bluuebunny/crossref_metadata_2025_split huggingface dataset:
Airborne Fumigants and Residual Chemicals in Shipping Containers Arriving in New Zealand
Authors: Hinz Ruth , ’t Mannetje Andrea , Glass Bill , McLean Dave , Douwes Jeroen 
Published: September 2021

Abstract

Background
Airborne fumigants and other hazardous chemicals inside unopened shipping containers may pose a risk to workers handling containers.

Methods
Grab air samples from 490 sealed containers arriving in New Zealand were analysed for fumigants and other hazardous chemicals. We also collected grab air samples of 46 containers immediately upon opening and measured the total concentration of volatile organic compounds in real-time during ventilation. Additive Mixture Values (AMV) were calculated using the New Zealand Workplace Exposure standard (WES) and ACGIH Threshold Limit Values (TLV) of the 8-h, time-weighted average (TWA) exposure limit. Regression analyses assessed associations with container characteristics.

Results
Fumigants were detectable in 11.4% of sealed containers, with ethylene oxide detected most frequently (4.7%), followed by methyl bromide (3.5%). Other chemicals, mainly formaldehyde, were detected more frequently (84.7%). Fumigants and other chemicals exceeded the WES/TLV in 6.7%/7.8%, and 7.8%/20.0% of all containers, respectively. Correspondingly, they more frequently exceeded ‘1’ for the AMV-TLV compared to the AMV-WES (25.7% versus 7.8%). In samples taken upon opening of doors, fumigants were detected in both fumigated and non-fumigated containers, but detection frequencies and exceedances of the WES, TLV, and AMVs were generally higher in fumigated containers. Detection frequencies for other chemicals were similar in fumigated and non-fumigated containers, and only formaldehyde exceeded both the WES and TLV in both container groups. Volatile compounds in container air reduced rapidly during ventilation. Some cargo types (tyres; personal hygiene, beauty and medical products; stone and ceramics; metal and glass; and pet food) and countries of origin (China) were associated with elevated airborne chemical and fumigant concentrations.

Conclusion
Airborne chemicals in sealed containers frequently exceed exposure limits, both in fumigated and non-fumigated containers, and may contribute to short-term peak exposures of workers unloading or inspecting containers.
English and Development: Voices from a Rural Bangladeshi Madrasa
Authors: Chowdhury Qumrul Hasan 
Published: September 2021

Abstract
Because of its global status, donors and states promote English for economic development of countries in the global South such as Bangladesh. Governments, donors, and western leaders propose that people in madrasas (Islamic educational institutes) should learn English for development and security. But voices from madrasas are little heard. Based on a linguistic ethnography, this article presents some of these neglected perspectives on English for development at a private and unreformed Qawmi madrasa in rural Bangladesh. The findings show that people in the madrasa from a reflexively traditional stance, reject economic progress and western development programmes, and largely resist English as a language of development. These positions are considerably shaped by their commitments to religion and Arabic, supporting their alternative language and development visions. This article, based on the findings and drawing on Southern theory, interrogates the promotion of English for development, and asks how alert it is to heterogenous and complex southern realities.
‘Did You See That?’—The Role of Repetition and Enhancement on Lexical Bundle Processing in English Learning Materials
Authors: Northbrook Julian , Allen David , Conklin Kathy 
Published: September 2021

Abstract
For second-language learners, the use of formulaic language can benefit processing. Previous studies have explored the development of a ‘processing advantage’ for lexical bundles and investigated whether learning materials can be optimized via repetition or enhancement in order to facilitate it. However, studies have tended to consider these factors in isolation, and little is understood about how repetition and enhancement interact as learning occurs. This is the focus of the current study. Japanese learners of English read a series of short stories repeating enhanced or un-enhanced, low-frequency lexical bundles. After each reading, participants performed a phrasal judgement task (PJT) including these lexical bundles, as well as control lexical bundles not presented in the story. Responses were faster to items repeated in the stories, and there was an initial benefit from input enhancement. A post-test indicated that students retained some knowledge of the lexical bundles from both the stories, as well as from items that only appeared in the PJTs. This study shows that including high-frequency lexical bundles in such texts is beneficial to learners.
Integrating Neuropsychology into Interprofessional Geriatrics Clinics
Authors: Brunette Amanda M , Rycroft Sarah Seligman , Colvin Leigh , Schwartz Andrea Wershof , Driver Jane A , Nothern Alexandra , Harrington Mary Beth , Jackson Colleen E 
Published: September 2021

