cssi/SciSciGPT-SciSciNet huggingface dataset:
UNMIX-ME: spectral and lifetime fluorescence unmixing via deep learning.

Hyperspectral fluorescence lifetime imaging allows for the simultaneous acquisition of spectrally resolved temporal fluorescence emission decays. In turn, the acquired rich multidimensional data set enables simultaneous imaging of multiple fluorescent species for a comprehensive molecular assessment of biotissues. However, to enable quantitative imaging, inherent spectral overlap between the considered fluorescent probes and potential bleed-through must be considered. Such a task is performed via either spectral or lifetime unmixing, typically independently. Herein, we present “UNMIX-ME” (unmix multiple emissions), a deep learning-based fluorescence unmixing routine, capable of quantitative fluorophore unmixing by simultaneously using both spectral and temporal signatures. UNMIX-ME was trained and validated using an in silico framework replicating the data acquisition process of a compressive hyperspectral fluorescent lifetime imaging platform (HMFLI). It was benchmarked against a conventional LSQ method for tri and quadri-exponential simulated samples. Last, UNMIX-ME’s potential was assessed for NIR FRET in vitro and in vivo preclinical applications.
Incomplete sulfate aerosol neutralization despite excess ammonia in the eastern US: a possible role of organic aerosol

Acid-base neutralization of sulfate aerosol (S(VI) ≡ H 2 SO 4 (aq) + HSO 4 - + SO 4 2- ) by ammonia (NH 3 ) has important implications for aerosol mass, hygroscopicity, and acidity. Surface network and aircraft observations across the eastern US show that sulfate aerosol is not fully neutralized even in the presence of excess ammonia, at odds with thermodynamic equilibrium models. The sulfate aerosol 15
Spirituality and religion in the workplace: History, theory, and research.

The role of spirituality and religion in the workplace (SRW) is a relatively new area of inquiry that has emerged from scholarly fields not typically associated with the study of the psychology of religion and spirituality. This article explores the underlying assumptions and history as well as the state of current theory and empirical research regarding SRW. We first describe the history of the efforts to integrate spirituality and religion into the workplace, with their foundational roots in the Protestant Work Ethic and their emergence through the Faith at Work movement. Next we review the major theoretical developments in this area that have established a domain of relevant definitions, constructs, frameworks, and models. Then we review the empirical research on spirituality in the workplace and conclude that 2 major streams have emerged that have, to date, discovered similar findings in regard to their significant impact on relevant individual and organizational outcomes. Finally, we explore particular challenges associated with integrative work and future theory building and research.
Chapter 2 – Exploration Strategies and Techniques

Publisher Summary The scientific tools that are now available and routinely used at geothermal prospects allow for better characterization of the resource before the costly phase of deep well drilling. This chapter discusses five main things that a geothermal program should accomplish. It describes the usual steps in a full exploration program. These steps are necessary to fully characterize the resource. Some of the scientific phases may be combined to save time and to create synergy among the various investigations. The conceptual model of the geothermal system depicts graphically the major subsurface features of the system, including the locations of rock units, faults, and fluid flow paths. The job of creating this map begins with the geologic survey and continues as more data comes in from the other surveys. When the geoscientific survey is completed, it is necessary to synthesize all the acquired data and to draw conclusions based on the totality of the evidence. The best way to visualize the comprehensive picture of the geothermal prospect is to construct, on a workable scale, a composite map, or synthesis map, of the site. The main purpose of the synthesis map is to identify the best targets for the first few deep wells.
The Value of Sharing Intermittent Spectrum

We examine a model of Cournot competition with congestion motivated by recent policy to allow commercial sharing of wireless spectrum that is assigned to other users such as government agencies. A ...
VADR: validation and annotation of virus sequence submissions to GenBank.

GenBank contains over 3 million viral sequences. The National Center for Biotechnology Information (NCBI) previously made available a tool for validating and annotating influenza virus sequences that is used to check submissions to GenBank. Before this project, there was no analogous tool in use for non-influenza viral sequence submissions. We developed a system called VADR (Viral Annotation DefineR) that validates and annotates viral sequences in GenBank submissions. The annotation system is based on the analysis of the input nucleotide sequence using models built from curated RefSeqs. Hidden Markov models are used to classify sequences by determining the RefSeq they are most similar to, and feature annotation from the RefSeq is mapped based on a nucleotide alignment of the full sequence to a covariance model. Predicted proteins encoded by the sequence are validated with nucleotide-to-protein alignments using BLAST. The system identifies 43 types of “alerts” that (unlike the previous BLAST-based system) provide deterministic and rigorous feedback to researchers who submit sequences with unexpected characteristics. VADR has been integrated into GenBank’s submission processing pipeline allowing for viral submissions passing all tests to be accepted and annotated automatically, without the need for any human (GenBank indexer) intervention. Unlike the previous submission-checking system, VADR is freely available (https://github.com/nawrockie/vadr) for local installation and use. VADR has been used for Norovirus submissions since May 2018 and for Dengue virus submissions since January 2019. Since March 2020, VADR has also been used to check SARS-CoV-2 sequence submissions. Other viruses with high numbers of submissions will be added incrementally. VADR improves the speed with which non-flu virus submissions to GenBank can be checked and improves the content and quality of the GenBank annotations. The availability and portability of the software allow researchers to run the GenBank checks prior to submitting their viral sequences, and thereby gain confidence that their submissions will be accepted immediately without the need to correspond with GenBank staff. Reciprocally, the adoption of VADR frees GenBank staff to spend more time on services other than checking routine viral sequence submissions.
Impact of Recipient Age in Combined Liver-Kidney Transplantation: Caution Is Needed for Patients ≥70 Years.

