cssi/SciSciGPT-SciSciNet huggingface dataset:
Islands and current singularities in quasisymmetric toroidal plasmas

The presence of current singularities in a quasisymmetric magnetic field is explored. Quasisymmetry is shown effective in isolating Pfirsch–Schluter singularities, to leading order, to a single magnetic surface resonant with the helicity of the symmetry. The effects of pressure driven currents are analyzed, indicating that exclusion of this surface from the plasma volume reduces the potential opening of islands but does not generally eliminate them completely due to higher order asymmetric geometric effects. These three-dimensional effects are contained in quasisymmetry and indicate the complexity of finding consistent solutions and their potential sensitivity. The δ-function current singularities show a distinct quasisymmetric behavior only when the higher-order Fourier content of B is relevant for the resistive stability parameter DR (not included in leading-order near-axis expansions). In such scenarios, quasisymmetry proves advantageous, both in simplicity and avoidance of amplification by low-order rational surfaces.
Non-Monotonicity of Closed Convexity in Neural Codes

Neural codes are lists of subsets of neurons that fire together. Of particular interest are neurons called place cells, which fire when an animal is in specific, usually convex regions in space. A fundamental question, therefore, is to determine which neural codes arise from the regions of some collection of open convex sets or closed convex sets in Euclidean space. This work focuses on how these two classes of codes – open convex and closed convex codes – are related. As a starting point, open convex codes have a desirable monotonicity property, namely, adding non-maximal codewords preserves open convexity; but here we show that this property fails to hold for closed convex codes. Additionally, while adding non-maximal codewords can only increase the open embedding dimension by 1, here we demonstrate that adding a single such codeword can increase the closed embedding dimension by an arbitrarily large amount. Finally, we disprove a conjecture of Goldrup and Phillipson, and also present an example of a code that is neither open convex nor closed convex.
Efficient computation of Jacobian matrices for entropy stable summation-by-parts schemes

Abstract Entropy stable schemes replicate an entropy inequality at the semi-discrete level. These schemes rely on an algebraic summation-by-parts (SBP) structure and a technique referred to as flux differencing. We provide simple and efficient formulas for Jacobian matrices for the semi-discrete systems of ODEs produced by entropy stable discretizations. These formulas are derived based on the structure of flux differencing and derivatives of flux functions, which can be computed using automatic differentiation (AD). Numerical results demonstrate the efficiency and utility of these Jacobian formulas, which are then used in the context of two-derivative explicit time-stepping schemes and implicit time-stepping.
Three-dimensional stochastic numerical breast phantoms for enabling virtual imaging trials of ultrasound computed tomography.

Ultrasound computed tomography (USCT) is an emerging imaging modality for breast imaging that can produce quantitative images that depict the acoustic properties of tissues. Computer-simulation studies, also known as virtual imaging trials, provide researchers with an economical and convenient route to systematically explore imaging system designs and image reconstruction methods. When simulating an imaging technology intended for clinical use, it is essential to employ realistic numerical phantoms that can facilitate the objective, or task-based, assessment of image quality. Moreover, when computing objective image quality measures, an ensemble of such phantoms should be employed that display the variability in anatomy and object properties that is representative of the to-be-imaged patient cohort. Such stochastic phantoms for clinically relevant applications of USCT are currently lacking. In this work, a methodology for producing realistic three-dimensional (3D) numerical breast phantoms for enabling clinically-relevant computer-simulation studies of USCT breast imaging is presented. By extending and adapting an existing stochastic 3D breast phantom for use with USCT, methods for creating ensembles of numerical acoustic breast phantoms are established. These breast phantoms will possess clinically relevant variations in breast size, composition, acoustic properties, tumor locations, and tissue textures. To demonstrate the use of the phantoms in virtual USCT studies, two brief case studies are presented that address the development and assessment of image reconstruction procedures. Examples of breast phantoms produced by use of the proposed methods and a collection of 52 sets of simulated USCT measurement data have been made open source for use in image reconstruction development.
Exploiting Multi-Object Relationships for Detecting Adversarial Attacks in Complex Scenes

Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples. Recent research has shown that checking the intrinsic consistencies in the input data is a promising way to detect adversarial attacks (e.g., by checking the object co-occurrence relationships in complex scenes). However, existing approaches are tied to specific models and do not offer generalizability. Motivated by the observation that language descriptions of natural scene images have already captured the object co-occurrence relationships that can be learned by a language model, we develop a novel approach to perform context consistency checks using such language models. The distinguishing aspect of our approach is that it is independent of the deployed object detector and yet offers very high accuracy in terms of detecting adversarial examples in practical scenes with multiple objects.
microRNA-mediated regulation of microRNA machinery controls cell fate decisions

