cssi/SciSciGPT-SciSciNet huggingface dataset:
A scalable spectral Stokes solver for simulation of time-periodic flows in complex geometries

Abstract Simulation of unsteady creeping flow in complex geometries has traditionally required the use of a time-stepping procedure, which is typically costly and unscalable. To reduce the cost and allow for computations at much larger scales, we propose an alternative approach that is formulated based on the unsteady Stokes equation expressed in the time-spectral or frequency domain. This transformation results in a boundary value problem with an imaginary source term proportional to the computed mode that is discretized and solved in a complex-valued finite element solver using Bubnov-Galerkin formulation. This transformed spatio-spectral formulation presents several advantages over the traditional spatio-temporal techniques. Firstly, for cases with boundary conditions varying smoothly in time, it provides a significant saving in computational cost as it can resolve time-variation of the solution using a few modes rather than thousands of time steps. Secondly, in contrast to the traditional time integration scheme with a finite order of accuracy, this method exhibits a super convergence behavior versus the number of computed modes. Thirdly, in contrast to the stabilized finite element methods for fluid, no stabilization term is employed in our formulation, producing a solution that is consistent and more accurate. Fourthly, the proposed approach is embarrassingly parallelizable owing to the independence of the solution modes, thus enabling scalable calculations at a much larger number of processors. The comparison of the proposed technique against a standard stabilized finite element solver is performed using two- and three-dimensional canonical and complex geometries. The results show that the proposed method can produce more accurate results at 1% to 11% of the cost of the standard technique for the studied cases.
Towards Real-World Applications of ServiceX, an Analysis Data Transformation System

One of the biggest challenges in the High-Luminosity LHC (HLLHC) era will be the significantly increased data size to be recorded and analyzed from the collisions at the ATLAS and CMS experiments. ServiceX is a software R&D project in the area of Data Organization, Management and Access of the IRIS-HEP to investigate new computational models for the HLLHC era. ServiceX is an experiment-agnostic service to enable on-demand data delivery specifically tailored for nearly-interactive vectorized analyses. It is capable of retrieving data from grid sites, on-the-fly data transformation, and delivering user-selected data in a variety of different formats. New features will be presented that make the service ready for public use. An ongoing effort to integrate ServiceX with a popular statistical analysis framework in ATLAS will be described with an emphasis of a practical implementation of ServiceX into the physics analysis pipeline.
Optically and thermally driven huge lattice orbital and spin angular momenta from spinning fullerenes

Lattice vibration in solids may carry angular momentum. But unlike the intrinsic spin of electrons, the lattice vibration is rarely rotational. To induce angular momentum, one needs to find a material that can accommodate a twisted normal mode, two orthogonal modes, or excitation of magnons. If excitation is too strong, one may exceed the Lindemann limit, so the material melts. Therefore these methods are not ideal. Here, we theoretically propose a route to phonon angular momentum in a molecular crystal ${\mathrm{C}}_{60}$. We find that a single laser pulse is able to inject a significant amount of angular momentum to ${\mathrm{C}}_{60}$, and the momentum transfer is helicity dependent. Changing from right-circularly polarized light to left-circularly polarized light switches the direction of phonon angular momentum. On the ultrafast timescale, the orbital angular momentum change closely resembles the displacive excitation of coherent phonons, with a cosine-function dependence on time, different from the spin counterpart. Atomic displacements, even under strong laser excitation, remain far below the Lindemann criterion. Under thermal excitation, spinning ${\mathrm{C}}_{60}$ even at room temperature generates a huge angular momentum close to several hundred $\ensuremath{\hbar}$. Our finding opens the door to a large group of fullerenes, from ${\mathrm{C}}_{60},\phantom{\rule{0.16em}{0ex}}{\mathrm{C}}_{70}$ to their endohedral derivatives, where angular momentum can be generated through light or temperature. This paves the way to the phononic control electronic spin and harvesting thermal energy through phonon angular momentum.
Complete Stokes vector analysis with a compact, portable rotating waveplate polarimeter

Accurate calibration of polarization-dependent optical elements is often necessary in optics experiments. A versatile polarimeter device to measure the polarization state of light is a valuable tool in these experiments. Here, we report a rotating waveplate-based polarimeter capable of complete Stokes vector analysis of collimated light. Calibration of the device allows accurate measurements over a range of wavelengths, with a bandwidth of >30 nm in this implementation. A photo-interrupter trigger system supplies the phase information necessary for full determination of the Stokes vector. An Arduino microcontroller performs rapid analysis and displays the results on a liquid crystal display. The Arduino can also be interfaced with a computer to store time series of Stokes vectors. The optical measurement apparatus of the polarimeter is compact and can be placed anywhere on an optical table on a single standard post. The components to construct the device are only a fraction of the cost of commercially available devices, while the accuracy and precision of the measurements are of the same order of magnitude.
Taylor dispersion of elongated rods

