cssi/SciSciGPT-SciSciNet huggingface dataset:
Genetic analysis of coronary artery disease using tree-based automated machine learning informed by biology-based feature selection.

Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-based Pipeline Optimization Tool (TPOT), have been developed to take some of the guesswork out of ML thus making this technology available to users from more diverse backgrounds. The goals of this study were to assess applicability of TPOT to genomics and to identify combinations of single nucleotide polymorphisms (SNPs) associated with coronary artery disease (CAD), with a focus on genes with high likelihood of being good CAD drug targets. We leveraged public functional genomic resources to group SNPs into biologically meaningful sets to be selected by TPOT. We applied this strategy to data from the UK Biobank, detecting a strikingly recurrent signal stemming from a group of 28 SNPs. Importance analysis of these SNPs uncovered functional relevance of the top SNPs to genes whose association with CAD is supported in the literature and other resources. Furthermore, we employed game-theory based metrics to study SNP contributions to individual-level TPOT predictions and discover distinct clusters of well-predicted CAD cases. The latter indicates a promising approach towards precision medicine.
Comment on “The Wave-Driven Current in Coastal Canopies” by M. Abdolahpour et al.

Laboratory and field measurements made over the past decade have shown the presence of a strong wave-driven mean current in submerged vegetation canopies. Luhar et al. (2010) suggested that this mean current is analogous to the streaming flow generated in wave boundary layers over bare beds, and developed a simple energy and momentum balance model to predict its magnitude. However, this model predicts that the magnitude of the mean current does not depend on canopy spatial density, which is inconsistent with the measurements made by Abdolahpour et al. (2017) in recent laboratory experiments. Motivated by observations that the wave-driven mean flow is most pronounced at the canopy interface, Abdolahpour et al. (2017) proposed an alternate explanation for its origin: that it is driven by the vertical heterogeneity in orbital motion created by canopy drag. Such heterogeneity can give rise to incomplete particle orbits near the canopy interface and a Lagrangian mean current analogous to Stokes drift in the direction of wave propagation. A model guided by this physical insight and dimensional analysis is able to generate much more accurate predictions. This comment aims to reconcile these two different models for the wave-driven mean flow in submerged canopies.
Exact Acceleration of K-Means++ and K-Means||.

K-Means++ and its distributed variant K-Means$\|$ have become de facto tools for selecting the initial seeds of K-means. While alternatives have been developed, the effectiveness, ease of implementation, and theoretical grounding of the K-means++ and $\|$ methods have made them difficult to "best" from a holistic perspective. By considering the limited opportunities within seed selection to perform pruning, we develop specialized triangle inequality pruning strategies and a dynamic priority queue to show the first acceleration of K-Means++ and K-Means$\|$ that is faster in run-time while being algorithmicly equivalent. For both algorithms we are able to reduce distance computations by over $500\times$. For K-means++ this results in up to a 17$\times$ speedup in run-time and a $551\times$ speedup for K-means$\|$. We achieve this with simple, but carefully chosen, modifications to known techniques which makes it easy to integrate our approach into existing implementations of these algorithms.
Predicting depression in dementia caregivers: do religious/spiritual struggles play a role?

Using a stress process framework model, the goal of this study was to address the current gap in our understanding of the prevalence and predictive power of specific types of religious/spiritual st...
Selective dephosphorylation by PP2A-B55 directs the meiosis I - meiosis II transition in oocytes

Meiosis is a specialized cell cycle that requires sequential changes to the cell division machinery to facilitate changing functions. To define the mechanisms that enable the oocyte-to-embryo transition, we performed time-course proteomics in synchronized sea star oocytes from prophase I through the first embryonic cleavage. Although we found that protein levels were broadly stable, our analysis reveals that dynamic waves of phosphorylation underlie each meiotic stage. We found that the phosphatase PP2A-B55 is reactivated at the meiosis I/meiosis II (MI/MII) transition, resulting in the preferential dephosphorylation of threonine residues. Selective dephosphorylation is critical for directing the MI/MII transition as altering PP2A-B55 substrate preferences disrupts key cell cycle events after MI. In addition, threonine to serine substitution of a conserved phosphorylation site in the substrate INCENP prevents its relocalization at anaphase I. Thus, through its inherent phospho-threonine preference, PP2A-B55 imposes specific phosphoregulated behaviors that distinguish the two meiotic divisions.
Inscribed rectangles in a smooth Jordan curve attain at least one third of all aspect ratios