microRNAs associate with Argonaute proteins, forming the microRNA-induced silencing complex (miRISC), to repress target gene expression post-transcriptionally. Although microRNAs are critical regulators in mammalian cell differentiation, our understanding of how microRNA machinery, such as the miRISC, are regulated during development is still limited. We previously showed that repressing the production of one Argonaute protein, Ago2, by Trim71 is important for mouse embryonic stem cells (mESCs) self-renewal (Liu et al., 2021). Here, we show that among the four Argonaute proteins in mammals, Ago2 is the major developmentally regulated Argonaute protein in mESCs. Moreover, in pluripotency, besides the Trim71-mediated regulation of Ago2 (Liu et al., 2021), Mir182/Mir183 also repress Ago2. Specific inhibition of this microRNA-mediated repression results in stemness defects and accelerated differentiation through the let-7 microRNA pathway. These results reveal a microRNA-mediated regulatory circuit on microRNA machinery that is critical to maintaining pluripotency.
Interpretable data-driven methods for subgrid-scale closure in LES for transcritical LOX/GCH4 combustion

Abstract Although data-driven methods have shown high accuracy as closure models for simulating turbulent flames, these models are often criticized for lack of physical interpretability, wherein they provide answers but no insight into their underlying rationale. In this work, we show that two interpretable machine learning algorithms, namely the random forest regressor and the sparse symbolic regression, can offer opportunities for discovering analytic expressions for subgrid-scale (SGS) terms of a turbulent transcritical flame. These transcritical conditions are found in various combustion systems that operate under high pressures that surpass the thermodynamic critical limit of fuel-oxidizer mixtures, and require the consideration of complex fluid behaviors that can cast doubts on the validity of existing subgrid-scale (SGS) models in large-eddy simulations. To this end, direct numerical simulations (DNS) of transcritical liquid-oxygen/gaseous-methane (LOX/GCH4) inert and reacting flows are performed. Using this data, a priori analysis is performed on the Favre-filtered DNS data to compare the accuracy of random forest SGS-models with conventional physics-based SGS-models. SGS stresses calculated with the gradient model are shown to have good agreement with the exact terms extracted from filtered DNS. Results demonstrate that random forests can perform as effectively as algebraic models when modeling subgrid stresses, when trained on a sufficiently representative database and with a suitable choice of the feature set. The employment of the random forest feature importance score is shown to enable the discovery of a analytic model for subgrid-scale stresses through sparse symbolic regression. The generalizability of random forest and sparse symbolic regression is demonstrated by modeling the subgrid-scale temperature, a term that arises from filtering the non-linear real-fluid equation-of-state, with good accuracy.
Recurrent Mask Refinement for Few-Shot Medical Image Segmentation

Although having achieved great success in medical image segmentation, deep convolutional neural networks usually require a large dataset with manual annotations for training and are difficult to generalize to unseen classes. Few-shot learning has the potential to address these challenges by learning new classes from only a few labeled examples. In this work, we propose a new framework for few-shot medical image segmentation based on prototypical networks. Our innovation lies in the design of two key modules: 1) a context relation encoder (CRE) that uses correlation to capture local relation features between foreground and background regions; and 2) a recurrent mask refinement module that repeatedly uses the CRE and a prototypical network to recapture the change of context relationship and refine the segmentation mask iteratively. Experiments on two abdomen CT datasets and an abdomen MRI dataset show the proposed method obtains substantial improvement over the state-of-the-art methods by an average of 16.32%, 8.45% and 6.24% in terms of DSC, respectively. Code is publicly available.
Multi-agent Reinforcement Learning for Decentralized Stable Matching

In the real world, people/entities usually find matches independently and autonomously, such as finding jobs, partners, roommates, etc. It is possible that this search for matches starts with no initial knowledge of the environment. We propose the use of a multi-agent reinforcement learning (MARL) paradigm for a spatially formulated decentralized two-sided matching market with independent and autonomous agents. Having autonomous agents acting independently makes our environment very dynamic and uncertain. Moreover, agents lack the knowledge of preferences of other agents and have to explore the environment and interact with other agents to discover their own preferences through noisy rewards. We think such a setting better approximates the real world and we study the usefulness of our MARL approach for it. Along with conventional stable matching case where agents have strictly ordered preferences, we check the applicability of our approach for stable matching with incomplete lists and ties. We investigate our results for stability, level of instability (for unstable results), and fairness. Our MARL approach mostly yields stable and fair outcomes.
DeepGreen: deep learning of Green's functions for nonlinear boundary value problems.

