cssi/SciSciGPT-SciSciNet huggingface dataset:
Polarization-Controlled Directional Multiphoton Photoemission from Hot Spots on Single Au Nanoshells

Directional photoemission from single Au nanoshells is demonstrated in the low-intensity, multiphoton regime. This directionality is shown to be due to the plasmonic excitation of highly photoemissive, nanometer scale surface regions, which are characterized by correlated momentum mapping, scanning electron microscopy (SEM), and laser polarization-dependence studies. Furthermore, the photoelectron flux from a single nanoshell can be systematically rotated by over 90° in momentum space simply by polarization-controlled coupling to different hot spots. Photoelectron distributions are directly characterized in momentum space via velocity map imaging (VMI) of the two-dimensional transverse (px, py) momentum components for single nanoshells. For the majority of nanoshells studied, the photoemission is directionally orthogonal to the laser polarization, which implicates nanoscale crevice-shaped “hot spots” clearly observed in the correlated SEM/VMI studies, with the near-field plasmonic nature of these crevices...
Chromatin organization by an interplay of loop extrusion and compartmental segregation

Mammalian chromatin is spatially organized at many scales showing two prominent features in interphase: (i) alternating regions (1-10 Mb) of active and inactive chromatin that spatially segregate into different compartments, and (ii) domains (<1 Mb), that is, regions that preferentially interact internally [topologically associating domains (TADs)] and are central to gene regulation. There is growing evidence that TADs are formed by active extrusion of chromatin loops by cohesin, whereas compartmentalization is established according to local chromatin states. Here, we use polymer simulations to examine how loop extrusion and compartmental segregation work collectively and potentially interfere in shaping global chromosome organization. A model with differential attraction between euchromatin and heterochromatin leads to phase separation and reproduces compartmentalization as observed in Hi-C. Loop extrusion, essential for TAD formation, in turn, interferes with compartmentalization. Our integrated model faithfully reproduces Hi-C data from puzzling experimental observations where altering loop extrusion also led to changes in compartmentalization. Specifically, depletion of chromatin-associated cohesin reduced TADs and revealed finer compartments, while increased processivity of cohesin strengthened large TADs and reduced compartmentalization; and depletion of the TAD boundary protein CTCF weakened TADs while leaving compartments unaffected. We reveal that these experimental perturbations are special cases of a general polymer phenomenon of active mixing by loop extrusion. Our results suggest that chromatin organization on the megabase scale emerges from competition of nonequilibrium active loop extrusion and epigenetically defined compartment structure.
Buoyant Motion of a Turbulent Thermal

AbstractBy introducing an equivalence between magnetostatics and the equations governing buoyant motion, we derive analytical expressions for the acceleration of isolated density anomalies (thermal...
Learning to Forecast and Refine Residual Motion for Image-to-Video Generation

We consider the problem of image-to-video translation, where an input image is translated into an output video containing motions of a single object. Recent methods for such problems typically train transformation networks to generate future frames conditioned on the structure sequence. Parallel work has shown that short high-quality motions can be generated by spatiotemporal generative networks that leverage temporal knowledge from the training data. We combine the benefits of both approaches and propose a two-stage generation framework where videos are generated from structures and then refined by temporal signals. To model motions more efficiently, we train networks to learn residual motion between the current and future frames, which avoids learning motion-irrelevant details. We conduct extensive experiments on two image-to-video translation tasks: facial expression retargeting and human pose forecasting. Superior results over the state-of-the-art methods on both tasks demonstrate the effectiveness of our approach.
Should We Measure Adenoma Detection Rate for Gastroenterology Fellows in Training

Background Adenoma detection rate (ADR) is a proven quality metric for colonoscopy. The value of ADR for the evaluation of gastroenterology fellows is not well established. The aim of this study is to calculate and evaluate the utility of ADR as a measure of competency for gastroenterology fellows. Methods Colonoscopies for the purposes of screening and surveillance, on which gastroenterology fellows participated at the Richard L. Roudebush VAMC (one of the primary training sites at Indiana University), during a 9-month period, were included. ADR, cecal intubation rate, and indirect withdrawal time were measured. These metrics were compared between the levels of training. Results A total of 591 screening and surveillance colonoscopies were performed by 14 fellows. This included six, four and four fellows, in the first, second and third year of clinical training, respectively. Fellows were on rotation at the VAMC for a mean of 1.9 months (range 1 to 3 months) during the study period. The average ADR was 68.8% (95% CI 65.37 - 72.24). The average withdrawal time was 27.59 min (95% CI 23.45 - 31.73). The average cecal intubation rate was 99% (95% CI 98-100%). There was no significant difference between ADRs, cecal intubation rates, and withdrawal times at different levels of training; however, a trend toward swifter withdrawal times with advancing training was noted. Conclusions ADR appears not to be a useful measure of competency for gastroenterology fellows. Consideration should be given to alternative metrics that could avoid bias and confounders.
Graying of U.S. Bankruptcy: Fallout from Life in a Risk Society

