bluuebunny/crossref_metadata_2025 huggingface dataset:
Axial motion of collector plasma in a relativistic backward wave oscillator
Authors: Xiao Renzhen , Chen Changhua , Deng Yuqun , Cao Yibing , Sun Jun , Li Jiawei
Published: June 2016

In this paper, it is proposed that plasma formed at the collector may drift back to the cathode and cause pulse shortening of the relativistic backward wave oscillator. Theoretical analysis shows that the axial drift velocity of plasma ions can be up to 5 mm/ns due to the presence of space charge potential provided by an intense relativistic electron beam. Particle-in-cell simulations indicate that the plasma electrons are initially trapped around the collector surface. With the accumulation of the plasma ions, a large electrostatic field forms and drives the plasma electrons to overcome the space charge potential and enter the beam-wave interaction region along the magnetic field lines. As a result, the beam current modulation is disturbed and the output microwave power falls rapidly. The plasma ions move in the beam-wave interaction region with an average axial velocity of 5–8 mm/ns. After the plasma ions reach the diode region, the emitted current at the cathode rises due to the charge neutralizations by the ions. The impedance collapse leads to further decrease of the microwave power. In experiments, when the diode voltage and beam current were 850 kV and 9.2 kA, and the collector radius was 2.15 cm, the output microwave power was 2.4 GW with a pulse width of less than 20 ns. The ion drift velocity was estimated to be about 5 mm/ns. After an improved collector with 3.35 cm radius was adopted, the pulse width was prolonged to more than 30 ns.
Optimal laser wavelength for efficient laser power converter operation over temperature
Authors: Höhn O. , Walker A. W. , Bett A. W. , Helmers H.
Published: June 2016

A temperature dependent modeling study is conducted on a GaAs laser power converter to identify the optimal incident laser wavelength for optical power transmission. Furthermore, the respective temperature dependent maximal conversion efficiencies in the radiative limit as well as in a practically achievable limit are presented. The model is based on the transfer matrix method coupled to a two-diode model, and is calibrated to experimental data of a GaAs photovoltaic device over laser irradiance and temperature. Since the laser wavelength does not strongly influence the open circuit voltage of the laser power converter, the optimal laser wavelength is determined to be in the range where the external quantum efficiency is maximal, but weighted by the photon flux of the laser.
Fabrication and characterization of a MEMS nano-Tesla ferromagnetic-piezoelectric magnetic sensor array
Authors: Qu Peng , Gollapudi Sreenivasulu , Bidthanapally Rao , Srinivasan Gopalan , Petrov Vladimir , Qu Hongwei
Published: June 2016

A self-biased MEMS magnetic sensor array with ferromagnetic-piezoelectric composites has been fabricated and characterized. The array with two Quartz-Nickel-Metglas cantilevers with nano-tesla sensitivity was fabricated by MEMS processes including silicon-quartz low temperature bonding, quartz wafer thinning, and electroplating of thick nickel thin films. Under self-biasing due to magnetization grading of ferromagnetic layer, magnetoelectric coefficients of 6.6 and 5.6 V/cm Oe and resolutions of ∼0.58 and ∼0.75 nT are obtained at the mechanical resonant frequencies of 191.5 and 184.8 Hz for the two sensors in the array, respectively. Such arrays have the potential for applications in biomagnetic imaging technologies including magneto-cardiography.
An equation for the quench propagation velocity valid for high field magnet use of REBCO coated conductors
Authors: Bonura M. , Senatore C.
Published: June 2016

Based on a study of the thermophysical properties, we derived a practical formula for the normal zone propagation velocity appropriate for REBa2Cu3O7-x coated conductors in high magnetic fields. An analytical expression to evaluate the current sharing temperature as a function of the operating conditions is also proposed. The presented study has allowed us to account for experimental results not fully understood in the framework of the models widely used in the literature. In particular, we provided a fundamental understanding of the experimental evidence that the normal zone propagation velocity in REBa2Cu3O7-x coated conductors can be mainly determined by the operating current, regardless of the applied field and temperature.
Triple-well potential with a uniform depth: Advantageous aspects in designing a multi-stable energy harvester
Authors: Kim Pilkee , Son Dowung , Seok Jongwon
Published: June 2016

