bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterisation, identification, clustering, and classification of disease
Authors: Webster A. J. , Gaitskell K. , Turnbull I. , Cairns B. J. , Clarke R. 
Published: March 2021

AbstractThe importance of quantifying the distribution and determinants of multimorbidity has prompted novel data-driven classifications of disease. Applications have included improved statistical power and refined prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases, with studies using molecular information, age of disease incidence, and sequences of disease onset (“disease trajectories”) to classify disease clusters. Here we consider whether easily measured risk factors such as height and BMI can effectively characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for analysis using clinical and epidemiological criteria, and conventional proportional hazards models were used to estimate associations with 12 established risk factors. Several diseases had strongly sex-dependent associations of disease risk with BMI. Importantly, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. These included 10 diseases presently classified as “Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified”. Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.
Spectral collapse in multiqubit two-photon Rabi model
Authors: Lo C. F. 
Published: March 2021

AbstractWe have shown that the smallest possible singel-qubit critical coupling strength of the N-qubit two-photon Rabi model is only 1/N times that of the two-photon Rabi model. The spectral collapse can thus occur at a more attainable value of the critical coupling. For both of the two-qubit and three-qubit cases, we have also rigorously demonstrated that at the critical coupling the system not only has a set of discrete eigenenergies but also a continuous energy spectrum. The discrete eigenenergy spectrum can be derived via a simple one-to-one mapping to the bound state problem of a particle of variable effective mass in the presence of a finite potential well and a nonlocal potential. The energy difference of each qubit, which specifies both the depth of the finite potential well and the strength of the nonlocal potential, determines the number of bound states available, implying that the extent of the incomplete spectral collapse can be monitored in a straightforward manner.
Brain pathology recapitulates physiology: A network meta-analysis
Authors: Vanasse Thomas J. , Fox Peter T. , Fox P. Mickle , Cauda Franco , Costa Tommaso , Smith Stephen M. , Eickhoff Simon B. , Lancaster Jack L. 
Published: March 2021

AbstractNetwork architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic ‘cost’ significantly differs along this transdiagnostic/multimodal gradient.
Conductive electrodes of metallic-organic compound CH3CuS nanowires for all-solid-state flexible supercapacitors
Authors: Wang Xiaodan , Lu Yao , Zhao Haofei , Sun Yinghui , Wang Rongming 
Published: March 2021

Flexible and conductive electrodes are one of the most important components for flexible supercapacitor. Herein, a flexible supercapacitor device based on CH3CuS nanowire electrodes was fabricated.
An autophagy-related prognostic signature associated with immune microenvironment features of uveal melanoma
Authors: Zheng Zhuotao , Zhang Lingyue , Tu Zewei , Deng Yan , Yin Xiaolong 
Published: March 2021

Abstract
Autophagy is involved in cancer initiation and progression but its role in uveal melanoma (UM) was rarely investigated. Herein, we built an autophagy-related gene (ARG) risk model of UM patients by univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression model and filtrated out nine prognostic ARGs in The Cancer Genome Atlas (TCGA) cohort. Survival and Receiver Operating Characteristic (ROC) Curve analysis in the TCGA and other four independent UM cohorts (GSE22138, GSE27831, GSE44295 and GSE84976) proved that the ARG-signature possessed robust and steady prognosis predictive ability. We calculated risk scores for patients included in our study and patients with higher risk scores showed worse clinical outcomes. We found the expressions of the nine ARGs were significantly associated with clinical and molecular features (including risk score) and overall survival (OS) of UM patients. Furthermore, we utilized univariate and multivariate Cox regression analyses to determine the independent prognostic ability of the ARG-signature. Functional enrichment analysis showed the ARG-signature was correlated with several immune-related processes and pathways like T-cell activation and T-cell receptor signaling pathway. Gene set enrichment analysis (GSEA) found tumor hallmarks including angiogenesis, IL6-JAK-STAT3-signaling, reactive oxygen species pathway and oxidative phosphorylation were enriched in high-risk UM patients. Finally, infiltrations of several immune cells and immune-related scores were found significantly associated with the ARG-signature. In conclusion, the ARG-signature might be a strong predictor for evaluating the prognosis and immune infiltration of UM patients.
Efficient secret key generation scheme of physical layer security communication in ubiquitous wireless networks
Authors: Xiong Hailiang , Wang Guangyuan , Ding Jian , Zhu Weihong , Xu Hongji , Hu Changwu , Mai Zhenzhen , Bian Ruochen 
Published: March 2021

