bluuebunny/crossref_metadata_2025_split huggingface dataset:
The SparSpec algorithm and the application to the detection of spatial periodicities in tokamaks: using memory with relaxation
*
Authors: Testa D , Carfantan H , Perrone L M 
Published: April 2021

Abstract
A common problem in many complex physical systems is the determination of pulsation modes from irregularly sampled time-series, and there is a wealth of signal processing techniques that are being applied to post-pulse and real-time data analysis in such complex systems. The aim of this report is studying the problem of detecting in real-time spatial periodicities in the spectrum of magnetic fluctuations in tokamaks, for which optimization of the algorithm run-time is essential. The main tool used hereafter will be the SparSpec algorithm, initially devised for astrophysical purposes and already applied to the analysis of magnetic fluctuation data in various tokamaks, both currently or previously operating (JET, TCV, Alcator C-mod) and under construction (ITER, DTT). For JET, the baseline version of the SparSpec algorithm, dubbed SS-H2, already regularly runs in real-time on a 1 ms clock for detecting Toroidal Alfvén Eigenmodes using synchronously-detected magnetic perturbation. It was noted that the solution is only slowly changing in time as the background plasma typically also slowly evolves. Therefore, as a specifically real-time acceleration tool, we will focus on the use of a memory with relaxation scheme, whereby solutions obtained at previous time points are used to provide weighted input constraints for the solution at the current time point. Use of the measurement uncertainties to weight the data, the spectral window and the ensuing penalization criterion (dubbed the SS-V5ν0 algorithm) is reported in a companion work. The behaviour of the SparSpec algorithm under a variety of simulated circumstances, and one actual test case from the JET tokamak, is analysed and appropriate conditions for the convergence of the memory-penalised solutions are derived. The tuning of the input parameters is discussed based on the results of our simulations. It is found that the implementation of SparSpec using such a memory with relaxation scheme is quite a complex procedure, and only when correctly optimized the results are superior, both in terms of the speed and the accuracy of the calculations, to those obtained with the SS-H2 and SS-V5ν0 versions of the SparSpec algorithm.
Study of diamond like carbon coatings formed by pulsed hydrocarbon ions irradiations over different substrate materials using plasma focus device
Authors: Niranjan Ram , Joycee J , Srivastava R , Patel N N , Joshi K D 
Published: April 2021

Abstract
Pulsed hydrocarbon ions produced in a plasma focus device were used to irradiate different substrate materials (Si, Ti, Mo and W) and to deposit thin films of carbon material over it. High energetic and high intensity pulsed hydrocarbon ions were produced when plasma focus device was filled with 0.5 mbar of acetylene gas and operated at 2 kJ. Effects of substrate materials properties, its thermal evolution under pulsed irradiation of energetic ions and plasma streams on the deposited films have been studied. Visible Raman spectroscopic measurements confirmed that deposited films were of diamond-like-carbon. Fraction of sp3 bonded carbon in films on different substrate materials (16%, 8.7%, 13% and 18.9% on Si, Ti, Mo and W respectively) was found to be correlated to substrate materials thermal properties i.e. high fraction of sp3 bonded carbon was observed over substrate materials having high thermal conductivity. Carbon atom concentrations were measured to be different (22.46 at. %, 22.7 at. %, 10.4 at. % and 32 at. % on Si, Ti, Mo and W respectively) over different substrates. Surface morphologies of DLC were also observed to be different for different substrates. On inserting graphite at anode tip, fraction of sp3 bonded carbon in DLC coating over Si substrate increased to 19.5%.
Electronic structure of cesium-based photocathode materials from density functional theory: performance of PBE, SCAN, and HSE06 functionals
Authors: Saßnick Holger-Dietrich , Cocchi Caterina 
Published: April 2021

Abstract
The development of novel materials for vacuum electron sources in particle accelerators is an active field of research that can greatly benefit from the results of ab initio calculations for the characterization of the electronic structure of target systems. As state-of-the-art many-body perturbation theory calculations are too expensive for large-scale material screening, density functional theory offers the best compromise between accuracy and computational feasibility. The quality of the obtained results, however, crucially depends on the choice of the exchange–correlation potential, v
xc. To address this essential point, we systematically analyze the performance of three popular approximations of v
xc [PBE, strongly constrained and appropriately normed (SCAN), and HSE06] on the structural and electronic properties of bulk Cs3Sb and Cs2Te as representative materials of Cs-based semiconductors employed in photocathode applications. Among the adopted approximations, PBE shows expectedly the largest discrepancies from the target: the unit cell volume is overestimated compared to the experimental value, while the band gap is severely underestimated. On the other hand, both SCAN and HSE06 perform remarkably well in reproducing both structural and electronic properties. Spin–orbit coupling, which mainly impacts the valence region of both materials inducing a band splitting and, consequently, a band-gap reduction of the order of 0.2 eV, is equally captured by all functionals. Our results indicate SCAN as the best trade-off between accuracy and computational costs, outperforming the considerably more expensive HSE06.
Development of a low-voltage driven non-resonant three-DOF eyeball-like piezoelectric actuator
Authors: Zheng Ke , Yang Ying , Qiu Jianmin , Ma Xinchi , Zhang Jiyang , Wang Yiping 
Published: April 2021

