bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene expression inference with deep learning
Authors: Chen Yifei , Li Yi , Narayan Rajiv , Subramanian Aravind , Xie Xiaohui 
Published: December 2015

AbstractMotivationLarge-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ῀1,000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression, limiting its accuracy since it does not capture complex nonlinear relationship between expression of genes.ResultsWe present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based GEO dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms linear regression with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than linear regression in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2,921 expression profiles. Deep learning still outperforms linear regression with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes.AvailabilityD-GEX is available athttps://github.com/uci-cbcl/D-GEX.Contactxhx@ics.uci.edu
Architecting a distributed bioinformatics platform with iRODS and iPlant Agave API
Authors: Wang Liya , Van Buren Peter , Ware Doreen 
Published: December 2015

AbstractOver the past few years, cloud-based platforms have been proposed to address storage, management, and computation of large-scale data, especially in the field of genomics. However, for collaboration efforts involving multiple institutes, data transfer and management, interoperability and standardization among different platforms have imposed new challenges. This paper proposes a distributed bioinformatics platform that can leverage local clusters with remote computational clusters for genomic analysis using the unified bioinformatics workflow. The platform is built with a data server configured with iRODS, a computation cluster authenticated with iPlant Agave system, and web server to interact with the platform. A Genome-Wide Association Study workflow is integrated to validate the feasibility of the proposed approach.
White box, black box and self-organization
Authors: Kasianiuk Krzysztof 
Published: December 2015

Purpose
– The purpose of this paper is to present two system identification models – “white box” and “black box” – as useful tools that help understand self-organization processes within and outside the organizations facilitated by leaders. Every leader is presented as a “systems designer” who plays a fundamental role in the process of self-organization, both within and outside the organization under study.

Design/methodology/approach
– First, “white box” and “black box” system identification models are presented as a basis for an integrated model of the “system” and its “environment.” Next, the ideas of “closed” and “open” systems as the prerequisites of self-organization processes are described. Finally, two basic leadership tactics as well as their combination are characterized and discussed.

Findings
– Two system identification models give a complementary view to the reality, as they combine both reductionist and holistic perspectives. The argument presented in the paper shows that there is a far reaching complementarity of the two system identification models.

Practical implications
– Since leaders need to comprehend complex adaptive processes taking place in the organizations and in their environment, they search for the best strategy to approach this task. The tactics presented in the paper could serve as a cognitive tools that help approach the reality leaders are immersed in.

Originality/value
– The paper utilizes two categories that are well recognized in systems theory and cybernetics, combines them with the idea of self-organization and puts it all in the context of leadership. It provides an integrated, yet relatively simple cognitive scheme that may be of theoretical and practical use.
An optimization model of the acceptable consensus and its economic significance
Authors: Gong Zaiwu , Xu Xiaoxia , Forrest Jeffrey , Yang Yingjie 
Published: December 2015

Purpose
– The purpose of this paper is to construct an optimal resource reallocation model of the limited resource by a moderator for reaching the greatest consensus, and show how to reallocate the limited resources by using optimization methodology once the consensus opinion is reached. Moreover, this paper also devotes to theoretically exploring when or what is the condition that the group decision-making (GDM) system is stable; and when new opinions enter into the GDM, how the level of consensus changes.

Design/methodology/approach
– By minimizing the differences between the individuals’ opinions and the collective consensus opinion, this paper constructs a consensus optimization model and shows that the objective weights of the individuals are actually the optimal solution to this model.

Findings
– If all individual deviations of the decision makers (DMs) from the consensus balance each other out, the information entropy theorem shows this GDM is most stable, and economically each individual DM gets the same optimal unit of compensation. Once the consensus opinion is determined and each individual opinion of the DMs is under an acceptable consensus level, the consensus is still acceptable even if additional DMs are added, and the moderator’s cost is still no more than a fixed upper limitation.