Elderly recipients (≥70 y) account for 2.6% of all liver transplants (LTs) in the United States and have similar outcomes as younger recipients. Although the rate of elderly recipients in combined liver-kidney transplant (CLKT) is similar, limited data are available on how elderly recipients perform after CLKT. Methods We have previously shown excellent outcomes in CLKT using delayed kidney transplant (Indiana) Approach (mean kidney cold ischemia time = 53 ± 14 h). Between 2007 and 2018, 98 CLKTs were performed using the Indiana Approach at Indiana University (IU) and the data were retrospectively analyzed. Recipients were subgrouped based on their age: 18-45 (n = 16), 46-59 (n = 34), 60-69 (n = 40), and ≥70 years (n = 8). Results Overall, more elderly patients received LT at IU (5.2%) when compared nationally (2.6%). The rate of elderly recipients in CLKT at IU was 8.2% (versus 2% Scientific Registry of Transplant Recipient). Recipient and donor characteristics were comparable between all age groups except recipient age and duration of dialysis. Patient survival at 1 and 3 years was similar among younger age groups, whereas patient survival was significantly lower in elderly recipients at 1 (60%) and 3 years (40%) (P = 0.0077). Control analyses (replicating Scientific Registry of Transplant Recipient's survival stratification: 18-45, 46-64, ≥65 y) showed similar patient survival in all age groups. Conclusions Although LT can be safely performed in elderly recipients, extreme caution is needed in CLKT due to the magnitude of operation.
An open-source Simulink-based program for simulating power systems integrated with renewable energy sources

This paper presents an open-source Simulink-based program developed for simulating power systems integrated with renewable energy sources (RESs). The generic model of a photovoltaic, wind turbine, and battery energy storage is used for the RES. The program can be used for educational and research studies. It comes with several important subjects in power systems including power system modeling and integration, linearization, modal analysis, participation factor analysis, controller selection using residue analysis, and frequency response analysis. IEEE 68-bus dynamic test system is used to verify the performance of the program. The results show the efficiency and speed of the program to simulate a large-scale modern power system.
Diode Laser Ignition Mechanism for Hybrid Propulsion Systems

A novel diode laser-based ignition technique for hybrid propulsion systems has been developed. In an effort to determine the physical ignition mechanism, a test series was conducted in an optically...
Calibrating Structured Output Predictors for Natural Language Processing.

We address the problem of calibrating prediction confidence for output entities of interest in natural language processing (NLP) applications. It is important that NLP applications such as named entity recognition and question answering produce calibrated confidence scores for their predictions, especially if the applications are to be deployed in a safety-critical domain such as healthcare. However the output space of such structured prediction models are often too large to directly adapt binary or multi-class calibration methods. In this study, we propose a general calibration scheme for output entities of interest in neural network based structured prediction models. Our proposed method can be used with any binary class calibration scheme and a neural network model. Additionally, we show that our calibration method can also be used as an uncertainty-aware, entity-specific decoding step to improve the performance of the underlying model at no additional training cost or data requirements. We show that our method outperforms current calibration techniques for Named Entity Recognition, Part-of-speech tagging and Question Answering systems. We also observe an improvement in model performance from our decoding step across several tasks and benchmark datasets. Our method improves the calibration and model performance on out-of-domain test scenarios as well.
Embedding Graphs into Embedded Graphs

A (possibly degenerate) drawing of a graph G in the plane is approximable by an embedding if it can be turned into an embedding by an arbitrarily small perturbation. We show that testing whether a piece-wise linear drawing of a planar graph G in the plane is approximable by an embedding can be carried out in polynomial time, if a desired embedding of G belongs to a fixed isotopy class. In other words, we show that c-planarity with embedded pipes is tractable for graphs with prescribed combinatorial embedding. To the best of our knowledge, an analogous result was previously known essentially only when G is a cycle.
Extent, Heritability, and Functional Relevance of Single Cell Expression Variability in Highly Homogeneous Populations of Human Cells