AbstractThis paper focuses on high efficiency secret key generation mechanism of physical‐layer communication over fading channels in ubiquitous wireless networks. The secret key rate via traditional physical‐layer approach could be limited when the wireless propagation channels connecting two sensors change slowly. To generate a high‐rate secret key and improve the communication efficiency over quasi‐static block fading channels, a novel multi‐randomness device‐to‐device secret key generation strategy and a cooperative communication mechanism aided by relay nodes are proposed. In the proposed schemes, the legitimate members to send random signals rotationally in every coherent time are set; thus, two legitimate ubiquitous wireless network members, Alice and Bob, can obtain the potential correlated information by exploiting the randomness and the reciprocity of the wireless propagation channels. Considering the reciprocity of wireless channels is variable while the forward channel gain and backward channel gain are correlated in coherent time, a modified secret key generation scheme is proposed via layered coding with theoretical secret key rates derived. The simulation results show that the proposed scheme outperforms traditional approaches with favourable application prospects in ubiquitous wireless communications networks and internet of things.
Towards accurate classification of skin cancer from dermatology images
Authors: Gautam Anjali , Raman Balasubramanian 
Published: March 2021

AbstractSkin cancer is the most well‐known disease found in the individuals who are exposed to the Sun's ultra‐violet (UV) radiations. It is identified when skin tissues on the epidermis grow in an uncontrolled manner and appears to be of different colour than the normal skin tissues. This paper focuses on predicting the class of dermascopic images as benign and malignant. A new feature extraction method has been proposed to carry out this work which can extract relevant features from image texture. Local and gradient information from and directions of images has been utilized for feature extraction. After that images are classified using machine learning algorithms by using those extracted features. The efficacy of the proposed feature extraction method has been proved by conducting several experiments on the publicly available image dataset 2016 International Skin Imaging Collaboration (ISIC 2016). The classification results obtained by the method are also compared with state‐of‐the‐art feature extraction methods which show that it performs better than others. The evaluation criteria used to obtain the results are accuracy, true positive rate (TPR) and false positive rate (FPR) where TPR and FPR are used for generating receiver operating characteristic curves.
Two‐dimensional DFT with sliding and hopping windows for edge map generation of road images
Authors: Vishwakarma Amit Kr. , Sukumar N. , Sumathi P. 
Published: March 2021

AbstractAn edge map generation technique based on two‐dimensional discrete Fourier transform with sliding and hopping windows is proposed for road images to detect the lanes and road markings. A 2 2 sliding/hopping window DFT with bin indices () for horizontal edge detection and () for vertical edge detection has been proposed. The 2‐D SDFT/HDFT‐based edge detector has been proved to be more efficient for lane and road marking images in comparison with conventional edge detectors and cellular neural network based edge detectors. In the presence of noise and various signal to noise ratio conditions, the horizontal and vertical edges have been efficiently recovered with good Pratt figure of merit without applying any pre‐processing, noise removal process, and post processing techniques. The PFOM was found to be quite stable with wide threshold range for various noise levels. The consistent performance of the proposed edge detector is proved with MSE and PSNR determination of detected edge images. Moreover, the proposed 2‐D SDFT/HDFT‐based edge detector performs well in developing edge maps for real‐time road videos. The system‐on‐chip implementation of the 2‐D SDFT/HDFT edge detector on Cyclone IV FPGA chip is also carried out for detecting the lane and road markings.
Impact of adding activated bentonite to thermally aged ester‐based TiO2 nanofluids on insulation performance
Authors: Amalanathan A. J. , Harid N. , Griffiths H. , Sarathi R. 
Published: March 2021

AbstractThe authors report the key findings from an experimental study that explored the use of activated bentonite for the reclamation of thermally aged ester‐based transformer nanofluids to improve their insulation performance. Bentonite activated with acid treatment caused an increase in the specific surface area and pore volume of bentonite compared to the bentonite sample before treatment, thus imparting an improved adsorption capability. Physico‐chemical diagnostic studies were carried out to characterise the activated bentonite. The insulation performance of the reclaimed natural ester and nano‐filled ester fluid samples was assessed by measuring the corona inception voltage and breakdown voltage of each fluid sample, apart form measuring the flow electrification current using the spinning disk method. The results revealed that the reclamation process improved the corona inception voltage, dissipation factor and the breakdown voltage of the base ester fluid sample due to attraction of carbon particles to activated bentonite, but no significant variation was observed with nanofluids due to the depletion of the electrical double layer. The flow electrification current of ester and ester nanofluids reduced after treatment with activated bentonite, may be attributed to the interaction between copper and bentonite that alters the double layer formation responsible for the separation of charges.
A survey of IRAS young stellar object candidates
Authors: López Rosario , Riera Angels , Estalella Robert , Gómez Gabriel 
Published: March 2021