Analytical expressions for the bi- and tri-stable conditions of a multi-stable energy harvester (MEH) are derived on the basis of bifurcation analyses, and the associated multi-stable regions are characterized in a 2-D parametric space. It is found that a special boundary condition exists for a triple-well with a uniform depth (TU boundary condition), originating from a degenerate pitchfork bifurcation (DPF) point. Interestingly, the outermost well-to-well distance of the triple-well potential, when subjected to the condition that the maximum well depth is kept constant, becomes widest when the well depth is uniform. Accordingly, instead of investigating all possible parametric conditions, the design parameters for the optimal well configuration of the MEH can be sought most efficiently by simply tracing them on the TU boundary. A detailed examination of the potential well configurations along the TU boundary reveals that the most efficient energy harvesting from low-intensity ambient vibrations can be achieved on a TU boundary point, near the DPF point but inevitably a certain distance apart, by inducing an enlarged interwell motion. This investigation is experimentally validated.
Modelling of electrokinetic phenomena for capture of PEGylated ribonuclease A in a microdevice with insulating structures
Authors: Mata-Gomez Marco A. , Perez-Gonzalez Victor H. , Gallo-Villanueva Roberto C. , Gonzalez-Valdez Jose , Rito-Palomares Marco , Martinez-Chapa Sergio O.
Published: June 2016

Synthesis of PEGylated proteins results in a mixture of protein-polyethylene glycol (PEG) conjugates and the unreacted native protein. From a ribonuclease A (RNase A) PEGylation reaction, mono-PEGylated RNase A (mono-PEG RNase A) has proven therapeutic effects against cancer, reason for which there is an interest in isolating it from the rest of the reaction products. Experimental trapping of PEGylated RNase A inside an electrokinetically driven microfluidic device has been previously demonstrated. Now, from a theoretical point of view, we have studied the electrokinetic phenomena involved in the dielectrophoretic streaming of the native RNase A protein and the trapping of the mono-PEG RNase A inside a microfluidic channel. To accomplish this, we used two 3D computational models, a sphere and an ellipse, adapted to each protein. The effect of temperature on parameters related to trapping was also studied. A temperature increase showed to rise the electric and thermal conductivities of the suspending solution, hindering dielectrophoretic trapping. In contrast, the dynamic viscosity of the suspending solution decreased as the temperature rose, favoring the dielectrophoretic manipulation of the proteins. Also, our models were able to predict the magnitude and direction of the velocity of both proteins indicating trapping for the PEGylated conjugate or no trapping for the native protein. In addition, a parametric sweep study revealed the effect of the protein zeta potential on the electrokinetic response of the protein. We believe this work will serve as a tool to improve the design of electrokinetically driven microfluidic channels for the separation and recovery of PEGylated proteins in one single step.
Sub-terahertz spectroscopy of magnetic resonance in BiFeO3 using a vector network analyzer
Authors: Caspers Christian , Gandhi Varun P. , Magrez Arnaud , de Rijk Emile , Ansermet Jean-Philippe
Published: June 2016

Detection of sub-THz spin cycloid resonances (SCRs) of stoichiometric BiFeO3 (BFO) was demonstrated using a vector network analyzer. Continuous wave absorption spectroscopy is possible, thanks to heterodyning and electronic sweep control using frequency extenders for frequencies from 480 to 760 GHz. High frequency resolution reveals SCR absorption peaks with a frequency precision in the ppm regime. Three distinct SCR features of BFO were observed and identified as Ψ1 and Φ2 modes, which are out-of-plane and in-plane modes of the spin cycloid, respectively. A spin reorientation transition at 200 K is evident in the frequency vs temperature study. The global minimum in linewidth for both Ψ modes at 140 K is ascribed to the critical slowing down of spin fluctuations.
Analysis of low efficiency droop of semipolar InGaN quantum well light-emitting diodes by modified rate equation with weak phase-space filling effect
Authors: Fu Houqiang , Lu Zhijian , Zhao Yuji
Published: June 2016

We study the low efficiency droop characteristics of semipolar InGaN light-emitting diodes (LEDs) using modified rate equation incoporating the phase-space filling (PSF) effect where the results on c-plane LEDs are also obtained and compared. Internal quantum efficiency (IQE) of LEDs was simulated using a modified ABC model with different PSF filling (n0), Shockley-Read-Hall (A), radiative (B), Auger (C) coefficients and different active layer thickness (d), where the PSF effect showed a strong impact on the simulated LED efficiency results. A weaker PSF effect was found for low-droop semipolar LEDs possibly due to small quantum confined Stark effect, short carrier lifetime, and small average carrier density. A very good agreement between experimental data and the theoretical modeling was obtained for low-droop semipolar LEDs with weak PSF effect. These results suggest the low droop performance may be explained by different mechanisms for semipolar LEDs.
Evolution of a multilevel framework for health program evaluation
Authors: Masso Malcolm , Quinsey Karen , Fildes Dave
Published: June 2016