Because of recent technological developments, single-cell assays such as single-cell RNA sequencing (scRNA-seq) have become much more widely available and have achieved unprecedented resolution in revealing cell heterogeneity. The extent of intrinsic cell-to-cell variability in gene expression, or single cell expression variability (scEV), has thus been increasingly appreciated. However, it remains unclear whether this variability is functionally important and, if so, what its implications are for multi-cellular organisms. We therefore analyzed multiple scRNA-seq data sets from lymphoblastoid cell lines (LCLs), lung airway epithelial cells (LAECs), and dermal fibroblasts (DFs). For each of the three cell types, we estimated scEV in homogeneous populations of cells; we identified 465, 466, and 291 highly variable genes (HVGs), respectively. These HVGs were enriched with specific functions precisely relevant to the cell types, from which the scRNA-seq data used to identify HVGs were generated — e.g., HVGs identified in lymphoblastoid cells were enriched in cytokine signaling pathways, LAECs collagen formation, and DFs keratinization. HVGs were deeply embedded in gene regulatory networks specific to corresponding cell types. We also found that scEV is a heritable trait, partially determined by cell donors’ genetic makeups. Furthermore, across genes, especially immune genes, levels of scEV and between-individual variability in gene expression were positively correlated, suggesting a potential link between the two variabilities measured at different organizational levels. Taken together, our results support the “variation is function” hypothesis, which postulates that scEV is required for higher-level system function. Thus, we argue that quantifying and characterizing scEV in relevant cell types may deepen our understating of normal as well as pathological cellular processes.
Non-ionic CT contrast solutions rapidly alter bovine cartilage and meniscus mechanics.

Objective To evaluate effects of a common CT contrast agent (iohexol) on the mechanical behaviors of cartilage and meniscus. Methods Indentation responses of juvenile bovine cartilage and meniscus were monitored following exposure to undiluted contrast agent (100% CA), 50% CA/water, 50% CA/Phosphate Buffered Saline (PBS) or PBS alone, and during re-equilibration in PBS. The normalized peak force (Fpk¯), effective osmotic strain (eosm), and normalized effective contact modulus (Ec¯) were calculated for every cycle, with time constants determined for both exposure and recovery via mono- or biexponential fits to Fpk¯. Results All cartilage CA groups exhibited long-term increases in Fpk¯ following exposure, although the hyperosmolal 100% CA and 50% CA/PBS groups showed an initial transient decrease. Meniscus presented opposing trends, with decreasing Fpk¯ for all CA groups. Re-equilibration in PBS for 1hr after exposure to 100% CA produced recovery to baseline Fpk¯ in cartilage but not in meniscus, and extended tests indicated that meniscus required ∼2.5 hours to recover halfway. Ec¯ increased with CA exposure time for cartilage but decreased for meniscus, suggesting an increased effective stiffness for cartilage and decreased stiffness for meniscus. Long-term changes to eosm in both tissues were consistent with changes in Ec¯. Conclusion Exposure to iohexol solutions affected joint tissues differentially, with increased cartilage stiffness, likely relating to competing hyperosmotic and hypotonic interactions with tissue fixed charges, and decreased meniscus stiffness, likely dominated by hyperosmolarity. These altered tissue mechanics could allow non-physiological deformation during ambulatory weight-bearing, resulting in an increased risk of tissue or cell damage.
Predicting Choice with Set-Dependent Aggregation

Providing users with alternatives to choose from is an essential component in many online platforms, making the accurate prediction of choice vital to their success. A renewed interest in learning choice models has led to significant progress in modeling power, but most current methods are either limited in the types of choice behavior they capture, cannot be applied to large-scale data, or both. Here we propose a learning framework for predicting choice that is accurate, versatile, theoretically grounded, and scales well. Our key modeling point is that to account for how humans choose, predictive models must capture certain set-related invariances. Building on recent results in economics, we derive a class of models that can express any behavioral choice pattern, enjoy favorable sample complexity guarantees, and can be efficiently trained end-to-end. Experiments on three large choice datasets demonstrate the utility of our approach.
Association of Digestive Symptoms and Hospitalization in Patients With SARS-CoV-2 Infection.

Introduction High rates of concurrent gastrointestinal manifestations have been noted in patients with corona virus disease 2019 (COVID-19); however, the association between these digestive manifestations and need for hospitalization has not been established. Methods This is a retrospective review of consecutive patients diagnosed with COVID-19. A total of 207 patients were identified; 34.5% of patients noted concurrent gastrointestinal symptoms, with 90% of gastrointestinal symptoms being mild. Results In a multivariate regression model controlled for demographics and disease severity, an increased risk of hospitalization was noted in patients with any digestive symptom (adjusted odds ratio 4.84, 95% confidence interval: 1.68-13.94). Discussion The presence of digestive symptoms in COVID-19 is associated with a need for hospitalization.
Rotary-wing aeroelasticity: Current status and future trends

