bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemometric Approaches for Developing Infrared Nanosensors to Image Anthracyclines
Authors: Bonis-O’Donnell Jackson Travis Del , Pinals Rebecca , Jeong Sanghwa , Thakrar Ami , Wolfinger Russ , Landry Markita 
Published: September 2018

AbstractGeneration, identification, and validation of optical probes to image molecular targets in a biological milieu remains a challenge. Synthetic molecular recognition approaches leveraging the intrinsic near-infrared fluorescence of single-walled carbon nanotubes is a promising approach for chronic biochemical imaging in tissues. However, generation of nanosensors for selective imaging of molecular targets requires a heuristic approach. Here, we present a chemometric platform for rapidly screening libraries of candidate single-walled carbon nanotube nanosensors against biochemical analytes to quantify fluorescence response to small molecules including vitamins, neurotransmitters, and chemotherapeutics. We further show this approach can be leveraged to identify biochemical analytes that selectively modulate the intrinsic near-infrared fluorescence of candidate nanosensors. Chemometric analysis thus enables identification of nanosensor-analyte ‘hits’ and also nanosensor fluorescence signaling modalities such as wavelength-shifts that are optimal for translation to biological imaging. Through this approach, we identify and characterize a nanosensor for the chemotherapeutic anthracycline doxorubicin, which provides an up to 17 nm fluorescence red-shift and exhibits an 8 µM limit of detection, compatible with peak circulatory concentrations of doxorubicin common in therapeutic administration. We demonstrate selectivity of this nanosensor over dacarbazine, a chemotherapeutic commonly co-injected with DOX. Lastly, we demonstrate nanosensor tissue compatibility for imaging of doxorubicin in muscle tissue by incorporating nanosensors into the mouse hindlimb and measuring nanosensor response to exogenous DOX administration. Our results motivate chemometric approaches to nanosensor discovery for chronic imaging of drug partitioning into tissues and towards real-time monitoring of drug accumulation.
Modular preprocessing pipelines can reintroduce artifacts into fMRI data
Authors: Lindquist Martin A. , Geuter Stephan , Wager Tor D. , Caffo Brian S. 
Published: September 2018

AbstractThe preprocessing pipelines typically used in both task and restingstate fMRI (rs-fMRI) analysis are modular in nature: They are composed of a number of separate filtering/regression steps, including removal of head motion covariates and band-pass filtering, performed sequentially and in a flexible order. In this paper we illustrate the shortcomings of this approach, as we show how later preprocessing steps can reintroduce artifacts previously removed from the data in prior preprocessing steps. We show that each regression step is a geometric projection of data onto a subspace, and that performing a sequence of projections can move the data into subspaces no longer orthogonal to those previously removed, reintroducing signal related to nuisance covariates. Thus, linear filtering operations are not commutative, and the order in which the preprocessing steps are performed is critical. These issues can arise in practice when any combination of standard preprocessing steps—including motion regression, scrubbing, component-based correction, global signal regression, and temporal filtering—are performed sequentially. In this work we focus primarily on rs-fMRI. We illustrate the problem both theoretically and empirically through application to a test-retest rs-fMRI data set, and suggest remedies. These include (a) combining all steps into a single linear filter, or (b) sequential orthogonalization of covariates/linear filters performed in series.
A low-cost DIY device for high resolution, continuous measurement of microbial growth dynamics
Authors: Sasidharan Kalesh , Martinez-Vernon Andrea S. , Chen Jing , Fu Tiantian , Soyer Orkun S 
Published: September 2018

ABSTRACTHigh-resolution data on microbial growth dynamics allow characterisation of microbial physiology, as well as optimisation of genetic alterations thereof. Such data are routinely collected using bench-top spectrophotometers or so-called plate readers. These equipments present several drawbacks: (i) measurements from different devices cannot be compared directly, (ii) proprietary nature of devices makes it difficult for standardisation methods to be developed across devices, and (iii) high costs limit access to devices, which can become a bottleneck for researchers, especially for those working with anaerobic organisms or at higher containment level laboratories. These limitations could be lifted, and data reproducibility improved, if the scientific community could adopt standardised, low-cost and open-source devices that can be built in-house. Here, we present such a device, MicrobeMeter, which is a do-it-yourself (DIY), simple, yet robust photometer with continuous data-logging capability. It is built using 3D-printing and open-source Arduino platform, combined with purpose-built electronic circuits. We show that MicrobeMeter displays linear relation between culture density and turbidity measurement for microbes from different phylogenetic domains. In addition, culture density estimated from MicrobeMeter measurements produced less variance compared against three commercial bench-top spectrophotometers, indicating that its measurements are less affected by the differences in cell types. We show the utility of MicrobeMeter, as a programmable wireless continuous measurement device, by collecting long-term growth dynamics up to 458 hours from aerobic and anaerobic cultures. We provide a full open-source description of MicrobeMeter and its implementation for faster adaptation and future development by the scientific community. The blueprints of the device, as well as ready-to-assemble kit versions are also made available throughwww.humanetechnologies.co.uk.
CONFESS: Fluorescence-based single-cell ordering in R
Authors: Motakis Efthymios , Low Diana H.P. 
Published: September 2018