A well-conceived evaluation framework increases understanding of a program’s goals and objectives, facilitates the identification of outcomes and can be used as a planning tool during program development. Herein we describe the origins and development of an evaluation framework that recognises that implementation is influenced by the setting in which it takes place, the individuals involved and the processes by which implementation is accomplished. The framework includes an evaluation hierarchy that focuses on outcomes for consumers, providers and the care delivery system, and is structured according to six domains: program delivery, impact, sustainability, capacity building, generalisability and dissemination. These components of the evaluation framework fit into a matrix structure, and cells within the matrix are supported by relevant evaluation tools. The development of the framework has been influenced by feedback from various stakeholders, existing knowledge of the evaluators and the literature on health promotion and implementation science. Over the years, the framework has matured and is generic enough to be useful in a wide variety of circumstances, yet specific enough to focus data collection, data analysis and the presentation of findings. What is known about the topic? Evaluation in healthcare typically investigates the implementation of complex innovations in uncontrolled ‘real world’ settings. This presents many challenges for evaluators and those wanting to commission evaluations. What does this paper add? Herein we describe the origins and development of an evaluation framework that is structured in terms of three levels and six domains. The framework has stood the test of time and been used to evaluate a variety of innovations in the delivery of health and aged care. Novel aspects of the framework include the concepts of levels, capacity building and sustainability. What are the implications for practitioners? The structure of the evaluation framework is simple, yet comprehensive, and is suitable for use in a wide range of settings. The framework can also be used to both evaluate and plan the implementation of innovations in health service delivery.
Superresolution imaging reveals nanometer- and micrometer-scale spatial distributions of T-cell receptors in lymph nodes
Authors: Hu Ying S. , Cang Hu , Lillemeier Björn F.
Published: June 2016

Significance

T-cell receptors (TCRs) recognize pathogens during T-cell–mediated adaptive immune responses. Here we directly observed the organization of TCRs and their rearrangement on lymph node-resident T cells during an immune response. We found that TCRs were preclustered into nanometer-scale protein islands, which were organized into larger membrane territories, and that T-cell activation induced the formation of microclusters. Our data provide the first evidence, to our knowledge, of subdiffraction membrane organizations during immune responses in an animal model system.
Conserved 33-kb haplotype in the MHC class III region regulates chronic arthritis
Authors: Yau Anthony C. Y. , Tuncel Jonatan , Haag Sabrina , Norin Ulrika , Houtman Miranda , Padyukov Leonid , Holmdahl Rikard
Published: June 2016

Significance

The role of the MHC region has been a long-standing issue in chronic inflammatory diseases, such as rheumatoid arthritis, and it has not been possible to identify the underlying specific polymorphism. Here, we provide evidence that some of the MHC association must be explained by how closely linked genes operate together as haplotype blocks. We identified a conserved haplotype,
Ltab-Ncr3,
comprising five genes (
lymphotoxin α
and
β, Tnf
,
leukocyte-specific transcript 1
, and
natural cytotoxicity-triggering receptor 3
) within MHC class III, regulating arthritis. We found significant coexpression of the
Ltab-Ncr3
genes, indicating how these genes may work together as a haplotype. Furthermore, haplotype-specific differences in
Ltab-Ncr3
gene expression and alternative splicing correlate remarkably to susceptibility to arthritis. Our data show that a conserved haplotype within MHC class III regulates arthritis development.
Defining chromosomal translocation risks in cancer
Authors: Hogenbirk Marc A. , Heideman Marinus R. , de Rink Iris , Velds Arno , Kerkhoven Ron M. , Wessels Lodewyk F. A. , Jacobs Heinz
Published: June 2016

Significance

Applying innovative integrative analyses of multifactorial genome-wide data, we now demonstrate that an open chromatin configuration, which is generically enriched promoter-proximal but not promoter-specific, is the common denominator and key translocation risk-determinant of active chromatin. The finding that gene size directly correlated with its translocation risk, in both mice and cancer patients, independently emphasized the generic irrelevance of any promoter-specific activity. These data exclude activation-induced cytidine deaminase, Spt5, transcription, and promoter-proximal regions as critical risk-determinants and specific targets for genome-wide chromosomal translocations. Our insights are fundamental in understanding the origin of chromosome translocations and, consequently, cancer.
Singlet oxygen- and EXECUTER1-mediated signaling is initiated in grana margins and depends on the protease FtsH2
Authors: Wang Liangsheng , Kim Chanhong , Xu Xia , Piskurewicz Urszula , Dogra Vivek , Singh Somesh , Mahler Hanno , Apel Klaus
Published: June 2016