Concise Perspective and Previous Surveys W HEN reviewing research in rotary-wing aeroelasticity (RWA), it is important to mention a few historical facts. The Wright brothers flew in 1903, and Sikorsky built and started flying the first operational helicopter, the R-4 or (VS-316), in 1942. The R-4 was a three-bladed helicopter with a rotor diameter of 11.6 m and was powered by a 185-hp engine. Thus, there is an initial gap of approximately four decades between fixed-wing and rotary-wing technologies. Therefore, it is not surprising that certain rotary-wing problems, particularly those pertaining to unsteady aerodynamics, are still not well understood. The situation is further compounded by the complexity of the vehicle when compared to fixed-wing aircraft. The field of RWA has been the most active area in aeroelasticity during the last three decades. This vigorous research activity has generated a considerable number of survey papers as well as several books that have been published on this topic. These review papers, when considered in chronological order, provide a historical perspective on this evolving field.1−13 One of the first significant reviews of rotary-wing dynamic and aeroelastic problems was provided by Loewy,11 where a wide range of dynamic problems was reviewed in considerable detail. A more limited survey emphasizing the role of unsteady aerodynamics and vibration problems in forward flight was presented by Dat.2 Two comprehensive reviews of rotary-wing aeroelasticity were presented by Friedmann.3,4 In Ref. 3, a detailed chronological discussion of the flap-lag and coupled flap-lag-torsion problems in hover and forward flight was presented, emphasizing the inherently nonlinear nature of the hingeless-blade aeroelastic stability problem. The nonlinearities considered were geometrical nonlinearities because of moderate blade deflections. In Ref. 4, the role of unsteady aerodynamics, including dynamic stall, was examined, together with the treatment of nonlinear aeroelastic problems in forward flight. Finite element solutions to RWA problems were also considered, together with the treatment of coupled rotor-fuselage problems. Another detailed survey by Ormiston12 discussed the aeroelasticity of hingeless and bearingless rotors, in hover, from an experimental and theoretical point of view.
Langevin Monte Carlo without smoothness

Langevin Monte Carlo (LMC) is an iterative algorithm used to generate samples from a distribution that is known only up to a normalizing constant. The nonasymptotic dependence of its mixing time on the dimension and target accuracy is understood mainly in the setting of smooth (gradient-Lipschitz) log-densities, a serious limitation for applications in machine learning. In this paper, we remove this limitation, providing polynomial-time convergence guarantees for a variant of LMC in the setting of nonsmooth log-concave distributions. At a high level, our results follow by leveraging the implicit smoothing of the log-density that comes from a small Gaussian perturbation that we add to the iterates of the algorithm and controlling the bias and variance that are induced by this perturbation.
The value of summary statistics for anomaly detection in temporally evolving networks: A performance evaluation study

Network data has emerged as an active research area in statistics. Much of the focus of ongoing research has been on static networks that represent a single snapshot or aggregated historical data unchanging over time. However, most networks result from temporally-evolving systems that exhibit intrinsic dynamic behavior. Monitoring such temporally-varying networks to detect anomalous changes has applications in both social and physical sciences. In this work, we perform an evaluation study of summary statistics for anomaly detection in temporally-evolving networks by incorporating principles from statistical process monitoring. In contrast to previous studies, we deliberately incorporate temporal auto-correlation in our study. Other considerations in our comprehensive assessment include types and duration of anomaly, model type, and sparsity in temporally-evolving networks. We conclude that summary statistics can be valuable tools for network monitoring and often perform better than more complicated statistics.
Combined Selective Plane Illumination Microscopy and FRAP Maps Intranuclear Diffusion of NLS-GFP.

Abstract Since its initial development in 1976, fluorescence recovery after photobleaching (FRAP) has been one of the most popular tools for studying diffusion and protein dynamics in living cells. Its popularity is derived from the widespread availability of confocal microscopes and the relative ease of the experiment and analysis. FRAP, however, is limited in its ability to resolve spatial heterogeneity. Here, we combine selective plane illumination microscopy (SPIM) and FRAP to create SPIM-FRAP, wherein we use a sheet of light to bleach a two-dimensional (2D) plane and subsequently image the recovery of the same image plane. This provides simultaneous quantification of diffusion or protein recovery for every pixel in a given 2D slice, thus moving FRAP measurements beyond these previous limitations. We demonstrate this technique by mapping both intranuclear diffusion of NLS-GFP and recovery of 53BP1-mCherry, a marker for DNA damage, in live MDA-MB-231 cells. SPIM-FRAP proves to be an order of magnitude faster than fluorescence-correlation-spectroscopy-based techniques for such measurements. We observe large length-scale (>∼500 nm) heterogeneity in the recovery times of NLS-GFP, which is validated against simulated data sets. 2D maps of NLS-GFP recovery times showed no pixel-by-pixel correlation with histone density, although slower diffusion was observed in nucleoli. Additionally, recovery of 53BP1-mCherry was observed to be slowed at sites of DNA damage. We finally developed a diffusion simulation for our SPIM-FRAP experiments to compare across techniques. Our measured diffusion coefficients are on the order of previously reported results, thus validating the quantitative accuracy of SPIM-FRAP relative to well-established methods. With the recent rise of accessibility of SPIM systems, SPIM-FRAP is set to provide a straightforward means of quantifying the spatial distribution of protein recovery or diffusion in living cells.
Correlation of thermomagnetic behavior of carbonaceous chondrites with chemical petrographic classification

Some degree of correlation was noted between the thermomagnetic behavior of the carbonaceous chondrites and the chemical-petrographic classification scheme of Van Schmus and Hayes.
Controlling Singlet Fission with Coordination Chemistry-Induced Assembly of Dipyridyl Pyrrole Bipentacenes.