AbstractModern high-throughput single-cell technologies facilitate the efficient processing of hundreds of individual cells to comprehensively study their morphological and genomic heterogeneity. Fluidigm’s C1 Auto Prep system isolates fluorescence-stained cells into specially designed capture sites, generates high-resolution image data and prepares the associated cDNA libraries for mRNA sequencing. Current statistical methods focus on the analysis of the gene expression profiles and ignore the important information carried by the images. Here we propose a new direction for single-cell data analysis and develop CONFESS, a customized cell detection and fluorescence signal estimation model for images coming from the Fluidigm C1 system. Applied to a set of HeLa cells expressing fluorescence cell cycle reporters, the method predicted the progression state of hundreds of samples and enabled us to study the spatio-temporal dynamics of the HeLa cell cycle. The output can be easily integrated with the associated single-cell RNA-seq expression profiles for deeper understanding of a given biological system. CONFESS R package is available at Bioconductor (http://bioconductor.org/packages/release/bioc/html/CONFESS.html).
Image analysis for taxonomic identification of Javanese butterflies
Authors: de Vetter Saskia , Vos Rutger 
Published: September 2018

SummaryTaxonomic experts classify millions of specimens, but this is very time-consuming and therefore expensive. Image analysis is a way to automate identification and was previously done at Naturalis Biodiversity Center for slipper orchids (Cypripedioideae) by the program ‘OrchID’. This program operated by extracting a pre-defined number of features from images, and these features were used to train artificial neural networks (ANN) to classify out-of-sample images. This program was extended to work for a collection of Javanese butterflies, donated to Naturalis by the Van Groenendael-Krijger Foundation. Originally, for the orchids, an image was divided into a pre-defined number of horizontal and vertical bins and the mean blue-green-red values of each bin were calculated (BGR method) to obtain image features. In the extended implementation, characteristic image features were extracted using the SURF algorithm implemented in OpenCV and clustered with the BagOfWords method (SURF-BOW method). In addition, a combination of BGR- and SURF-BOW was implemented to extract both types of features in a single dataset (BGR-SURF method). A selection of the butterfly and orchid images was made to create datasets with at least 5 and at most 50 specimens per species. The SURF-BOW and BGR-SURF methods were applied to both selected datasets, and the original BGR method was applied to the selected butterfly dataset. PCA plots were made to inspect visually how well the applied methods discriminated among the species. For the butterflies, both genus and species appeared to cluster together in the plots of the SURF-BOW method. However, no obvious clustering was noticeable for the orchid plots. The performance of the ANNs was validated by a stratified k-fold cross validation. For the butterflies, the BGR-SURF method scored best with an accuracy of 77%, against 71% for the SURF-BOW method and 66% for the BGR method, all for chained genus and species prediction with k = 10. The new methods could not improve the accuracy of the orchid classification with k = 10, which was 75% on genus, 52% on genus and section and 48% on genus, section and species in the original framework and now less than 25% for all. The validation results also showed that at least about 15 specimens per species were necessary for a good prediction with the SURF-BOW method. The BGR-SURF method was found to be the best of these methods for butterflies, but the original BGR method was best for the slipper orchids. In the future these methods may be tested with other datasets, for example with mosquitoes. In addition, other classifiers may be tested for better performance, like support vector machines.
Remotely sensed indicators and open-access biodiversity data to assess bird diversity patterns in Mediterranean rural landscapes
Authors: Ribeiro Inês , Proença Vânia , Ruiz Pere Serra , Palma Jorge , Domingo Cristina , Pons Xavier , Domingos Tiago 
Published: September 2018