Significance

Singlet oxygen (
1
O
2
)- and EXECUTER1 (EX1)-dependent signaling triggers programmed cell death in seedlings and inhibits growth of mature plants of the
fluorescent
(
flu
) mutant of
Arabidopsis
. The EX1 protein has been located in chloroplasts to the grana margins close to where chlorophyll is synthesized and the disassembly of damaged photosystem II (PSII) and reassembly of active PSII take place. With the onset of
1
O
2
-mediated signaling there is a rapid decline of EX1 that depends on the ATP-dependent zinc metalloprotease FtsH. Generation of
1
O
2
without the decline of EX1 is not sufficient to activate
1
O
2
signaling. As FtsH cleaves also the D1 reaction center protein of damaged PSII, EX1-dependent signaling seems not only spatially but also functionally linked to the repair of PSII.
Emergent perversions in the buckling of heterogeneous elastic strips
Authors: Liu Shuangping , Yao Zhenwei , Chiou Kevin , Stupp Samuel I. , Olvera de la Cruz Monica
Published: June 2016

Significance

Perversions in an otherwise uniform helical structure provide the mechanism of helical symmetry breaking. In this work, using a three-dimensional elastomeric bistrip model, we investigate the intrinsic properties of perversions that are independent of specific strip shapes. Besides the fundamental role as generic domain walls that connect states of distinct symmetries, this study reveals richer physics of perversions in the three-dimensional elastic system. The major findings include the condensation of strain energy over perversions, the identification of the repulsive nature of the perversion–perversion interaction, and the coalescence of perversions. These intrinsic properties of perversions may have implications to the understanding of relevant biological motifs and the designing of micromuscles and soft robotics.
Glass‐Eel‐Stage American Eels Respond to Conspecific Odor as a Function of Concentration
Authors: Schmucker Andrew K. , Johnson Nicholas S. , Galbraith Heather S. , Li Weiming
Published: June 2016

The American Eel Anguilla rostrata has experienced staggering population declines in recent decades and is now the focus of restoration efforts. Studies have demonstrated that olfaction is critical to anguillid behavior and that glass eels (the life stage which migrates inland from saltwater to freshwater) are attracted to conspecific washings. We evaluated conspecific cueing as a potential mechanism for American Eel inland migration coordination by assessing (1) the affinity of glass eels to conspecific washings, (2) the concentration–response relationships, and (3) changes in responsiveness to washings during the glass eel‐to‐elver transition. In two‐choice maze assays, glass eels were attracted to glass eel washings over a wide range of concentrations (0.20–0.40 g of glass eels·L−1·h−1), and a logarithmic function provided the best fit to the concentration–response relationship. When given a choice between two conspecific washings of higher and lower concentrations, the glass eels generally preferred the higher concentration. Responses to undiluted glass eel washings did not significantly differ among stage‐3–7 glass eels, although stage‐7 eels were not attracted to the washings, whereas the other stages were. Washing affinity remained similar over the course of several weeks. These results support aspects of the conspecific cueing hypothesis at the glass eel life stage under laboratory conditions, suggesting that conspecific cueing is an important component of migration coordination among juvenile American Eels and warrants additional study.

Received September 11, 2015; accepted January 20, 2016 Published online June 15, 2016
Trends in Abundance of Northern Snakeheads in Virginia Tributaries of the Potomac River
Authors: Odenkirk John S. , Isel Mike W.
Published: June 2016

A population of nonnative Northern Snakeheads Channa argus was documented in the Potomac River system during 2004. We estimated relative abundance (fish/h of boat electrofishing) for up to 12 years in four Virginia creeks within and downstream of the original area of colonization. Population estimates were also calculated for adult Northern Snakeheads in Little Hunting Creek (one of the four study creeks). Relative abundance increased dramatically after colonization, but trends suggest that increases in abundance may have slowed. Population estimates for Little Hunting Creek (12–22 fish/ha) declined each year from 2013 to 2015, supporting the assertion that Northern Snakehead density increases have slowed or that density has stabilized in some creeks.

Received October 6, 2015; accepted January 26, 2016 Published online June 15, 2016
Effects of No Feeding, Maintenance Feeding, and Refeeding on Production and Processing Characteristics of Market-Size Hybrid Catfish
Authors: Li Menghe H , Wise David J , Bosworth Brian G , Lucas Penelope M , Kingery Kyle
Published: June 2016

