bluuebunny/crossref_metadata_2025_split huggingface dataset:
The interaction between atomic-scale pores and particles
Authors: Hassani Nasim , Neek-Amal Mehdi 
Published: September 2021

Abstract
Using first-principles calculations for angstrom-sized pores (3–10 Å), we investigate pore-particle interaction. The translocation energy barrier (TEB) plays important role for the angstrom-scale pores created in 2D-materials such as graphene which is calculated for the translocation of rare gases (He, Ne, Ar, Xe), diatomic molecules (H2 and N2), CO2, and CH4. The critical incident angle (the premeance beyond that is zero) was found to be 40°, which is different from classical model’s prediction of 19–37°. The calculated TEB (Δ) and the surface diffusion energy barrier (Δ′) for the particles with small kinetic diameter (He, Ne and H2), show that the direct flow is the dominant permeation mechanism (Δ ≈ 0 and Δ′ > 30 meV). For the other particles with larger kinetic diameters (Ar, Kr, N2, CH4 and CO2), we found that both surface diffusion and direct flow mechanisms are possible, i.e. Δ and Δ′ ≠ 0. This work provides important insights into the gas permeation theory and into the design and development of gas separation and filtration devices.
Conic formulation of fluence map optimization problems
Authors: ten Eikelder S C M , Ajdari A , Bortfeld T , den Hertog D 
Published: September 2021

Abstract
The convexity of objectives and constraints in fluence map optimization (FMO) for radiation therapy has been extensively studied. Next to convexity, there is another important characteristic of optimization functions and problems, which has thus far not been considered in FMO literature: conic representation. Optimization problems that are conically representable using quadratic, exponential and power cones are solvable with advanced primal-dual interior-point algorithms. These algorithms guarantee an optimal solution in polynomial time and have good performance in practice. In this paper, we construct conic representations for most FMO objectives and constraints. This paper is the first that shows that FMO problems containing multiple biological evaluation criteria can be solved in polynomial time. For fractionation-corrected functions for which no exact conic reformulation is found, we provide an accurate approximation that is conically representable. We present numerical results on the TROTS data set, which demonstrate very stable numerical performance for solving FMO problems in conic form. With ongoing research in the optimization community, improvements in speed can be expected, which makes conic optimization a promising alternative for solving FMO problems.
Experimental validation of daily adaptive proton therapy
Authors: Nenoff Lena , Matter Michael , Charmillot Marjolaine , Krier Serge , Uher Klara , Weber Damien Charles , Lomax Antony John , Albertini Francesca 
Published: September 2021

Abstract
Anatomical changes during proton therapy require rapid treatment plan adaption to mitigate the associated dosimetric impact. This in turn requires a highly efficient workflow that minimizes the time between imaging and delivery. At the Paul Scherrer Institute, we have developed an online adaptive workflow, which is specifically designed for treatments in the skull-base/cranium, with the focus set on simplicity and minimizing changes to the conventional workflow. The dosimetric and timing performance of this daily adaptive proton therapy (DAPT) workflow has been experimentally investigated using an in-house developed DAPT software and specifically developed anthropomorphic phantom. After a standard treatment preparation, which includes the generation of a template plan, the treatment can then be adapted each day, based on daily imaging acquired on an in-room CT. The template structures are then rigidly propagated to this CT and the daily plan is fully re-optimized using the same field arrangement, DVH constraints and optimization settings of the template plan. After a dedicated plan QA, the daily plan is delivered. To minimize the time between imaging and delivery, clinically integrated software for efficient execution of all online adaption steps, as well as tools for comprehensive and automated QA checks, have been developed. Film measurements of an end-to-end validation of a multi-fraction DAPT treatment showed high agreement to the calculated doses. Gamma pass rates with a 3%/3 mm criteria were >92% when comparing the measured dose to the template plan. Additionally, a gamma pass rate >99% was found comparing measurements to the Monte Carlo dose of the daily plans reconstructed from the logfile, accumulated over the delivered fractions. With this, we experimentally demonstrate that the described adaptive workflow can be delivered accurately in a timescale similar to a standard delivery.
Morphology of positive ionization waves in atmospheric pressure air: influence of electrode set-up geometry
Authors: Bourdon Anne , Péchereau François , Tholin Fabien , Bonaventura Zdenek 
Published: September 2021