Singlet fission has the potential to surpass current efficiency limits in next-generation photovoltaics and to find use in quantum information science. Despite the demonstration of singlet fission in various materials, there is still a great need for fundamental design principles that allow for tuning of photophysical parameters, including the rate of fission and triplet lifetimes. Here we describe the synthesis and photophysical characterization of a novel bipentacene dipyridyl pyrrole (HDPP-Pent) and its Li- and K-coordinated derivatives. HDPP-Pent undergoes singlet fission at roughly 50% efficiency (τSF = 730 ps), whereas coordination in the Li complex induces significant structural changes to generate a dimer, resulting in a 5-fold rate increase (τSF = 140 ps) and near fully efficient singlet fission with virtually no sacrifice in triplet lifetime. We thus illustrate novel design principles to produce favorable singlet fission properties, wherein through-space control can be achieved via coordination chemistry-induced multi-pentacene assembly.
A Deterministic Theory of Low Rank Matrix Completion

The problem of completing a large low rank matrix using a subset of revealed entries has received much attention in the last ten years. The main result of this paper gives a necessary and sufficient condition, stated in the language of graph limit theory, for a sequence of matrix completion problems with arbitrary missing patterns to be asymptotically solvable. It is then shown that a small modification of the Candes–Recht nuclear norm minimization algorithm provides the required asymptotic solution whenever the sequence of problems is asymptotically solvable. The theory is fully deterministic, with no assumption of randomness. A number of open questions are listed.
Varieties of planes on intersections of three quadrics

We study the geometry of spaces of planes on smooth complete intersections of three quadrics, with a view toward rationality questions.
Dynamics for Encircling an Exceptional Point in a Nonlinear Non-Hermitian System

We study the dynamics of a non-Hermitian system with gain saturation non-linearity. We find the chiral state transfer behavior is recovered, and new phenomenon such as bistability and high gain threshold lasing emerges.
A robust algorithm to calculate parent β grain shapes and orientations from α phase electron backscatter diffraction data in α/β-titanium alloys

Abstract This paper presents a new model and open-source algorithm for reconstructing prior β phase orientation and grain shapes from measured α-phase electron backscatter diffraction data in α/β titanium alloys. It is based on the image segmentation model of Mumford and Shah, which includes a regularization term that helps create smooth boundaries and overcomes shortcomings of prior reconstruction techniques. Additionally, the new algorithm is resilient to noise. Our algorithm’s effectiveness is demonstrated on simulated and real world data.
On deformations of Gorenstein-projective modules over Nakayama and triangular matrix algebras

Abstract Let k be a fixed field of arbitrary characteristic and let Λ be a basic connected Nakayama k -algebra without simple projective modules. In this article we prove that if V is an indecomposable finitely generated Gorenstein-projective left Λ-module, then the versal deformation ring R ( Λ , V ) (in the sense of F. M. Bleher and the author) is universal and stable after taking syzygies. We also prove the following result. Let Σ = ( Λ B 0 Γ ) be a triangular matrix finite dimensional Gorenstein k -algebra with B projective as a left Λ-module and with Γ of finite global dimension. If ( V W ) f is a finitely generated Gorenstein-projective left Σ-module with End _ Σ ( ( V W ) f ) = k , then V is also a finitely generated Gorenstein-projective left Λ-module with End _ Λ ( V ) = k , and the versal deformation rings R ( Σ , ( V W ) f ) and R ( Λ , V ) are both universal and isomorphic.
Effect of an Aerosol Box on Intubation in Simulated Emergency Department Airways: A Randomized Crossover Study.

Author(s): Turner, Joseph S.; Falvo, Lauren E.; Ahmed, Rami A.; Ellender, Timothy J.; Corson-Knowles, Dan; Bona, Anna M.; Sarmiento, Elisa J.; Cooper, Dylan D. | Abstract: Introduction: The use of transparent plastic aerosol boxes as protective barriers during endotracheal intubation has been advocated during the severe acute respiratory syndrome coronavirus 2 pandemic. There is evidence of worldwide distribution of such devices, but some experts have warned of possible negative impacts of their use. The objective of this study was to measure the effect of an aerosol box on intubation performance across a variety of simulated difficult airway scenarios in the emergency department.Methods: This was a randomized, crossover design study. Participants were randomized to intubate one of five airway scenarios with and without an aerosol box in place, with randomization of intubation sequence. The primary outcome was time to intubation. Secondary outcomes included number of intubation attempts, Cormack-Lehane view, percent of glottic opening, and resident physician perception of intubation difficulty.Results: Forty-eight residents performed 96 intubations. Time to intubation was significantly longer with box use than without (mean 17 seconds [range 6-68 seconds] vs mean 10 seconds [range 5-40 seconds], p l0.001). Participants perceived intubation as being significantly more difficult with the aerosol box. There were no significant differences in the number of attempts or quality of view obtained.Conclusion: Use of an aerosol box during difficult endotracheal intubation increases the time to intubation and perceived difficulty across a range of simulated ED patients.
Learning Latent Factors From Diversified Projections and Its Applications to Over-Estimated and Weak Factors