A pond study was initiated to evaluate effects of no feeding, maintenance feeding, and refeeding on production and processing characteristics of market-size hybrid catfish (female Channel Catfish Ictalurus punctatus × male Blue Catfish I. furcatus). Fish with an average weight of 644 g were stocked into 20 earthen ponds (0.04 ha) at 14,826 fish/ha at the end of May. They were either not fed (N2), fed once weekly (W2) to satiation for 2 months to simulate a long-term harvest delay, or fed daily (D2) to satiation. After 2 months fish in half the ponds in each of the two feed-restricted treatments were harvested, and all fish in the remaining ponds were fed daily for an additional month. After 2 months N2 fish experienced a 14.3% weight loss compared with a weight gain of 6.7% for FW2 fish. After 2 months both N2 and W2 fish had reduced visceral fat and fillet yield compared with fish fed daily, but there were no significant differences in visceral fat percentage and fillet yield between N2 and W2 fish. At the end of 3 months, there were no significant differences in weight gain, net yield, fillet yield, or visceral fat whether fish were previously not fed or fed once weekly for the first 2 months, but fish fed daily throughout had significantly higher visceral fat and marginally higher fillet yield. Feeding once weekly for 2 months followed by 1-month full feeding resulted in significantly higher feed conversion ratio than fish fed daily for 3 months. Results demonstrate feeding once weekly can generally maintain body weight of hybrid catfish. No feeding or feeding once weekly for 2 months does not affect survival but significantly reduces fillet yield. One month of full feeding following no feeding or maintenance feeding improves fillet yield relative to values before refeeding.
Use of Copper Sulfate to Control Egg Saprolegniasis at a Commercial Sunshine Bass Hatchery
Authors: Straus David L , Farmer Bradley D , Ledbetter Cynthia K , Beck Benjamin H , Williams Rick S , Clark Mike L , Freeze T Mike
Published: June 2016

An obstacle to the larval production of sunshine bass (female White Bass Morone chrysops × male Striped Bass M. saxatilis) is fungal growth on the eggs caused by the water mold, Saprolegnia spp. Copper sulfate (CuSO4) is commonly used for fungus control in troughs at catfish hatcheries, but the effectiveness in other fish-egg hatching systems is unknown. Because sunshine bass eggs begin hatching after 48 h, CuSO4 treatments (0, 10, 20, and 40 mg/L) began the afternoon of spawning with a 10-min, aerated, static bath and were repeated the morning and afternoon of day 2; eggs were not treated after hatching began. An in vitro assay was developed for this treatment regimen that indicated maximum fungal inhibition was achieved with 20 mg/L CuSO4. In the effectiveness experiment in McDonald hatching jars (n = 3), fungus was severe in the untreated controls (27.7% survival), but very little fungus was present in treatments receiving 10 mg/L CuSO4 (31.4% survival) or higher. The control was not significantly different from the 10-mg/L treatment. The highest survival was at 40 mg/L CuSO4 (50.5% survival); however, the survival from the 20-mg/L CuSO4 treatment (45.8%) was not significantly different from that in the 40-mg/L treatment and thus allows for a greater margin of safety. Fungus samples were identified as Saprolegnia ferax through genetic sequencing. Toxicity experiments on sunshine bass larvae indicated the 24- and 48-h LC50 values were 5.4 and 3.9 mg/L CuSO4, respectively; the no observed effect concentrations were 0.5 and 0.25 mg/L CuSO4, respectively. This study confirms that CuSO4 can be an economical and valuable resource in hatchery management for the control of saprolegniasis on sunshine bass eggs in McDonald jars.
Effects of Rearing Density on Return to Creel of Hatchery Catchable Rainbow Trout Stocked in Idaho Lentic Waters
Authors: Cassinelli John D , Meyer Kevin A , Koenig Martin K
Published: June 2016

Evaluating rearing techniques that maximize angler returns to creel of hatchery trout is an essential tool in shaping hatchery management practices and maximizing the public use of hatchery products. The goal of this study was to determine the effects of raceway rearing density on return to creel of catchable-sized (mean TL ≈ 252 mm) hatchery Rainbow Trout Oncorhynchus mykiss. In 2011 and 2012, Idaho Department of Fish and Game reared catchable-sized trout targeting three maximum density indices (0.15, 0.25, and 0.30 lb·ft−3·in−1) at three different state fish hatcheries. Each hatchery stocked fish into the same 11 lakes and reservoirs to evaluate return-to-creel rates by rearing density. Although there was a trend of lower angler catch for fish reared at a higher raceway density, the relationship was not statistically significant. Instead, angler catch was significantly influenced by fish size at stocking and the surface area of the water being stocked, whereby larger fish and smaller waters had higher return-to-creel rates. At the densities tested in this study, we concluded that fish size at stocking is more important than rearing density in determining return-to-creel rates for hatchery catchable Rainbow Trout. Rearing trout at a lower density reduces total hatchery production while not providing a sufficient increase in returns to creel to offset the decreased production.
Inheritance of Red Eyes in Ornamental Koi Carp
Authors: Gomelsky Boris , Warner Jeffrey L , Delomas Thomas A , Nason Laurel A
Published: June 2016