Boundary value problems (BVPs) play a central role in the mathematical analysis of constrained physical systems subjected to external forces. Consequently, BVPs frequently emerge in nearly every engineering discipline and span problem domains including fluid mechanics, electromagnetics, quantum mechanics, and elasticity. The fundamental solution, or Green’s function, is a leading method for solving linear BVPs that enables facile computation of new solutions to systems under any external forcing. However, fundamental Green’s function solutions for nonlinear BVPs are not feasible since linear superposition no longer holds. In this work, we propose a flexible deep learning approach to solve nonlinear BVPs using a dual-autoencoder architecture. The autoencoders discover an invertible coordinate transform that linearizes the nonlinear BVP and identifies both a linear operator L and Green’s function G which can be used to solve new nonlinear BVPs. We find that the method succeeds on a variety of nonlinear systems including nonlinear Helmholtz and Sturm–Liouville problems, nonlinear elasticity, and a 2D nonlinear Poisson equation and can solve nonlinear BVPs at orders of magnitude faster than traditional methods without the need for an initial guess. The method merges the strengths of the universal approximation capabilities of deep learning with the physics knowledge of Green’s functions to yield a flexible tool for identifying fundamental solutions to a variety of nonlinear systems.
Readmissions in patients with Cerebral Cavernous Malformations (CCMs): a National Readmission Database (NRD) study.

Background Cerebral cavernous malformations (CCMs) are microvascular CNS lesions prone to hemorrhage leading to neurological sequela such as stroke and seizure. A subset of CCM patients have aggressive disease leading to multiple bleeding events, likely resulting multiple hospitalizations. Hospital admission rates are an important metric that has direct financial impact on hospitals and an indicator of overall disease burden. Furthermore, analysis of hospital readmissions can lead to early identification of high-risk patients and provides insight into the pathogenesis of CCM lesions. The purpose of this study is to identify high risk CCM patients with increased all cause readmission and comorbidities associated with increased readmissions. Methods All US hospital admissions due to CCMs were searched using the 2017 National Readmission Database (NRD). Patients with readmissions within 30 days of discharge from index hospitalization were identified and analyzed, relative to the remaining population. Results Among all patients hospitalized for CCM, 14.9% (13.7-16.2%) required all cause readmission within 30 days. Multivariate logistical regression analysis showed that substance abuse (p=0.003), diabetes (p=0.018), gastrointestinal bleed (p=0.002), renal failure (p=0.027), and coronary artery disease (p=0.010) were predictive of all cause readmissions, while age group 65-74 (p=0.042), private insurance (p Conclusions All identified comorbidities associated with increased risks of readmission contribute to vascular stress, suggesting its role in lesion pathogenesis. This is the first and only study to analyze readmission metrics for CCMs in order to identify high risk patient factors to date.
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies

Resting-state fMRI has been shown to provide surrogate biomarkers for the analysis of various diseases. In addition, fMRI data helps in understanding the brain's functional working during resting state and task-induced activity. To improve the statistical power of biomarkers and the understanding mechanism of the brain, pooling of multi-center studies has become increasingly popular. But pooling the data from multiple sites introduces variations due to hardware, software, and environment. In this paper, we look at the estimation problem of hierarchical Sparsity Connectivity Patterns (hSCPs) in fMRI data acquired on multiple sites. We introduce a simple yet effective matrix factorization based formulation to reduce site-related effects while preserving biologically relevant variations. We leverage adversarial learning in the unsupervised regime to improve the reproducibility of the components. Experiments on simulated datasets display that the proposed method can estimate components with improved accuracy and reproducibility. We also demonstrate the improved reproducibility of the components while preserving age-related variation on a real dataset compiled from multiple sites.
Commutativity of the Haagerup tensor product and base change for operator modules

By computing the completely bounded norm of the flip map on the Haagerup tensor product $C_0 Y_1\otimes_{C_0 X} C_0 Y_2$ associated to a pair of continuous mappings of locally compact Hausdorff spaces $Y_1\rightarrow X\leftarrow Y_2$, we establish a simple characterisation of the Beck-Chevalley condition for base change of operator modules over commutative $C^*$-algebras, and a descent theorem for continuous fields of Hilbert spaces.
Collaborative Causal Discovery with Atomic Interventions

We introduce a new Collaborative Causal Discovery problem, through which we model a common scenario in which we have multiple independent entities each with their own causal graph, and the goal is to simultaneously learn all these causal graphs. We study this problem without the causal sufficiency assumption, using Maximal Ancestral Graphs (MAG) to model the causal graphs, and assuming that we have the ability to actively perform independent single vertex (or atomic) interventions on the entities. If the $M$ underlying (unknown) causal graphs of the entities satisfy a natural notion of clustering, we give algorithms that leverage this property and recovers all the causal graphs using roughly logarithmic in $M$ number of atomic interventions per entity. These are significantly fewer than $n$ atomic interventions per entity required to learn each causal graph separately, where $n$ is the number of observable nodes in the causal graph. We complement our results with a lower bound and discuss various extensions of our collaborative setting.
Verified Quadratic Virtual Substitution for Real Arithmetic.