In many complex fluids, the geometry of particles in suspension can be complex, prompting the need to understand how shape influences their bulk transport. We consider the Taylor dispersion of passive, elongated Brownian rods subject to a background Poiseuille flow. Monte-Carlo simulations demonstrate that elongated particles exhibit enhanced longitudinal dispersion compared to their spherical counterparts, in excellent agreement with integral expressions derived from asymptotic analysis. For particles of high aspect-ratio, the dispersion coefficient can be collapsed along a single curve, providing a simple correction factor that extends Taylor's seminal results to elongated particles.
Robust photon-mediated entangling gates between quantum dot spin qubits

Significant experimental advances in single-electron silicon spin qubits have opened the possibility of realizing long-range entangling gates mediated by microwave photons. Recently proposed imaginary swap (iswap) gates, however, require tuning qubit energies into resonance and have limited fidelity due to charge noise. We present a photon-mediated cross-resonance gate that is consistent with realistic experimental capabilities and requires no resonant tuning. Furthermore, we propose gate sequences capable of suppressing errors due to quasistatic noise for both the cross-resonance and iswap gates.
Emergent classicality in general multipartite states and channels

In a quantum measurement process, classical information about the measured system spreads throughout the environment. Meanwhile, quantum information about the system becomes inaccessible to local observers. Here we prove a result about quantum channels indicating that an aspect of this phenomenon is completely general. We show that for any evolution of the system and environment, for everywhere in the environment excluding an $O(1)$-sized region we call the "quantum Markov blanket," any locally accessible information about the system must be approximately classical, i.e. obtainable from some fixed measurement. The result strengthens the earlier result of arXiv:1310.8640 in which the excluded region was allowed to grow with total environment size. It may also be seen as a new consequence of the principles of no-cloning or monogamy of entanglement. Our proof offers a constructive optimization procedure for determining the "quantum Markov blanket" region, as well as the effective measurement induced by the evolution. Alternatively, under channel-state duality, our result characterizes the marginals of multipartite states.
Visual speech differentially modulates beta, theta, and high gamma bands in auditory cortex

Speech perception is a central component of social communication. Although principally an auditory process, accurate speech perception in everyday settings is supported by meaningful information extracted from visual cues. Visual speech modulates activity in cortical areas subserving auditory speech perception including the superior temporal gyrus (STG). However, it is unknown whether visual modulation of auditory processing is a unitary phenomenon or, rather, consists of multiple functionally distinct processes. To explore this question, we examined neural responses to audiovisual speech measured from intracranially implanted electrodes in 21 patients with epilepsy. We found that visual speech modulated auditory processes in the STG in multiple ways, eliciting temporally and spatially distinct patterns of activity that differed across frequency bands. In the theta band, visual speech suppressed the auditory response from before auditory speech onset to after auditory speech onset (-93 ms to 500 ms) most strongly in the posterior STG. In the beta band, suppression was seen in the anterior STG from -311 to -195 ms before auditory speech onset and in the middle STG from -195 ms to 235 ms after speech onset. In high gamma, visual speech enhanced the auditory response from -45 ms to 24 ms only in the posterior STG. We interpret the visual-induced changes prior to speech onset as reflecting crossmodal prediction of speech signals. In contrast, modulations after sound onset may reflect a decrease in sustained feedforward auditory activity. These results are consistent with models that posit multiple distinct mechanisms supporting audiovisual speech perception.
Optical response from charge-density waves in Weyl semimetals

The study of charge-density wave (CDW) distortions in Weyl semimetals has recently returned to the forefront, inspired by experimental interest in materials such as ${\text{(TaSe}}_{4}{\text{)}}_{2}\text{I}$. However, the interplay between collective phonon excitations and charge transport in Weyl-CDW systems has not been systematically studied. In this paper, we examine the longitudinal electromagnetic response due to collective modes in a Weyl semimetal gapped by a quasi-one-dimensional CDW order, using both continuum and lattice-regularized models. We systematically compute the contributions of the collective modes to the linear and nonlinear optical conductivity of our models, both with and without tilting of the Weyl cones. We discover that, unlike in a single-band CDW, the gapless CDW collective mode does not contribute to the conductivity unless the Weyl cones are tilted. Going further, we show that the lowest nontrivial collective mode contribution to charge transport with untilted Weyl cones comes in the third-order conductivity for a single collective mode. This third-order process is mediated by the gapped amplitude mode. We show that this leads to a sharply peaked third-harmonic response at frequencies below the single-particle energy gap. We discuss the implications of our findings for transport experiments in Weyl-CDW systems.
Remaining Useful Life Prediction from 3D Scan Data with Genetically Optimized Convolutional Neural Networks.