Abstract
Interprofessional healthcare teams are increasingly viewed as a clinical approach to meet the complex medical, psychological, and psychosocial needs of older adult patients. Despite the fact that older adults are at risk for cognitive difficulties, neuropsychologists are not routinely included on Geriatrics consult teams. The primary aim of this paper is to highlight the utility of neuropsychology within an interprofessional Geriatrics consult clinic. To address this aim, we describe specific benefits to patient care that may be associated with the inclusion of neuropsychologists on Geriatrics consult teams, including differential diagnosis, enhanced patient care, and reduced barriers to care. We provide a description of the integration of neuropsychology within a Veterans Health Administration (VA) interprofessional Geriatrics consult clinic team in order to illustrate the implementation of this model.
MAResNet: predicting transcription factor binding sites by combining multi-scale bottom-up and top-down attention and residual network
Authors: Han Ke , Shen Long-Chen , Zhu Yi-Heng , Xu Jian , Song Jiangning , Yu Dong-Jun 
Published: September 2021

AbstractAccurate identification of transcription factor binding sites is of great significance in understanding gene expression, biological development and drug design. Although a variety of methods based on deep-learning models and large-scale data have been developed to predict transcription factor binding sites in DNA sequences, there is room for further improvement in prediction performance. In addition, effective interpretation of deep-learning models is greatly desirable. Here we present MAResNet, a new deep-learning method, for predicting transcription factor binding sites on 690 ChIP-seq datasets. More specifically, MAResNet combines the bottom-up and top-down attention mechanisms and a state-of-the-art feed-forward network (ResNet), which is constructed by stacking attention modules that generate attention-aware features. In particular, the multi-scale attention mechanism is utilized at the first stage to extract rich and representative sequence features. We further discuss the attention-aware features learned from different attention modules in accordance with the changes as the layers go deeper. The features learned by MAResNet are also visualized through the TMAP tool to illustrate that the method can extract the unique characteristics of transcription factor binding sites. The performance of MAResNet is extensively tested on 690 test subsets with an average AUC of 0.927, which is higher than that of the current state-of-the-art methods. Overall, this study provides a new and useful framework for the prediction of transcription factor binding sites by combining the funnel attention modules with the residual network.
Genome optimization via virtual simulation to accelerate maize hybrid breeding
Authors: Cheng Qian , Jiang Shuqing , Xu Feng , Wang Qian , Xiao Yingjie , Zhang Ruyang , Zhao Jiuran , Yan Jianbing , Ma Chuang , Wang Xiangfeng 
Published: September 2021

Abstract
The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented ‘genome optimization via virtual simulation (GOVS)’ using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant ‘optimal genotypes’ or ‘advantageous alleles’ in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize.
Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant ‘optimal genotypes’ in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize.
IntelliPy: a GUI for analyzing IntelliCage data
Authors: Ruffini Nicolas , Müller Marianne B , Schmitt Ulrich , Gerber Susanne 
Published: September 2021

Abstract

Summary
The IntelliCage systems offer the possibility to conduct long-term behavioral experiments on mice in social groups without human intervention. Although this setup provides new findings, only about 150 studies with the IntelliCage system have been published in the last two decades, which is also caused by the challenging problems of processing and handling the large and heterogeneous amounts of captured data. This application note introduces the Python-GUI IntelliPy, especially designed for users not very experienced in using programming languages. IntelliPy allows users to quickly analyze the IntelliCage output in a user-friendly way, thus making the systems more accessible to a broader audience.

Availability and implementation
https://github.com/NiRuff/IntelliPy.