Context. Jets and outflows are associated with young stellar objects across the stellar mass spectrum, from brown dwarf protostars to massive Ae/Be stars. Frequently the jet morphology is spatially discontinuous because of the temporal variability of the ejection from the driving source. Images covering a wide field of view around the jet-driving source are useful to map the large-scale jet emission and to explore the mass ejection history.
Aims. The aim of our work was to search for large-scale optical Herbig-Haro (HH) objects lying in a wide field around a sample of IRAS sources, which are candidates to trace young stellar objects.
Methods. Deep narrowband images through the Hα and [S II] emission lines, and through an off-line continuum filter, covering a wide (~15′) field around the IRAS targets were acquired. The images in the three filters were analyzed to identify shock-excited line emission (i.e., HH) in contrast to scattered line emission.
Results. New images of a sample of 15 IRAS sources, obtained in a homogeneous way are presented. HH emission was detected in six fields, and the astrometry of the knot features is given. The nature of the extended emission as scattered emission around nine of the IRAS targets is confirmed. For seven IRAS sources with unclear optical counterparts, a more plausible counterpart is proposed. A refined value of the source distance is reported for seven targets. An update of the main data available for each of the sampled fields, including images from public data archives, is also presented.
Iridium(III)-Catalyzed C−H Functionalization of Triarylphosphine Oxides with Diazo Dicarbonyl Compounds: Synthesis of α-Aryl 1,3-Dicarbonyl Derivatives
Authors: Yang Shang-Dong , Lou Qin-Xin , Li Jing-Yu 
Published: March 2021

AbstractA novel (pentamethylcyclopenta-1,3-dienyl)iridium(III)-catalyzed direct C–H functionalization of triarylphosphine oxides with diazo dicarbonyl compounds through carbene insertion has been developed. This strategy provides a simple and efficient route to the construction of α-arylated 1,3-dicarbonyl compounds, which are important building blocks in pharmaceutical chemistry.
What is robotics made of? The interdisciplinary politics of robotics research
Authors: Michalec Ola , O’Donovan Cian , Sobhani Mehdi 
Published: March 2021

AbstractUnder framings of grand challenges, robotics has been proposed as a solution to a wide range of societal issues such as road safety, ageing society, economic productivity and climate change. However, what exactly is robotics research? From its inception, robotics has been an inherently interdisciplinary field, bringing together diverse domains such as engineering, cognitive science, computer science and, more recently, knowledge from social sciences and humanities. Previous research on interdisciplinarity shows that this mode of knowledge production is often driven by societal concerns and political choices. The politics of who gets to make these choices and on what terms is the focus of empirical research in this paper. Using a novel mixed-method approach combining bibliometrics, desk-based analysis and fieldwork, this article builds a narrative of interdisciplinarity at the UK’s largest public robotics lab, the Bristol Robotics Laboratory. This paper argues for the recognition of the plural ways of knowing interdisciplinarity. From citation analysis, through tracing of the emerging fields and disciplines, to, finally, the investigation of researchers’ experiences; each method contributes a distinct and complementary outlook on “what robotics is made of”. While bibliometrics allows visualising prominent disciplines and keywords, document analysis reveals influential and missing stakeholders. Meanwhile, fieldwork explores the logics underpinning robotics and identifies the capabilities necessary to perform the research. In doing so, the paper synthesises plural ways of locating politics in interdisciplinary research and provides recommendations for enabling “structural preparedness for interdisciplinarity”.
Predicting organizational performance from motivation in Oromia Seed Enterprise Bale branch
Authors: Jobira Askalech Feyisa , Mohammed Abdulnasir Abdulmelike 
Published: March 2021