In the current industrial landscape, increasingly pervaded by technological innovations, the adoption of optimized strategies for asset management is becoming a critical key success factor. Among the various strategies available, the “Prognostics and Health Management” strategy is able to support maintenance management decisions more accurately, through continuous monitoring of equipment health and “Remaining Useful Life” forecasting. In the present study, convolutional neural network-based deep neural network techniques are investigated for the remaining useful life prediction of a punch tool, whose degradation is caused by working surface deformations during the machining process. Surface deformation is determined using a 3D scanning sensor capable of returning point clouds with micrometric accuracy during the operation of the punching machine, avoiding both downtime and human intervention. The 3D point clouds thus obtained are transformed into bidimensional image-type maps, i.e., maps of depths and normal vectors, to fully exploit the potential of convolutional neural networks for extracting features. Such maps are then processed by comparing 15 genetically optimized architectures with the transfer learning of 19 pretrained models, using a classic machine learning approach, i.e., support vector regression, as a benchmark. The achieved results clearly show that, in this specific case, optimized architectures provide performance far superior (MAPE = 0.058) to that of transfer learning, which, instead, remains at a lower or slightly higher level (MAPE = 0.416) than support vector regression (MAPE = 0.857).
Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior.

Direct reconstruction methods have been developed to estimate parametric images directly from the measured PET sinograms by combining the PET imaging model and tracer kinetics in an integrated framework. Due to limited counts received, signal-to-noise-ratio (SNR) and resolution of parametric images produced by direct reconstruction frameworks are still limited. Recently supervised deep learning methods have been successfully applied to medical imaging denoising/reconstruction when large number of high-quality training labels are available. For static PET imaging, high-quality training labels can be acquired by extending the scanning time. However, this is not feasible for dynamic PET imaging, where the scanning time is already long enough. In this work, we proposed an unsupervised deep learning framework for direct parametric reconstruction from dynamic PET, which was tested on the Patlak model and the relative equilibrium Logan model. The training objective function was based on the PET statistical model. The patient's anatomical prior image, which is readily available from PET/CT or PET/MR scans, was supplied as the network input to provide a manifold constraint, and also utilized to construct a kernel layer to perform non-local feature denoising. The linear kinetic model was embedded in the network structure as a 1×1×1 convolution layer. Evaluations based on dynamic datasets of 18F-FDG and 11C-PiB tracers show that the proposed framework can outperform the traditional and the kernel method-based direct reconstruction methods.
Deep Equilibrium Architectures for Inverse Problems in Imaging

Recent efforts on solving inverse problems in imaging via deep neural networks use architectures inspired by a fixed number of iterations of an optimization method. The number of iterations is typically quite small due to difficulties in training networks corresponding to more iterations; the resulting solvers cannot be run for more iterations at test time without incurring significant errors. This paper describes an alternative approach corresponding to an infinite number of iterations, yielding a consistent improvement in reconstruction accuracy above state-of-the-art alternatives and where the computational budget can be selected at test time to optimize context-dependent trade-offs between accuracy and computation. The proposed approach leverages ideas from Deep Equilibrium Models, where the fixed-point iteration is constructed to incorporate a known forward model and insights from classical optimization-based reconstruction methods.
MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding

In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as efficiently as possible. The multi-agent planning problem in these applications involves allocating and sequencing goals for each agent while simultaneously producing conflict-free paths for the agents. In this article, we introduce a new algorithm called MS* which computes an optimal solution for this multi-agent problem by fusing and advancing state of the art solvers for multi-agent path finding (MAPF) and multiple travelling salesman problem (mTSP). MS* leverages our prior subdimensional expansion approach for MAPF and embeds the mTSP solvers to optimally allocate and sequence goals for agents. Numerical results show that our new algorithm can solve the multi-agent problem with 20 agents and 50 goals in a minute of CPU time on a standard laptop.
Powassan Viruses Spread Cell to Cell During Direct Isolation from Ixodes Ticks and Persistently Infect Human Brain Endothelial Cells and Pericytes.

