature on statistical power for SWDs primarily focuses on designs with a single treatment. However, SWDs with multiple treatments are being proposed and conducted. We present a linear mixed model for a SWD with two treatments, with and without an interaction between them. We derive closed form solutions for the standard errors of the treatment effect coefficients for such models along with power calculation methods. We consider repeated cross-sectional designs as well as open and closed cohort designs and different random effect structures. Design features are examined to determine their impact on power for main treatment and interaction effects.
How do intrinsically disordered protein regions encode a driving force for liquid–liquid phase separation?

Liquid-liquid phase separation is the mechanism underlying the formation of biomolecular condensates. Disordered protein regions often drive phase separation, but the molecular interactions mediating this phenomenon are not well understood, sometimes leading to the conflation that all disordered protein regions drive phase separation. Given the critical role of phase separation in many cellular processes, and that dysfunction of phase separation can lead to debilitating diseases, it is important that we understand the interactions and sequence properties underlying phase behavior. A conceptual framework that divides IDRs into interacting and solvating regions has proven particularly useful, and analytical instantiations and coarse-grained models can test our understanding of the driving forces against experimental phase behavior. Validated simulation paradigms enable the exploration of sequence space to help our understanding of how disordered protein regions can encode phase behavior, which IDRs may mediate phase separation in cells, and which IDRs are highly soluble.
An Analysis of the Performance of Target Date Funds

This article presents a thorough evaluation of target date funds for the period 2010–2020. Target date funds have grown enormously in assets, reaching $1.4 trillion at the end of 2019, and account for approximately 24% of all assets in 401(k) accounts. We report on the results of a style analysis evaluation of TDFs that determines their effective asset allocation. It examines both the constant in the style analysis regressions and resulting Sharpe ratios, which reflect the over- or under-performance of the funds relative to a passive benchmark with the same asset allocation. Lower cost TDFs tend to match the benchmark returns, while higher cost TDFs deviate from them considerably. We examine how TDFs performed in the stock market crash between February 19 and March 23, 2020, during which five-week period broad market averages fell by about one-third. We find that the value of long-dated TDFs (those with a target date of 2045 and beyond) fell by between 30% and 35%, while the 2025 funds, designed for people roughly 60 years old, lost between 20% and 25% of their value. We find that past performance only weakly influences future expected performance. As with equity funds in general in this period, TDFs with actively managed ingredient funds, on average, trailed the performance of their cheaper passively managed counterparts. TOPICS:Pension funds, portfolio theory, risk management, performance measurement Key Findings ▪ Even near term TDFs have considerable equity exposure. For instance, 2025 TDFs lost between 20 and 25% of their value in the five weeks between February 19 and March 23, 2020. Many longer horizon TDFs did no better than pure equity funds in this period. ▪ 75% of actively managed TDFs failed to do as well as the best fitting set of reference ETFs. ▪ Past performance is only a weak predictor of future performance for TDFs. An extra 1% per year return in 2010–14 period only increases the expected return in 2015–19 by 9 basis points per year.
Health Policy in the Supreme Court and a New Conservative Majority.

This Viewpoint looks at the range of medical and public health issues that could be adversely affected by appointment of Justice Amy Coney Barrett to the US Supreme Court, including weakening or elimination of the Affordable Care Act, Medicaid work requirements that could reduce eligibility, and reduced reproductive rights and governmental public health emergency powers.
Regression calibration to correct correlated errors in outcome and exposure

Measurement error arises through a variety of mechanisms. A rich literature exists on the bias introduced by covariate measurement error and on methods of analysis to address this bias. By comparison, less attention has been given to errors in outcome assessment and nonclassical covariate measurement error. We consider an extension of the regression calibration method to settings with errors in a continuous outcome, where the errors may be correlated with prognostic covariates or with covariate measurement error. This method adjusts for the measurement error in the data and can be applied with either a validation subset, on which the true data are also observed (eg, a study audit), or a reliability subset, where a second observation of error prone measurements are available. For each case, we provide conditions under which the proposed method is identifiable and leads to consistent estimates of the regression parameter. When the second measurement on the reliability subset has no error or classical unbiased measurement error, the proposed method is consistent even when the primary outcome and exposures of interest are subject to both systematic and random error. We examine the performance of the method with simulations for a variety of measurement error scenarios and sizes of the reliability subset. We illustrate the method's application using data from the Women's Health Initiative Dietary Modification Trial.
Non-Uniform Sampling of Fixed Margin Binary Matrices