We prove that for every smooth Jordan curve $\gamma$, if $X$ is the set of all $r \in [0,1]$ so that there is an inscribed rectangle in $\gamma$ of aspect ratio $\tan(r\cdot \pi/4)$, then the Lebesgue measure of $X$ is at least $1/3$. To do this, we study disjoint Mobius strips bounding a $(2n,n)$-torus link in the solid torus times an interval. We prove that any such set of Mobius strips can be equipped with a natural total ordering. We then combine this total ordering with some additive combinatorics to prove that $1/3$ is a sharp lower bound on the probability that a Mobius strip bounding the $(2,1)$-torus knot in the solid torus times an interval will intersect its rotation by a uniformly random angle.
Facilitators and barriers of children's participation in nutrition, physical activity, and obesity interventions: A systematic review

Recruitment of children into clinical trials is challenging. Most systematic reviews exploring facilitators and barriers of child recruitment in clinical trials are related to drugs or experimental treatments for various health conditions. This may differ in nutrition, physical activity, and obesity interventions. The objective was to conduct a systematic review of facilitators and barriers for children's participation in nutrition, physical activity, and obesity interventions from the perspective of parents, children, and researchers. Studies were identified from five databases and restricted to children 2-18 years and the English language. Studies without results on facilitators and barriers of recruitment were excluded. Four hundred twenty-three records were identified; 94 duplicates and 269 unrelated records were initially excluded; 60 records were reviewed for full-text, and subsequently 34 were excluded, for a total of 26 included studies. The top barriers for recruiting children into clinical trials were time constraints, understanding of clinical trial information or complexity of consent/trial info, and transportation/lack of childcare. The most common facilitators were benefits to others and self, compensation/incentives, physician recommendations/referrals, and support. These barriers and facilitators should be addressed in future studies to assist in the successful recruitment of children into nutrition, physical activity, and obesity interventions.
On the uniqueness of quantal response equilibria and its application to network games

This paper studies the uniqueness of a quantal response equilibrium (QRE) in a broad class of n-person normal form games. We make three main contributions. First, we show that the uniqueness of a QRE is determined by a precise relationship between the strong concavity of players’ payoffs, a bound on the intensity of strategic interaction, and the number of players in the game. Second, we introduce three new parametric models which allow for correlation among alternatives: the generalized nested logit, the ordered generalized extreme value (OGEV), and the nested logit (NL) models. For these three models, we provide a simple uniqueness condition which captures the degree of correlation between players’ actions. Finally, we apply our results to the study of network games. In particular, we apply the OGEV model to study treatment participation and public goods games. In addition, we apply the NL model to study technology adoption in networked environments. In these three applications, we show that the uniqueness of a QRE is determined by the network topology and its interaction with a measure of correlation between players’ actions.
Convergence of a Distributed Kiefer-Wolfowitz Algorithm

This paper proposes a proof of the convergence of a distributed and asynchronous version of the Kiefer-Wolfowitz algorithm where the agents do not exchange information with one another.
Proposal for a continuous wave laser with linewidth well below the standard quantum limit.

Due to their high coherence, lasers are ubiquitous tools in science. We show that by engineering the coupling between the gain medium and the laser cavity as well as the laser cavity and the output port, it is possible to eliminate most of the noise due to photons entering as well as leaving the laser cavity. Hence, it is possible to reduce the laser linewidth by a factor equal to the number of photons in the laser cavity below the standard quantum limit. We design and theoretically analyze a superconducting circuit that uses Josephson junctions, capacitors and inductors to implement a microwave laser, including the low-noise couplers that allow the design to surpass the standard quantum limit. Our proposal relies on the elements of superconducting quantum information, and thus is an example of how quantum engineering techniques can inspire us to re-imagine the limits of conventional quantum systems. Laser performance is constrained by various factors. Here, the authors show theoretically that the linewidth can be reduced below the standard quantum limit by engineering the output coupling of a laser to reduce noise, and discuss the potential practical implementation of this approach.
Situated language learning via interactive narratives.

Summary This paper provides a roadmap that explores the question of how to imbue learning agents with the ability to understand and generate contextually relevant natural language in service of achieving a goal. We hypothesize that two key components in creating such agents are interactivity and environment grounding, shown to be vital parts of language learning in humans, and posit that interactive narratives should be the environments of choice for such training these agents. These games are simulations in which an agent interacts with the world through natural language—perceiving, acting upon, and talking to the world using textual descriptions, commands, and dialogue—and, as such, exist at the intersection of natural language processing, storytelling, and sequential decision making. We discuss the unique challenges a text games' puzzle-like structure combined with natural language state-and-action spaces provides: knowledge representation, common-sense reasoning, and exploration. Beyond the challenges described so far, progress in the realm of interactive narratives can be applied in adjacent problem domains. These applications provide interesting challenges of their own as well as extensions to those discussed so far. We describe three of them in detail: (1) evaluating artificial intelligence (AI) systems’ common-sense understanding by automatically creating interactive narratives; (2) adapting abstract text-based policies to include other modalities, such as vision; and (3) enabling multi-agent and human-AI collaboration in shared, situated worlds.
Mixed-Integer Convex Representability