Originality/value
– The optimization model based on acceptable consensus is constructed in this paper, and its economic significance, including the theoretical and practical significance, is emphatically analyzed: it is shown that the weight information of the optimization model carries important economic significance. Besides, some properties of the proposed model are discussed by analyzing its particular solutions: the stability of the consensus system is explored by introducing information entropy theory and variance distribution; in addition, the effect of adding new DMs on the stability of the acceptable consensus system is discussed by analyzing the convergence of consensus level: it is also built up the condition that once the consensus opinion is determined, the consensus degree will not decrease even when additional DMs are added to the GDM.
The interaction matrix: from individual goal-setting to the four modes of coexistence
Authors: Nechansky Helmut 
Published: December 2015

Purpose
– The purpose of this paper is to show how individual acts of goal-setting of two persons or systems A and B determine, which modes of coexistence become possible in an interaction of the two.

Design/methodology/approach
– Some person or system A can approach another person or system B with an inclination to realize one of four goal-setting processes: first, A sets goals for B; second, A sets no own goals; third, A pursues own goals alone; and fourth, A and B develop mutual goals. And an interaction of A and B can lead to just four modes of coexistence: first, conflict – A and B fight; second, hierarchy – A submits to B; third, independence in niches – A and B do not interact; and fourth, cooperation – A and B work together.

Findings
– Placing the inclinations of A and B to realize one of the four goal-setting processes in a 4×4 matrix leads to the interaction matrix. It shows that individual goal-setting processes predetermine and limit the available modes of coexistence, i.e. cause certain patterns of interactions.

Practical implications
– The interaction matrix can be applied to all interactions between persons, groups and social units generally.

Originality/value
– The paper introduces a theoretical framework covering all options of goal-orientated behavior. It explains the interrelation between individual goal-setting of persons and systems and the resulting behavioral options in interactions. It is applicable to all behavioral sciences.
2-tuple linguistic Muirhead mean operators for multiple attribute group decision making and its application to supplier selection
Authors: Qin Jindong , Liu Xinwang 
Published: December 2015

Purpose– The purpose of this paper is to develop some 2-tuple linguistic aggregation operators based on Muirhead mean (MM), which is combined with multiple attribute group decision making (MAGDM) and applied the proposed MAGDM model for supplier selection under 2-tuple linguistic environment.Design/methodology/approach– The supplier selection problem can be regarded as a typical MAGDM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MAGDM problems with 2-tuple linguistic information based on traditional MM operator. The MM operator is a well-known mean type aggregation operator, which has some particular advantages for aggregating multi-dimension arguments. The prominent characteristic of the MM operator is that it can capture the whole interrelationship among the multi-input arguments. Motivated by this idea, in this paper, the authors develop the 2-tuple linguistic Muirhead mean (2TLMM) operator and the 2-tuple linguistic dual Muirhead mean (2TLDMM) operator for aggregating the 2-tuple linguistic information, respectively. Some desirable properties and special cases are discussed in detail. Based on which, two approaches to deal with MAGDM problems under 2-tuple linguistic information environment are developed. Finally, a numerical example concerns the supplier selection problem is provided to illustrate the effectiveness and feasibility of the proposed methods.Findings– The results show that the proposed can solve the MAGDM problems within the context of 2-tuple linguistic information, in which the attributes are existing interaction phenomenon. Some 2-tuple aggregation operators based on MM have been developed. A case study of supplier selection is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.Practical implications– The proposed methods can solve the 2-tuple linguistic MAGDM problem, in which the interactions exist among the attributes. Therefore, it can be used to supplier selection problems and other similar management decision problems.Originality/value– The paper develop some 2-tuple aggregation operators based on MM, and further present two methods based on the proposed operators for solving MAGDM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.
The Burden of Major Adverse Cardiac Events and Antiplatelet Prevention in Patients with Coronary or Peripheral Arterial Disease
Authors: Khoury Hanane , Lavoie Louis , Welner Sharon , Folkerts Kerstin 
Published: December 2015