Data sets in the form of binary matrices are ubiquitous across scientific domains, and researchers are often interested in identifying and quantifying noteworthy structure. One approach is to compare the observed data to that which might be obtained under a null model. Here we consider sampling from the space of binary matrices which satisfy a set of marginal row and column sums. Whereas existing sampling methods have focused on uniform sampling from this space, we introduce modified versions of two elementwise swapping algorithms which sample according to a non-uniform probability distribution defined by a weight matrix, which gives the relative probability of a one for each entry. We demonstrate that values of zero in the weight matrix, i.e. structural zeros, are generally problematic for swapping algorithms, except when they have special monotonic structure. We explore the properties of our algorithms through simulation studies, and illustrate the potential impact of employing a non-uniform null model using a classic bird habitation dataset.
When are randomized trials unnecessary? A signal detection theory approach to approving new treatments based on non-randomized studies.

RATIONALE, AIMS AND OBJECTIVES New therapies are increasingly approved by regulatory agencies such as the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) based on testing in non-randomized clinical trials. These treatments have typically displayed "dramatic effects" (ie, effects that are considered large enough to obviate the combined effects of biases and random errors that may affect the study results). The agencies, however, have not identified how large these effects should be to avoid the need for further testing in randomized controlled trials (RCTs). We investigated the effect size that would circumvent the need for further RCTs testing by the regulatory agencies. We hypothesized that the approval of therapeutic interventions by regulators is based on heuristic decision making whose accuracy can be best characterized by the application of signal detection theory (SDT). METHODS We merged the EMA and FDA database of approvals based on non-RCT comparisons. We excluded duplicate entries between the two databases. We included a total of 134 approvals of drugs and devices based on non-RCTs. We integrated Weber-Fechner law of psychophysics and recognition heuristics within SDT to provide descriptive explanations of the decisions made by the FDA and EMA to approve new treatments based on non-randomized studies without requiring further testing in RCTs. RESULTS Our findings suggest that when the difference between novel treatments and the historical control is at least one logarithm (base 10) of magnitude, the veracity of testing in non-RCTs seems to be established. CONCLUSION Drug developers and practitioners alike can use the change in one logarithm of effect size as a benchmark to decide if further testing in RCTs should be pursued, or as a guide to interpreting the results reported in non-randomized studies. However, further research would be useful to better characterize the threshold of effect size above which testing in RCTs is not needed.
Interaction of Poly(methyl acrylate) with Carbon Nanotubes as a Function of CNT Diameter, Chirality, and Temperature

The use of carbon nanotubes (CNTs) is promising for ultrahigh-strength composite materials with tunable electrical and thermal properties. Noncovalent polymer wrapping onto CNTs has proven effectiv...
PROTEUS: Rule-Based Self-Adaptation in Photonic NoCs for Loss-Aware Co-Management of Laser Power and Performance

The performance of on-chip communication in the state-of-the-art multi-core processors that use the traditional electronic NoCs has already become severely energy-constrained. To that end, emerging photonic NoCs (PNoC) are seen as a potential solution to improve the energy-efficiency (performance per watt) of on-chip communication. However, existing PNoC designs cannot realize their full potential due to their excessive laser power consumption. Prior works that attempt to improve laser power efficiency in PNoCs do not consider all key factors that affect the laser power requirement of PNoCs. Therefore, they cannot yield the desired balance between the reduction in laser power, achieved performance and energy-efficiency in PNoCs. In this paper, we present PROTEUS framework that employs rule-based self-adaptation in PNoCs. Our approach not only reduces the laser power consumption, but also minimizes the average packet latency by opportunistically increasing the communication data rate in PNoCs, and thus, yields the desired balance between the laser power reduction, performance, and energy-efficiency in PNoCs. Our evaluation with PARSEC benchmarks shows that our PROTEUS framework can achieve up to 24.5% less laser power consumption, up to 31% less average packet latency, and up to 20% less energy-per-bit, compared to another laser power management technique from prior work.
Small Business Bankruptcy Reform in the Arab World: Two Steps Forward, One Step Back

This article assesses a series of recently adopted bankruptcy laws in the Arab world, situating them within three historical phases of global bankruptcy reform. It introduces recently released recommendations from international standard-setting organizations for best practices in the bankruptcies of small and medium enterprises (SMEs) and applies them to evaluate the key details of recent bankruptcy reforms in Saudi Arabia, the United Arab Emirates, Egypt, Morocco, Tunisia, Oman, and Bahrain. Seeking an explanation for the persistent absence of an especially crucial element of effective SME rescue policy, it recalls the Islamic Law relating to debt distress and recovery. Finally, it reveals a revolutionary new approach to this controversial topic, adopted by one Arab state to produce a bankruptcy law that is truly and exceptionally responsive to the needs of SMEs.
Heterotic String Compactification and New Vector Bundles