Motivated by recent advances in solution methods for mixed-integer convex optimization (MICP), we study the fundamental and open question of which sets can be represented exactly as feasible region...
A Framework for Multisensory Foresight for Embodied Agents

Predicting future sensory states is crucial for learning agents such as robots, drones, and autonomous vehicles. In this paper, we couple multiple sensory modalities with exploratory actions and propose a predictive neural network architecture to address this problem. Most existing approaches rely on large, manually annotated datasets, or only use visual data as a single modality. In contrast, the unsupervised method presented here uses multi-modal perceptions for predicting future visual frames. As a result, the proposed model is more comprehensive and can better capture the spatio-temporal dynamics of the environment, leading to more accurate visual frame prediction. The other novelty of our framework is the use of sub-networks dedicated to anticipating future haptic, audio, and tactile signals. The framework was tested and validated with a dataset containing 4 sensory modalities (vision, haptic, audio, and tactile) on a humanoid robot performing 9 behaviors multiple times on a large set of objects. While the visual information is the dominant modality, utilizing the additional non-visual modalities improves the accuracy of predictions.
A Legged Soft Robot Platform for Dynamic Locomotion

This paper presents an open-source untethered quadrupedal soft robot platform for dynamic locomotion (e.g., high-speed running and backflipping). The robot is mostly soft (80 vol.%) while driven by four geared servo motors. The robot’s soft body and soft legs were 3D printed with gyroid infill using a flexible material, enabling it to conform to the environment and passively stabilize during locomotion in multi-terrain environments. In addition, we simulated the robot in a real-time soft body simulation. With tuned gaits in simulation, the real robot can locomote at a speed of 0.9 m/s (2.5 body length/second), substantially faster than most untethered legged soft robots published to date. We hope this platform, along with its verified simulator, can catalyze agile soft robots' development.
Decoding of cortex-wide brain activity from local recordings of neural potentials.

Objective Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions. Approach To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings. Main results The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials. Significance These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.
A registration-free approach for statistical process control of 3D scanned objects via FEM

Abstract Recent work in on-line Statistical Process Control (SPC) of manufactured 3-dimensional (3-D) objects has been proposed based on the estimation of the spectrum of the Laplace-Beltrami (LB) operator, a differential operator that encodes the geometrical features of a manifold and is widely used in Machine Learning (i.e., Manifold Learning). The resulting spectra are an intrinsic geometrical feature of each part, and thus can be compared between parts to assess the state of the manufacturing process while avoiding part to part registration (or “part localization”) pre-processing or the need for equal size meshes, characteristics which are required in previous approaches for SPC of 3D parts. The recent spectral SPC methods, however, are limited to monitoring surface data from objects such that the scanned meshes have no boundaries, holes or missing portions. In this paper we extend spectral methods by first considering a more accurate and general estimator of the LB spectrum that is obtained by application of Finite Element Methods (FEM) to the solution of Helmholtz's equation with boundaries. It is shown how the new spectral FEM approach, while it retains the advantages of not requiring part localization/registration or equal size datasets scanned from each part, it provides more accurate spectrum estimates, which results in faster detection of out of control conditions than earlier methods, can be applied to both mesh or volumetric (solid) scans, and furthermore, it is shown how it can be applied to partial scans that result in open meshes (surface or volumetric) with boundaries, increasing the practical applicability of the methods. The present work brings SPC methods closer to contemporary research in Computer Graphics and Manifold Learning. MATLAB code that reproduces the examples of this paper is provided in the supplementary materials.
Antagonistic effects of chemical mixtures on the oxidative stress response are silenced by heat stress and reversed under dietary restriction

Chemical agents released into the environment can induce oxidative stress in organisms, which is detrimental for health and has been linked to neurodegenerative diseases. C. elegans has been important as model organism to understand oxidative stress caused by chemical agents. In this work, we explore how chemical mixtures drive the oxidative stress response under various conditions. Our results indicate that mixtures drive responses differently than individual components, and that altering environmental conditions, such as increased heat and reduced food availability, result in dramatically different oxidative stress responses mounted by C. elegans. When exposed to heat, the oxidative stress response is diminished. Notably, when exposed to limited food, the oxidative stress response to juglone is significantly heightened, while interactions between some naphthoquinones components in mixtures cease to be antagonistic. This suggests that organismal responses depend on the environment and stressor interactions. Given the high number of variables under study, and their potential combinations, a simplex centroid design was used to capture such non-trivial response over the design space. This makes the case for the adoption of Design of Experiments approaches as they can greatly expand the experimental space probed in noisy biological readouts. Our results also reveal gaps in our current knowledge of the stress response, which can be addressed by employing sophisticated design of experiments approaches to identify significant interactions.
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning

Unsupervised domain adaptation (UDA) enables cross-domain learning without target domain labels by transferring knowledge from a labeled source domain whose distribution differs from the target. However, UDA is not always successful and several accounts of "negative transfer" have been reported in the literature. In this work, we prove a simple lower bound on the target domain error that complements the existing upper bound. Our bound shows the insufficiency of minimizing source domain error and marginal distribution mismatch for a guaranteed reduction in the target domain error, due to the possible increase of induced labeling function mismatch. This insufficiency is further illustrated through simple distributions for which the same UDA approach succeeds, fails, and may succeed or fail with an equal chance. Motivated from this, we propose novel data poisoning attacks to fool UDA methods into learning representations that produce large target domain errors. We evaluate the effect of these attacks on popular UDA methods using benchmark datasets where they have been previously shown to be successful. Our results show that poisoning can significantly decrease the target domain accuracy, dropping it to almost 0\% in some cases, with the addition of only 10\% poisoned data in the source domain. The failure of UDA methods demonstrates the limitations of UDA at guaranteeing cross-domain generalization consistent with the lower bound. Thus, evaluation of UDA methods in adversarial settings such as data poisoning can provide a better sense of their robustness in scenarios unfavorable for UDA.
Machine Learning Based Prediction of Future Stress Events in a Driving Scenario

This paper presents a model for predicting a driver’s stress level up to one minute in advance. Successfully predicting future stress would allow stress mitigation to begin before the subject becomes stressed, reducing or possibly avoiding the performance penalties of stress. The proposed model takes features extracted from Galvanic Skin Response (GSR) signals on the foot and hand and Respiration and Electrocardiogram (ECG) signals from the chest of the driver. The data used to train the model was retrieved from an existing database and then processed to create statistical and frequency features. A total of 42 features were extracted from the data and then expanded into a total of 252 features by grouping the data and taking six statistical measurements of each group for each feature. A Random Forest Classifier was trained and evaluated using a leave-one-subject-out testing approach. The model achieved 94% average accuracy on the test data. Results indicate that the model performs well and could be used as part of a vehicle stress prevention system.
Times series forecasting for urban building energy consumption based on graph convolutional network

Abstract The world is increasingly urbanizing, and to improve urban sustainability, many cities adopt ambitious energy-saving strategies through retrofitting existing buildings and constructing new communities. In this situation, an accurate urban building energy model (UBEM) is the foundation to support the design of energy-efficient communities. However, current UBEM are ineffective to capture the inter-building interdependency due to their dynamic and non-linear characteristics. Those conventional models either ignored or oversimplified these building interdependencies, which can substantially affect the accuracy of urban energy modeling. To fill the research gap, this study proposes a novel data-driven UBEN synthesizing the solar-based building interdependency and spatio-temporal graph convolutional network (ST-GCN) algorithm. Especially, we took a university campus located in the downtown area of Atlanta as an example to predict the hourly energy consumption. Furthermore, we tested the feasibility of the ST-GCN model by comparing the performance of the ST-GCN model with other common time-series machine learning models. The results indicate that the ST-GCN model overall outperforms in different scenarios, the mean absolute percentage error of ST-GCN is around 5%. More importantly, the accuracy of ST-GCN is enhanced when simulating buildings with higher edge weight and in-degrees, this phenomenon is magnified in summer daytime and winter daytime, which validated the interpretability of the ST-GCN models. After discussion, it is found that data-driven models integrated with engineering or physics knowledge can significantly improve urban building energy use prediction.
Surveillance and Security: Technological Politics and Power in Everyday Life

This is a volume of original contributions from scholars in eight different humanities and social science disciplines. The aim of the book is to present a range of surveillance technologies used in everyday life and investigate the politics of their use. It is truly an interdisciplinary project that will find purchase in courses on security studies and the sociology of culture and the sociology of science. Courses on security studies and its impact on culture can be found in a variety of academic departments including STS, criminology, sociology, women's studies, anthropology, political science and justice studies.
Sequence and Misfolding in the Ancient TIM Barrel Motif

Protein folding energy landscapes have been driven by evolution to minimize the energetic and topological frustration experienced during the folding reaction. Small 2 state folders, whose folding r...
Progressive Evaluation of XML Queries for Online Aggregation and Progress Indicator