The purpose of this study was to investigate the inheritance of red eyes in ornamental koi, a variant of Common Carp Cyprinus carpio. The study included crossing fish with different eye color phenotypes and analyzing fish segregations in progenies. In progeny 1, obtained by crossing a red-eyed, yellow male with a black-eyed, white-red female, the segregation “red eyes : black eyes” in juveniles did not differ significantly from the 1:1 Mendelian ratio. In two progenies obtained by crosses of red-eyed fish from progeny 1, the segregations of larvae with light and dark lenses and the segregations “red eyes : black eyes” in juveniles not having black pigmentation on the body did not differ from the 3:1 Mendelian ratio. In two progenies obtained by crosses of black-eyed fish from progeny 1, larvae with only dark lenses and juveniles with only black eyes were observed. Based on these data, it was suggested that the appearance of red eyes in koi is controlled by a dominant mutation of one gene (R/r); koi with genotypes RR and Rr have red eyes, while koi with genotype rr do not possess this trait. Significant proportions of juveniles from fish of progeny 1 had black pigmentation on the body. In pigmented juveniles the ratio red eyes : black eyes was shifted towards black-eyed fish likely due to the influence of genes controlling the development of melanin on the body on the expression of mutation R. Based on the occurrence of fish with red eyes and black pigmentation on the body it was suggested that the appearance of red eyes in koi is caused not by an albino but by another demelanization mutation. In a progeny obtained by crossing a red-eyed female from progeny 1 with a Common Carp with wild-type color, all fish had black eyes while about 50% of the fish in this progeny had a light yellowish body. This shows that the mutation R causes the appearance of red eyes only in koi; in Common Carp with wild-type color this mutation causes only partial demelanization of the fish's body.
Comprehensive evaluation of the linear stability of Alfvén eigenmodes driven by alpha particles in an ITER baseline scenario
Authors: Figueiredo A.C.A. , Rodrigues P. , Borba D. , Coelho R. , Fazendeiro L. , Ferreira J. , Loureiro N.F. , Nabais F. , Pinches S.D. , Polevoi A.R. , Sharapov S.E.
Published: June 2016

The linear stability of Alfvén eigenmodes in the presence of fusion-born alpha particles is thoroughly assessed for two variants of an ITER baseline scenario, which differ significantly in their core and pedestal temperatures. A systematic approach based on CASTOR-K (Borba and Kerner 1999 J. Comput. Phys. 153 101; Nabais et al 2015 Plasma Sci. Technol. 17 89) is used that considers all possible eigenmodes for a given magnetic equilibrium and determines their growth rates due to alpha-particle drive and Landau damping on fuel ions, helium ashes and electrons. It is found that the fastest growing instabilities in the aforementioned ITER scenario are core-localized, low-shear toroidal Alfvén eigenmodes. The largest growth-rates occur in the scenario variant with higher core temperatures, which has the highest alpha-particle density and density gradient, for eigenmodes with toroidal mode numbers

n
≈
30

. Although these eigenmodes suffer significant radiative damping, which is also evaluated, their growth rates remain larger than those of the most unstable eigenmodes found in the variant of the ITER baseline scenario with lower core temperatures, which have

n
≈
15

and are not affected by radiative damping.
Continuum-wise expansiveness and specification for set-valued functions and topological entropy
Authors: Cordeiro Welington , Pacífico Maria
Published: June 2016

We define the concept of continuum-wise expansiveness for set-valued functions. We prove that for a compact metric space

X
X

with positive topological dimension, if a set-valued function is

c
w

cw

-expansive, then its topological entropy is positive. We also introduce the notion of point-wise specification property for set-valued functions and prove that set-valued functions with this property have positive entropy.
Upper bound of the multiplicity of a Du Bois singularity
Authors: Shibata Kohsuke
Published: June 2016

This paper answers in the affirmative a question raised by Huneke and Watanabe concerning an upper bound on the multiplicity of a normal Cohen-Macaulay Du Bois singularity.
Monotonicity of zeros of Jacobi-Angelesco polynomials
Authors: dos Santos Eliel
Published: June 2016

We study the monotonic behaviour of the zeros of the multiple Jacobi-Angelesco orthogonal polynomials, in the diagonal case, with respect to the parameters

α
,
β

\alpha ,\beta

and

γ
\gamma

. We prove that the zeros are monotonic functions of

α
\alpha

and

γ
\gamma

and consider some special cases of how the zeros depend on

β
\beta

, especially in the presence of symmetry. As a consequence we obtain results about monotonicity of zeros of Jacobi-Laguerre and Laguerre-Hermite multiple orthogonal polynomials too.
Independence of volume and genus 𝑔 bridge numbers
Authors: Purcell Jessica , Zupan Alexander
Published: June 2016