Estimations and applications of factor models often rely on the crucial condition that the number of latent factors is consistently estimated, which in turn also requires that factors be relatively...
Efficient Multi-class Fetal Brain Segmentation in High Resolution MRI Reconstructions with Noisy Labels

Segmentation of the developing fetal brain is an important step in quantitative analyses. However, manual segmentation is a very time-consuming task which is prone to error and must be completed by highly specialized individuals. Super-resolution reconstruction of fetal MRI has become standard for processing such data as it improves image quality and resolution. However, different pipelines result in slightly different outputs, further complicating the generalization of segmentation methods aiming to segment super-resolution data. Therefore, we propose using transfer learning with noisy multi-class labels to automatically segment high resolution fetal brain MRIs using a single set of segmentations created with one reconstruction method and tested for generalizability across other reconstruction methods. Our results show that the network can automatically segment fetal brain reconstructions into 7 different tissue types, regardless of reconstruction method used. Transfer learning offers some advantages when compared to training without pre-initialized weights, but the network trained on clean labels had more accurate segmentations overall. No additional manual segmentations were required. Therefore, the proposed network has the potential to eliminate the need for manual segmentations needed in quantitative analyses of the fetal brain independent of reconstruction method used, offering an unbiased way to quantify normal and pathological neurodevelopment.
Bayesian parameter estimation for effective field theories

We present procedures based on Bayesian statistics for estimating, from data, the parameters of effective field theories (EFTs). The extraction of low-energy constants (LECs) is guided by theoretical expectations in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools is developed that analyzes the fit and ensures that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems, including the extraction of LECs for the nucleon-mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
Nature of segregation of reactants in diffusion controlled A + B reactions: role of mobility in forming compact clusters

We investigate the A + B = 0 bimolecular chemical reaction taking place in low-dimensional spaces when the mobilities of the two reacting species are not equal. While the case of different reactant mobilities has been previously reported as not affecting the scaling of the reactant densities with time, but only the pre-exponential factor, the mechanism for this had not been explained before. By using Monte-Carlo simulations, we show that the nature of segregation is very different when compared to the normal case of equal reactant mobilities. The clusters of the mobile species are statistically homogeneous and randomly distributed in space, but the clusters of the less mobile species are much more compact and restricted in space. Due to the asymmetric mobilities, the initial symmetric random density fluctuations in time turn into asymmetric density fluctuations. We explain this trend by calculating the correlation functions for the positions of particles for the several different cases.
The Starspots of HAT-P-11: Evidence for a Solar-like Dynamo

We measure the starspot radii and latitude distribution on the K4 dwarf HAT-P-11 from Kepler short-cadence photometry. We take advantage of starspot occultations by its highly-misaligned planet to compare the spot size and latitude distributions to those of sunspots. We find that the spots of HAT-P-11 are distributed in latitude much like sunspots near solar activity maximum, with mean spot latitude of $16 \pm 1$ degrees. The majority of starspots of HAT-P-11 have physical sizes that closely resemble the sizes of sunspots at solar maximum. We estimate the mean spotted area coverage on HAT-P-11 is $3^{+6}_{-1}\%$, roughly two orders of magnitude greater than the typical solar spotted area.
Regulatory inhibition of biological tissue mineralization by calcium phosphate through post-nucleation shielding by fetuin-A

In vertebrates, insufficient availability of calcium and inorganic phosphate ions in extracellular fluids leads to loss of bone density and neuronal hyper-excitability. To counteract this problem, calcium ions are usually present at high concentrations throughout bodily fluids—at concentrations exceeding the saturation point. This condition leads to the opposite situation where unwanted mineral sedimentation may occur. Remarkably, ectopic or out-of-place sedimentation into soft tissues is rare, in spite of the thermodynamic driving factors. This fortunate fact is due to the presence of auto-regulatory proteins that are found in abundance in bodily fluids. Yet, many important inflammatory disorders such as atherosclerosis and osteoarthritis are associated with this undesired calcification. Hence, it is important to gain an understanding of the regulatory process and the conditions under which it can go awry. In this manuscript, we extend mean-field continuum classical nucleationtheory of the growth of clusters to encompass surface shielding. We use this formulation to study the regulation of sedimentation of calcium phosphate salts in biological tissues through the mechanism of post-nuclear shielding of nascent mineral particles by binding proteins. We develop a mathematical description of this phenomenon using a countable system of hyperbolic partial differential equations. A critical concentration of regulatory protein is identified as a function of the physical parameters that describe the system.
Statistical mechanics of low-rank tensor decomposition*