We propose a construction of Kahler and non-Kahler Calabi–Yau manifolds by branched double covers of twistor spaces. In this construction we use the twistor spaces of four-manifolds with self-dual conformal structures, with the examples of connected sum of n\({\mathbb{P}^{2}}\)s. We also construct K3-fibered Calabi–Yau manifolds from the branched double covers of the blow-ups of the twistor spaces. These manifolds can be used in heterotic string compactifications to four dimensions. We also construct stable and polystable vector bundles. Some classes of these vector bundles can give rise to supersymmetric grand unified models with three generations of quarks and leptons in four dimensions.
A compact orbital angular momentum spectrometer using quantum zeno interrogation

We present a scheme to measure the orbital angular momentum spectrum of light using a precisely timed optical loop and quantum non-demolition measurements. We also discuss the influence of imperfect optical components.
The Ramsey theory of the universal homogeneous triangle-free graph

The universal homogeneous triangle-free graph, constructed by Henson [A family of countable homogeneous graphs, Pacific J. Math. 38(1) (1971) 69–83] and denoted ℋ3, is the triangle-free analogue of...
Complex Far-Field Geometries Determine the Stability of Solid Tumor Growth with Chemotaxis

In this paper, we develop a sharp interface tumor growth model to study the effect of the tumor microenvironment using a complex far-field geometry that mimics a heterogeneous distribution of vasculature. Together with different nutrient uptake rates inside and outside the tumor, this introduces variability in spatial diffusion gradients. Linear stability analysis suggests that the uptake rate in the tumor microenvironment, together with chemotaxis, may induce unstable growth, especially when the nutrient gradients are large. We investigate the fully nonlinear dynamics using a spectrally accurate boundary integral method. Our nonlinear simulations reveal that vascular heterogeneity plays an important role in the development of morphological instabilities that range from fingering and chain-like morphologies to compact, plate-like shapes in two dimensions.
STAR FORMATION IN DENSE CLUSTERS

A model of core-clump accretion with equally likely stopping describes star formation in the dense parts of clusters, where models of isolated collapsing cores may not apply. Each core accretes at a constant rate onto its protostar, while the surrounding clump gas accretes as a power of protostar mass. Short accretion flows resemble Shu accretion and make low-mass stars. Long flows resemble reduced Bondi accretion and make massive stars. Accretion stops due to environmental processes of dynamical ejection, gravitational competition, and gas dispersal by stellar feedback, independent of initial core structure. The model matches the field star initial mass function (IMF) from 0.01 to more than 10 solar masses. The core accretion rate and the mean accretion duration set the peak of the IMF, independent of the local Jeans mass. Massive protostars require the longest accretion durations, up to 0.5?Myr. The maximum protostar luminosity in a cluster indicates the mass and age of its oldest protostar. The distribution of protostar luminosities matches those in active star-forming regions if protostars have a constant birthrate but not if their births are coeval. For constant birthrate, the ratio of young stellar objects to protostars indicates the star-forming age of a cluster, typically ~1?Myr. The protostar accretion luminosity is typically less than its steady spherical value by a factor of ~2, consistent with models of episodic disk accretion.
Rotating Wave Solutions to Lattice Dynamical Systems I: The Anti-continuum Limit

Rotating waves are a fascinating feature of a wide array of complex systems, particularly those arising in the study of many chemical and biological processes. With many rigorous mathematical investigations of rotating waves relying on the model exhibiting a continuous Euclidean symmetry, this work is aimed at understanding these nonlinear waves in the absence of such symmetries. Here we will consider a spatially discrete lattice dynamical system of Ginzburg–Landau type and prove the existence of rotating waves in the anti-continuum limit. This result is achieved by providing a link between the work on phase systems stemming from the study of identically coupled oscillators on finite lattices to carefully track the solutions as the size of the lattice grows. It is shown that in the infinite square lattice limit of these phase systems that a rotating wave solution exists, which can be extended to the Ginzburg–Landau system of study here. The results of this work provide a necessary first step in the investigation of rotating waves as solutions to lattice dynamical systems in an effort to understand the dynamics of such solutions outside of the idealized situation where the underlying symmetry of a differential equation can be exploited.
Vibrational Decoherence in Ion Trap Quantum Computers

