bluuebunny/crossref_metadata_2025_split huggingface dataset:
CrosstalkNet: mining large-scale bipartite co-expression networks to characterize epi-stroma crosstalk
Authors: Manem Venkata , Adam George , Gruosso Tina , Gigoux Mathieu , Bertos Nicholas , Park Morag , Haibe-Kains Benjamin 
Published: January 2017

ABSTRACTBackground:Over the last several years, we have witnessed the metamorphosis of network biology from being a mere representation of molecular interactions to models enabling inference of complex biological processes. Networks provide promising tools to elucidate intercellular interactions that contribute to the functioning of key biological pathways in a cell. However, the exploration of these large-scale networks remains a challenge due to their high-dimensionality.Results:CrosstalkNet is a user friendly, web-based network visualization tool to retrieve and mine interactions in large-scale bipartite co-expression networks. In this study, we discuss the use of gene co-expression networks to explore the rewiring of interactions between tumor epithelial and stromal cells. We show how CrosstalkNet can be used to efficiently visualize, mine, and interpret large co-expression networks representing the crosstalk occurring between the tumour and its microenvironment.Conclusion:CrosstalkNet serves as a tool to assist biologists and clinicians in exploring complex, large interaction graphs to obtain insights into the biological processes that govern the tumor epithelial-stromal crosstalk. A comprehensive tutorial along with case studies are provided with the application.Availability:The web-based application is available at the following location:http://epistroma.pmgenomics.ca/app/. The code is open-source and freely available fromhttp://github.com/bhklab/EpiStroma-webapp.Contact:bhaibeka@uhnresearch.ca
Resolution of conflict between parental genomes in a hybrid species
Authors: Eroukhmanoff Fabrice , Bailey Richard I. , Elgvin Tore O. , Hermansen Jo S. , Runemark Anna R. , Trier Cassandra N. , Sætre Glenn-Peter 
Published: January 2017

AbstractThe development of reproductive barriers against parent species is crucial during hybrid speciation, and post-zygotic isolation can be important in this process. Genetic incompatibilities that normally isolate the parent species can become sorted in hybrids to form reproductive barriers towards either parent. However, the extent to which this sorting process is systematically biased and therefore predictable in which loci are involved and which alleles are favored is largely unknown. Theoretically, reduced fitness in hybrids due to the mixing of differentiated genomes can be resolved through rapid evolution towards allelic combinations ancestral to lineage-splitting of the parent species, as these alleles have successfully coexisted in the past. However, for each locus, this effect may be influenced by its chromosomal location, function, and interactions with other loci. We use the Italian sparrow, a homoploid hybrid species that has developed post-zygotic barriers against its parent species, to investigate this prediction. We show significant bias towards fixation of the ancestral allele among 57 nuclear intragenic SNPs, particularly those with a mitochondrial function whose ancestral allele came from the same parent species as the mitochondria. Consistent with increased pleiotropy leading to stronger fitness effects, genes with more protein-protein interactions were more biased in favor of the ancestral allele. Furthermore, the number of protein-protein interactions was especially low among candidate incompatibilities still segregating within Italian sparrows, suggesting that low pleiotropy allows steep intraspecific clines in allele frequencies to form. Finally, we report evidence for pervasive epistatic interactions within one Italian sparrow population, particularly involving loci isolating the two parent species but not hybrid and parent. However there was a lack of classic incompatibilities and no admixture linkage disequilibrium. This suggests that parental genome admixture can continue to constrain evolution and prevent genome stabilization long after incompatibilities have been purged.
Mitochondrial RNA processing in absence of tRNA punctuations in octocorals
Authors: Shimpi Gaurav G. , Vargas Sergio , Poliseno Angelo , Gert Wörheide 
Published: January 2017