This paper presents a formally verified quantifier elimination (QE) algorithm for first-order real arithmetic by linear and quadratic virtual substitution (VS) in Isabelle/HOL. The Tarski-Seidenberg theorem established that the first-order logic of real arithmetic is decidable by QE. However, in practice, QE algorithms are highly complicated and often combine multiple methods for performance. VS is a practically successful method for QE that targets formulas with low-degree polynomials. To our knowledge, this is the first work to formalize VS for quadratic real arithmetic including inequalities. The proofs necessitate various contributions to the existing multivariate polynomial libraries in Isabelle/HOL. Our framework is modularized and easily expandable (to facilitate integrating future optimizations), and could serve as a basis for developing practical general-purpose QE algorithms. Further, as our formalization is designed with practicality in mind, we export our development to SML and test the resulting code on 378 benchmarks from the literature, comparing to Redlog, Z3, Wolfram Engine, and SMT-RAT. This identified inconsistencies in some tools, underscoring the significance of a verified approach for the intricacies of real arithmetic.
Toward Uncensorable, Anonymous and Private Access Over Satoshi Blockchains

Providing unrestricted access to sensitive content such as news and software is difficult in the presence of adaptive and resourceful surveillance and censoring adversaries. In this paper we leverage the distributed and resilient nature of commercial Satoshi blockchains to develop the first provably secure, censorship resistant, cost-efficient storage system with anonymous and private access, built on top of commercial cryptocurrency transactions. We introduce max-rate transactions, a practical construct to persist data of arbitrary size entirely in a Satoshi blockchain. We leverage max-rate transactions to develop UWeb, a blockchain-based storage system that charges publishers to self-sustain its decentralized infrastructure. UWeb organizes blockchainstored content for easy retrieval, and enables clients to store and access content with provable anonymity, privacy and censorship resistance properties. We present results from UWeb experiments with writing 268.21 MB of data into the live Litecoin blockchain, including 4.5 months of live-feed BBC articles, and 41 censorship resistant tools. The max-rate writing throughput (183 KB/s) and blockchain utilization (88%) exceed those of state-of-the-art solutions by 2-3 orders of magnitude and broke Litecoin's record of the daily average block size. Our simulations with up to 3,000 concurrent UWeb writers confirm that UWeb does not impact the confirmation delays of financial transactions.
VAINE: Visualization and AI for Natural Experiments

Natural experiments are observational studies where the assignment of treatment conditions to different populations occurs by chance "in the wild". Researchers from fields such as economics, healthcare, and the social sciences leverage natural experiments to conduct hypothesis testing and causal effect estimation for treatment and outcome variables that would otherwise be costly, infeasible, or unethical. In this paper, we introduce VAINE (Visualization and AI for Natural Experiments), a visual analytics tool for identifying and understanding natural experiments from observational data. We then demonstrate how VAINE can be used to validate causal relationships, estimate average treatment effects, and identify statistical phenomena such as Simpson's paradox through two usage scenarios.
Acute Myeloid Leukemias

The acute myeloid leukemias (AML) are a heterogeneous group of malignant diseases of hematopoietic progenitor cells with a spectrum of molecular genetic abnormalities, clinical characteristics, and variable outcomes with available treatments. A virtual explosion has been seen in the identification and characterization of disease alleles in AML in cell culture and murine models of leukemia. These insights have provided a platform for development of molecularly targeted therapies of AML that may improve clinical outcome.
Spectroscopic Signatures of Spin-Charge Separation in a Quasi-One-Dimensional Organic Conductor

In interacting one-dimensional (1D) metals conventional Fermi liquid behavior is expected to break down due to a dynamical decoupling of charge and spin degrees of freedom. Angle-resolved photoelectron spectroscopy (ARPES) on the electronic structure of the quasi-1D organic conductor TTF-TCNQ indeed reveals significant discrepancies to band theory. Instead, the experimental spectra can be well explained by the 1D Hubbard model, which accounts for the intramolecular Coulomb interaction and predicts signatures of spin-charge separation over the entire conduction band width. The model description can even be made quantitative, if one accounts for an enhanced hopping integral at the surface related to a relaxation of the topmost molecular layer. The importance of strong 1D correlation effects is further supported by a remarkable temperature dependence of the ARPES data. These results provide strong spectroscopic evidence for the occurrence of spin-charge separation in the finite energy physics of TTF-TCNQ. Deviations of the Hubbard model description for the low-energy spectral behavior is attributed to the neglect of interchain coupling, long-range Coulomb interaction and/or electron-phonon coupling.
THE BUREAUCRAT AND THE INDIAN

The past decade has witnessed a significant rise in the number of client-advocacy organizations. Their role in the social welfare system has made it necessary for social service agencies to establish relationships with them. This paper examines one dimension of this new type of interorganizational relationship, namely, the problems encountered when a nonbureaucmtically structured Canadian Indian organizational establishes a relationship with a traditional government bureaucracy. The paper proceeds from an analysis of a joint social service program conducted by these two organizations to the implications this had for the evolution of the advocacy organization's identity.
The Godunov Schemes