The social safety net for older Americans has been shrinking for the past couple decades. The risks associated with aging, reduced income, and increased healthcare costs, have been off-loaded onto older individuals. At the same time, older Americans are increasingly likely to file consumer bankruptcy, and their representation among those in bankruptcy has never been higher. Using data from the Consumer Bankruptcy Project, we find more than a two-fold increase in the rate at which older Americans (age 65 and over) file for bankruptcy and an almost five-fold increase in the percentage of older persons in the U.S. bankruptcy system. The magnitude of growth in older Americans in bankruptcy is so large that the broader trend of an aging U.S. population can explain only a small portion of the effect. In our data, older Americans report they are struggling with increased financial risks, namely inadequate income and unmanageable costs of healthcare, as they try to deal with reductions to their social safety net. As a result of these increased financial burdens, the median senior bankruptcy filer enters bankruptcy with negative wealth of $17,390 as compared to more than $250,000 for their non-bankrupt peers. For an increasing number of older Americans, their golden years are fraught with economic risks, the result of which is often bankruptcy.
Information Elicitation for Bayesian Auctions

In this paper we design information elicitation mechanisms for Bayesian auctions. While in Bayesian mechanism design the distributions of the players’ private types are often assumed to be common knowledge, information elicitation considers the situation where the players know the distributions better than the decision maker. To weaken the information assumption in Bayesian auctions, we consider an information structure where the knowledge about the distributions is arbitrarily scattered among the players. In such an unstructured information setting, we design mechanisms for auctions with unit-demand or additive valuation functions that aggregate the players’ knowledge, generating revenue that are constant approximations to the optimal Bayesian mechanisms with a common prior. Our mechanisms are 2-step dominant-strategy truthful and the revenue increases gracefully with the amount of knowledge the players collectively have.
Reservoirs to Match our Climatic Fluctuations

Alternating wet and dry periods, each of several years' duration, are suggested by the records of precipitation at several localities in the southwestern United States, and they are indicated also by the records of natural streamflow. In some regions, the precipitation and runoff since 1930 have been at a significantly lesser rate than in the quarter-century prior to 1930, and in most of the Southwest drought has been prevalent since about 1945. A large proportion of the precipitation stations and stream-gaging stations in the Southwest have been established subsequent to 1930, and records from them are likely to be too short to indicate the climatic norm. Reservoirs, both surface and subsurface, can smooth out the marked daily, seasonal, and annual variations in water supply from precipitation, and can furnish water at rates more nearly in accordance with human needs. Many ground-water reservoirs, and some surface reservoirs, after being well filled during years of abundant precipitation and runoff, have...
Hold Up: Machine Delay in Architectural Design

This paper introduces an architectural design approach that is founded on working with digital fabrication machines, materials, and time. This approach is called Machine Delay Fabrication. Machine Delay Fabrication is contextualized within the lineage of productive delays using two examples from other creative disciplines. It is then contrasted with the “real-time” approach to digital fabrication research and practice. The concept of machine delay is outlined along with the three types of machine delay that are pertinent to digital fabrication. A new concrete 3D printing method called pointillistic time-based deposition, or dripping, is introduced as an example of Machine Delay Fabrication. The setup and variables of dripping are discussed, along with some experimental findings. Finally, dripping is used to demonstrate the constructive and aesthetic possibilities of Machine Delay Fabrication in architectural design.
Dynamic Learning and Pricing with Model Misspecification

We study a multiperiod dynamic pricing problem with contextual information, where the seller uses a misspecified demand model. The seller sequentially observes past demand, updates model parameters...
Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level-Set Method

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill-merge-spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level-set method based on graph theory. The proposed level-set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level-set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine-resolution Light Detection and Ranging-derived DEMs show that the raster-based level-set algorithm is much more efficient (~150 times faster) than the vector-based contour tree method. The proposed level-set algorithm has great potential for being applied to large-scale ecohydrological analysis and watershed modeling.
Molecular and evolutionary strategies of meiotic cheating by selfish centromeres

Asymmetric division in female meiosis creates selective pressure favoring selfish centromeres that bias their transmission to the egg. This centromere drive can explain the paradoxical rapid evolution of both centromere DNA and centromere-binding proteins despite conserved centromere function. Here, we define a molecular pathway linking expanded centromeres to histone phosphorylation and recruitment of microtubule destabilizing factors in an intraspecific hybrid, leading to detachment of selfish centromeres from spindle microtubules that would direct them to the polar body. We also introduce a second hybrid model, exploiting centromere divergence between species, and show that winning centromeres in one hybrid become losers in the other. Our results indicate that increasing destabilizing activity is a general strategy for drive, but centromeres have evolved distinct strategies to increase that activity. Furthermore, we show that drive depends on slowing meiotic progression, suggesting that a weakened meiotic spindle checkpoint evolved as a mechanism to suppress selfish centromeres.
Operations in Space: Exploring a New Industry