Abstract
A numerical parametric study on positive diffuse discharges in point-to-plane geometry in air at atmospheric pressure is presented. Different discharge characteristics are studied: ignition time, connection time to the grounded cathode plane, shape of the discharge and its maximum radius at the connection time, evolution of the maximum electric field in the discharge front and velocity of the ionization front during its propagation. First, a case at a DC voltage of 50 kV applied on a rod anode ended by a semi-sphere with a radius of 100 μm set at 1.6 cm from a grounded cathode plane is considered. The influence of the rod radius, the position of a disc holder, the shape of the anode electrode and the radial extension of the computational domain are studied. The radius of curvature of the anode tip (varied between 100 and 1000 μm) and the shape of the anode electrode (rod or hyperbola) are shown to have a negligible influence on discharge characteristics. Conversely, the presence of a disc holder or a small radial computational domain lead to a decrease of the maximum discharge radius at the connection time and a change in the discharge shape from a conical to an ellipsoidal shape. These changes on the discharge morphology have only a limited impact on the propagation velocity of the discharge front and maximum electric field on the discharge axis. Then, a point-to-plane geometry with a rod electrode of 50 μm radius, in a 1.6 cm gap, with a 100 kV voltage applied with a rise time of 1 ns is studied. The influence of a disc holder on the discharge characteristics is the same as for lower DC voltages. Finally, the time evolution of the absolute value of the electric field at different test points on the discharge axis is studied. Close to the anode tip, rapidly after the peak of electric field due to the passage of the ionization front, the electric field in the discharge channel is shown to increase to values higher than the breakdown field.
Changes in Brain Dopamine Extracellular Concentration after Ethanol Administration; Rat Microdialysis Studies
Authors: Dahchour Abdelkader , Ward Roberta J 
Published: September 2021

AbstractAimsThe purpose of this review is to evaluate microdialysis studies where alterations in the dopaminergic system have been evaluated after different intoxication states, in animals showing preference or not for alcohol, as well as during alcohol withdrawal.MethodsEthanol administration induces varying alterations in dopamine microdialysate concentrations, thereby modulating the functional output of the dopaminergic system.ResultsAdministration of low doses of ethanol, intraperitoneally, intravenously, orally or directly into the nucleus accumbens, NAc, increases mesolimbic dopamine, transmission, as shown by increases in dopamine content. Chronic alcohol administration to rats, which show alcohol-dependent behaviour, induced little change in basal dopamine microdialysis content. In contrast, reduced basal dopamine content occurred after ethanol withdrawal, which might be the stimulus to induce alcohol cravings and consumption. Intermittent alcohol consumption did not identify any consistent changes in dopamine transmission. Animals which have been selectively or genetically bred for alcohol preference did not show consistent changes in basal dopamine content although, exhibited a significant ethanol-evoked dopamine response by comparison to non-preference animals.ConclusionsMicrodialysis has provided valuable information about ethanol-evoked dopamine release in the different animal models of alcohol abuse. Acute ethanol administration increases dopamine transmission in the rat NAc whereas chronic ethanol consumption shows variable results which might reflect whether the rat is prior to or experiencing ethanol withdrawal. Ethanol withdrawal significantly decreases the extracellular dopamine content. Such changes in dopamine surges will contribute to both drug dependence, e.g. susceptibility to drug withdrawal, and addiction, by compromising the ability to react to normal dopamine fluctuations.
‘In defence of the empire’: Mauritius’ government slaves in eighteenth-century Mauritius
Authors: Teelock Vijayalakshmi 
Published: September 2021

Abstract
Mauritius' Government slaves form a unique body of slaves emerging out of its French colonial past. Slaves bought by the colonial administration formed part of the 'public works' department and built the infrastructure of the islans as well as manning forts, manufacturing gunpowder and even being recruited in the French naval squadrons going to fight the British in India.
The fobitools framework: the first steps towards food enrichment analysis
Authors: Castellano-Escuder Pol , Andrés-Lacueva Cristina , Sánchez-Pla Alex 
Published: September 2021

Abstract

Motivation
The FOBI ontology can be of great help in nutrimetabolomic studies due to its wide variety of applications, including the possibility of performing different enrichment analyses. However, the programming skills required to query and explore it may limit its use by the scientific community.

Results
Here, we present the fobitools framework, comprised of an R/Bioconductor package and its complementary web interface. These two tools allow researchers to interact and explore the FOBI ontology in a highly user-friendly way. The fobitools framework is focused on the novel concept of food enrichment analysis in nutrimetabolomic studies. However, other useful features, such as the network interactive visualization of FOBI and the automatic annotation of dietary free-text data are also presented.

Availability and implementation
Both the fobitools R/Bioconductor package and the fobitoolsGUI web-based application, together with their installation instructions and examples, are freely available at https://github.com/nutrimetabolomics/fobitools and https://github.com/nutrimetabolomics/fobitoolsGUI, respectively.