In one of his earliest papers concerned with numerical schemes for solving equations of Gas Dynamics Godunov (1959) seeks an alternative to the Method of Characteristics. He proposes three main requirements for such schemes. Firstly, they should retain the simplicity of Characteristics Methods while overcoming the inconveniences introduced by shearing and distortion of characteristics networks. Secondly, they should be able to include consideration of surfaces of discontinuity such as shock waves and fluid interfaces. Thirdly, when applied to linearized equations they should predict a solution for physical variables which is in qualitative agreement with analytical solutions.
Exponential Attractors in Banach Spaces

In this paper we extend the theory of exponential attractors from the Hilbert space setting in [4] to the Banach space setting. No squeezing conditions are needed; the only requirements are for the semiflow to be C1 in some absorbing ball, and for the linearized semiflow at every point inside the absorbing ball to split into the sum of a compact operator plus a contraction.
In vitro antimicrobial activity and human pharmacology of cephaloglycin

Serum and urine concentrations of cephaloglycin (an orally absorbed derivative of cephalosporin C) were determined in normal volunteers and in patients. The in vitro activity of cephaloglycin was also studied. All strains of group A streptococci (Streptococcus pyogenes) and Diplococcus pneumoniae were inhibited by 0.4 mug of cephaloglycin per ml. Eighty per cent of the Staphylococcus aureus strains and about 50% of the Escherichia coli and Proteus mirabilis strains were inhibited by 1.6 mug of cephaloglycin per ml. Klebsiella-Aerobacter species were more resistant to cephaloglycin and 12.5 mug per ml was required to inhibit 70% of these strains. When single doses of 250, 500, or 1,000 mg of cephaloglycin were administered to fasting volunteers, a peak serum concentration of at least 0.5 mug per ml was achieved. A full breakfast did not interfere with absorption of cephaloglycin. Probenecid enhanced both the peak serum concentration and the duration of antibiotic activity in the serum. Serum concentrations of cephaloglycin were even higher in patients who were receiving repeated doses. The peak serum concentrations of cephaloglycin in all volunteers and patients were adequate to inhibit all strains of group A streptococci and D. pneumoniae. Many of the peak serum concentrations were adequate to inhibit some strains of S. aureus, E. coli, and P. mirabilis. Urine levels of cephaloglycin were high enough in all volunteers and patients to inhibit more than 90% of the E. coli and P. mirabilis strains and over 70% of the strains of Klebsiella-Aerobacter.
Industry Self-Regulation as a Solution of Reputation Commons: A Case of the Commercial Bank Clearinghouse

The performance of organizations depends partly on the reputations of their industries. Such reputations are “intangible commons.” Interest in protecting mutual welfare motivates members of an industry to engage in self-regulation. However, the current literature tends to have a pessimistic view of the efficacy of self-regulation in solving the problem of reputational commons. We argue that the obstacles forecasted by such pessimistic reasoning are context-bound and can be overcome if industry self-regulation includes effective sanctions and exclusion strategies. We investigate the case of the New York Clearing House Association, a community-based self-regulatory program, which, by promoting prudence among members, successfully ameliorated the negative spillover effect on market confidence during bank panics. We then identify five conditions that account for the efficacy of this self-regulation. We conclude by showing how research on institutional solutions to the problem of reputation commons can be extended.
Energy balance of the PLT tokamak

Abstract PLT discharges are categorized in terms of energy balance into three types: radiation dominated (RD); transport dominated (TD), and an intermediate type (TR). Control of plasma edge conditions is essential for the formation of these types. Measurements and calculations show the relative importance of radiation, transport, and electron-ion coupling in different regions of the discharge. Ion heating for neutral beam injection is found to be effective in all types. Electron heating by neutral beam injection is only consistently obtained for TD discharges.
A phase I study of cediranib in combination with cilengitide in patients with recurrent glioblastoma

Background Despite being a highly vascularized tumor, glioblastoma response to anti-vascular endothelial growth factor (VEGF) therapy is transient, possibly because of tumor co-option of preexisting blood vessels and infiltration into surrounding brain. Integrins, which are upregulated after VEGF inhibition, may play a critical role in this resistance mechanism. We designed a study of cediranib, a vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitor, combined with cilengitide, an integrin inhibitor. Methods This phase I study was conducted through the Adult Brain Tumor Consortium in patients with recurrent glioblastoma. Once the maximum tolerated dose was determined, 40 patients enrolled in a dose expansion cohort with 20 being exposed to anti-VEGF therapy and 20 being naive. The primary endpoint was safety. Secondary endpoints included overall survival, proportion of participants alive and progression free at 6 months, radiographic response, and exploratory analyses of physiological imaging and blood biomarkers. Results Forty-five patients enrolled, and no dose toxicities were observed at a dose of cediranib 30 mg daily and cilengitide 2000 mg twice weekly. Complete response was seen in 2 participants, partial response in 2, stable disease in 13, and progression in 21; 7 participants were not evaluable. Median overall survival was 6.5 months, median progression-free survival was 1.9 months, and progression-free survival at 6 months was 4.4%. Plasma-soluble VEGFR2 decreased with treatment and placental growth factor, carbonic anhydrase IX, and SDF1α, and cerebral blood flow increased. Conclusions The combination of cediranib with cilengitide was well tolerated and associated with changes in pharmacodynamic blood and imaging biomarkers. However, the survival and response rates do not warrant further development of this combination.
Studies of the Negative Effects of Climate Change on Crop Productivityand Global Food Security