Supplementary information
Supplementary data are available at Bioinformatics online.
ACES: Analysis of Conservation with an Extensive list of Species
Authors: Padhi Evin M , Ng Jeffrey K , Mehinovic Elvisa , Sams Eleanor I , Turner Tychele N 
Published: September 2021

Abstract

Motivation
An abundance of new reference genomes is becoming available through large-scale sequencing efforts. While the reference FASTA for each genome is available, there is currently no automated mechanism to query a specific sequence across all new reference genomes.

Results
We developed ACES (Analysis of Conservation with an Extensive list of Species) as a computational workflow to query specific sequences of interest (e.g. enhancers, promoters, exons) against reference genomes with an available reference FASTA. This automated workflow generates BLAST hits against each of the reference genomes, a multiple sequence alignment file, a graphical fragment assembly file and a phylogenetic tree file. These data files can then be used by the researcher in several ways to provide key insights into conservation of the query sequence.

Availability and implementation
ACES is available at https://github.com/TNTurnerLab/ACES

Supplementary information
Supplementary data are available at Bioinformatics online.
CNN-PepPred: an open-source tool to create convolutional NN models for the discovery of patterns in peptide sets—application to peptide–MHC class II binding prediction
Authors: Junet Valentin , Daura Xavier 
Published: September 2021

Abstract

Summary
The ability to unveil binding patterns in peptide sets has important applications in several biomedical areas, including the development of vaccines. We present an open-source tool, CNN-PepPred, that uses convolutional neural networks to discover such patterns, along with its application to peptide–HLA class II binding prediction. The tool can be used locally on different operating systems, with CPUs or GPUs, to train, evaluate, apply and visualize models.

Availability and implementation
CNN-PepPred is freely available as a Python tool with a detailed User’s Guide at https://github.com/ComputBiol-IBB/CNN-PepPred. The site includes the peptide sets used in this study, extracted from IEDB (www.iedb.org).

Supplementary information
Supplementary data are available at Bioinformatics online.
Panache: a web browser-based viewer for linearized pangenomes
Authors: Durant Éloi , Sabot François , Conte Matthieu , Rouard Mathieu 
Published: September 2021

Abstract

Motivation
Pangenomics evolved since its first applications on bacteria, extending from the study of genes for a given population to the study of all of its sequences available. While multiple methods are being developed to construct pangenomes in eukaryotic species there is still a gap for efficient and user-friendly visualization tools. Emerging graph representations come with their own challenges, and linearity remains a suitable option for user-friendliness.

Results
We introduce Panache, a tool for the visualization and exploration of linear representations of gene-based and sequence-based pangenomes. It uses a layout similar to genome browsers to display presence absence variations and additional tracks along a linear axis with a pangenomics perspective.

Availability and implementation
Panache is available at github.com/SouthGreenPlatform/panache under the MIT License.
Sciviewer enables interactive visual interrogation of single-cell RNA-Seq data from the Python programming environment
Authors: Kotliar Dylan , Colubri Andrés 
Published: September 2021

Abstract

Motivation
Visualizing two-dimensional embeddings (such as UMAP or tSNE) is a useful step in interrogating single-cell RNA sequencing (scRNA-Seq) data. Subsequently, users typically iterate between programmatic analyses (including clustering and differential expression) and visual exploration (e.g. coloring cells by interesting features) to uncover biological signals in the data. Interactive tools exist to facilitate visual exploration of embeddings such as performing differential expression on user-selected cells. However, the practical utility of these tools is limited because they don’t support rapid movement of data and results to and from the programming environments where most of the data analysis takes place, interrupting the iterative process.

Results
Here, we present the Single-cell Interactive Viewer (Sciviewer), a tool that overcomes this limitation by allowing interactive visual interrogation of embeddings from within Python. Beyond differential expression analysis of user-selected cells, Sciviewer implements a novel method to identify genes varying locally along any user-specified direction on the embedding. Sciviewer enables rapid and flexible iteration between interactive and programmatic modes of scRNA-Seq exploration, illustrating a useful approach for analyzing high-dimensional data.