AbstractChanges in ecosystem area are often used to assess human impacts on habitats and estimate biodiversity change. However, because species respond to structural changes at fine spatial scales the use of area alone may not capture all relevant changes. Operational costs limit the assessment of biodiversity change at a simultaneously fine spatial resolution and large scales. The development of cost-effective and expedite methods to monitor biodiversity change is therefore required. We use open access satellite imagery and biodiversity data to investigate the importance of variables of habitat extent and structure in explaining species richness and community dissimilarity of forest and open-land birds at the regional scale. Moreover, because Mediterranean landscapes are subject to seasonal dynamics, we explore the indicator value of remotely sensed variables measured in spring and summer. A large-scale dataset of bird occurrence data, including 8042 observations and 78 species, distributed by 40 landscape-sized cells, was assembled from GBIF after controlling for data quality. We found that summer satellite imagery, when the green perennial vegetation is more apparent, is particularly suited to model the diversity patterns of forest species, because distribution of tree cover in the landscape is well captured. Summer data is also useful to monitor the perennial elements that shape landscape structure and the habitat of open-land species. Specifically, mean NDVI and a second-order NDVI texture variable, were found to be good indicators of forest and open-land habitats, respectively. The use of spring imagery appears to be useful to monitor habitat structure within open-land habitat patches. Overall, NDVI texture measures were found to be good predictors of bird diversity patterns at large scales. Also, we were able to successfully conduct a regional scale analysis using open-access data, which illustrates their potential to inform large scale biodiversity monitoring.
Stress-induced changes in the S-palmitoylation and S-nitrosylation of synaptic proteins
Authors: Zareba-Koziol Monika , Bartkowiak-Kaczmarek Anna , Figiel Izabela , Krzystyniak Adam , Wojtowicz Tomasz , Bijata Monika , Wlodarczyk Jakub 
Published: September 2018

SummaryThe precise regulation of synaptic integrity is critical for neuronal network connectivity and proper brain function. Essential aspects of the activity and localization of synaptic proteins are regulated by posttranslational modifications. S-palmitoylation is a reversible covalent modification of the cysteine with palmitate. It modulates affinity of the protein for cell membranes and membranous compartments. Intracellular palmitoylation dynamics are regulated by other posttranslational modifications, such as S-nitrosylation. Still unclear, however, are the ways in which this crosstalk is affected in brain pathology, such as stress-related disorders. Using a newly developed mass spectrometry-based approach (Palmitoylation And Nitrosylation Interplay Monitoring), we analyzed the endogenous S-palmitoylation and S-nitrosylation of postsynaptic density proteins at the level of specific single cysteines in a mouse model of chronic stress. Our results suggest that atypical mechanism of crosstalk between the S-palmitoylation and S-nitrosylation of synaptic proteins might be one of the major events associated with chronic stress disorders.
Analysis of intermittent instabilities in switching power converters using Filippov’s method
Authors: Muppala Kumar Kavitha , A. Kavitha , Duraisamy John Christilda Nancy 
Published: September 2018

Purpose
In the design and development stage of the power converter systems, an abnormal intermittency is naturally experienced in nonautonomous system because of coupling of the interference signals. The study of identifying the possible conditions at which such an undesirable operation emerges is vital. Hence, the purpose of this paper is to explore the intermittent instabilities that evolve in the voltage-mode controlled quadratic buck converter when the sinusoidal interference signal coupled in reference voltage.

Design/methodology/approach
Voltage-mode controlled quadratic buck converter with the sinusoidal interference signal coupled in reference voltage manifests a symmetrical period-doubling bifurcation in intermittent periods for significant interference signal strength with the frequency near to the switching frequency or its rational multiples. The complete dynamics of the system is investigated for the various inference signal frequencies by numerical simulations.

Findings
Here, the intermittent instabilities are verified using a simple Filippov’s method with supporting evidence of Floquet multipliers (eigenvalues) movement. The analytical result obtained is found to agree well with the simulation results.

Practical implications
Power supplies are liable to an ambiguous complex behavior when it is seldom protected against the interference signal. The experimental study has made an attempt to explicit a detailed behavior observed in voltage-mode controlled quadratic buck converter when a sinusoidal intruding signal of different amplitude and frequency are coupled with the reference voltage. Such an analysis gives considerable focus for the power electronics engineers to meet the design requirements.

Originality/value
To the authors’ knowledge, all the research works on intermittent instabilities in power converters are analyzed only using conventional method of Poincare map technique which emerges to be complicated when the order of the system is higher. Alternatively, in this paper, Filippov’s technique is used for stability analysis of periodic orbit. The evolution of bifurcation point is predicted by the calculating the Floquet multipliers of monodromy matrix, and it is known to achieve the same objective as the Poincare map technique in much more straightforward way.
Constrained optimization of the magnetostrictive actuator with the use of penalty function method
Authors: Knypinski Lukasz , Kowalski Krzysztof , Nowak Lech 
Published: September 2018

Purpose
The purpose of this paper is to elaborate algorithm and software for the optimization of the actuator–capacitor system taking the dynamics parameters into account. The system is applied for driving the valve of plasma gun. Two optimization strategies are proposed and pondered. The penalty function approach has been expanded in detail.