Climate change has a non-linearity effect on the global food supplies system when the atmospheric CO 2 reaches a new level. Although one may assume that higher CO 2 may increase the earth vegetations due to the need for CO 2 in photosynthesis, increase in CO 2 has negative effects on plant growth mostly because increases in CO 2 increases the earth temperature causing greater soil moisture evaporations affecting the plant growth. However in certain cases, the increase in warmth along with rain falls has resulted in improved plant growth via the sequestration of airborne CO 2 in plants.
Economic Evaluation of Combined Diet and Physical Activity Promotion Programs to Prevent Type 2 Diabetes Among Persons at Increased Risk: A Systematic Review for the Community Preventive Services Task Force

This systematic review for the CPSTF examined evidence from 28 studies about the cost and cost-effectiveness of combined diet and physical activity promotion programs for persons at increased risk ...
Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual‐Process Model

What role does “discursive consciousness” play in decision-making? How does it interact with “practical consciousness?” These two questions constitute two important gaps in strong practice theory that extend from Pierre Bourdieu's habitus to Stephen Vaisey's sociological dual-process model and beyond. The goal of this paper is to provide an empirical framework that expands the sociological dual-process model in order to fill these gaps using models from cognitive neuroscience. In particular, I use models of memory and moral judgment that highlight the importance of executive functions and semantic memory. I outline each model as it pertains to the aforementioned gaps in strong practice theory. I then use the models from cognitive neuroscience to create an expanded dual-process model that addresses how and when conscious mental systems override and interact with subconscious mental systems in the use of cultural ends for decision-making. Finally, using this expanded model I address the sociological debate over the use of interview and survey data. My analysis reveals that surveys and interviews both elicit information encoded in declarative memory and differ primarily in the process of information retrieval that is required of respondents.
In Vitro Development of Mouse Oocytes

Several aspects of the early in vitro development of the laboratory mouse were examined: oocyte nuclear maturation, fertilization, fertilization of oocytes matured in vitro, and fetal development of oocytes matured and fertilized ii, vitro. Initially, optimum conditions for both oocyte nuclear maturation and fertilization were established. Oocyte nuclear maturation was greatest (91.7%) when oocytes were cultured with cumulus cells. The reduction in maturation when oocytes were cultured without cumulus cells (to 59.2%) was significant (p < 0.02) only when serum was not present in the medium. Fertilization i,i vitro of oviducal oocytes, measured by the number of two-cell ova formed, was greatest (90.1%) when the medium contained 30 mg/ml protein and the oocytes were fertilized with adhering cumulus cells. The removal of the cumulus cells from the oocytes prior to fertilization reduced (p < 0.001) the number of two-cell ova formed (90.1% to 46.3%). Using the optimum conditions which produced 91.7% nuclear maturation and 90.1% fertilization, 37.5% of oocytes matured in vitro were fertilized In vitro. When serum was omitted from the maturation medium a significant drop (p < 0.01) to 22.5% fertilization occurred. When oocytes matured and fertilizedin vitro were transferred into foster mothers, 3.2% developed into 15-day-old fetuses, thus demonstrating that normal oocyte maturation processes can occur in vitro.
Electrical - Mechanical Design of the Bonneville Second Powerhouse

Development of upstream storage in the existing Columbia River basin made it economically attractive to add a second powerhouse to the existing Bonneville Project. The design problem concerned integrating the new powerhouse into a 40 year old project while meeting environmental constraints in river flow and providing for anadromous fish passage. Scope of treatment involves a general discussion of project ectrical and mechanical features with a review of equipment selected and reasons for selection in Certain cases. The resulting discussion provides information on the design of a large low head hydroelectric powerhouse which began commerical operation in 1981
The C. elegans SoxC protein SEM-2 opposes differentiation factors to promote a proliferative blast cell fate in the postembryonic mesoderm

The proper development of multicellular organisms requires precise regulation and coordination of cell fate specification, cell proliferation and differentiation. Abnormal regulation and coordination of these processes could lead to disease, including cancer. We have examined the function of the sole C. elegans SoxC protein, SEM-2, in the M lineage, which produces the postembryonic mesoderm. We found that SEM-2/SoxC is both necessary and sufficient to promote a proliferating blast cell fate, the sex myoblast fate, over a differentiated striated bodywall muscle fate. A number of factors control the specific expression of sem-2 in the sex myoblast precursors and their descendants. This includes direct control of sem-2 expression by a Hox-PBC complex. The crucial nature of the HOX/PBC factors in directly enhancing expression of this proliferative factor in the C. elegans M lineage suggests a possible more general link between Hox-PBC factors and SoxC proteins in regulating cell proliferation.
Reply to Smith and Shortle: Lacking evidence of hydraulic efficiency changes