Supplementary information
Supplementary data are available at Bioinformatics online.
Accelerating Big Data Analysis through LASSO-Random Forest Algorithm in QSAR Studies
Authors: Motamedi Fahimeh , Pérez-Sánchez Horacio , Mehridehnavi Alireza , Fassihi Afshin , Ghasemi Fahimeh 
Published: September 2021

Abstract

Motivation
The aim of quantitative structure–activity prediction (QSAR) studies is to identify novel drug-like molecules that can be suggested as lead compounds by means of two approaches, which are discussed in this article. First, to identify appropriate molecular descriptors by focusing on one feature-selection algorithms; and second to predict the biological activities of designed compounds. Recent studies have shown increased interest in the prediction of a huge number of molecules, known as Big Data, using deep learning models. However, despite all these efforts to solve critical challenges in QSAR models, such as over-fitting, massive processing procedures, is major shortcomings of deep learning models. Hence, finding the most effective molecular descriptors in the shortest possible time is an ongoing task. One of the successful methods to speed up the extraction of the best features from big datasets is the use of least absolute shrinkage and selection operator (LASSO). This algorithm is a regression model that selects a subset of molecular descriptors with the aim of enhancing prediction accuracy and interpretability because of removing inappropriate and irrelevant features.

Results
To implement and test our proposed model, a random forest was built to predict the molecular activities of Kaggle competition compounds. Finally, the prediction results and computation time of the suggested model were compared with the other well-known algorithms, i.e. Boruta-random forest, deep random forest and deep belief network model. The results revealed that improving output correlation through LASSO-random forest leads to appreciably reduced implementation time and model complexity, while maintaining accuracy of the predictions.

Supplementary information
Supplementary data are available at Bioinformatics online.
RLM: fast and simplified extraction of read-level methylation metrics from bisulfite sequencing data
Authors: Hetzel Sara , Giesselmann Pay , Reinert Knut , Meissner Alexander , Kretzmer Helene 
Published: September 2021

Abstract

Summary
Bisulfite sequencing data provide value beyond the straightforward methylation assessment by analyzing single-read patterns. Over the past years, various metrics have been established to explore this layer of information. However, limited compatibility with alignment tools, reference genomes or the measurements they provide present a bottleneck for most groups to routinely perform read-level analysis. To address this, we developed RLM, a fast and scalable tool for the computation of several frequently used read-level methylation statistics. RLM supports standard alignment tools, works independently of the reference genome and handles most sequencing experiment designs. RLM can process large input files with a billion reads in just a few hours on common workstations.

Availability and implementation
https://github.com/sarahet/RLM.

Supplementary information
Supplementary data are available at Bioinformatics online.
Prediction of antimicrobial resistance based on whole-genome sequencing and machine learning
Authors: Ren Yunxiao , Chakraborty Trinad , Doijad Swapnil , Falgenhauer Linda , Falgenhauer Jane , Goesmann Alexander , Hauschild Anne-Christin , Schwengers Oliver , Heider Dominik 
Published: September 2021

Abstract

Motivation
Antimicrobial resistance (AMR) is one of the biggest global problems threatening human and animal health. Rapid and accurate AMR diagnostic methods are thus very urgently needed. However, traditional antimicrobial susceptibility testing (AST) is time-consuming, low throughput and viable only for cultivable bacteria. Machine learning methods may pave the way for automated AMR prediction based on genomic data of the bacteria. However, comparing different machine learning methods for the prediction of AMR based on different encodings and whole-genome sequencing data without previously known knowledge remains to be done.

Results
In this study, we evaluated logistic regression (LR), support vector machine (SVM), random forest (RF) and convolutional neural network (CNN) for the prediction of AMR for the antibiotics ciprofloxacin, cefotaxime, ceftazidime and gentamicin. We could demonstrate that these models can effectively predict AMR with label encoding, one-hot encoding and frequency matrix chaos game representation (FCGR encoding) on whole-genome sequencing data. We trained these models on a large AMR dataset and evaluated them on an independent public dataset. Generally, RFs and CNNs perform better than LR and SVM with AUCs up to 0.96. Furthermore, we were able to identify mutations that are associated with AMR for each antibiotic.

Availability and implementation
Source code in data preparation and model training are provided at GitHub website (https://github.com/YunxiaoRen/ML-iAMR).