With the rapid proliferation of XML data, large-scale online applications are emerging. In this research, we aim to enhance the XML query processors with the ability to process queries progressively and report partial results and query progress continually. The methodology lays its foundation on sampling. We shed light on how effective samples can be drawn from semi-structured XML data, as opposed to flat-table relational data. Several innovative sampling schemes on XML data are designed. The proposed methodology advances XML query processing to the next level - being more flexible, responsive, user-informed, and user-controllable, to meet emerging needs and future challenges.
Percutaneous Transjugular Implantation of MELODY® Valve into Tricuspid Bioprosthesis

We present the technique of transcatheter balloon expandable (MELODY®) valve-in-valve deployment in a frail octogenarian with a failed previous tricuspid bioprosthesis. In patients who are not candidates for conventional surgery, transcatheter approach provides an alternative that warrants careful consideration.
Construction and Optimization of a Parallel Engine for Answer Set Programming

In this paper we study the use of parallelism to speed up execution of Answer Set Programs (ASP). ASP is an emerging programming paradigm which combines features from constraint programming, logic programming, and non-monotonic reasoning, and has found relevant applications in areas such as planning and intelligent agents. We propose different methodologies to parallelize execution of ASP programs, and we describe a prototype which exploits one form of parallelism.
Database of Average-Power Damage Thresholds at 1064 nm

We have completed a database of average-power, laser-induced, damage thresholds at 1064 nm on a variety of materials. Measurements were made with a newly constructed laser to provide design input for moderate and high average-power laser projects. The measurements were conducted with 16-ns pulses at pulse-repetition frequencies ranging from 6 to 120 Hz. Samples were typically irradiated for time ranging from a fraction of a second up to 5 minutes (36,000 shots). We tested seven categories of samples which included antireflective coatings, high reflectors, polarizers, single and multiple layers of the same material, bare and overcoated metal surfaces, bare polished surfaces, and bulk materials. The measured damage threshold ranged from 46 J/cm/sup 2/ for a bare polished glass substrate. 4 refs., 7 figs., 1 tab.
Fault-tolerant computer system design

In the ten years since the publication of the first edition of this book, the field of fault-tolerant design has broadened in appeal, particularly with its emerging application in distributed computing. This new edition specifically deals with this dynamically changing computing environment, incorporating new topics such as fault-tolerance in multiprocessor and distributed systems.
Dying for Growth: Global Inequality and the Health of the Poor

Dying for Growth: Global Inequality and the Health of the Poor. Jim Young Kim. Joyce V. Millen. Alec Irwin. and John Gershaman. eds. Monroe, ME: Common Courage Press, 2000. xix. 584 pp.
Learning a sequential search for landmarks

We propose a general method to find landmarks in images of objects using both appearance and spatial context. This method is applied without changes to two problems: parsing human body layouts, and finding landmarks in images of birds. Our method learns a sequential search for localizing landmarks, iteratively detecting new landmarks given the appearance and contextual information from the already detected ones. The choice of landmark to be added is opportunistic and depends on the image; for example, in one image a head-shoulder group might be expanded to a head-shoulder-hip group but in a different image to a head-shoulder-elbow group. The choice of initial landmark is similarly image dependent. Groups are scored using a learned function, which is used to expand them greedily. Our scoring function is learned from data labelled with landmarks but without any labeling of a detection order. Our method represents a novel spatial model for the kinematics of groups of landmarks, and displays strong performance on two different model problems.
Hexa-μ-acetato-1:2κ4O,O′;1:2κ2O:O;2:3κ4O,O′;2:3κ2O:O-bis­(4,4′-dimethyl-2,2′-bi­pyridine)-1κ2N,N′;3κ2N,N′-2-calcium-1,3-dizinc

In the centrosymmetric trinuclear ZnII⋯CaII⋯ZnII title complex, [CaZn2(CH3COO)6(C12H12N2)2], the CaII ion lies on an inversion centre and is octa­hedrally coordinated by six acetate O atoms. The ZnII ion is coordinated by two N atoms from a bidentate di­methyl­bipyridine ligand and three O atoms from acetate ligands bridging to the CaII ion, leading to a distorted square-pyramidal coordination sphere. The Zn⋯Ca distance is 3.4668 (5) A.
Kolmogorov complexity leads to a representation theorem for idempotent probabilities (σ-maxitive measures)

In many application areas, it is important to consider maxitive measures (idempotent probabilities), i.e., mappings m for which m(A ∪ B) = max(m(A), m(B)). In his papers, J. H. Lutz has used Kolmogorov complexity to show that for constructively defined sets A, one maxitive measure - fractal dimension - can be represented as m(A) = sup f(x). We show that a similar representation is possible for an arbitrary maxitive measure.
A CHANCE-CONSTRAINED GOAL PROGRAMMING MODEL TO EVALUATE RESPONSE RESOURCES FOR MARINE POLLUTION DISASTERS