After calcium silicate amendment to an entire watershed at the Hubbard Brook Experimental Forest, evapotranspiration (ET) increased by ∼20% for 2 y, broadly attributed to a fertilization of tree physiology (1). We suggested that the increase in ET most likely arose from enhanced transpiration due to increased stomatal conductance (gs) associated with increased photosynthesis. Smith and Shortle (2) point out that enhanced xylem conductivity due to increased soil water ionic strength could help account for increased stomatal conductance because of the role calcium plays in the construction and efficiency of xylem water transport. We accept that this may be a relevant mechanism due to the importance of the entire hydraulic architecture of a tree to stomatal function (3). However, although we agree that enhanced xylem conductivity could have contributed to the enhanced ET response after calcium silicate amendment, we have no evidence that this mechanism was active during the enhancement. Our data were consistent with increased photosynthetic capacity [a major control on stomatal conductance (4)], which led to a general stimulation of primary production (tree and leaf biomass) during and after the enhanced ET (1). Thus, the available information leads us to conclude that increased gs was related to increased photosynthesis.
Better to Be

Suppose a couple knows that if they conceive a child, the child’s life on the whole will contain a million units of pleasure and a hundred units of pain. Call this the Lucky Couple. If the Lucky Couple decides to conceive, will their act of conceiving harm the resulting child? Most people would say no. To harm a person is to make things worse for that person than they would otherwise be. If the Lucky Couple conceives a child, the child will experience a great balance of pleasure over pain. If the Lucky Couple does not conceive a child, the child will not exist at all, and thus will not experi enceany pleasure or any pain. It is not worse to experience a great balance of pleasure over pain than not to experience any pleasure or any pain. And so, most people will conclude, if the Lucky Couple decides to conceive, their act of conceiving will not harm the resulting child.
The impact of posttraumatic seizures on 1-year neuropsychological and psychosocial outcome of head injury

This study examined the relationship of posttraumatic seizures and head injury severity to neuropsychological performance and psychosocial functioning in 210 adults who were prospectively followed and assessed 1 year after moderate to severe traumatic head injury. Eighteen percent (n = 38) of the patients experienced 1 or more late seizures (i.e., seizures occurring 8 or more days posttrauma) by the time of the 1-year followup. As expected, the head injured patients who experienced late posttraumatic seizures were those with the most severe head injuries, and they were significantly more impaired on the neuropsychological and psychosocial measures compared to those who remained seizure free. However, after the effects of head injury severity were controlled, there were no significant differences in neuropsychological and psychosocial outcome at 1 year as a function of having seizures. These findings suggest that worse outcomes in patients who develop posttraumatic seizures up to 1 year posttrauma largely reflect the effects of the brain injuries that cause seizures, rather than the effect of seizures.
Reasoning as a Pedagogical Tool: Tolstoy’s Real Happening Stories for Children

Viewing Tolstoy’s works from psychological and intellectual perspectives demonstrates his approach to children’s literacy and especially the development of reasoning, which he presents in his writing for children and the stories he includes in his New ABC book (1875a) and four Readers (1875b). This article examines Tolstoy’s reasoning approach in education and its application in his real happening stories for children. Some of Tolstoy’s ideas about upbringing that are expressed in his stories are similar to ideas of Jean-Jacques Rousseau (1712–1778) and a Swiss developmental physiologist contemporary to Tolstoy, Jean Piaget (1896–1980). Tolstoy’s real happening stories treat situations that a child might actually experience; they propose and teach scenarios that might influence a child’s or an adult’s thinking about ways to obtain an education. Thus, in Tolstoy’s approach to children’s education, reasoning becomes a pedagogical tool, used to develop knowledge, experience and critical thinking ability.
Public managed care: Comprehensive community support in Massachusetts

The restructuring of the system has not come without a price. Along with the successes, there were some unavoidable disruptions in services. Hospital closures, consolidations, and privatization resulted in the dislocation of some staff as a result of layoffs and “bumping,” and particularly affected vendor-operated community clinics to which DMH clinical staff had historically been assigned. This practice was discontinued in June 1991 when the Department “cashed out” the state positions. The clinics (and subsequently, a number of clinical staff) were offered contract funds instead. Not unexpectedly, clients of these clinics, and their family members, resented the disruptions and the uncertainties regarding continuity of care. On balance, a report completed in December 1992 by DMH for the legislature concluded that the vast majority of the Department's patients who were moved as a result of the hospital closures are receiving “equal or better treatment.” As always, there is resistance to change. However, public managed care offers an exciting opportunity and a great challenge — an opportunity to use existing resources to restructure the service system into an effective system of care for people with serious mental illness; and the challenge to maintain access and quality while thoughtfully shifting the locus of care to the community. At the same time the Department must assure consumers, family members, advocates, and legislators that it is committed to providing care in the most normalized setting, in a way that is consumer-focused, and which continues to be responsible for ensuring that appropriate services are in place.
Defining Prognostic Variables in Recurrent Endometrioid Endometrial Cancer: A 15-Year Single-Institution Review