This article sets the stage for examining operations management research opportunities in the emerging industry that involves operations in outer space. Currently, space exploration is moving in new and exciting directions, thanks to private investment and a more collaborative, commercial industry structure. While we do not yet know if space will be the next big industry, we make the case that the potential is certainly there. In this paper, we outline the challenges presented within the “space industry” and highlight opportunities for operations management researchers in three categories – manufacturing operations, supply chain management, and sustainable operations. We also outline important questions related to stakeholder decisions and needs.
Deep learning facilitates rapid cohort identification using human and veterinary clinical narratives

Background: In public health research, there is currently a need to close the gap between care delivery and cohort identification. We need dedicated tagging staff to allocate a considerable amount of effort to assigning clinical codes after reading patient summaries. Machine learning automation can facilitate the classification of these clinical narratives, but sufficient availability of electronic medical records is still a bottleneck. Veterinary medical records represent a largely untapped data source that could be used to benefit both human and non-human patients. Very few approaches utilizing veterinary data sources currently exist. Methods: In this retrospective cross-sectional and chart review study, we trained separate long short-term memory (LSTM) Recurrent Neural Networks (RNNs) on 52,722 human records and 89,591 veterinary records, tested the models' efficacy in a standard train-test split setup, and probed the portability of these models across species domains. We trained versions of our models using first the free-text clinical narratives, and then only using extracted clinically relevant terms from MetaMap Lite, a natural language processing tool intended for this purpose. Findings: We show that our LSTM approach correctly classifies across top-level codes in the veterinary records (F1 score =0.83), and identifies top-level neoplasia records in veterinary records (F1 score = 0.93). The model trained with veterinary data can be ported over to identify neoplasia records in the human records (F1 score = 0.70). Interpretation: Our findings suggest that free-text clinical narratives can be used to learn classification models that allow the rapid identification of patient cohorts. Ultimately, this effort can lead to new insights that can address emerging public health concerns. Digitization of health information will continue to be a reality in both human and veterinary data; our approach serves as first proof-of-concept regarding how these two domains can learn from, and inform, one another.
Autonomous Vehicles SEnsor Needs

The Internet of Things (IoT) is all about making life simpler and more exciting for consumers by interconnecting the world around them. But how can this promise of the ioT be fulfilled? In the world of IoT, microelectromechanical systems (MEMS) sensors form the backbone of the interface between the user and the multitudes of devices that surround us, such as smartphones, wearables, robots and drones. However, making devices able to sense and be connected is simply not enough to realize the grand promise of the IoT. The fact remains, that loT will only be successful if it follows a user-centric approach, i.e. by solving real-life everyday challenges, making life simpler, enhancing ease of use. Furthermore, ubiquitous sensing of everything on all manner of devices in an ever-increasing number of complex environments poses definite and growing challenges for sensor providers.
The Evolution of Ethnic Identity From Adolescence to Middle Adulthood: The Case of the Immigrant Second Generation:

Through an analysis of qualitative interview and survey data, this study examines ethnic identity development from midadolescence to middle adulthood among a representative sample of immigrants’ ch...
Triggered Palliative Care for Late-Stage Dementia: A Pilot Randomized Trial

Abstract Context Persons with late-stage dementia have limited access to palliative care. Objective The objective of this study was to test dementia-specific specialty palliative care triggered by hospitalization. Methods This pilot randomized controlled trial enrolled 62 dyads of persons with late-stage dementia and family decision-makers on admission to hospital. Intervention dyads received dementia-specific specialty palliative care consultation plus postacute transitional care. Control dyads received usual care and educational information. The primary outcome was 60-day hospital or emergency department visits. Secondary patient- and family-centered outcomes were patient comfort, family distress, palliative care domains addressed in the treatment plan, and access to hospice or community-based palliative care. Secondary decision-making outcomes were discussion of prognosis, goals of care, completion of Medical Orders for Scope of Treatment (MOST), and treatment decisions. Results Of 137 eligible dyads, 62 (45%) were enrolled. The intervention proved feasible, with protocol completion ranging from 77% (family two-week call) to 93% (initial consultation). Hospital and emergency department visits did not differ (intervention vs. control, 0.68 vs. 0.53 transfers per 60 days, P = 0.415). Intervention patients had more palliative care domains addressed and were more likely to receive hospice (25% vs. 3%, P Conclusion Specialty palliative care consultation for hospitalized patients with late-stage dementia is feasible and promising to improve decision-making and some treatment outcomes.
Correctness of Speculative Optimizations with Dynamic Deoptimization