Abstract
In this work, a low-voltage driven non-resonant three degree-of-freedom (DOF) eyeball-like piezoelectric actuator is proposed. Elliptical motions on the driving feet are formed from the pushing and pulling actions of the flexible displacement amplification (FDA) mechanism in the piezoelectric actuator. There are three types of elliptical movements to drive the spherical rotor around three coordinate axes while driving the different groups of piezoelectric stacks. The principles of the three-DOF rotations are analysed by theoretical and simulation methods. Fabrication of a miniature piezoelectric prototype of 34mm × 34mm × 34mm is conducted. Under a driving voltage of 40

V

0
−
p

,

the maximum rotary velocities of the rotor around X, Y and Z axes reach to 62.5 r min−1, 65 r min−1 and 46 r min−1 at 1.5 kHz. High resolutions around X and Y axes up to 2.5

μ
rad

and 5

μ
rad

are obtained. The remarkable comprehensive performances enable much potential applications of this three-DOF eyeball-like piezoelectric actuator in precision pointing, attitude adjustment and bionic eye positioning systems.
A free-energy principle for representation learning
Authors: Gao Yansong , Chaudhari Pratik 
Published: April 2021

Abstract
This paper employs a formal connection of machine learning with thermodynamics to characterize the quality of learned representations for transfer learning. We discuss how information-theoretic functionals such as rate, distortion and classification loss of a model lie on a convex, so-called, equilibrium surface. We prescribe dynamical processes to traverse this surface under specific constraints; in particular we develop an iso-classification process that trades off rate and distortion to keep the classification loss unchanged. We demonstrate how this process can be used for transferring representations from a source task to a target task while keeping the classification loss constant. Experimental validation of the theoretical results is provided on image-classification datasets.
Association Between Hurricane Sandy and Emergency Department Visits in New York City by Age and Cause
Authors: Weinberger Kate R , Kulick Erin R , Boehme Amelia K , Sun Shengzhi , Dominici Francesca , Wellenius Gregory A 
Published: April 2021

Abstract
The magnitude, timing, and etiology of morbidity associated with tropical cyclones remains incompletely quantified. We examined the relative change in cause-specific emergency department (ED) visits among residents of New York City during and after Hurricane Sandy, a tropical cyclone that affected the northeastern United States in October 2012. We used quasi-Poisson constrained distributed lag models to compare the number of ED visits on and after Hurricane Sandy with all other days, 2005–2014, adjusting for temporal trends. Among residents aged ≥65 years, Hurricane Sandy was associated with a higher rate of ED visits due to injuries and poisoning (relative risk (RR) = 1.19, 95% confidence interval (CI): 1.10, 1.28), respiratory disease (RR = 1.35, 95% CI: 1.21, 1.49), cardiovascular disease (RR = 1.10, 95% CI: 1.02, 1.19), renal disease (RR = 1.44, 95% CI: 1.22, 1.72), and skin and soft tissue infections (RR = 1.20, 95% CI: 1.03, 1.39) in the first week following the storm. Among adults aged 18–64 years, Hurricane Sandy was associated with a higher rate of ED visits for renal disease (RR = 2.15, 95% CI: 1.79, 2.59). Among those aged 0–17 years, the storm was associated with lower rates of ED visits for up to 3 weeks. These results suggest that tropical cyclones might result in increased health-care utilization due to a wide range of causes, particularly among older adults.
Examining the Relationship Between Occupational Physical Activity and Hypertension Status: Evidence from the Ghana WHO Study on Global Ageing and Adult Health
Authors: Konkor Irenius , Dogoli Maurice Anfaara , Kuuire Vincent , Wilson Kathi 
Published: April 2021