Often, large, high dimensional datasets collected across multiple modalities can be organized as a higher order tensor. Low-rank tensor decomposition then arises as a powerful and widely used tool to discover simple low dimensional structures underlying such data. However, we currently lack a theoretical understanding of the algorithmic behavior of low-rank tensor decompositions. We derive Bayesian approximate message passing (AMP) algorithms for recovering arbitrarily shaped low-rank tensors buried within noise, and we employ dynamic mean field theory to precisely characterize their performance. Our theory reveals the existence of phase transitions between easy, hard and impossible inference regimes, and displays an excellent match with simulations. Moreover, it reveals several qualitative surprises compared to the behavior of symmetric, cubic tensor decomposition. Finally, we compare our AMP algorithm to the most commonly used algorithm, alternating least squares (ALS), and demonstrate that AMP significantly outperforms ALS in the presence of noise.
Support varieties for rational representations

We introduce support varieties for rational representations of a linear algebraic group $G$ of exponential type over an algebraically closed field $k$ of characteristic $p > 0$. These varieties are closed subspaces of the space $V(G)$ of all 1-parameter subgroups of $G$. The functor $M \mapsto V(G)_M$ satisfies many of the standard properties of support varieties satisfied by finite groups and other finite group schemes. Furthermore, there is a close relationship between $V(G)_M$ and the family of support varieties $V_r(G)_M$ obtained by restricting the $G$ action to Frobenius kernels $G_{(r)} \subset G$. These support varieties seem particularly appropriate for the investigation of infinite dimensional rational $G$-modules.
The Discrepancy in G-Band Contrast: Where is the Quiet Sun?

We compare the rms contrast in observed speckle reconstructed G-band images with synthetic filtergrams computed from two magnetohydrodynamic simulation snapshots. The observations consist of 103 bursts of 80 frames each, taken at the Dunn Solar Telescope (DST), sampled at twice the diffraction limit of the telescope. The speckle reconstructions account for the actions of the adaptive optics (AO) system at the DST in order to supply reliable photometry. We find a considerable discrepancy between the observed rms contrast of 14.1% for the best reconstructed images and the synthetic rms contrast of 21.5% in a simulation snapshot thought to be representative of the quiet Sun. The areas of features in the synthetic filtergrams that have positive or negative contrast beyond the minimum and maximum values in the reconstructed images have spatial scales that should be resolved. This leads us to conclude that there are fundamental differences in the rms G-band contrast between observed and computed filtergrams. On the basis of the substantially reduced granular contrast of 16.3% in the synthetic plage filtergram, we speculate that the quiet Sun may contain more weak magnetic field than previously thought.
On purely loxodromic actions

We construct an example of an isometric action of F(a, b) on a $$\delta $$ -hyperbolic graph Y, such that this action is acylindrical, purely loxodromic, has asymptotic translation lengths of nontrivial elements of F(a, b) separated away from 0, has quasiconvex orbits in Y, but such that the orbit map $$F(a,b)\rightarrow Y$$ is not a quasi-isometric embedding.
Whittaker Coefficients of Metaplectic Eisenstein Series

We study Whittaker coefficients for maximal parabolic Eisenstein series on metaplectic covers of split reductive groups. By the theory of Eisenstein series these coefficients have meromorphic continuation and functional equation. However they are not Eulerian and the standard methods to compute them in the reductive case do not apply to covers. For “cominuscule” maximal parabolics, we give an explicit description of the coefficients as Dirichlet series whose arithmetic content is expressed in an exponential sum. The exponential sum is then shown to satisfy a twisted multiplicativity, reducing its determination to prime power contributions. These, in turn, are connected to Lusztig data for canonical bases on the dual group using a result of Kamnitzer. The exponential sum at prime powers is shown to simplify for generic Lusztig data. At the remaining degenerate cases, the exponential sum seems best expressed in terms of Gauss sums depending on string data for canonical bases, as shown in a detailed example in GL 4. Thus we demonstrate that the arithmetic part of metaplectic Whittaker coefficients is intimately connected to the relations between these two expressions for canonical bases.
A Search for Moderate-redshift Survivors from the Population of Luminous Compact Passive Galaxies at High Redshift

From a search of a ∼2400 deg{sup 2} region covered by both the Sloan Digital Sky Survey and UKIRT Infrared Deep Sky Survey databases, we have attempted to identify galaxies at z ∼ 0.5 that are consistent with their being essentially unmodified examples of the luminous passive compact galaxies found at z ∼ 2.5. After isolating good candidates via deeper imaging, we further refine the sample with Keck moderate-resolution spectroscopy and laser guide star adaptive-optics imaging. For four of the five galaxies that so far remain after passing through this sieve, we analyze plausible star-formation histories based on our spectra in order to identify galaxies that may have survived with little modification from the population formed at high redshift. We find two galaxies that are consistent with having formed ≳ 95% of their mass at z > 5. We attempt to estimate masses both from our stellar population determinations and from velocity dispersions. Given the high frequency of small axial ratios, both in our small sample and among samples found at high redshifts, we tentatively suggest that some of the more extreme examples of passive compact galaxies may have prolate morphologies.
Conformal Laplace superintegrable systems in 2D: polynomial invariant subspaces