Abstract This paper develops a model to aid Coast Guard managers in formulating appropriate policies with respect to planning for various types of equipment required to contain major pollution incidents. The model is elaborated in terms of three primary stages of response: offloading, containment, and removal. The zero order rule of chance constrained programming is used to obtain a deterministic equivalent of the original chance constrained model. This is then replaced by a goal programming formulation to allow for plans that come “as close as possible” to desired quality and risk levels for each pertinent region and type of incident. Numerical examples illustrate potential uses of the model with special emphasis on its value for budgetary (equipment) planning by central management that extends to evaluation of risk and performance quality levels, as well as the usual dual evaluator approaches for evaluating initially prescribed levels for equipment and their efficiency coefficients.
KIVA-4

The KIVA family of codes was developed to simulate the thermal and fluid processes taking place inside an internal combustion engine. In this latest version of this open source code, KIVA-4, the numerics have been generalized to unstructrured meshes. This change required modifications to the Lagrangian phase of the computations, the pressure solution and fundamental changes in the fluxing schemes of the rezoning phase. This newest version of the code inherits all the droplet phase capabilities and physical sub-models of previous versions. The integration of the gas phase equations with moving solid boundaries continues to employ the successful arbitrary Lagrangian-Eulerian (ALE) methodology. Its new unstructured capability facilitates grid construction in complicated geometries and affords a higher degree of flexibility. The numerics of the code, emphasizing the new additions, are described. Various computational examples are performed demonstrating the new capabilities of the code.
Effects of disulfiram and dopamine beta-hydroxylase knockout on cocaine-induced seizures.

The antialcoholism drug disulfiram has shown recent promise as a pharmacotherapy for treating cocaine dependence, probably via inhibition of dopamine β-hydroxylase (DBH), the enzyme that catalyzes the conversion of dopamine (DA) to norepinephrine (NE). We previously showed that DBH knockout (Dbh -/-) mice, which lack NE, are susceptible to seizures and are hypersensitive to the psychomotor, rewarding, and aversive effects of cocaine, suggesting that disulfiram might exacerbate cocaine-induced seizures (CIS) by inhibiting DBH. To test this, we examined CIS in wild-type and Dbh -/- mice following administration of disulfiram or the selective DBH inhibitor nepicastat. We found that Dbh genotype had no effect on CIS probability or frequency, whereas disulfiram, but not nepicastat, increased the probability of having CIS in both wild-type and Dbh -/- mice. Both disulfiram and nepicastat increased CIS frequency in wild-type but not Dbh -/- mice. There were no genotype or treatment effects on serum cocaine levels, except for an increase in disulfiram-treated Dbh -/- mice at the highest dose of cocaine. These results suggest that disulfiram enhances CIS via two distinct mechanisms: it both increases CIS frequency by inhibiting DBH and increases CIS frequency in a DBH-independent manner.
Why buy when you can rent? A brief investigation of differences in acquisition mode based on duration

This article highlights an intriguing finding that the duration of use significantly affects consumers' choice of acquisition mode. When the duration is short, renting is preferred, while buying is preferred for longer durations, even when the economic consequences of both choices are exactly the same.
Vibrational effects on the polarized light scattering from fluids of spherical molecules in the vertical-vertical geometry

Abstract It is shown that, within the framework of the work of Weinberg and Oppenheim on fluids of spherical molecules with vibrational degrees of freedom, a dispersion in the sound velocity occurs when the rate of vibration-translation exchange is comparable with the reciprocal of the Brillouin frequency. In addition the Brillouin width, in this case, has a more complicated k dependence than k 2 .
Global climatology of inertial instability and Rossby wave breaking in the stratosphere

[1] Climatologies using United Kingdom Met Office assimilated analyses from November 1991 through March 2004 are used to juxtapose the evolution of inertial instability and Rossby wave breaking in longitude, latitude, altitude, and time. The results for the upper and middle stratosphere indicate deep poleward and eastward channels of higher inertial instability frequency extending from the central equatorial Pacific in both winter hemispheres. These corridors of enhanced inertial instability frequency are generally found just poleward of regions of frequent Rossby wave breaking, a result confirmed with a case study drawn from the period of the climatology. Both of these patterns are evident from the stratopause downward into the middle stratosphere, with the frequency of events diminishing with decreasing altitude. Analysis of interannual variability of Rossby wave breaking and inertial instability in the middle stratosphere channels confirms a correlation between them, as well as a possible quasi-biennial oscillation signal in the early years of the climatology. In the lower stratosphere a channel of enhanced inertial instability frequency exists near east Asia in Northern Hemisphere winter, again just poleward of a Rossby wave breaking maximum. These results generally agree closely in space and time with, and significantly extend, the relatively few previously published climatologies and case studies of episodes of Rossby wave-triggered inertial instability for the stratosphere.
Sequence analysis of steroid- and prostaglandin-metabolizing enzymes: application to understanding catalysis.