Abstract
The employment landscape has changed significantly over the past few years in emerging economies including Ghana where many people are rapidly transitioning from livelihood activities that originally involved physical exertion to work environments where performance of duties are mostly non-physical. Working under non-active conditions could, however, exacerbate the risk of developing chronic diseases that are increasingly becoming problematic in many developing countries. Drawing on a cross-sectional nationally representative sample data of 4425 adult Ghanaian workers collected by the WHO Study on Global Ageing and Adult Health in developing countries, we examined the relationship between occupational physical activity and hypertensive status. We employed the complementary log–log analysis technique to build nested models with results presented in odds ratios. After controlling for several relevant variables, the results show that performing sedentary related work (AOR = 1.23, CI = 1.06–1.42) is significantly associated with a higher likelihood of being hypertensive compared with those whose work involved moderate physical activity. Other factors that were significantly associated with being hypertensive included tobacco use (AOR = 1.33, CI = 1.05–1.70), living in an urban environment (AOR = 1.15, CI = 1.01–1.32), and being a female (AOR = 1.18, CI = 1.01–1.37) and being an older person. Policies on reducing the risk of developing chronic conditions especially hypertension need to recognize the contributions of the work environment in emerging developing economies.
Identification of cell-type-specific marker genes from co-expression patterns in tissue samples
Authors: Qiu Yixuan , Wang Jiebiao , Lei Jing , Roeder Kathryn 
Published: April 2021

Abstract

Motivation
Marker genes, defined as genes that are expressed primarily in a single-cell type, can be identified from the single-cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern.

Results
To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list.

Availability and implementation
We implement this method as an R package markerpen, hosted on CRAN (https://CRAN.R-project.org/package=markerpen).

Supplementary information
Supplementary data are available at Bioinformatics online.
KG4SL: knowledge graph neural network for synthetic lethality prediction in human cancers
Authors: Wang Shike , Xu Fan , Li Yunyang , Wang Jie , Zhang Ke , Liu Yong , Wu Min , Zheng Jie 
Published: April 2021

Abstract

Motivation
Synthetic lethality (SL) is a promising gold mine for the discovery of anti-cancer drug targets. Wet-lab screening of SL pairs is afflicted with high cost, batch-effect, and off-target problems. Current computational methods for SL prediction include gene knock-out simulation, knowledge-based data mining and machine learning methods. Most of the existing methods tend to assume that SL pairs are independent of each other, without taking into account the shared biological mechanisms underlying the SL pairs. Although several methods have incorporated genomic and proteomic data to aid SL prediction, these methods involve manual feature engineering that heavily relies on domain knowledge.

Results
Here, we propose a novel graph neural network (GNN)-based model, named KG4SL, by incorporating knowledge graph (KG) message-passing into SL prediction. The KG was constructed using 11 kinds of entities including genes, compounds, diseases, biological processes and 24 kinds of relationships that could be pertinent to SL. The integration of KG can help harness the independence issue and circumvent manual feature engineering by conducting message-passing on the KG. Our model outperformed all the state-of-the-art baselines in area under the curve, area under precision-recall curve and F1. Extensive experiments, including the comparison of our model with an unsupervised TransE model, a vanilla graph convolutional network model, and their combination, demonstrated the significant impact of incorporating KG into GNN for SL prediction.

Availability and implementation
: KG4SL is freely available at https://github.com/JieZheng-ShanghaiTech/KG4SL.

Supplementary information
Supplementary data are available at Bioinformatics online.
PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma
Authors: Oh Jung Hun , Choi Wookjin , Ko Euiseong , Kang Mingon , Tannenbaum Allen , Deasy Joseph O 
Published: April 2021

Abstract

Motivation
Convolutional neural networks (CNNs) have achieved great success in the areas of image processing and computer vision, handling grid-structured inputs and efficiently capturing local dependencies through multiple levels of abstraction. However, a lack of interpretability remains a key barrier to the adoption of deep neural networks, particularly in predictive modeling of disease outcomes. Moreover, because biological array data are generally represented in a non-grid structured format, CNNs cannot be applied directly.

Results
To address these issues, we propose a novel method, called PathCNN, that constructs an interpretable CNN model on integrated multi-omics data using a newly defined pathway image. PathCNN showed promising predictive performance in differentiating between long-term survival (LTS) and non-LTS when applied to glioblastoma multiforme (GBM). The adoption of a visualization tool coupled with statistical analysis enabled the identification of plausible pathways associated with survival in GBM. In summary, PathCNN demonstrates that CNNs can be effectively applied to multi-omics data in an interpretable manner, resulting in promising predictive power while identifying key biological correlates of disease.

Availability and implementation
The source code is freely available at: https://github.com/mskspi/PathCNN.
Bacteriophage classification for assembled contigs using graph convolutional network
Authors: Shang Jiayu , Jiang Jingzhe , Sun Yanni 
Published: April 2021

Abstract

Motivation
Bacteriophages (aka phages), which mainly infect bacteria, play key roles in the biology of microbes. As the most abundant biological entities on the planet, the number of discovered phages is only the tip of the iceberg. Recently, many new phages have been revealed using high-throughput sequencing, particularly metagenomic sequencing. Compared to the fast accumulation of phage-like sequences, there is a serious lag in taxonomic classification of phages. High diversity, abundance and limited known phages pose great challenges for taxonomic analysis. In particular, alignment-based tools have difficulty in classifying fast accumulating contigs assembled from metagenomic data.