High-performance dynamic language implementations make heavy use of speculative optimizations to achieve speeds close to statically compiled languages. These optimizations are typically performed by a just-in-time compiler that generates code under a set of assumptions about the state of the program and its environment. In certain cases, a program may execute code compiled under assumptions that are no longer valid. The implementation must then deoptimize the program on-the-fly; this entails finding a semantically equivalent code fragment that does not rely on invalid assumptions, translating program state to that expected by the target code, and transferring control. This paper looks at the interaction between optimization and deoptimization, and shows that reasoning about speculation is surprisingly easy when assumptions are made explicit in the program representation. This insight is demonstrated on a compiler intermediate representation, named sourir, modeled after the high-level representation for a dynamic language. Traditional compiler optimizations such constant folding, dead code elimination and function inlining are shown to be correct in the presence of assumption. Furthermore, the paper establishes the correctness of compiler transformations specific to deoptimization: namely unrestricted deoptimization, predicate hoisting and assume composition.
Dynamics of entangled polymer chains with nanoparticle attachment under large amplitude oscillatory shear

This paper presents a nonlinear viscoelastic model for polymer nanocomposites and the computed model response to large amplitude oscillatory shear flow. The model predicts the stress in a mixture of entangled polymer chains, with different convective constraint release (CCR) rates for free chains and nanoparticle‐attached chains, through an averaging scheme which is consistent with double reptation in the Marrucci–Ianniruberto constitutive equation. The nonlinear response of the mixture is evaluated both numerically in terms of Q and by an asymptotic analysis in terms of four frequency dependent parameters of medium amplitude oscillatory shear (MAOS) as well as the intrinsic nonlinearity parameter Q₀. In the case of free polymer chains alone, the MAOS signatures are comparable to those of the Giesekus model with the notable difference of a minimum in the elastic parameter [e₁] at De >1. The viscous nonlinear parameters of the mixture model depart significantly from those of the free chains, especially in mixtures where the CCR parameter for attached chains is larger than that for the free chains: [v₁] has a prominent minimum and [v₃] has a prominent maximum near De = 2/c, the low frequency plateau region, along with a higher Q₀ compared to the matrix at all Deborah numbers. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019, 57, 62–76
Does a Rising School Climate Lift All Boats? Differential Associations of Perceived Climate and Achievement for Students with Disabilities and Limited English Proficiency.

Previous research studies show that a positive school climate is associated with desirable academic outcomes for youth. In the United States, students with disabilities and English language learner...
Statistical Model Checking-Based Analysis of Biological Networks

We introduce a framework for analyzing ordinary differential equation (ODE) models of biological networks using statistical model checking (SMC). A key aspect of our work is the modeling of single-cell variability by assigning a probability distribution to intervals of initial concentration values and kinetic rate constants. We propagate this distribution through the system dynamics to obtain a distribution over the set of trajectories of the ODEs. This in turn opens the door for performing statistical analysis of the ODE system’s behavior. To illustrate this, we first encode quantitative data and qualitative trends as bounded linear time temporal logic (BLTL) formulas. Based on this, we construct a parameter estimation method using an SMC-driven evaluation procedure applied to the stochastic version of the behavior of the ODE system. We then describe how this SMC framework can be generalized to hybrid automata by exploiting the given distribution over the initial states and the—much more sophisticated—system dynamics to associate a Markov chain with the hybrid automaton. We then establish a strong relationship between the behaviors of the hybrid automaton and its associated Markov chain. Consequently, we sample trajectories from the hybrid automaton in a way that mimics the sampling of the trajectories of the Markov chain. This enables us to verify approximately that the Markov chain meets a BLTL specification with high probability. We have applied these methods to ODE-based models of Toll-like receptor signaling and the crosstalk between autophagy and apoptosis, as well as to systems exhibiting hybrid dynamics including the circadian clock pathway and cardiac cell physiology. We present an overview of these applications and summarize the main empirical results. These case studies demonstrate that our methods can be applied in a variety of practical settings.
Two Problems Afflicting the Search for a Standard Model of the Mind.