Powassan viruses (POWVs) are neurovirulent tick-borne flaviviruses emerging in the Northeastern U.S., with a 2% prevalence in Long Island (LI) deer ticks (Ixodes scapularis). POWVs are transmitted in as little as 15 minutes of a tick bite, and enter the CNS to cause encephalitis (10% fatal) and long-term neuronal damage. POWV-LI9 and POWV-LI41 present in LI Ixodes ticks were isolated by directly inoculating VeroE6 cells with tick homogenates and detecting POWV infected cells by immunoperoxidase staining. Inoculated POWV-LI9 and LI41 were exclusively present in infected cell foci, indicative of spread cell to cell, despite growth in liquid culture without an overlay. Cloning and sequencing establish POWV-LI9 as a phylogenetically distinct lineage II POWV strain circulating in LI deer ticks. Primary human brain microvascular endothelial cells (hBMECs) and pericytes form a neurovascular complex that restricts entry into the CNS. We found that POWV-LI9, -LI41 and Lineage I POWV-LB, productively infect hBMECs and pericytes and that POWVs were basolaterally transmitted from hBMECs to lower chamber pericytes without permeabilizing polarized hBMECs. Synchronous POWV-LI9 infection of hBMECs and pericytes induced proinflammatory chemokines, interferon-β (IFNβ) and IFN-stimulated genes, with delayed IFNβ secretion by infected pericytes. IFN inhibited POWV infection, but despite IFN secretion a subset of POWV infected hBMECs and pericytes remained persistently infected. These findings suggest a potential mechanism for POWVs (LI9/LI41 and LB) to infect hBMECs, spread basolaterally to pericytes and enter the CNS. hBMEC and pericyte responses to POWV infection suggest a role for immunopathology in POWV neurovirulence and potential therapeutic targets for preventing POWV spread to neuronal compartments. Importance We isolated POWVs from LI deer ticks (I. scapularis) directly in VeroE6 cells and sequencing revealed POWV-LI9 as a distinct lineage II POWV strain. Remarkably, inoculating VeroE6 cells with POWV containing tick homogenates resulted in infected cell foci in liquid culture, consistent with cell to cell spread. POWV-LI9, -LI41, and Lineage I POWV-LB strains infected hBMECs and pericytes that comprise neurovascular complexes. POWVs were nonlytically transmitted basolaterally from infected hBMECs to lower chamber pericytes, suggesting a mechanism for POWV transmission across BBB. POWV-LI9 elicited inflammatory responses from infected hBMEC and pericytes that may contribute to immune cell recruitment and neuropathogenesis. This study reveals a potential mechanism for POWVs to enter the CNS by infecting hBMECs and spreading basolaterally to abluminal pericytes. Our findings reveal that POWV-LI9 persists in cells that form a neurovascular complex spanning the BBB, and suggest potential therapeutic targets for preventing POWV spread to neuronal compartments.
Social, Environmental, and Technical: Factors at Play in the Current Use and Future Design of Small-Group Captioning

Real-time captioning is a critical accessibility tool for many d/Deaf and hard of hearing (DHH) people. While the vast majority of captioning work has focused on formal settings and technical innovations, in contrast, we investigate captioning for informal, interactive small-group conversations, which have a high degree of spontaneity and foster dynamic social interactions. This paper reports on semi-structured interviews and design probe activities we conducted with 15 DHH participants to understand their use of existing real-time captioning services and future design preferences for both in-person and remote small-group communication. We found that our participants' experiences of captioned small-group conversations are shaped by social, environmental, and technical considerations (e.g., interlocutors' pre-established relationships, the type of captioning displays available, and how far captions lag behind speech). When considering future captioning tools, participants were interested in greater feedback on non-speech elements of conversation (e.g., speaker identity, speech rate, volume) both for their personal use and to guide hearing interlocutors toward more accessible communication. We contribute a qualitative account of DHH people's real-time captioning experiences during small-group conversation and future design considerations to better support the groups being captioned, both in person and online.?
Linking Free Text Documentation of Functioning and Disability to the ICF With Natural Language Processing

Background: Invaluable information on patient functioning and the complex interactions that define it is recorded in free text portions of the Electronic Health Record (EHR). Leveraging this information to improve clinical decision-making and conduct research requires natural language processing (NLP) technologies to identify and organize the information recorded in clinical documentation. Methods: We used NLP methods to analyze information about patient functioning recorded in two collections of clinical documents pertaining to claims for federal disability benefits from the U.S. Social Security Administration (SSA). We grounded our analysis in the International Classification of Functioning, Disability and Health (ICF), and used the ICF’s Activities and Participation domain to classify information about functioning in three key areas: Mobility, Self-Care, and Domestic Life. After annotating functional status information in our datasets through expert clinical review, we trained machine learning-based NLP models to automatically assign ICF codes to mentions of functional activity. Results: We found that rich and diverse information on patient functioning was documented in the free text records. Annotation of 289 documents for Mobility information yielded 2,455 mentions of Mobility activities and 3,176 specific actions corresponding to 13 ICF-based codes. Annotation of 329 documents for Self-Care and Domestic Life information yielded 3,990 activity mentions and 4,665 specific actions corresponding to 16 ICF-based codes. NLP systems for automated ICF coding achieved over 80% macro-averaged F-measure on both datasets, indicating strong performance across all ICF codes used. Conclusions: NLP can help to navigate the tradeoff between flexible and expressive clinical documentation of functioning and standardizable data for comparability and learning. The ICF has practical limitations for classifying functional status information in clinical documentation, but presents a valuable framework for organizing the information recorded in health records about patient functioning. This study advances the development of robust, ICF-based NLP technologies to analyze information on patient functioning, and has significant implications for NLP-powered analysis of functional status information in disability benefits management, clinical care, and research.
Real time operation of high-capacity electric vehicle ridesharing fleets