A theorem of Jorgensen and Thurston implies that the volume of a hyperbolic 3–manifold is bounded below by a linear function of its Heegaard genus. Heegaard surfaces and bridge surfaces often exhibit similar topological behavior; thus it is natural to extend this comparison to ask whether a

(
g
,
b
)

(g,b)

-bridge surface for a knot

K
K

in

S
3

S^3

carries any geometric information related to the knot exterior. In this paper, we show that — unlike in the case of Heegaard splittings — hyperbolic volume and genus

g
g

-bridge numbers are completely independent. That is, for any

g
g

, we construct explicit sequences of knots with bounded volume and unbounded genus

g
g

-bridge number, and explicit sequences of knots with bounded genus

g
g

-bridge number and unbounded volume.
DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank
Authors: Yuan Qingjun , Gao Junning , Wu Dongliang , Zhang Shihua , Mamitsuka Hiroshi , Zhu Shanfeng
Published: June 2016

Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets.

Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning.

Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs.

Availability:  http://datamining-iip.fudan.edu.cn/service/DrugE-Rank

Contact:  zhusf@fudan.edu.cn

Supplementary information:  Supplementary data are available at Bioinformatics online.
Jumping across biomedical contexts using compressive data fusion
Authors: Zitnik Marinka , Zupan Blaz
Published: June 2016

Motivation: The rapid growth of diverse biological data allows us to consider interactions between a variety of objects, such as genes, chemicals, molecular signatures, diseases, pathways and environmental exposures. Often, any pair of objects—such as a gene and a disease—can be related in different ways, for example, directly via gene–disease associations or indirectly via functional annotations, chemicals and pathways. Different ways of relating these objects carry different semantic meanings. However, traditional methods disregard these semantics and thus cannot fully exploit their value in data modeling.

Results: We present Medusa, an approach to detect size-k modules of objects that, taken together, appear most significant to another set of objects. Medusa operates on large-scale collections of heterogeneous datasets and explicitly distinguishes between diverse data semantics. It advances research along two dimensions: it builds on collective matrix factorization to derive different semantics, and it formulates the growing of the modules as a submodular optimization program. Medusa is flexible in choosing or combining semantic meanings and provides theoretical guarantees about detection quality. In a systematic study on 310 complex diseases, we show the effectiveness of Medusa in associating genes with diseases and detecting disease modules. We demonstrate that in predicting gene–disease associations Medusa compares favorably to methods that ignore diverse semantic meanings. We find that the utility of different semantics depends on disease categories and that, overall, Medusa recovers disease modules more accurately when combining different semantics.

Availability and implementation: Source code is at http://github.com/marinkaz/medusa

Contact:  marinka@cs.stanford.edu, blaz.zupan@fri.uni-lj.si
PHOCOS: inferring multi-feature phenotypic crosstalk networks
Authors: Deng Yue , Altschuler Steven J. , Wu Lani F.
Published: June 2016

Motivation: Quantification of cellular changes to perturbations can provide a powerful approach to infer crosstalk among molecular components in biological networks. Existing crosstalk inference methods conduct network-structure learning based on a single phenotypic feature (e.g. abundance) of a biomarker. These approaches are insufficient for analyzing perturbation data that can contain information about multiple features (e.g. abundance, activity or localization) of each biomarker.

Results: We propose a computational framework for inferring phenotypic crosstalk (PHOCOS) that is suitable for high-content microscopy or other modalities that capture multiple phenotypes per biomarker. PHOCOS uses a robust graph-learning paradigm to predict direct effects from potential indirect effects and identify errors owing to noise or missing links. The result is a multi-feature, sparse network that parsimoniously captures direct and strong interactions across phenotypic attributes of multiple biomarkers. We use simulated and biological data to demonstrate the ability of PHOCOS to recover multi-attribute crosstalk networks from cellular perturbation assays.

Availability and implementation: PHOCOS is available in open source at https://github.com/AltschulerWu-Lab/PHOCOS

Contact:  steven.altschuler@ucsf.edu or lani.wu@ucsf.edu
Prediction of ribosome footprint profile shapes from transcript sequences
Authors: Liu Tzu-Yu , Song Yun S.
Published: June 2016

Motivation: Ribosome profiling is a useful technique for studying translational dynamics and quantifying protein synthesis. Applications of this technique have shown that ribosomes are not uniformly distributed along mRNA transcripts. Understanding how each transcript-specific distribution arises is important for unraveling the translation mechanism.