We describe two serious problems afflicting the search for a standard model of the mind (SMM), as carried out and prescribed by Laird, Lebiere, and Rosenbloom (LLR). The first problem concerns a glaring omission from SMM, while the second calls into question the evidentiary standards for convergence that motivates the entire SMM agenda. It may well be that neither problem is insuperable, even in the short term. On the other hand, both problems currently stand in the way of making any present pronouncements to the effect that a standard model (or substantive portion thereof) exists and can be used as a benchmark against which other researchers might compare their approaches. The pair of problems is offered in a spirit of collaboration, and in the hope that grappling with them will help move the search a bit closer to the sort of undisputed rigor and predictive power afforded by such models in physics. Our order of business in the sequel is straightforward: we present and briefly discuss each of the two problems in turn, and wrap up with some remarks regarding whether or not these problems can be surmounted, and if so, how. In what follows, we argue that even on the most liberal identification of the term “mind” with a project in defining a consensus view of cognitive architecture, consciousness remains a deeply conspicuous omission that flirts with rendering the project incoherent. We open with a rough-and-ready discussion of how consciousness is often characterized in information-processing terms, and its most plausible correlate in LLR’s proposed SMM.We show that the introductionof consciousness as a phenomena to be accounted for reveals fault-lines between architectures that are claimed by LLR to be similar enough to warrant the postulation of the SMM. We then consider and rebut a range of objections to both the general requirement of accounting for consciousness within the SMM and to the specifics of our argument. The analysis we offer with respect to consciousness is diagnostic of what we see as a far more insidious and difficult problemto remedy, which will be explored in the second part of this paper.
Dice in the Black Box: User Experiences with an Inscrutable Algorithm.

We demonstrate that users may be prone to place an inordinate amount of trust in black box algorithms that are framed as intelligent. We deploy an algorithm that purportedly assesses the positivity and negativity of a users' writing emotional writing. In actuality, the algorithm responds in a random fashion. We qualitatively examine the paths to trust that users followed while testing the system. In light of the ease with which users may trust systems exhibiting "intelligent behavior" we recommend corrective approaches.
Observables of Macdonald processes

We present a framework for computing averages of various observables of Macdonald processes. This leads to new contour--integral formulas for averages of a large class of multilevel observables, as well as Fredholm determinants for averages of two different single level observables.
An Examination of How District Attorneys Perceive Justice.

Scholars have identified four primary types of justice: distributive, procedural, interpersonal, and informational. These four types of justice correspond, respectively, to the perceived fairness of one’s outcomes, to the perceived fairness of the procedures used to determine one’s outcomes, to the degree to which people are treated with dignity and respect, and to whether individuals receive complete, truthful, and timely explanations of procedures and decisions. A significant amount of criminal justice research has examined how perceptions of justice affect attitudes and behavior (Denver 2011). Understanding how district attorneys view justice gives insight into the decisions they make including how to dispose of cases, what charges to bring against defendants, what sentences to recommend, and even how victims should be treated throughout the court process. As noted by Colquitt (2001), a large number of studies have sought to link justice perceptions to a variety of organizational outcomes, including job satisfaction, organizational commitment, withdrawal, and organizational citizenship behavior (p. 425). Nonetheless, the extant literature is lacking on conceptualizations of justice related to jury trials. Since ensuring that justice prevails is the primary responsibility of the district attorney (Felkenes 1975), this study seeks to examine district attorneys’ perceptions of justice resulting from the use of jury trials.
Share repurchases and accounting conservatism

The prior literature indicates that financial policy (e.g., payout policy) as well as accounting policy (e.g., conservatism) can be used to address incentive problems in firms but finds mixed evidence. We conjecture that stock repurchases, an increasingly popular form of payout, and conservatism are potential mechanisms to counter managerial propensity to engage in overinvestment using free cash flows. Consequently, we expect a negative relation between repurchases and conservatism as well as a stronger negative relation between these two mechanisms in firms with high levels of free cash flows. We find results consistent with these expectations. By contrast, we find a weaker negative relation between repurchases and conservatism when CEO tenure is higher, which confirms that more entrenched CEOs have less incentives to solve the overinvestment problem.
Effect of side chain and backbone length on lamellar spacing in polystyrene-block-poly(dimethyl siloxane) brush block copolymers

We report the synthesis of polystyrene‐block‐poly(dimethyl siloxane) (PS‐b‐PDMS) brush block copolymers (BBCPs) through sequential ROMP of norbornene‐modified macromonomers (‐NB) and explore the effect of side chain length (Nₛc) and total backbone degree of polymerization (Nbb) on the self‐assembly of lamellar morphologies. Group I (PS‐NB Mₙ = 2.9 kg/mol, PDMS‐NB Mₙ = 4.8 kg/mol) exhibits asymmetric side chains, while Group II (PS‐NB Mₙ = 4.7 kg/mol, PDMS‐NB Mₙ = 4.8 kg/mol) possess a more symmetric arrangement. Both families rapidly self‐assemble into well‐ordered lamellar morphologies with domain spacings (d₀) ranging from d₀ = 54 to 140 nm. The scaling relationship between d₀ and Nbb (d₀ ~Nbbᵅ) was determined as the measure of backbone flexibility. Exponents of α = 0.71 and α = 0.81 are observed for Groups I and II, respectively, indicating the BBCPs adopt an extended backbone conformation. The presence of a low Tg side chain such as PDMS increases apparent flexibility of the backbone. The interplay between contrasting characteristics of the side chains is discussed and reveals the importance of understanding the physical consequences of block architecture on controlling BBCP assembly. These findings provide necessary information for future investigations of complex phases and well‐defined nanostructures fabricated using the brush architecture. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019, 57, 691–699
Universal quantum control through deep reinforcement learning