Availability and implementation
Code and examples are provided at https://github.com/colabobio/sciviewer.
PaReBrick: PArallel REarrangements and BReaks identification toolkit
Authors: Zabelkin Alexey , Yakovleva Yulia , Bochkareva Olga , Alexeev Nikita 
Published: September 2021

Abstract

Motivation
High plasticity of bacterial genomes is provided by numerous mechanisms including horizontal gene transfer and recombination via numerous flanking repeats. Genome rearrangements such as inversions, deletions, insertions and duplications may independently occur in different strains, providing parallel adaptation or phenotypic diversity. Specifically, such rearrangements might be responsible for virulence, antibiotic resistance and antigenic variation. However, identification of such events requires laborious manual inspection and verification of phyletic pattern consistency.

Results
Here, we define the term ‘parallel rearrangements’ as events that occur independently in phylogenetically distant bacterial strains and present a formalization of the problem of parallel rearrangements calling. We implement an algorithmic solution for the identification of parallel rearrangements in bacterial populations as a tool PaReBrick. The tool takes a collection of strains represented as a sequence of oriented synteny blocks and a phylogenetic tree as input data. It identifies rearrangements, tests them for consistency with a tree, and sorts the events by their parallelism score. The tool provides diagrams of the neighbors for each block of interest, allowing the detection of horizontally transferred blocks or their extra copies and the inversions in which copied blocks are involved. We demonstrated PaReBrick’s efficiency and accuracy and showed its potential to detect genome rearrangements responsible for pathogenicity and adaptation in bacterial genomes.

Availability and implementation
PaReBrick is written in Python and is available on GitHub: https://github.com/ctlab/parallel-rearrangements.

Supplementary information
Supplementary data are available at Bioinformatics online.
Phylogenomics of alligator lizards elucidate diversification patterns across the Mexican Transition Zone and support the recognition of a new genus
Authors: Blair Christopher , Bryson Robert W , García-Vázquez Uri O , Nieto-Montes De Oca Adrián , Lazcano David , Mccormack John E , Klicka John 
Published: September 2021

AbstractGenomic data continue to advance our understanding of species limits and biogeographic patterns. However, there is still no consensus regarding appropriate methods of phylogenomic analysis that make the best use of these heterogeneous data sets. In this study, we used thousands of ultraconserved element (UCE) loci from alligator lizards in the genus Gerrhonotus to compare and contrast species trees inferred using multiple contemporary methods and provide a time frame for biological diversification across the Mexican Transition Zone (MTZ). Concatenated maximum likelihood (ML) and Bayesian analyses provided highly congruent results, with differences limited to poorly supported nodes. Similar topologies were inferred from coalescent analyses in Bayesian Phylogenetics and Phylogeography and SVDquartets, albeit with lower support for some nodes. All divergence times fell within the Miocene, linking speciation to local Neogene vicariance and/or global cooling trends following the mid-Miocene Climatic Optimum. We detected a high level of genomic divergence for a morphologically distinct species restricted to the arid mountains of north-eastern Mexico, and erected a new genus to better reflect evolutionary history. In summary, our results further advocate leveraging the strengths and weaknesses of concatenation and coalescent methods, provide evidence for old divergences for alligator lizards, and indicate that the MTZ continues to harbour substantial unrecognized diversity.
Partial separability and functional graphical models for multivariate Gaussian processes
Authors: Zapata J , Oh S Y , Petersen A 
Published: September 2021

SummaryThe covariance structure of multivariate functional data can be highly complex, especially if the multivariate dimension is large, making extensions of statistical methods for standard multivariate data to the functional data setting challenging. For example, Gaussian graphical models have recently been extended to the setting of multivariate functional data by applying multivariate methods to the coefficients of truncated basis expansions. However, compared with multivariate data, a key difficulty is that the covariance operator is compact and thus not invertible. This paper addresses the general problem of covariance modelling for multivariate functional data, and functional Gaussian graphical models in particular. As a first step, a new notion of separability for the covariance operator of multivariate functional data is proposed, termed partial separability, leading to a novel Karhunen–Loève-type expansion for such data. Next, the partial separability structure is shown to be particularly useful in providing a well-defined functional Gaussian graphical model that can be identified with a sequence of finite-dimensional graphical models, each of identical fixed dimension. This motivates a simple and efficient estimation procedure through application of the joint graphical lasso. Empirical performance of the proposed method for graphical model estimation is assessed through simulation and analysis of functional brain connectivity during a motor task.