AbstractBackgroundMitogenome diversity is staggering among early branching animals with respect to size, gene density and content, gene orders, and number of tRNA genes, especially in cnidarians. This last point is of special interest as tRNA cleavage drives the maturation of mitochondrial mRNAs and is a primary mechanism for mt-RNA processing in animals. Mitochondrial RNA processing in non-bilaterian metazoans, some of which possess a single tRNA gene in their mitogenomes, is essentially unstudied despite its importance in understanding the evolution of mitochondrial transcription in animals.ResultsWe characterized the mature mitochondrial mRNA transcripts in a species of the octocoral genusSinularia(Alcyoniidae: Octocorallia), and defined precise boundaries of transcription units using different molecular methods. Most mt-mRNAs were polycistronic units containing two or three genes and 5’ and/or 3’ untranslated regions (UTRs) of varied length. The octocoral specific, mtDNA-encoded mismatch repair gene,mtMutS, was found to undergo alternative polyadenylation (APA), and exhibited differential expression of alternate transcripts suggesting a unique regulatory mechanism for this gene. In addition, a long noncoding RNA complementary to the ATP6 gene (lncATP6) potentially involved in antisense regulation was detected.ConclusionsMt-mRNA processing in octocorals bearing a single mt-tRNA is complex. Considering the variety of mitogenome arrangements known in cnidarians, and in general among non-bilaterian metazoans, our findings provide a first glimpse into the complex mtDNA transcription, mt-mRNA processing, and regulation among early branching animals and represents a first step towards understanding its functional and evolutionary implications.
Inferring the Joint Demographic History of Multiple Populations: Beyond the Diffusion Approximation
Authors: Jouganous Julien , Long Will , Gravel Simon 
Published: January 2017

AbstractUnderstanding variation in allele frequencies across populations is a central goal of population genetics. Classical models for the distribution of allele frequencies, using forward simulation, coalescent theory, or the diffusion approximation, have been applied extensively for demographic inference, medical study design, and evolutionary studies. Here we propose a tractable model of ordinary differential equations for the evolution of allele frequencies that is closely related to the diffusion approximation but avoids many of its limitations and approximations. We show that the approach is typically faster, more numerically stable, and more easily generalizable than the state-of-the-art software implementation of the diffusion approximation. We present a number of applications to human sequence data, including demographic inference with a five-population joint frequency spectrum and a discussion of the transferability of demographic histories across populations.
Benchmarking and improving mass transit systems in the United States based on best-in class practices
Authors: Min Hokey , Ahn Young-Hyo , Lambert Thomas 
Published: January 2017

Purpose
The purpose of this paper is to find ways to develop more efficient mass transit systems across the USA and, thus, make the best use of state/federal/municipal government funds and taxpayers’ monies. This paper conducts benchmarking studies. In doing so, this paper identifies the best-in class mass transit practices that every regional mass transit system can emulate.

Design/methodology/approach
The continuous underutilization of a mass transit system can increase public scrutiny concerning the increased investment in mass transit services. To defuse such scrutiny, this paper analyzes the past (in year 2011) performances of 515 mass transit agencies in the USA using data envelopment analysis (DEA). Also, to identify which factors influences those performances, the authors paired DEA scores for transit efficiency at the state level against a set of independent variables using a special form of regression analysis called Tobit regression.

Findings
The authors found that the greater population density of the service area, the greater number of riders can be served in a short amount of distance and time. Also, the authors discovered that the transportation mode of mass transit services could affect mass transit efficiency. On the other hand, the authors found no evidence indicating that the public ownership or private operation of transit systems could make any differences in the transit efficiency.

Originality/value
This paper is one of the few that assessed the performance of mass transit systems in comparison to their peers using a large-scale data and identify the leading causes of mass transit inefficiency. Thus, this paper helps transit authorities in handling juggling acts of protecting the conflicting interests of government policy makers against the general public and, then, make sensible future investment decisions.
Urban transportation: innovations in infrastructure planning and development
Authors: Narayanaswami Sundaravalli 
Published: January 2017

Purpose
New services design and development are difficult to plan, execute, measure and evaluate. Particularly, new services that are capital-intensive and involve a long gestation and development time are considered extremely risky. The purpose of this paper is to discuss a list of innovative practices in various managerial aspects in designing, planning and development of a large scale infrastructure intensive public transportation service. A contemporary new public transportation service development is discussed as evidence of proven and benchmarked criteria.