AbstractMotivation is one of the most researched yet crucial topics in academia from various perspectives. Despite this, researches show mixed results about the effect of extrinsic motivation on intrinsic motivation and organizational performance. Studies in Ethiopia also lack causal analysis and theoretical underpinning that made contributions from academia very little. Hence, this research is important to assess the effect of extrinsic motivation on intrinsic motivation and organizational performance from a cognitive evaluation theory perspective. The researchers adopted an explanatory research design with a quantitative approach. The entire 119 employees of the Oromia Seed Enterprise, Bale branch were included in the study to collect primary data through a close-ended questionnaire. The collected data was processed by SPSS software version 20. The relationship analysis was addressed by correlation and binary logistic regression analysis. Seen from extrinsic and intrinsic motivation aspects, the findings of the study showed that Oromia Seed Enterprise had a moderate level of organizational performance and a moderate level of employees’ motivation. The correlation analysis result indicated that employees’ extrinsic and intrinsic motivation had a positive relationship with organizational performance. The binary logistic regression analysis also indicated that extrinsic and intrinsic motivation had a positive and significant influence on organizational performance. However, the interaction effect of intrinsic and extrinsic motivation on organizational performance was not significant, implying the absence of influence when both intrinsic and extrinsic motivations happen at the same time. Finally, the study results have a theoretical contribution for compensating the lack of actual experience in the Ethiopian organization’s context. Equally, the understanding of the moderated relationship among the study variables may encourage Oromia Seed Enterprise and its managers to develop a practical motivation system, which entertains the complex interaction of motivation variables to improve organizational performance. In addition, studies of this nature can inform policymakers to strengthen an incentive system as well as other motivation veins in the Ethiopian public organizations.
Revealing lineage-related signals in single-cell gene expression using random matrix theory
Authors: Nitzan Mor , Brenner Michael P. 
Published: March 2021

Significance
Single-cell technologies are rapidly advancing, allowing us to gauge the heterogeneity and structure of cellular communities, tissues, and full organisms. The correlations between genes and between cells within such systems can reveal patterns of regulatory interactions, physical structure, and temporal progression of cells along biological processes. However, it is generally a challenge to identify and tease apart these mixed signals within the noisy, high-dimensional single-cell data. Here, we show it is possible to detect a signature for lineage in the covariance spectrum of single-cell data, predict how it will change with developmental time, and predict how it can be extended to examine the spatial structure of a tissue.
The evolution of altruism through war is highly sensitive to population structure and to civilian and fighter mortality
Authors: Dyble Mark 
Published: March 2021

Significance
Many evolutionary theorists have suggested that the human capacity for altruism was forged in war, with cohesive and altruistic groups outcompeting their selfish neighbors. Assessing this “parochial altruism” hypothesis relies largely on computational modeling. Here, I reexamine a well-known model that explores the coevolution of altruism and war. As well as clarifying the importance of factors such as the lethality of war to fighters and civilians, the results show that the evolution of altruism in this model relies on a degree of genetic differentiation between groups that exceeds that seen among hunter-gatherers. Furthermore, when the model produces a more realistic population structure, altruism does not evolve, casting doubt on the plausibility of the parochial altruism hypothesis.
Behavioral responses across a mosaic of ecosystem states restructure a sea otter–urchin trophic cascade
Authors: Smith Joshua G. , Tomoleoni Joseph , Staedler Michelle , Lyon Sophia , Fujii Jessica , Tinker M. Tim 
Published: March 2021

SignificanceEcological processes that enhance or dampen the likelihood of shifts between top-down (i.e., predator-driven) and bottom-up (i.e., resource-driven) forcing underpin community regulation, functioning, and stability. Here, we demonstrate how the behavioral response of an apex predator to changes in prey behavior and condition (i.e., energetic profitability) can dramatically alter the strength of top-down forcing and enhance the role (or relative contribution) of bottom-up community regulation, depending on the spatial organization of diverse ecosystem states. These results highlight the role of consumer and predator trait-mediated responses to resource mosaics that are common throughout the natural world and enhance understanding of reciprocal feedbacks between top-down and bottom-up forcing on the regional stability of ecosystems.
A conserved Ctp1/CtIP C-terminal peptide stimulates Mre11 endonuclease activity
Authors: Zdravković Aleksandar , Daley James M. , Dutta Arijit , Niwa Tatsuya , Murayama Yasuto , Kanamaru Shuji , Ito Kentaro , Maki Takahisa , Argunhan Bilge , Takahashi Masayuki , Tsubouchi Hideo , Sung Patrick , Iwasaki Hiroshi 
Published: March 2021

Significance
A DNA double-strand break (DSB) can be repaired accurately by homologous recombination. The Mre11-Rad50-Nbs1 (MRN) complex is responsible for initiating homologous recombination by degrading 5′-ended DNA strand, where its activation by the Ctp1 cofactor plays a pivotal role. Here, by using purified fission yeast proteins, we show that two major elements comprise MRN activation. First, phosphorylation of Ctp1 promotes the physical interaction between MRN and Ctp1. Second, the C terminus of Ctp1 activates nucleolytic processing of DSB ends. In the latter case, a small peptide comprising only 15 amino acids from the Ctp1 C terminus is sufficient to activate MRN. Our results elucidate the core elements underlying MRN activation by Ctp1.