Objective: This study aimed to examine the pattern of recurrence in patients with endometrioid endometrial cancer and to identify clinically important prognostic factors in the recurrent population. Methods: With institutional review board approval, a retrospective review identified 1061 patients who underwent primary surgery and treatment of endometrioid endometrial cancer at our institution from 1994 to 2007. Of this cohort, 77 (7.2%) patients developed a recurrence. Clinical factors were recorded, and Spearman correlation coefficients and χ2 test were used to determine associations between groups. Kaplan-Meier survival estimates and Cox proportional-hazards model were used to determine how prognostic variables affected survival after recurrence (RS) and overall survival (OS). Results: Of 77 patients, site of recurrence was not available in 5 patients. The distribution of recurrence in the remaining 72 patients was as follows: isolated vaginal 18% (13/72), nonvaginal pelvic 12% (9/72), distant 31% (22/72), abdominal 24% (17/72), and nodal 15% (11/72). There was an overrepresentation of advanced stage (P Conclusions: Those patients with high-grade histology at the time of initial diagnosis manifest a decreased OS and RS, suggesting that the intrinsic biology of the tumor has the greatest prognostic importance.
Discourse Rating Tasks: A Teaching Tool for Developing Sociocultural Competence.

This paper introduces a teaching activity designed to address sociocultural competence in the classroom. It recommends the use of discourse rating tasks (DRTs) to develop students awareness of appropriate second language use, and then offers structured practice with DRTs and role-plays as a means of transforming students' sociocultural awareness into sociocultural performance. Two levels of sociocultural competence, speaker-related and context-related factors, are proposed to give teachers and students a more tangible way to target factors involved in appropriate language use. This activity encourages students and teachers to co-construct their learning experience. With these methods, students can go beyond formulaic expressions to convey the subtleties of language appropriate to the communicative situation.
Synthesis, Characterization, and Reactivity of Group 4 Metalloporphyrin Diolate Complexes

A number of group 4 metalloporphyrin diolate complexes were synthesized via various approaches. For example, treatment of imido complex (TTP)HfNAriPr with diols resulted in formation of the corresp...
Patrick LeGales, European Cities(Oxford, United Kingdom: Oxford University Press, 2002). Bernard Jouve and Chritian Lefèvre, Local Power, Territory and Institutions in European Metropolitan Regions(London, United Kingdom: Frank Cass Publishers, 2002). François Baraize et Emmanuel Négrier, L’Invention Politique De L’Agglomèration(Paris, France: L’Harmattan, 2001).

The roots of a discipline can determine its direction, and this is no less true of urban affairs. Because American municipalities exercise more policy discretion than their counterparts in other pa...
Oregon Emergency Medical Technicians' Attitudes toward Physician‐assisted Suicide

. Objectives: To determine Oregon intermediate and advanced emergency medical technicians' (EMTs') attitudes toward physician-assisted suicide (PAS) and factors associated with those attitudes. Methods: An anonymous survey was sent to a random sample of 498 EMTs registered in Oregon. Results: Surveys were delivered to 498 EMTs and 343 completed surveys were returned, for a response rate of 69%. The mean age of the respondents was 37.5 years (±8.73) and 79% were male. 232 (68%) agreed that PAS should be legal, 263 (77%) agreed that terminally ill people have a right to decide to commit suicide, while 57 (17%) thought not attempting resuscitation would be immoral. 251 (73%) reported seeing attempted suicide in terminally ill patients at least once, with 117 (34%) experiencing such calls >5 times. Only 22 (6%) stated that they would be unable to work in a system that directed them to withhold resuscitation after a PAS attempt, and 277 (81%) agreed that treatment protocols should direct EMTs to withhold resuscitation. 105 (31%) thought EMTs should participate in the decision to withhold resuscitation. 206 (60%) thought the law should allow lethal injection for terminally ill patients. 201 (59%) agreed there were circumstances under which they might personally consider PAS. If PAS were legal, EMTs stated they would withhold treatment from a terminally ill patient following attempted suicide in the following circumstances: based on standing orders, 78%; with on-line medical direction, 67%; after speaking with the primary physician, 53%; if the patient had decision-making capacity, 45%; with written documentation from the patient's physician, 68%; and never, 6%. Conclusions: A majority of Oregon EMTs responding to this survey expressed support for PAS, think treatment protocols should direct paramedics to withhold resuscitation in such cases, and would feel comfortable withholding resuscitation given appropriate protocols. Nearly 3 out of 4 Oregon EMTs report seeing at least 1 terminally ill patient who had attempted suicide.