SummaryBackgroundPatients with a history of a cardiovascular (CV) disease are at high risk of suffering secondary major adverse cardiac events (MACE), namely death, nonfatal myocardial infarction (MI), stroke, symptomatic pulmonary embolism, CV and all‐cause hospitalization, and bleeding.MethodsA comprehensive review of the literature was conducted to review the epidemiology and burden of MACE in patients with coronary or peripheral arterial disease (CAD or PAD) in Europe and other ex‐US regions. Relevant articles published between 2003 and 2013 were retrieved from PubMed and other sites.ResultsMACE incidence and prevalence in patients with CAD or PAD were increased by at least 1.4‐fold compared with matched controls with no CV disease. In patients with CAD, MACE mostly occurred within 30 days of primary percutaneous coronary intervention; incidence decreased with time. Increased oxidative stress in coronary and peripheral arteries, diabetes, and chronic kidney disease were identified as the main risk factors for MACE in patients with CAD and PAD. Registry data showed that, although preventive antiplatelet therapy was prescribed at high rates, a large proportion (9–56%) of patients did not receive treatment. Furthermore, adherence to treatment declined over time, potentially leading to disease worsening.ConclusionDespite gaps in the literature, this assessment showed that MACE's risk is substantial among patients with CAD or PAD and that the use of preventive therapies is suboptimal. Development of additional preventive therapies for these patients is warranted.
Fine structure of diffused pseudobranchial neurosecretory cells associated with carotid labyrinth in an air‐breathing catfish Clarias batrachus
Authors: Sengar Manvendra , Yadav Laxmi , Gopesh Anita , Zaccone Daniele , Lauriano Eugenia Rita , Capillo Gioiele 
Published: December 2015

AbstractFish are known to have branchial chemoreceptors and even extrabranchial chemoreceptors to meet the challenges of aquatic environment. The pseudobranchial neurosecretory system associated with carotid labyrinth (CL) is one such example. CL – a chemosensory organ is well known in amphibians. The homologous structure also exists in fish. Clusters of neurosecretory cells, close to the CL and the first two efferent branchial arteries occur in catfish and a few other groups of teleosts. These cells belong to the pseudobranchial neurosecretory system (PNS). To reveal the ultrastructure of CL and the pseudobranchial neurosecretory cells (PNSCs), environmental scanning electron microscope (ESEM) and transmission electron microscope (TEM) investigations were made in an Asian air‐breathing catfish Clarias batrachus. Under ESEM, the PNS appeared as a mass of cells innervated by nerves and supplied by blood capillaries. The CL appeared to have a network of blood capillaries. The transmission electron microscopic investigations showed pear shaped PNSCs having different sizes of dense cored vesicles (DCVs), numerous mitochondria, nerve varicosities, indicating a secretory function of the cells. The CL shows a close association with PNSCs and smooth muscles. Although the exact function of the CL and associated PNSCs in the biology of fish is far from clear, their morphology suggests they are involved in a stress response such as to hypoxia.
Regulatory T and B lymphocytes in a spontaneous autoimmune polyneuropathy
Authors: Quan S , Sheng J R , Abraham P M , Soliven B 
Published: December 2015

SummaryB7-2–/– non-obese diabetic (NOD) mice develop a spontaneous autoimmune polyneuropathy (SAP) that mimics the progressive form of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). In this study, we focused on the role of regulatory T cells (Tregs) and regulatory B cells (Bregs) in SAP. We found that deletion of B7-2 in female NOD mice led to a lower frequency and number of Tregs and Bregs in spleens and lymph nodes. Tregs but not Bregs suppressed antigen-stimulated splenocyte proliferation, whereas Bregs inhibited the T helper type 1 (Th1) cytokine response. Both Tregs and Bregs induced an increase in CD4+interleukin (IL)−10+ cells, although less effectively in the absence of B7-2. Adoptive transfer studies revealed that Tregs, but not Bregs, suppressed SAP, while Bregs attenuated disease severity when given prior to symptom onset. B cell deficiency in B cell-deficient (muMT)/B7-2–/– NOD mice prevented the development of SAP, which would indicate that the pathogenic role of B cells predominates over its regulatory role in this model. We conclude that Bregs and Tregs control the immunopathogenesis and progression of SAP in a non-redundant fashion, and that therapies aimed at expansion of Bregs and Tregs may be an effective approach in autoimmune neuropathies.
Mechanisms of Reference Frame Selection in Spatial Term Use: Computational and Empirical Studies
Authors: Schultheis Holger , Carlson Laura A. 
Published: December 2015