Results: Here, we apply kernel smoothing to construct predictive features and build a sparse model to predict the shape of ribosome footprint profiles from transcript sequences alone. Our results on Saccharomyces cerevisiae data show that the marginal ribosome densities can be predicted with high accuracy. The proposed novel method has a wide range of applications, including inferring isoform-specific ribosome footprints, designing transcripts with fast translation speeds and discovering unknown modulation during translation.

Availability and implementation: A software package called riboShape is freely available at https://sourceforge.net/projects/riboshape

Contact:  yss@berkeley.edu
Convolutional neural network architectures for predicting DNA–protein binding
Authors: Zeng Haoyang , Edwards Matthew D. , Liu Ge , Gifford David K.
Published: June 2016

Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications.

Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology.

Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu.

Contact:  gifford@mit.edu

Supplementary information:  Supplementary data are available at Bioinformatics online.
A novel method for discovering local spatial clusters of genomic regions with functional relationships from DNA contact maps
Authors: Hu Xihao , Shi Christina Huan , Yip Kevin Y.
Published: June 2016

Motivation: The three-dimensional structure of genomes makes it possible for genomic regions not adjacent in the primary sequence to be spatially proximal. These DNA contacts have been found to be related to various molecular activities. Previous methods for analyzing DNA contact maps obtained from Hi-C experiments have largely focused on studying individual interactions, forming spatial clusters composed of contiguous blocks of genomic locations, or classifying these clusters into general categories based on some global properties of the contact maps.

Results: Here, we describe a novel computational method that can flexibly identify small clusters of spatially proximal genomic regions based on their local contact patterns. Using simulated data that highly resemble Hi-C data obtained from real genome structures, we demonstrate that our method identifies spatial clusters that are more compact than methods previously used for clustering genomic regions based on DNA contact maps. The clusters identified by our method enable us to confirm functionally related genomic regions previously reported to be spatially proximal in different species. We further show that each genomic region can be assigned a numeric affinity value that indicates its degree of participation in each local cluster, and these affinity values correlate quantitatively with DNase I hypersensitivity, gene expression, super enhancer activities and replication timing in a cell type specific manner. We also show that these cluster affinity values can precisely define boundaries of reported topologically associating domains, and further define local sub-domains within each domain.

Availability and implementation: The source code of BNMF and tutorials on how to use the software to extract local clusters from contact maps are available at http://yiplab.cse.cuhk.edu.hk/bnmf/ .

Contact:  kevinyip@cse.cuhk.edu.hk

Supplementary information:  Supplementary data are available at Bioinformatics online.
Finding correct protein–protein docking models using ProQDock
Authors: Basu Sankar , Wallner Björn
Published: June 2016

Motivation: Protein–protein interactions are a key in virtually all biological processes. For a detailed understanding of the biological processes, the structure of the protein complex is essential. Given the current experimental techniques for structure determination, the vast majority of all protein complexes will never be solved by experimental techniques. In lack of experimental data, computational docking methods can be used to predict the structure of the protein complex. A common strategy is to generate many alternative docking solutions (atomic models) and then use a scoring function to select the best. The success of the computational docking technique is, to a large degree, dependent on the ability of the scoring function to accurately rank and score the many alternative docking models.

Results: Here, we present ProQDock, a scoring function that predicts the absolute quality of docking model measured by a novel protein docking quality score (DockQ). ProQDock uses support vector machines trained to predict the quality of protein docking models using features that can be calculated from the docking model itself. By combining different types of features describing both the protein–protein interface and the overall physical chemistry, it was possible to improve the correlation with DockQ from 0.25 for the best individual feature (electrostatic complementarity) to 0.49 for the final version of ProQDock. ProQDock performed better than the state-of-the-art methods ZRANK and ZRANK2 in terms of correlations, ranking and finding correct models on an independent test set. Finally, we also demonstrate that it is possible to combine ProQDock with ZRANK and ZRANK2 to improve performance even further.

Availability and implementation:  http://bioinfo.ifm.liu.se/ProQDock

Contact:  bjornw@ifm.liu.se

Supplementary information:  Supplementary data are available at Bioinformatics online.
RCK: accurate and efficient inference of sequence- and structure-based protein–RNA binding models from RNAcompete data
Authors: Orenstein Yaron , Wang Yuhao , Berger Bonnie
Published: June 2016

Motivation: Protein–RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein–RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset.

Results: We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein–RNA structure-based models on an unprecedented scale.

Availability and Implementation: Software and models are freely available at http://rck.csail.mit.edu/

Contact:  bab@mit.edu

Supplementary information:  Supplementary data are available at Bioinformatics online.