The ion trap quantum computer proposed by Cirac and Zoller [Phys. Rev. Lett. 74, 4091 (1995)] is analyzed for decoherence due to vibrations of the ions. An adiabatic approximation exploiting the vast difference between the frequencies of the optical intraionic transition and the vibrational modes is used to find the decoherence time at any temperature T. The scaling of this decoherence time with the number of ions is discussed, and compared with that due to spontaneous emission.
Direct Measurements of Magnetic Twist in the Solar Corona

In the present work, we study the evolution of magnetic helicity in the solar corona. We compare the rate of change of a quantity related to the magnetic helicity in the corona to the flux of magnetic helicity through the photosphere and find that the two rates are similar. This gives observational evidence that helicity flux across the photosphere is indeed what drives helicity changes in the solar corona during emergence. For the purposes of estimating coronal helicity, we neither assume a strictly linear force-free field nor attempt to construct a nonlinear force-free field. For each coronal loop evident in extreme ultraviolet, we find a best-matching line of a linear force-free field and allow the twist parameter {alpha} to be different for each line. This method was introduced and its applicability discussed in Malanushenko et al. The object of this study is emerging and rapidly rotating AR 9004 over about 80 hr. As a proxy for coronal helicity, we use the quantity ({alpha}{sub i} L{sub i} /2) averaged over many reconstructed lines of magnetic field. We argue that it is approximately proportional to the 'flux-normalized' helicity H/{Phi}{sup 2}, where H is the helicity and {Phi} is the total enclosed magneticmore » flux of the active region. The time rate of change of such a quantity in the corona is found to be about 0.021 rad hr{sup -1}, which is comparable with the estimates for the same region obtained using other methods, which estimated the flux of normalized helicity to be about 0.016 rad hr{sup -1}.« less
Fragment-based treatment of delocalization and static correlation errors in density-functional theory.

One of the most important open challenges in modern Kohn-Sham (KS) density-functional theory (DFT) is the correct treatment of systems involving fractional electron charges and spins. Approximate exchange-correlation functionals struggle with such systems, leading to pervasive delocalization and static correlation errors. We demonstrate how these errors, which plague density-functional calculations of bond-stretching processes, can be avoided by employing the alternative framework of partition density-functional theory (PDFT) even using the local density approximation for the fragments. Our method is illustrated with explicit calculations on simple systems exhibiting delocalization and static-correlation errors, stretched H2+, H2, He2+, Li2+, and Li2. In all these cases, our method leads to greatly improved dissociation-energy curves. The effective KS potential corresponding to our self-consistent solutions displays key features around the bond midpoint; these are known to be present in the exact KS potential, but are absent from most approximate KS potentials and are essential for the correct description of electron dynamics.
Asymmetric Twin Dark Matter

We study a natural implementation of Asymmetric Dark Matter in Twin Higgs models. The mirroring of the Standard Model strong sector suggests that a twin baryon with mass around 5 GeV is a natural Dark Matter candidate once a twin baryon number asymmetry comparable to the SM asymmetry is generated. We explore twin baryon Dark Matter in two different scenarios, one with minimal content in the twin sector and one with a complete copy of the SM, including a light twin photon. The essential requirements for successful thermal history are presented, and in doing so we address some of the cosmological issues common to many Twin Higgs models. The required interactions we introduce predict signatures at direct detection experiments and at the LHC.
Dynamics of correlations in two-dimensional quantum spin models with long-range interactions: a phase-space Monte-Carlo study

Interacting quantum spin models are remarkably useful for describing different types of physical, chemical, and biological systems. Significant understanding of their equilibrium properties has been achieved to date, especially for the case of spin models with short-range couplings. However, progress toward the development of a comparable understanding in long-range interacting models, in particular out-of-equilibrium, remains limited. In a recent work, we proposed a semiclassical numerical method to study spin models, the discrete truncated Wigner approximation (DTWA), and demonstrated its capability to correctly capture the dynamics of one- and two-point correlations in one-dimensional (1D) systems. Here we go one step forward and use the DTWA method to study the dynamics of correlations in two-dimensional (2D) systems with many spins and different types of long-range couplings, in regimes where other numerical methods are generally unreliable. We compute spatial and time-dependent correlations for spin-couplings that decay with distance as a power-law and determine the velocity at which correlations propagate through the system. Sharp changes in the behavior of those velocities are found as a function of the power-law decay exponent. Our predictions are relevant for a broad range of systems including solid state materials, atom–photon systems and ultracold gases of polar molecules, trapped ions, Rydberg, and magnetic atoms. We validate the DTWA predictions for small 2D systems and 1D systems, but ultimately, in the spirt of quantum simulation, experiments will be needed to confirm our predictions for large 2D systems.
Model atmospheres for massive gas giants with thick clouds: Application to the HR 8799 planets and predictions for future detections