Emerging reinforcement learning techniques using deep neural networks have shown great promise in control optimization. They harness non-local regularities of noisy control trajectories and facilitate transfer learning between tasks. To leverage these powerful capabilities for quantum control optimization, we propose a new control framework to simultaneously optimize the speed and fidelity of quantum computation against both leakage and stochastic control errors. For a broad family of two-qubit unitary gates that are important for quantum simulation of many-electron systems, we improve the control robustness by adding control noise into training environments for reinforcement learning agents trained with trusted-region-policy-optimization. The agent control solutions demonstrate a two-order-of-magnitude reduction in average-gate-error over baseline stochastic-gradient-descent solutions and up to a one-order-of-magnitude reduction in gate time from optimal gate synthesis counterparts. These significant improvements in both fidelity and runtime are achieved by combining new physical understandings and state-of-the-art machine learning techniques. Our results open a venue for wider applications in quantum simulation, quantum chemistry and quantum supremacy tests using near-term quantum devices.
Active Embedding Search via Noisy Paired Comparisons

Task : for a given user, estimate a preference vector $w \in {\mathbb{R}^d}$ in a similarity embedding of items
A simple method for preparation of N-mono- and N,N-di-alkylated α-amino acids

Abstract Reactions of α-amino acids with ketones under hydrogenation conditions using 20% Pd(OH) 2 /C as the catalyst gave N -mono-alkylated amino acids in high yields. Reductive methylation of N -mono-alkylated amino acids under the same hydrogenation conditions at 50°C afforded N , N -di-alkylated amino acids in excellent yields. This simple method has been used to synthesize N -mono- and N , N -di-alkylated amino acids on a scale of 200 g.
Phototransposition Chemistry of 4-Substituted Isothiazoles. The P4 Permutation Pathway

Upon irradiation in the presence of a small quantity of base, 4-substituted isothiazoles undergo photocleavage to yield substituted cyanosulfides, which can be trapped as their benzyl thioether derivatives, and substituted isocyanosulfides. Both products are suggested to arise via initial photocleavage of the sulfur−nitrogen bond, resulting in the formation of a substituted β-thioformylvinyl nitrene, which can rearrange to the observed cyanosulfide, or cyclize to an undetected thioformylazirine. Deprotonation of the azirine leads directly to the isocyanosulfide. The plight of the isocyanosulfide depends on the C-4 substituent. If the substituent is aromatic, the isocyanosulfide is reprotonated at the isocyanide carbon and spontaneously cyclizes to a 4-substituted thiazole, the observed transposition product. If the substituent is not aromatic, the isocyanosulfide is reprotonated at sulfur and the resulting species has a higher energy barrier to cyclization. In these cases, the isocyanosulfides can be obse...
Conformer Interconversion in the Excited State of Constrained Tryptophan Derivatives

The conformer model of tryptophan photophysics ascribes the multiple fluorescence lifetimes to ground-state heterogeneity. It is usually assumed that the different conformers do not interconvert in the excited state. Previous studies of two constrained tryptophan derivatives supported this assumption (Colucci, W. J.; Tilstra, L.; Sattler, M. C.; Fronczek, F. R.; Barkley, M. D. J. Am. Chem. Soc. 1990, 112, 9182-9190; Yu, H.-T.; Vela, M. A.; Fronczek, F. R.; McLaughlin, M. L.; Barkley, M. D. J. Am. Chem. Soc. 1995, 117, 348-357). Five constrained derivatives have been synthesized and shown to undergo conformer inversion during the lifetime of the excited state. All derivatives have two ground-state conformations as determined by X-ray crystallography, molecular mechanics calculations, and 1H-NMR. Fluorescence lifetime data were fit to singleand double-exponential models and to a reversible two-state excited-state reaction model. 2-Amino-1,2dihydrocyclopenta[b]indole-2-carboxylic acid has a single-exponential decay consistent with conformer inversion much faster than fluorescence decay. 1,2,3,4-Tetrahydrocarbazole-3-carboxylic acid, ethyl 1,2,3,4tetrahydrocarbazole-3-carboxylate, and their 9-methyl derivatives have double-exponential decays with a minor second component of small positive or negative amplitude. Conformer inversion rates of ∼107 s-1 were determined by analyzing the fluorescence decay data using the excited-state reaction model. Temperature dependence of the fluorescence lifetimes was measured in H2O and D2O, and solvent quenching rates were calculated from the Arrhenius parameters. The carboxylate and carbonyl functional groups appear to have little effect on solvent quenching of indole fluorescence. Model calculations examining the effect of conformer inversion rate on the decay parameters of a biexponential model indicate that the presence of a small amplitude, short lifetime component may be a good predictor of excited-state conformer interconversion of tryptophans in peptides and proteins.
The Language Zone: Differentiating writing instruction for students who are d/Deaf and hard of hearing