Abstract We study the feasibility of using electric vehicles in online, high-capacity ridepooling systems. Prior work has shown that online algorithms perform well for centrally-controlled, high-capacity ridepool systems. First, we propose a mixed integer linear program to expand past algorithms on ridepooling to electric vehicle fleets with the objective of scheduling vehicle charging to maintain sufficient fleet sizes at various times of day. Then we show a faster, scalable algorithm with similar performance that is practical for full-scale systems. Our contributions reinforce the importance of having knowledge and estimates of future demand even when operating in the online setting.
Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities

We consider the task of learning latent community structure from multiple correlated networks. First, we study the problem of learning the latent vertex correspondence between two edge-correlated stochastic block models, focusing on the regime where the average degree is logarithmic in the number of vertices. We derive the precise information-theoretic threshold for exact recovery: above the threshold there exists an estimator that outputs the true correspondence with probability close to 1, while below it no estimator can recover the true correspondence with probability bounded away from 0. As an application of our results, we show how one can exactly recover the latent communities using multiple correlated graphs in parameter regimes where it is information-theoretically impossible to do so using just a single graph.
Concurrent evolution of anti-aging gene duplications and cellular phenotypes in long-lived turtles.

There are many costs associated with increased body size and longevity in animals, including the accumulation of genotoxic and cytotoxic damage that comes with having more cells and living longer. Yet, some species have overcome these barriers and have evolved remarkably large body sizes and long lifespans, sometimes within a narrow window of evolutionary time. Here, we demonstrate through phylogenetic comparative analysis that multiple turtle lineages, including Galapagos giant tortoises, concurrently evolved large bodies, long lifespans, and reduced cancer risk. We also show through comparative genomic analysis that Galapagos giant tortoises have gene duplications related to longevity and tumor suppression. To examine the molecular basis underlying increased body size and lifespan in turtles, we treated cell lines from multiple species, including Galapagos giant tortoises, with drugs that induce different types of cytotoxic stress. Our results indicate that turtle cells, in general, are resistant to oxidative stress related to aging, while Galapagos giant tortoise cells, specifically, are sensitive to endoplasmic reticulum stress, which may give this species an ability to mitigate the effects of cellular stress associated with increased body size and longevity.
Finding the order in complexity: The electronic structure of 14-1-11 zintl compounds

Yb14MnSb11 and Yb14MgSb11 have rapidly risen to prominence as high-performing p-type thermoelectric materials. However, the fairly complex crystal structure of A14MX11 Zintl compounds renders the interpretation of the electronic band structure obscure, making it difficult to chemically guide band engineering and optimization efforts. In this work, we delineate the valence-balanced Zintl chemistry of A14MX11 compounds using the molecular orbital theory. By analyzing the electronic band structures of Yb14MgSb11 and Yb14AlSb11, we show that the conduction band minimum is composed of either an antibonding molecular orbital originating from the (Sb3)7– trimer or a mix of atomic orbitals of A, M, and X. The singly degenerate valence band is comprised of non-bonding Sb pz orbitals primarily from the Sb atoms in the (MSb4)m– tetrahedra and of isolated Sb atoms distributed throughout the unit cell. Such a chemical understanding of the electronic structure enables strategies to engineer electronic properties (e.g., the bandgap) of A14MX11 compounds.
Plasma-fixated nitrogen as fertilizer for turf grass

We investigated the use of plasma-fixated nitrogen, which produces nitrates (NO3−) in water, as a possible nitrogen fertilizer for recreational turf such as rye grass and bent grass. Experiments were carried out to study the effects of nitrate concentration on growth, the further effects of adding phosphorous (P) and potassium (K) to the plasma nitrated solution to make an N–P–K complete fertilizer, and to compare the efficacy of plasma-fixated nitrogen to sodium nitrate (NaNO3) and potassium nitrate (KNO3). The results indicate that the growth and biomass of the plants were strongly dependent on the concentration of the plasma-fixated nitrogen. Adding P–K to the plasma-fixated nitrogen improved grass growth. Grass that was supplied plasma-fixated nitrogen had improved growth compared to those supplied with equal amounts of NaNO3 and KNO3. This work highlights the potential use of plasma-fixated nitrogen as a fertilizer source for commonly used turf grass.
Mechanics of ultrasonic neuromodulation in a mouse subject