We have generated an extensive new suite of massive giant planet atmosphere models and used it to obtain fits to photometric data for the planets HR 8799b, c, and d. We consider a wide range of cloudy and cloud-free models. The cloudy models incorporate different geometrical and optical thicknesses, modal particle sizes, and metallicities. For each planet and set of cloud parameters, we explore grids in gravity and effective temperature, with which we determine constraints on the planet's mass and age. Our new models yield statistically significant fits to the data, and conclusively confirm that the HR 8799 planets have much thicker clouds than those required to explain data for typical L and T dwarfs. Both models with (1) physically thick forsterite clouds and a 60 {mu}m modal particle size and (2) clouds made of 1 {mu}m sized pure iron droplets and 1% supersaturation fit the data. Current data are insufficient to accurately constrain the microscopic cloud properties, such as composition and particle size. The range of best-estimated masses for HR 8799b, HR 8799c, and HR 8799d conservatively span 2-12 M{sub J} , 6-13 M{sub J} , and 3-11 M{sub J} , respectively, and imply coeval ages between {approx}10 andmore » {approx}150 Myr, consistent with previously reported stellar ages. The best-fit temperatures and gravities are slightly lower than values obtained by Currie et al. using even thicker cloud models. Finally, we use these models to predict the near-to-mid-IR colors of soon-to-be imaged planets. Our models predict that planet-mass objects follow a locus in some near-to-mid-IR color-magnitude diagrams that is clearly separable from the standard L/T dwarf locus for field brown dwarfs.« less
A see-saw model of sterile neutrino

Abstract If the smallness of the mass of the sterile neutrino is to be explained by the see-saw mechanism, the off-diagonal entries of the mass matrix needs to be protected by some symmetry not far above the electroweak scale. We implement see-saw mechanism in a gauge model based on SU(2)qL×SU(2)lL×U(1)qY×U(1)lY un-unified gauge group which breaks to SU(2)L×U(1)Y at the TeV region via a two-step symmetry breaking chain. The right handed diagonal block is tied to the highest scale up to which the un-unification symmetry holds. The sterile neutrino emerges from a quark-lepton mixed representation of the un-unified group.
On the Change in Archivability of Websites Over Time

As web technologies evolve, web archivists work to keep up so that our digital history is preserved. Recent advances in web technologies have introduced client-side executed scripts that load data without a referential identifier or that require user interaction (e.g., content loading when the page has scrolled). These advances have made automating methods for capturing web pages more difficult. Because of the evolving schemes of publishing web pages along with the progressive capability of web preservation tools, the archivability of pages on the web has varied over time. In this paper we show that the archivability of a web page can be deduced from the type of page being archived, which aligns with that page’s accessibility in respect to dynamic content. We show concrete examples of when these technologies were introduced by referencing mementos of pages that have persisted through a long evolution of available technologies. Identifying these reasons for the inability of these web pages to be archived in the past in respect to accessibility serves as a guide for ensuring that content that has longevity is published using good practice methods that make it available for preservation.
Volume bounds for generalized twisted torus links

Twisted torus knots and links are given by twisting adjacent strands of a torus link. They are geometrically simple and contain many examples of the smallest volume hyperbolic knots. Many are also Lorenz links. We study the geometry of twisted torus links and related generalizations. We de- termine upper bounds on their hyperbolic volumes that depend only on the number of strands being twisted. We exhibit a family of twisted torus knots for which this upper bound is sharp, and another family with volumes approaching infinity. Consequently, we show there exist twisted torus knots with arbitrarily large braid index and yet bounded volume.
A note on the knot Floer homology of fibered knots

We prove that the knot Floer homology of a fibered knot is nontrivial in its next-to-top Alexander grading. Immediate applications include new proofs of Krcatovich’s result that knots with L–space surgeries are prime and Hedden and Watson’s result that the rank of knot Floer homology detects the trefoil among knots in the 3–sphere. We also generalize the latter result, proving a similar theorem for nullhomologous knots in any 3–manifold. We note that our method of proof inspired Baldwin and Sivek’s recent proof that Khovanov homology detects the trefoil. As part of this work, we also introduce a numerical refinement of the Ozsvath–Szabo contact invariant. This refinement was the inspiration for Hubbard and Saltz’s annular refinement of Plamenevskaya’s transverse link invariant in Khovanov homology.