Results
In this work, we present a novel semi-supervised learning model, named PhaGCN, to conduct taxonomic classification for phage contigs. In this learning model, we construct a knowledge graph by combining the DNA sequence features learned by convolutional neural network and protein sequence similarity gained from gene-sharing network. Then we apply graph convolutional network to utilize both the labeled and unlabeled samples in training to enhance the learning ability. We tested PhaGCN on both simulated and real sequencing data. The results clearly show that our method competes favorably against available phage classification tools.

Availability and implementation
The source code of PhaGCN is available via: https://github.com/KennthShang/PhaGCN.
Classification below the species level: when are infraspecific groups biologically meaningful?
Authors: Reydon Thomas A C , Kunz Werner 
Published: April 2021

Abstract
Infraspecific taxa (subspecies, races and varieties) are often seen as real entities in nature and recognized as biologically meaningful groups. But because infraspecific taxa by definition are subdivisions of species, their status depends entirely on the status of ‘their’ species. This makes the status of infraspecific taxa crucially dependent on the way species are considered and thus on the various species concepts that have been advanced as answers to the ‘species problem’. Accordingly, there is a profound lack of clarity regarding the following questions. What are infraspecific taxa? What is their biological meaning? Are they real entities or merely instrumental units? When should an infraspecific group be ranked and named as an infraspecific taxon? In this paper, we aim to contribute to greater clarity about these issues by examining which types of infraspecific groups are biologically meaningful in light of the main results from the species debate.
Defining indocyanine green fluorescence to assess anastomotic perfusion during gastrointestinal surgery: systematic review
Authors: Slooter M D , Mansvelders M S E , Bloemen P R , Gisbertz S S , Bemelman W A , Tanis P J , Hompes R , van Berge Henegouwen M I , de Bruin D M 
Published: April 2021

Abstract

Background
The aim of this systematic review was to identify all methods to quantify intraoperative fluorescence angiography (FA) of the gastrointestinal anastomosis, and to find potential thresholds to predict patient outcomes, including anastomotic leakage and necrosis.

Methods
This systematic review adhered to the PRISMA guidelines. A PubMed and Embase literature search was performed. Articles were included when FA with indocyanine green was performed to assess gastrointestinal perfusion in human or animals, and the fluorescence signal was analysed using quantitative parameters. A parameter was defined as quantitative when a diagnostic numeral threshold for patient outcomes could potentially be produced.

Results
Some 1317 articles were identified, of which 23 were included. Fourteen studies were done in patients and nine in animals. Eight studies applied FA during upper and 15 during lower gastrointestinal surgery. The quantitative parameters were divided into four categories: time to fluorescence (20 studies); contrast-to-background ratio (3); pixel intensity (2); and numeric classification score (2). The first category was subdivided into manually assessed time (7 studies) and software-derived fluorescence–time curves (13). Cut-off values were derived for manually assessed time (speed in gastric conduit wall) and derivatives of the fluorescence–time curves (Fmax, T1/2, TR and slope) to predict patient outcomes.

Conclusion
Time to fluorescence seems the most promising category for quantitation of FA. Future research might focus on fluorescence–time curves, as many different parameters can be derived and the fluorescence intensity can be bypassed. However, consensus on study set-up, calibration of fluorescence imaging systems, and validation of software programs is mandatory to allow future data comparison.
GC–MS and Surface Characteristics of Polyvinyl Siloxane–An In Vitro Analysis
Authors: Kasim Mohamed K , Fathima Banu R , Anand Kumar V , Sundaram Lakshmi , Thyagarajan S P 
Published: April 2021

Abstract

Objective
To assess the surface characteristics, composition and release of components of Polyvinyl siloxane (PVS) impression material and explore the use of the material other than for impressions.

Methods
Forty samples of 0.5-mm thickness and 8-mm diameter PVS discs, with few perforations, were prepared and divided into four groups. Group 1 in methanol was analyzed by GC–MS immediately and on 1st, 7th and 14th day. Group 2 and 3 placed in 10 mL of human saliva and in artificial nasal fluid, respectively, were analyzed by GC–MS at 24 hours. Group 4 was subjected to surface characteristics analysis by placing five PVS discs each in 1 mL of human saliva and 1 mL of artificial nasal fluid, respectively.

Results
On Day 1, Dodecanoic acid, methyl ester, Cyclononasiloxane, octadecamethyl, Cyclodecasiloxane and eicosamethyl (four peaks) were observed in Group 1. At 24 hours, Group 2 had additional compounds of 2-Decene,7-methyl-(Z)-, 2-Undecene,8-methyl-(Z)- and Lauryl acetate. Group 3 showed release of 32 compounds, but their retention time was less. Surface characteristics on Day 14 revealed no noticeable changes.

Conclusions
The study revealed that there was a lack of any adverse component release from PVS for a period of 2 weeks based on GC–MS analysis.