AbstractPrevious studies have shown that multiple reference frames are available and compete for selection during the use of spatial terms such as “above.” However, the mechanisms that underlie the selection process are poorly understood. In the current paper we present two experiments and a comparison of three computational models of selection to shed further light on the nature of reference frame selection. The three models are drawn from different areas of human cognition, and we assess whether they may be applied to a reference frame selection by examining their ability to account for both existing and new empirical data comprising acceptance rates, response times, and response time distributions. These three models are the competitive shunting model (Schultheis,), the leaky competing accumulator (LCA) model (Usher & McClelland,), and a lexical selection model (Howard, Nickels, Coltheart, & Cole‐Virtue,). Model simulations show that only the LCA model satisfactorily accounts for the empirical observations. The key properties of this model that seem to drive its success are its bounded linear activation function, its number and type of processing stages, and its use of decay. Uncovering these critical properties has important implications for our understanding not only of spatial term use, in particular, but also of conflict and selection in human cognition more generally.
Changes in abundances of forest understorey birds on Africa's highest mountain suggest subtle effects of climate change
Authors: Dulle Hamadi I. , Ferger Stefan W. , Cordeiro Norbert J. , Howell Kim M. , Schleuning Matthias , Böhning‐Gaese Katrin , Hof Christian 
Published: December 2015

AbstractAimUnderstanding how species respond to climate and land use change is of prime importance for biodiversity conservation. However, studies using historical, empirical data to understand species responses to climate change and anthropogenic habitat disturbance remain scarce, especially for tropical mountain ecosystems. Here, we compare historical to recent mist net data to study changes in abundance of forest understorey birds along two elevational gradients.LocationMount Kilimanjaro, Tanzania.MethodsWe investigate patterns of understorey bird abundance along elevational and disturbance gradients on two slopes of Mt. Kilimanjaro between 1991 and 2011. To understand species responses to climate change and disturbance, we use a trait‐based approach. Specifically, we test whether and how species' traits (temperature, habitat and dietary preferences) affect species responses to environmental change.ResultsWe found that over the 20‐year time interval, mean minimum temperature increased across all sites along the elevational gradient, while levels of habitat disturbance remained similar. Mean abundance of understorey bird species increased significantly, especially at higher elevations and on the southern slope. Temporal increases were not related to species' temperature preferences and were detected for habitat generalists as well as herbivorous and omnivorous species, but not for forest specialists and insectivores.Main conclusionsOur results suggest subtle effects of climate change on bird abundances which would not have been detectable if we had examined elevational range shifts or changes in species richness. Both warm‐ and cold‐adapted species appear to have benefited from increases in minimum temperatures at high elevations. This was not the case for forest specialists and insectivores which remained stable between sampling periods. This demonstrates that different groups of birds vary in their response to ongoing climatic changes. Our results underline the importance of tropical mountain ecosystems not only as global biodiversity hotspots, but also as safe havens for biodiversity in the face of global climate change.
Contemporary niche contraction affects climate change predictions for elephants and giraffes
Authors: Martínez‐Freiría Fernando , Tarroso Pedro , Rebelo Hugo , Brito José C. 
Published: December 2015

AbstractAimClimate change assessments are largely based on correlative species distribution models (SDMs) that are sensible to spatial biases or incompleteness of input distribution data. We tested whether changes on the species' climatic niche resulting from recent human‐induced range contractions have a significant influence on SDM predictions of future species distributions.LocationAfrica.MethodsFor this study, we selected two highly detectable species with acknowledged human‐induced range contractions, namely the African savanna elephant (Loxodonta africana) and giraffe (Giraffa camelopardalis). We used presence data until the 1970s to describe each species' historical distribution, while more recent data characterized the contemporary distribution. We compared the temporal variation between these species distributions using multivariate analyses and the combination of four different SDM algorithms to predict historical, contemporary and future distributional ranges under climate change scenarios.ResultsWe show how range contraction differentially reduces the climatic variability associated with the species niche and has an important influence on the predictions of suitable climatic space and species vulnerability trend under climate change scenarios. Future predictions of the distribution of the elephant were mainly affected by the loss of occupied area at the margins of the historical distributions, resulting in a lesser predicted extent when using the contemporary dataset. As for the giraffe models, there were more dramatic consequences with large areas of West Africa failing to be predicted as suitable in the contemporary models, probably as a result from the loss of climatic information due to the species almost complete disappearance from that region.Main conclusionsOur findings support the importance of considering historical distributional ranges of species in climate change studies in order to account for their full climatic niche and to derive more reliable predictions of future distribution. This is particularly important in species for which distributional ranges have been strongly affected by human activities.