Design/methodology/approach
The field-circuit mathematical model of the dynamics operation consists of the strongly coupled equations of the transient electromagnetic fields and the equations of the electric circuit. The numerical implementation is based on finite element method and step-by-step Cranck–Nicholson procedure. The genetic algorithm has been used in the optimization procedure. The sigmoidal transformation has been applied to adjust the classical external penalty function method to the genetic algorithm.

Findings
The modification consists in adaptation of the penalty function to the genetic algorithm. In the proposed approach, operations involving successive iterations of increasing penalty function and operations containing genetic iterations are intertwined with each other. The differences between these two procedures are getting blurred. The proposed approach is very effective. It is possible to achieve optimal solution even more than ten times faster than using the classical method.

Originality/value
The proposed approach can be successfully applied to designing and optimization of different electromagnetic devices, including functional constraints.
A parallel finite element algorithm for nonstationary incompressible magnetohydrodynamics equations
Authors: Tang Qili 
Published: September 2018

PurposeThe purpose of this paper is to design a parallel finite element (FE) algorithm based on fully overlapping domain decomposition for solving the nonstationary incompressible magnetohydrodynamics (MHD).Design/methodology/approachThe fully discrete Euler implicit/explicit FE subproblems, which are defined in the whole domain with vast majority of the degrees of freedom associated with the particular subdomain, are solved in parallel. In each subproblem, the linear term is treated by implicit scheme and the nonlinear term is solved by explicit one.FindingsFor the algorithm, the almost unconditional convergence with optimal orders is validated by numerical tests. Some interesting phenomena are presented.Originality/valueThe proposed algorithm is effective, easy to realize with low communication costs and preferred for solving the strong nonlinear MHD system.
A landscape approach for cost‐effective large‐scale forest restoration
Authors: Molin Paulo Guilherme , Chazdon Robin , Frosini de Barros Ferraz Silvio , Brancalion Pedro H. S. 
Published: September 2018

Abstract

Achieving global targets for forest restoration will require cost‐effective strategies to return agricultural land to forest, while minimizing implementation costs and negative outcomes for agricultural production.

We present a landscape approach for optimizing the cost‐effectiveness of large‐scale forest restoration. Across three different landscapes within Brazil's Atlantic Forest biodiversity hotspot, we modelled landscape scenarios based on spatially explicit data on the probability of natural regeneration, restoration costs, land opportunity costs, and forest restoration outcomes for increasing carbon stocking and landscape connectivity. We compare benefits of our cost‐reduction approach to the legally mandated riparian restoration and randomly distributed approaches.

Compared with riparian prioritization and considering both implementation and opportunity costs, our cost‐reduction scenario produced the greatest savings (20.9%) in mechanized agricultural landscapes.

When only considering implementation costs, our cost‐reduction scenario led to the highest savings (38.4%) in the landscape with highest forest cover where natural regeneration potential is highest and enables cost‐effective carbon stocking and connectivity.

Synthesis and applications. We present a guide for forest restoration planning that maximizes specific outcomes with minimal costs and reduction of agricultural production. Furthermore, we show how policies could encourage prioritization of low‐cost restoration via natural regeneration, increasing cost‐effectiveness. While our study focuses on Brazil's Atlantic Forest, the approach can be parameterized for other regions.
Dietary Fumonisin and Growth Impairment in Children and Animals: A Review
Authors: Chen Chen , Riley Ronald T. , Wu Felicia 
Published: September 2018

AbstractFumonisins are mycotoxins produced primarily by the fungiFusarium verticillioidesandF. proliferatum, which colonize maize in tropical, subtropical, and temperate climates worldwide. Fumonisin exposure is the highest in rural populations that consume large amounts of maize and maize products. Among them, infants and young children are the most vulnerable when they are weaned onto maize‐based foods. Therefore, it is critical to understand the impact of fumonisin on children's health and growth. This review describes the evidence linking fumonisin exposure to child growth impairment. First, toxicological studies that attempt to elucidate the mechanism by which fumonisin may impair growth are discussed. Next, a description is given of candidate biomarkers for accurately capturing fumonisin exposure in humans. Potential human health effects of fumonisin exposure beyond growth impairment, including esophageal cancer and neural tube defects (NTDs), are briefly described. We review epidemiological studies that collectively show an increasing weight of evidence linking fumonisin exposure to growth impairment, particularly in world regions where young children consume maize‐based weaning foods. Additionally, the evidence linking fumonisin exposure to growth impairment in plants and a variety of animal species are reviewed. Finally, we describe interventions to reduce fumonisin in parts of the world where dietary fumonisin exposure is high and is likely to predispose populations to increased health risk.