Interactive Writing (IW) is a powerful support for language and literacy development; however, its emphasis on using oral language to construct written language can present challenges for deaf/Deaf and hard of hearing (d/Dhh) students due to their unique and diverse language experiences. Teachers (n = 14) using Strategic and Interactive Writing Instruction (SIWI) with grade 3–5 d/Dhh students in a variety of settings were observed using a space referred to as ‘the language zone’ to address the unique language and literacy needs of d/Dhh students. The language zone is the designated space in a classroom where the creation, translation and revision of ideas is made visible. Researchers developed a flowchart with three tiers to document the three purposes for which the teachers use the space. Accompanying scenarios provide concrete examples of three distinct ways in which the language zone can be used. Teachers can use this language zone flow chart as a tool to recognize, analyze and select instructional moves that have the potential to positively impact the language and literacy proficiencies of d/Dhh students.
SoS Notebook: an interactive multi-language data analysis environment.

Motivation Complex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking. Results We developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications. Availability and implementation SoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license.
Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

Single-cell gene expression measurements offer opportunities in deriving mechanistic understanding of complex diseases, including cancer. However, due to the complex regulatory machinery of the cell, gene regulatory network (GRN) model inference based on such data still manifests significant uncertainty. The goal of this paper is to develop optimal classification of single-cell trajectories accounting for potential model uncertainty. Partially-observed Boolean dynamical systems (POBDS) are used for modeling gene regulatory networks observed through noisy gene-expression data. We derive the exact optimal Bayesian classifier (OBC) for binary classification of single-cell trajectories. The application of the OBC becomes impractical for large GRNs, due to computational and memory requirements. To address this, we introduce a particle-based single-cell classification method that is highly scalable for large GRNs with much lower complexity than the optimal solution. The performance of the proposed particle-based method is demonstrated through numerical experiments using a POBDS model of the well-known T-cell large granular lymphocyte (T-LGL) leukemia network with noisy time-series gene-expression data.
The Biochemical Activities of the Saccharomyces cerevisiae Pif1 Helicase Are Regulated by Its N-Terminal Domain

Pif1 family helicases represent a highly conserved class of enzymes involved in multiple aspects of genome maintenance. Many Pif1 helicases are multi-domain proteins, but the functions of their non-helicase domains are poorly understood. Here, we characterized how the N-terminal domain (NTD) of the Saccharomyces cerevisiae Pif1 helicase affects its functions both in vivo and in vitro. Removal of the Pif1 NTD alleviated the toxicity associated with Pif1 overexpression in yeast. Biochemically, the N-terminally truncated Pif1 (Pif1ΔN) retained in vitro DNA binding, DNA unwinding, and telomerase regulation activities, but these activities differed markedly from those displayed by full-length recombinant Pif1. However, Pif1ΔN was still able to synergize with the Hrq1 helicase to inhibit telomerase activity in vitro, similar to full-length Pif1. These data impact our understanding of Pif1 helicase evolution and the roles of these enzymes in the maintenance of genome integrity.
Impacts of Recurrent Hitchhiking on Divergence and Demographic Inference in Drosophila

In species with large population sizes such as Drosophila, natural selection may have substantial effects on genetic diversity and divergence. However, the implications of this widespread nonneutrality for standard population genetic assumptions and practices remain poorly resolved. Here, we assess the consequences of recurrent hitchhiking (RHH), in which selective sweeps occur at a given rate randomly across the genome. We use forward simulations to examine two published RHH models for D. melanogaster, reflecting relatively common/weak and rare/strong selection. We find that unlike the rare/strong RHH model, the common/weak model entails a slight degree of Hill-Robertson interference in high recombination regions. We also find that the common/weak RHH model is more consistent with our genome-wide estimate of the proportion of substitutions fixed by natural selection between D. melanogaster and D. simulans (19%). Finally, we examine how these models of RHH might bias demographic inference. We find that these RHH scenarios can bias demographic parameter estimation, but such biases are weaker for parameters relating recently diverged populations, and for the common/weak RHH model in general. Thus, even for species with important genome-wide impacts of selective sweeps, neutralist demographic inference can have some utility in understanding the histories of recently diverged populations.
Reactions of aromatic ketones with 3‐mercapto‐1,2‐propanediol. Synthesis of cis‐ and trans‐2‐alkyl‐2‐aryl‐(1,3‐oxathiolane‐5‐methanols and 1,3‐dioxolane‐4‐methanethiols)