Supplementary information
Supplementary data are available at Bioinformatics online.
Quiet flight, the leading edge comb, and their ecological correlates in owls (Strigiformes)
Authors: Le Piane Krista , Clark Christopher J 
Published: September 2021

Abstract
Owls have evolved sensitive hearing facilitated by a facial disc, and flight that is quieted in part by a leading-edge comb on their wing. This comb is a series of modified barbs, or serrations, which project up from the outermost primary feathers on the leading edge of the wing. Here we explore the evolution of comb and facial disc morphology. We measured leading-edge comb morphology on museum skins of 147 owl species, and facial disc morphology from photos, as well as ecological traits, on 66 species. The first principal component of comb morphology loaded on serration length, which varied between 0 and ~6 mm long in the species we sampled. Comb size (PC1) was correlated with relative facial disc size, suggesting that owls with good hearing also tend to have quiet flight. Two non-exclusive hypotheses for why quiet flight evolved are for stealth, allowing the owl to approach prey undetected; or to reduce self-masking, enabling the owl to hear prey better midflight. We examined whether ecological variables (prey type, active period and habitat) suggest whether stealth or self-masking better explain the evolution of comb size. Phylogenetic analyses suggested support for both the stealth and the self-masking hypotheses for the evolution of quiet flight.
The Mindfulness-Based Social Work and Self-Care Programme: A Mixed Methods Evaluation Study
Authors: Maddock Alan , McCusker Pearse , Blair Carolyn , Roulston Audrey 
Published: September 2021

Abstract
During their social work education, students engage in a number of stressful learning activities, often simultaneously, which can negatively impact their well-being, mental health and social work practice. Mindfulness practices are beginning to be integrated into social work curricula globally to enhance student self-care along with key social work practice skills and values. This mixed methods study examined the effects of a bespoke six-week online mindfulness-based social work and self-care (MBSWSC) programme on the stress, burnout, well-being, anxiety and depression levels of thirty social work students from two universities in the UK. This study also examined the effects of MBSWSC on a number of mindfulness-based mediators of change in these outcomes. Participant perceptions of the benefits of the MBSWSC programme on their well-being and social work practice are further explored via a thematic analysis of an open-ended questionnaire. Statistically significant changes in all variables were found post-programme except for depression and loss of empathy/depersonalisation, a facet of burnout. The qualitative data provided a deeper insight into the potential benefits of the programme for the enhancement of student well-being, mental health and anti-oppressive social work practice (AOP).
Urine-derived stem cells: applications in skin, bone and articular cartilage repair
Authors: Zhang Wenqian , Hu Jungen , Huang Yizhou , Wu Chenyu , Xie Huiqi 
Published: September 2021

AbstractAs an emerging type of adult stem cell featuring non-invasive acquisition, urine-derived stem cells (USCs) have shown great potential for applications in tissue engineering and regenerative medicine. With a growing amount of research on the topic, the effectiveness of USCs in various disease models has been shown and the underlying mechanisms have also been explored, though many aspects still remain unclear. In this review, we aim to provide an up-to-date overview of the biological characteristics of USCs and their applications in skin, bone and articular cartilage repair. In addition to the identification procedure of USCs, we also summarize current knowledge of the underlying repair mechanisms and application modes of USCs. Potential concerns and perspectives have also been summarized.
News Fixers at the Digital Interface: Precarious Labor and International Journalism in the 21st Century
Authors: Palmer Lindsay 
Published: September 2021

Abstract
This article conducts a discursive interface analysis of World Fixer, the most visible online platform currently connecting foreign correspondents with local news workers who can help them translate interviews, navigate unfamiliar places, and stay safe in the field. Placing Johanna Drucker’s theory of the digital interface into conversation with the critical frameworks found in global communication studies, anti-colonial theory, and anti-racist communication scholarship, the goal is to illuminate both the opportunities that the World Fixer site provides its users, as well as the inequalities that the website still perpetuates.
EEG Spatiotemporal Patterns Underlying Self-other Voice Discrimination
Authors: Iannotti Giannina Rita , Orepic Pavo , Brunet Denis , Koenig Thomas , Alcoba-Banqueri Sixto , Garin Dorian F A , Schaller Karl , Blanke Olaf , Michel Christoph M 
Published: September 2021

Abstract
There is growing evidence showing that the representation of the human “self” recruits special systems across different functions and modalities. Compared to self-face and self-body representations, few studies have investigated neural underpinnings specific to self-voice. Moreover, self-voice stimuli in those studies were consistently presented through air and lacking bone conduction, rendering the sound of self-voice stimuli different to the self-voice heard during natural speech. Here, we combined psychophysics, voice-morphing technology, and high-density EEG in order to identify the spatiotemporal patterns underlying self-other voice discrimination (SOVD) in a population of 26 healthy participants, both with air- and bone-conducted stimuli. We identified a self-voice-specific EEG topographic map occurring around 345 ms post-stimulus and activating a network involving insula, cingulate cortex, and medial temporal lobe structures. Occurrence of this map was modulated both with SOVD task performance and bone conduction. Specifically, the better participants performed at SOVD task, the less frequently they activated this network. In addition, the same network was recruited less frequently with bone conduction, which, accordingly, increased the SOVD task performance. This work could have an important clinical impact. Indeed, it reveals neural correlates of SOVD impairments, believed to account for auditory-verbal hallucinations, a common and highly distressing psychiatric symptom.