Abstract Ultrasound neuromodulation (UNM), where a region in the brain is targeted by focused ultrasound (FUS), which, in turn, causes excitation or inhibition of neural activity, has recently received considerable attention as a promising tool for neuroscience. Despite its great potential, several aspects of UNM are still unknown. An important question pertains to the off-target sensory effects of UNM and their dependence on stimulation frequency. To understand these effects, we have developed a finite-element model of a mouse, including elasticity and viscoelasticity, and used it to interrogate the response of mouse models to focused ultrasound (FUS). We find that, while some degree of focusing and magnification of the signal is achieved within the brain, the induced pressure-wave pattern is complex and delocalized. In addition, we find that the brain is largely insulated, or ’cloaked’, from shear waves by the cranium and that the shear waves are largely carried away from the skull by the vertebral column, which acts as a waveguide. We find that, as expected, this waveguide mechanism is strongly frequency dependent, which may contribute to the frequency dependence of UNM effects. Our calculations further suggest that off-target skin locations experience displacements and stresses at levels that, while greatly attenuated from the source, could nevertheless induce sensory responses in the subject.
Altered Reinforcement Learning from Reward and Punishment in Anorexia Nervosa: Evidence from Computational Modeling.

OBJECTIVES Anorexia nervosa (AN) is associated with altered sensitivity to reward and punishment. Few studies have investigated whether this results in aberrant learning. The ability to learn from rewarding and aversive experiences is essential for flexibly adapting to changing environments, yet individuals with AN tend to demonstrate cognitive inflexibility, difficulty set-shifting and altered decision-making. Deficient reinforcement learning may contribute to repeated engagement in maladaptive behavior. METHODS This study investigated learning in AN using a probabilistic associative learning task that separated learning of stimuli via reward from learning via punishment. Forty-two individuals with Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 restricting-type AN were compared to 38 healthy controls (HCs). We applied computational models of reinforcement learning to assess group differences in learning, thought to be driven by violations in expectations, or prediction errors (PEs). Linear regression analyses examined whether learning parameters predicted BMI at discharge. RESULTS AN had lower learning rates than HC following both positive and negative PE (p < .02), and were less likely to exploit what they had learned. Negative PE on punishment trials predicted lower discharge BMI (p < .001), suggesting individuals with more negative expectancies about avoiding punishment had the poorest outcome. CONCLUSIONS This is the first study to show lower rates of learning in AN following both positive and negative outcomes, with worse punishment learning predicting less weight gain. An inability to modify expectations about avoiding punishment might explain persistence of restricted eating despite negative consequences, and suggests that treatments that modify negative expectancy might be effective in reducing food avoidance in AN.
Structure and Reactivity of Nitrogenase — An Overview

Nitrogenase is composed of two separately purified proteins called the molybdenum-iron protein (MoFe protein) and the iron protein (Fe protein).1. N2 fixation and all other reductions catalyzed by nitrogenase require both component proteins, a source of reducing equivalents, MgATP, protons and an anaerobic environment. This overview covers what has been learned recently about the composition, structure and redox properties of the two component proteins and the events that occur during nitrogenase turnover. Fortunately, diffraction quality crystals have recently been obtained for both the MoFe protein (Cp1 and Av1; Weiniger, Mortenson, 1982) and the Fe protein (Av2; Rees, Howard, 1983). Thus, many of the questions raised below may soon have definitive answers.
Chapter 2 Chemoattractant Receptors as Regulators of Phagocytic Cell Function

Publisher Summary This chapter discusses the physiological and biochemical parameters of the most thoroughly described chemo-attractant receptors whose physiology may provide a molecular basis for these complex functions of inflammatory cells. Chemoattractants mediate not only the directed migration of leukocytes but also induce a series of coordinated biochemical events, including ion fluxes, cytoskeletal rearrangements associated with morphological polarization, changes in lipid metabolism, activation of protein kinases, production of superoxide anion, and release of lysosomal enzymes. Chemo-attractant-mediated biological and biochemical responses can be divided into two major categories: those functions and biochemical processes that are triggered by the low concentrations of chemoattractants, such as cellular migration, and functions, such as activation of the oxidative burst associated with 10- to 100-fold higher concentrations of chemotactic factors. Advances have been made in the study of leukocyte chemo-attractant receptors mainly because of the availability of large numbers of single-cell suspensions of leukocytes from either peripheral blood or peritoneal exudates as well as the availability of stable, high-affinity, highly purified, radioactive ligands.
New fossil mousebird (Aves: Coliiformes) with feather preservation provides insight into the ecological diversity of an Eocene North American avifauna