2nd-order conformal superintegrable systems in n dimensions are Laplace equations on a manifold with an added scalar potential and independent 2nd order conformal symmetry operators. They encode all the information about Helmholtz (eigenvalue) superintegrable systems in an efficient manner: there is a 1-1 correspondence between Laplace superintegrable systems and Stackel equivalence classes of Helmholtz superintegrable systems. In this paper we focus on superintegrable systems in two-dimensions, n = 2, where there are 44 Helmholtz systems, corresponding to 12 Laplace systems. For each Laplace equation we determine the possible two-variate polynomial subspaces that are invariant under the action of the Laplace operator, thus leading to families of polynomial eigenfunctions. We also study the behavior of the polynomial invariant subspaces under a Stackel transform. The principal new results are the details of the polynomial variables and the conditions on parameters of the potential corresponding to polynomial solutions. The hidden gl 3-algebraic structure is exhibited for the exact and quasi-exact systems. For physically meaningful solutions, the orthogonality properties and normalizability of the polynomials are presented as well. Finally, for all Helmholtz superintegrable solvable systems we give a unified construction of one-dimensional (1D) and two-dimensional (2D) quasi-exactly solvable potentials possessing polynomial solutions, and a construction of new 2D PT-symmetric potentials is established.
Waveguide-integrated single-crystalline GaP resonators on diamond

Large-scale entanglement of nitrogen-vacancy (NV) centers in diamond will require integration of NV centers with optical networks. Toward this goal, we present the fabrication of single-crystalline gallium phosphide (GaP) resonator-waveguide coupled structures on diamond. We demonstrate coupling between 1 μm diameter GaP disk resonators and waveguides with a loaded Q factor of 3,800, and evaluate their potential for efficient photon collection if integrated with single photon emitters. This work opens a path toward scalable NV entanglement in the hybrid GaP/diamond platform, with the potential to integrate on-chip photon collection, switching, and detection for applications in quantum information processing.
Binary Capture Rates for Massive Protostars

The high multiplicity of massive stars in dense, young clusters is established early in their evolution. The mechanism behind this remains unresolved. Recent results suggest that massive protostars may capture companions through disk interactions with much higher efficiency than their solar mass counterparts. However, this conclusion is based on analytic determinations of capture rates and estimates of the robustness of the resulting binaries. We present the results of coupled n-body and SPH simulations of star-disk encounters to further test the idea that disk-captured binaries contribute to the observed multiplicity of massive stars.
Silicate Emission in the TW Hydrae Association

The TW Hydrae association is the nearest young stellar association. Among its members are HD 98800, HR 4796A, and TW Hydrae itself, the nearest known classical T Tauri star. We have observed these three stars spectroscopically between 3 and 13 μm. In TW Hya, the spectrum shows a silicate emission feature that is similar to many other young stars' with protostellar disks. The 11.2 μm feature indicative of significant amounts of crystalline olivine is not as strong as in some young stars and solar system comets. In HR 4796A, the thermal emission in the silicate feature is very weak, suggesting little in the way of (small silicate) grains near the star. The silicate band of HD 98800 (observed by us, but also reported by Sylvester & Skinner) is intermediate in strength between TW Hya and HR 4796A.
Thickness Estimation of Epitaxial Graphene on SiC Using Attenuation of Substrate Raman Intensity

A simple, noninvasive method using Raman spectroscopy for the estimation of the thickness of graphene layers grown epitaxially on silicon carbide (SiC) is presented, enabling simultaneous determination of thickness, grain size, and disorder using the spectra. The attenuation of the substrate Raman signal due to the graphene overlayer is found to be dependent on the graphene film thickness deduced from x-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) of the surfaces. We explain this dependence using an absorbing overlayer model. This method can be used for mapping graphene thickness over a region and is capable of estimating thickness of multilayer graphene films beyond that possible by XPS and Auger electron spectroscopy (AES).
ACCELERATION OF ENERGETIC PARTICLES BY LARGE-SCALE COMPRESSIBLE MAGNETOHYDRODYNAMIC TURBULENCE

Fast particles diffusing along magnetic field lines in a turbulent plasma can diffuse through and then return to the same eddy many times before the eddy is randomized in the turbulent flow. This leads to an enhancement of particle acceleration by large-scale compressible turbulence relative to previous estimates in which isotropic particle diffusion is assumed.
Sets of constant distance from a Jordan curve

We study the -level sets of the signed distance function to a planar Jordan curve , and ask what properties of ensure that the -level sets are Jordan curves, or uniform quasicircles, or uniform chord-arc curves for all suciently small . Sucient conditions are given in term of a scaled invariant parameter for measuring the local deviation of subarcs from their chords. The chordal conditions given are sharp.
TeV Scale Models of Neutrino Masses and Their Phenomenology

We review various TeV scale models for neutrino masses utilizing different types of seesaw mechanisms, higher dimensional operators, expanded gauge symmetries, or low scale extra dimensions. In addition, we discuss the implications of these models for the collider experiments and low energy lepton flavor violation searches.