Amino acid sequence comparisons have revealed that mammalian 11β-hydroxysteroid and 17β-hydroxysteroid dehydrogenases and bacterial 3α,20β- and 3β-hydroxysteroid dehydrogenases are homologs; that is, these enzymes are descended from a common ancestor. These steroid dehydrogenases are also homologous to human 15-hydroxyprostaglandin dehydrogenase and to proteins found in Rhizobia, bacteria that form nitrogen-fixing nodules in the roots of legumes. We constructed a multiple sequence alignment of these proteins, which, when combined with the recently determined tertiary structure of Streptomyces hydrogenans 3α,20β-hydroxysteroid dehydrogenase and a homologous enzyme, rat dihydropteridine reductase, identifies segments and residues that are likely to be structurally important in the functioning of these enzymes, especially regarding specificity for NADPH and NADH.
Poly (ADP-ribose) polymerase 14 and its enzyme activity regulates T(H)2 differentiation and allergic airway disease.

Background IL-4 and signal transducer and activator of transcription 6 (STAT6) play an important role in the progression of allergic airway disease (AAD) or asthma. IL-4 and STAT6 mediate T H 2 responses in T cells and immunoglobulin class-switching to IgE in B cells. Both T H 2 responses and IgE promote the asthmatic condition. We have previously demonstrated that poly (ADP-ribose) polymerase (PARP) 14, a member of the PARP family of proteins, regulates the transcription function of STAT6. However, the role of PARP-14 in AAD is not known. Objective Here we investigate the role of PARP-14 and the enzyme activity associated with it in a model of AAD dependent on airway hyperresponsiveness and lung inflammation. We also elucidate the mechanism by which PARP-14 regulates AAD. Methods The role of PARP-14 and its enzyme activity in AAD and T H 2 differentiation were examined by using a murine model of AAD and in vitro T H cell differentiation. Results PARP-14–deficient animals show reduced lung pathology and IgE levels when compared with control animals. Treating mice with a pharmacologic inhibitor for PARP activity reduced the severity of airway hyperresponsiveness and lung inflammation. Mechanistically, our data indicate that PARP-14 and its enzyme activity aid in the differentiation of T cells toward a T H 2 phenotype by regulating the binding of STAT6 to the Gata3 promoter. Conclusion PARP-14 and the catalytic activity associated with it promote T H 2 differentiation and AAD in a murine model, and targeting PARP-14 might be a potential new therapy for allergic asthma.
Uncovering quantitative protein interaction networks for mouse PDZ domains using protein microarrays.

One of the principal challenges in systems biology is to uncover the networks of protein−protein interactions that underlie most biological processes. To date, experimental efforts directed at this problem have largely produced only qualitative networks that are replete with false positives and false negatives. Here, we describe a domain-centered approach compatible with genome-wide investigations that enables us to measure the equilibrium dissociation constant (KD) of recombinant PDZ domains for fluorescently labeled peptides that represent physiologically relevant binding partners. Using a pilot set of 22 PDZ domains, 4 PDZ domain clusters, and 20 peptides, we define a gold standard dataset by determining the KD for all 520 PDZ−peptide combinations using fluorescence polarization. We then show that microarrays of PDZ domains identify interactions of moderate to high affinity (KD ≤ 10 μM) in a high-throughput format with a false positive rate of 14% and a false negative rate of 14%. By combining the th...
AMONOLITHIC WEIGHING LYSIMETER FOR CHARACTERIZING THE FATE AND TRANSPORT OF AGRICULTURAL CHEMICALS IN SOILS

Four monolithic weighing lysimeters (1.83 m × 1.83 m × 1.52 m deep) were installed at Kansas State University in 1994 with undisturbed soils from two different locations in Kansas. The soil tanks were constructed with 6.4-mm (0.25-in.) thick metal plate, instrumented with solute suction tubes, drain tubes, tensiometers, thermocouples, and neutron probe access tubes; and installed on load cells. A tipping bucket rain gauge was installed to monitor precipitation at the site. Load cells, thermocouples, and the rain gauge were connected to a datalogger and measurements were read automatically through a computer-telephone network system. Herbicides and fertilizers were applied at conventional rates for corn during 1995-1997. Weekly water samples collected from different depths of the lysimeters were analyzed for atrazine and nitrate-N concentrations. Soil moisture contents were measured using a neutron probe and tensiometers. During three years of chemical transport investigation, the system effectively characterized the fate and transport of agricultural chemicals in soils. This system will be utilized to collect several more years of chemical transport data for developing and validating predictive models of chemical leaching through soils.
Influence of extrusion ratio on the thermal properties and morphology of ultradrawn high‐density polyethylene