Coliiformes (mousebirds) are represented by just six extant species. These species, restricted to sub-Saharan Africa, are all primarily frugivorous and are among the most sedentary of living birds. Previously described fossil Coliiformes preserving feather traces share the short, rounded wing shape of extant mousebirds. Along with osteological evidence, these observations have been proposed to support poor sustained flight capabilities across the stem mousebird lineage. We report a new species of Coliiformes from the early Eocene (51.66 ± 0.09 Ma) Fossil Butte Member of the Green River Formation, represented by one of the comparatively few fossils from these deposits preserving carbonized traces of the wing and tail feathering. Feather traces indicate an elongate, tapering wing shape similar to that of some extant aerial insectivores, and suggestive of a capacity for sustained and agile open-air flight. Traces of the rectrices reveal the tail accounted for approximately two-thirds of the total length of the bird, a proportion similar to that in living mousebirds. Phylogenetic analysis places the new species as a stem representative of Coliiformes, demonstrating for the first time that the two major clades of Coliiformes – Sandcoleidae and Colii – co-occurred at Fossil Lake. Based on the recovered phylogeny, as well as the osteology and feathering of extant and fossil Coliiformes, the wing shape of the new species is interpreted as apomorphic. In addition to documenting unexpected morphological specialization within stem-lineage Coliiformes, the new species adds yet another taxon to the emerging reconstruction of the diverse Paleogene avifauna from the tightly dated and nearly synchronous fossiliferous deposits of the Fossil Butte Member. © 2010 The Linnean Society of London, Zoological Journal of the Linnean Society, 2010, 160, 685–706.
Deciphering the mechanism(s) of action of natural products: analgesic peroxide oil as example.

SUMMARY Background: There are multiple reports of natural products having therapeutic effect. In an era of evidence-based medicine, clinical trials inform clinical decisions regarding use of the product, but prevailing preference is to identify and use a single ‘active ingredient’. Yet, the clinical benefit of a natural product might derive from the fortuitous combination of its multiple components. Therefore, the elucidation of the mechanism(s) of action of natural products is important, but presents significant challenges. This article examines this issue using peroxide oil (essential oxygen oil) as an illustrative example. Objective: To review the published literature of a natural product in an effort to elucidate postulated mechanism(s) of action of a complex mixture. Methods: The clinical and preclinical literature was reviewed from the perspective of its contribution to elucidating a mechanism of analgesic action of a natural product. Results: Peroxide oil contains ingredients that are associated with analgesic mechanisms, such inhibition of lipid peroxidation and arachidonic acid metabolism and non-opioid, glibenclamidesensitive receptor-mediated and KATP–NO–cGMP channel pathways. Conclusion: Although its exact mechanism remains unknown, peroxide oil provides an example of how a natural product can be evaluated for plausible mechanistic explanation of its purported therapeutic efficacy. Such an approach seems valuable, since, as in this case, the constituents appear to contribute in an additive or synergistic manner, something not possible with a single substance.
Essentials of Design Robustness in Design for Six Sigma (DFSS) Methodology

Design for Six Sigma (DFSS) is a systematic process and a disciplined problem prevention approach to achieve business excellence. Robust design is the heart of DFSS. To enable the success of robust parameter design, one should start with good design concept. Axiomatic Design, a fundamental set of principles that determine good design practice, can help to facilitate a project team to accelerate the generation of good design concept. Axiomatic Design holds that uncoupled designs are to be preferred over coupled design. Although uncoupled designs are not always possible, application of axiomatic design principles in DFSS presents an approach to help DFSS team focus on functional requirements to achieve design intents and maximize product reliability. As a result of the application of axiomatic design followed by parameter design, the DFSS team achieved design robustness and reliability. A hydraulic lash adjuster case study will be presented.
Constructing case vignettes for evaluating clinical judgment: An empirical model

Abstract Studies of clinical judgment are frequently based on analogue research, which uses experimenter-controlled stimuli to elicit judgments. The stimuli may be live models, audio- or video-taped models, or written case vignettes describing a clinical encounter. A major challenge of analogue research is to construct stimuli that maintain a balance between experimental rigor and clinical reality. An ideal set of case vignettes, for example, will contain summaries that resemble actual case histories and that are varied only on the specific clinical factors being studied. The model presented here demonstrates the empirical development of written case analogues in which several variables are studied simultaneously. The model can be adapted to any setting in which professionals are required to make judgments or decisions about individuals. The vignettes described here have been used in a variety of clinical settings to assess the reliability of clinicians'judgments and to aid in evaluation and program planning.
An Efficient p-Fold Parallel Algorithm For Computing Robot Inverse Dynamics

This paper shows that the time lower bound of computing the inverse dynamics of an n-link robot manipulator parallelly using p processors is O(k 1 [n/p] + k 2 [log 2 p]), where k 1 and k 2 are constants. A novel parallel algorithm for computing the inverse dynamics using the Newton-Euler equations of motion was developed to be implemented on an SIMD computer with p procesors to achieve the time lower bound. When p = n, the proposed parallel algorithm achieves the Minsky's time lower bound O([log 2 n]) [22], which is the conjecture of parallel evaluation. The proposed p-fold parallel algorithm can be best described as consisting of p-parallel blocks with pipelined elements within each parallel block. The results from the computations in the p blocks form a new homogeneous linear recurrence of size p, which can be computed using the recurive doubling algorithm. A modified inverse perfect shuffle interconnection scheme was suggested to interconnect the p processors. Furthermore, the proposed parallel algorithm is susceptible to a systolic pipelined architecture, requiring three floating-point operations (Flops) per complete set of joint torques.
The transfusion medicine tutor: a case study in the design of an intelligent tutoring system