Aromatic ketones react with 3-mercapto-1,2-propanediol (1) in refluxing benzene under the catalytic influence of a sulfonic acid and with azeotropic removal of water to yield a mixture comprised predominantly of cis- and trans-2-alkyl-2-aryl-1,3-oxathiolane-5-methanols 7, accompanied by lesser amounts of cis- and trans-2-alkyl-2-aryl-1,3-dioxolane-4-methanethiols 8 (up to 30%). It was discovered that 8 is the kinetic product and is isomerized by 4-toluenesulfonic acid in hot benzene to the thermodynamically more stable 7. Under these conditions, ortho- and α-substituted aromatic ketones tend to produce more of 8, which can be attributed to steric hindrance encountered by the thiol as it attacks the ketone. Ketalizations of 1-aryl-2-(1H-imidazol-1-yl)-1- as well as 1-aryl-2-(1,H-1,2,4-triazol-1-yl)-1-ethanones by 1 fail under these conditions, even after 24 hours of reflux in toluene. However, 1-(4-chlorophenyl)-3-(1H-imidazol-1-yl)-1-propanone and 1-(4-bromophenyl)-4-(1H-imidazol-1-yl)-1-butanone are ketalized by 1 as expected. Interestingly, the reaction of 2-bromo-4′-chloroace-tophenone with 1 produces 1-(4-chlorophenyl)-2,8-dioxa-6-thiabicyclo[3.2.1]octane. Characterization of all isomers and separation of some diastereomers is described. Nuclear Overhauser enhancement experiments are utilized to establish the stereochemistry of 1,3-oxathiolanes.
Magnetic properties of a homologous series of vanadium jarosite compounds.

Redox-based, hydrothermal synthetic methodologies have enabled the preparation of a new series of stoichiometrically pure jarosites of the formula, AV3(OH)6(SO4)2 with A = Na+, K+, Rb+, Tl+, and NH4+. These jarosites represent the first instance of strong ferromagnetism within a Kagome layered framework. The exchange interaction, which is invariant to the nature of the A+ ion (ϑCW ≈ +53(1) K), propagates along the d2 magnetic sites of the triangular Kagome lattice through bridging hydroxyl groups. An analysis of the frontier orbitals suggests this superexchange pathway to possess significant π-orbital character. Measurements on a diamagnetic host jarosite doped with magnetically dilute spin carriers, KGa2.96V0.04(OH)6(SO4)2, reveal significant single-ion anisotropy for V3+ ion residing in the tetragonal crystal field. This anisotropy confines the exchange-coupled moments to lie within the Kagome layer. Coupling strengths are sufficiently strong to prevent saturation of the magnetization when an external f...
Serotonergic Regulation of Corticoamygdalar Neurons in the Mouse Prelimbic Cortex

Neuromodulatory transmitters, such as serotonin (5-HT), selectively regulate the excitability of subpopulations of cortical projection neurons to gate cortical output to specific target regions. For instance, in the mouse prelimbic cortex, 5-HT selectively excites commissurally projecting (COM) intratelencephalic neurons via activation of 5-HT2A (2A) receptors, while simultaneously inhibiting, via 5-HT1A (1A) receptors, corticofugally projecting pyramidal neurons targeting the pons. Here we characterize the physiology, morphology, and serotonergic regulation of corticoamygdalar (CAm) projection neurons in the mouse prelimbic cortex. Layer 5 CAm neurons shared a number of physiological and morphological characteristics with COM neurons, including higher input resistances, smaller HCN-channel mediated responses, and sparser dendritic arbors than corticopontine neurons. Across cortical lamina, CAm neurons also resembled COM neurons in their serotonergic modulation; focally applied 5-HT (100 μM; 1 s) generated 2A-receptor-mediated excitation, or 1A- and 2A-dependent biphasic responses, in ipsilaterally and contralaterally projecting CAm neurons. Serotonergic excitation depended on extrinsic excitatory drive, as 5-HT failed to depolarize CAm neurons from rest, but could enhance the number of action potentials generated by simulated barrages of synaptic input. Finally, using dual tracer injections, we identified double-labeled CAm/COM neurons that displayed primarily excitatory or biphasic responses to 5-HT. Overall, our findings reveal that prelimbic CAm neurons in layer 5 overlap, at least partially, with COM neurons, and that neurons projecting to either, or both targets, exhibit 2A-dependent serotonergic excitation. These results suggest that 5-HT, acting at 2A receptors, may promote cortical output to the amygdala.