Solid-state extrusion of high-density polyethylene (HDPE) has received considerable attention. It has been shown that extrudate may have high values of optical clarity, tensile modulus (∼70 GPa = 7 × 1011 dyn/cm2), and c-axis orientation. The effects of extrusion conditions on the properties of the resultant fibers have, however, not yet been clarified. A systematic study has thus been made here to evaluate extrusion pressure, temperature, and extrusion (draw) ratio, and the molecular weight of extruded HDPE. The effects of extrusion ratio on the degree of crystallinity, melting behavior, crystal orientation, and dimensional change along the extrusion direction are reported.
Theories of Violence: A Review of Textbooks on Human Behavior and the Social Environment

This review of 14 frequently used textbooks on human behavior and the social environment was conducted to assess for content regarding theories of violence, including etiology and impact. This analysis begins with a review and summary of James Gilligan's text Violence: Reflections on a National Epidemic, which proposes an integrated theory of violence that includes individual, social, and cultural factors that cause violence. Gilligan's theory provides a useful framework to ground the analysis of textbooks on human behavior and the social environment, which revealed inconsistency regarding content on violence. Few of the textbooks reviewed discussed causes or impact of violence from the individual, social, and environmental perspectives.
Abstract 4935: A quantitative model to study cell-type-specific transcriptional regulation between MCF-7 and LNCaP

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Transcriptional regulation lies at the heart of biological processes. To further understand the regulatory mechanism, we are studying the transcriptional networks of nuclear receptors in breast cancer cell line MCF-7 and prostate cancer cell line LNCaP. Based on whole-genome gene expression microarray data, we observed very different transcriptional programs induced by ligands of nuclear receptors between these two cell lines. In order to systematically explain cell-type-specific transcriptional regulation, we are trying to build a quantitative model to predict gene expression in different cellular contexts under different ligand stimulations. The model will be trained using data including genomic binding sites of nuclear receptors (ChIP-Seq), and time-series expression of nuclear receptors, cofactors and their target genes (Nanostring). The output of the model will be gene expression trajectories after ligand treatments in the two cell lines. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4935. doi:1538-7445.AM2012-4935
Impact of “Signal Ahead” pavement marking on driver behavior at signalized intersections

When drivers are approaching a signalized intersection at the onset of yellow signal, they may hesitate to decide whether to stop or cross the intersection due to the dilemma zone. As defined in the Traffic Engineering Handbook [Institute of Transportation Engineers (ITE). (1999). Traffic engineering handbook, Washington, DC: Institute of Transportation Engineers], the dilemma zone for an intersection is a specific road segment, prior to the intersection in which a vehicle approaching the intersection during the yellow phase can neither safely clear the intersection, nor stop comfortably at the stop line. In this study, a pavement marking countermeasure is proposed to reduce the dilemma zone and improve traffic safety at signalized intersections. A pavement marking with word message "Signal Ahead" that is placed on the pavement upstream of a signalized intersection may have a potential to assist drivers in stop/go decisions and improve driver performance during the signal change. This paper presents a simulator-based study that was designed to test the impact of the pavement marking countermeasure on driving behaviors, including driver's stop/go decision, red-light running violation, brake response time, and deceleration rate of the stopping vehicle. The experiment results indicated that the marking had positive effects on drivers' behaviors at signalized intersections. It was found that the marking can reduce the probabilities of both conservative-stop and risky-go decisions, contribute to a lower red-light running rate, and result in a lower deceleration rate for stopping drivers at higher speed limit intersections. These findings suggest that the marking countermeasure may have a potential to reduce the probabilities of both rear-end and angle crashes.Â Language: en
Snail‐eating frogs from the Ethiopian highlands: a new anuran specialization

Morphological studies and analysis of gut contents indicate that two species of montane Ethiopian frogs are specialized for selective feeding on terrestrial gastropod mollusks. Certain bony elements of the skull, such as the palatines and prevomers, are reduced and deflected dorsally, while lateral elements of the maxillary arch, such as die quadratojugals and maxillaries, are expanded. The nasal apparatus in both species is situated in an extreme anterior position. The two species are removed from the genus Kassina Girard and placed in die genus Tomierella Ahl. Morphology of the head suggests that these frogs grasp mollusks with their jaws, pull diem from die substrate, and swallow them whole. The sensory cues which trigger feeding are as yet unknown. Apparently, diese frogs are the first terrestrial vertebrates known to feed exclusively on whole mollusks, wimout crushing them or removing the soft parts from the shell.