Empirical studies of medical technology students indicated that there is a considerable need for additional skill development in performing tasks such as antibody identification. The transfusion medicine tutor (TMT) explores the use of a model of expert problem-solving to direct the application of a variety of teaching strategies in such an environment. This tutoring system focuses on red cell antibody identification, which is a problem-solving task where multiple primitive solutions can be true simultaneously. The approach to tutoring is the design of a problem-solving environment in which the computer plays an active role in tutoring the student. TMT allows students to gain experience by exploring a wide range of patient cases. The design of TMT makes it easy for the computer to detect certain types of errors. TMT allows more advanced students to compare the conclusions they have drawn from a particular test result with the computer's interpretation of the same data. >
Smoking status and gastric cancer risk: an updated meta-analysis of case-control studies published in the past ten years

BackgroundA meta-analysis of published studies was performed in order to clarify the risk of gastric cancer associated with cigarette smoking status.MethodsEligible studies were all the case-contro...
Radiation Survival of Food Pathogens in Complex Media

Abstract When 15 bacterial species representing genera associated with food-borne diseases were irradiated individually, all except Escherichia coli and Streptococcus faecalis showed typical linear dose-survival curves in Hartsell's broth. The minimal lethal dose (MLD) for the organisms tested ranged from 3.0 × 105 to 6.0 × 105 rad. Salmonella paratyphi B, S. wichita, S. typhi, E. coli, and S. faecalis were found to be the least sensitive to radiation. In commercially canned crabmeat the survival curves of S. typhi, S. paratyphi B, and S. wichita exhibited to varying degrees an initial linear death decline with increasing radiation doses, followed by a distinct tailing effect caused by survival of low numbers at the higher doses. The above species of Salmonella were further individually subjected to γ-radiation in various dilutions of crabmeat. The “tailing effect” gradually disappeared, with the dose-survival curve tending to become linear as the concentration of the crabmeat decreased.
Digital piracy of MP3s: consumer and ethical predispositions

Purpose – Illegal downloading of music has become an inexorable and rampant activity particularly among college students who have been little deterred by industry legal actions. The purpose of this research is to examine the present state of downloading and how ethical orientation and attitudes towards MP3 piracy impact such activities. The paper also aims to use ethical scenarios as a way of understanding the ethical reasoning in illegal downloading.Design/methodology/approach – Key research questions are proposed that are related to illegal downloading. A sample of 364 university students was used to examine each research question. Statistical results are reported.Findings – The results clearly show that downloading continues at a high rate today driven by a strong belief that it is not ethically wrong. Ethical orientation was found to be positively associated with awareness of the social cost of downloading, consequences of downloading, and ethical belief in downloading. Ethical scenarios show that eth...
Morphology of Phosphate Layer Investigated by Vacuum Depositing a Parylene C Film

Abstract Poly(monochloro-para-xylylene), or parylene C, was used to investigate the morphology of phosphates deposited on cold-rolled steel (CRS) and galvanized cold-rolled steel (GCRS). Vacuum dep...
The forces of matter

And to me too, who loves life, it seems that butterflies and soap-bubbles, and whatever is like them among men, know most about happiness. Nietzsche, Thus Spake Zarathustra The unique properties of the soap bubble, long a focus of science, demonstrated the potential for an air-supported architecture: even under conditions of duress, the bubble enclosed the maximum space with the minimum boundary and required no upright supports. While pneumatic architecture would never attain mainstream acceptability, for those who wished the profession to keep up with the cultural changes of the 1960s, air-supported structures had particular significance. Inflatables not only suggested a democratic alternative to conventional construction, but everything about the air-supported enclosure spoke of continuous change, from its constant adjustment to climatic conditions to the ease of its transportability. Moreover, British scientists had used the soap film to demonstrate that nature was not a series of abstract physical for...
Human adipose data for 2,3,7,8-tetrachlorodibenzo-p-dioxin in certain U.S. samples

Abstract We report the results of analyses of human adipose from 35 autopsy cases from Georgia and Utah for 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD). We also report the effect of storing the samples and our quality control plan. The geometric mean of values for 2,3,7,8-TCDD in these samples on a whole-weight basis was 7.1 ppt. The geometric mean of values for 2,3,7,8-TCDD in 31 of these samples on a lipid basis was 9.6 ppt.