Design/methodology/approach
This is a technical paper, where theoretical foundations of best practices in new service development project are discussed and supported by practice-based evidences from a real-life urban transportation project. A case study approach is adopted with secondary data.

Findings
Worldwide during and after economic recession of 2008, several projects were stalled or abandoned. The inference through this work is that through efficient management practices, a large capital-intensive new service development project can be made successful even during a turbulent economy in a region marred by more challenges than elsewhere.

Practical implications
Several issues in large scale services development, such as urban transportation are domain specific. Some of the issues faced in urban transportation are common to several Gulf countries; therefore the policy guidelines, managerial practices and development strategies reported in this paper can be replicated in many of them. The commercial impact of the service project is a significant drive towards fuel conservation and to save huge amounts of productive time.

Social implications
Public transportation with a high quality of networked service improves the quality of life to a large extent. Unless certain measurable demands are not met, an affluent society is less likely to endorse public transportation. In addition, endorsement of public transportation is been promoted in several parts of the world as a drive towards a green, energy efficient, low-carbon emission and sustainable environment.

Originality/value
To the best of the authors’ knowledge, new services planning and development is a key operations management topic, on which very little is written about. Particularly no other paper has presented a real-world large scale infrastructure intensive project development to this detail, and along with a theoretical background to benchmark performance and development practices.
Multi-period reverse logistics network design with emission cost
Authors: John Sajan T. , Sridharan Rajagopalan , Kumar P.N. Ram 
Published: January 2017

PurposeThe purpose of this paper is to develop a mathematical model for the network design of a reverse supply chain in a multi-product, multi-period environment. The emission cost due to transportation activities is incorporated into the model to reduce the total cost of emission and study the significance of inclusion of emission cost on the network design decisions.Design/methodology/approachMixed integer linear programming formulation is used to model the network. The developed model is solved and analysed using the commercial solver LINGO.FindingsThe mathematical model provides a unified design of the network for the entire planning horizon comprising of different periods. A reduction in the total cost of emission is achieved. The analysis of the problem environment shows that the network design decisions significantly vary with the consideration of emission cost.Research limitations/implicationsA single mode of transportation is considered in this study. Also, a single type of vehicle is considered for the transportation purpose.Practical implicationsThe developed model can aid the decision makers in making better decisions while reducing the total emission cost. The quantification of the emission cost due to transportation activities is presented in an Indian context and can be used for future studies.Originality/valueAn all-encompassing approach for the design of reverse logistics networks with explicit consideration of product structure and emission cost.
Appraisements of material handling system in context of fiscal and environment extent
Authors: Sahu Anoop Kumar , Sahu Atul Kumar , Sahu Nitin Kumar 
Published: January 2017

Purpose
In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi criteria MHS hierarchical module consists of ecological cum fiscal criteria. Moreover, similar literature review assisted the authors to resolve and eventually construct the effectual and robust approach. The purpose of this paper is to facilitate the managers for benchmarking the MHS alternatives operating under similar module via robust decision support system (DSS).

Design/methodology/approach
In present research, the proposed module dealt with ecological (subjective) and fiscal (objective) criteria, where subjective criteria associated with incompleteness, vagueness, imprecision, as well as inconsistency, solicited the discrete information in terms of Grey set via linguistic scale from experts panel. The objective information (capital) has been assigned by expert’s panel in terms of Grey set. To robustly evaluate and select the admirable MHS, three approaches named: degree of possibility, technique for order preference similar to ideal solution as well as Grey relational analysis fruitfully applied to connect and unite discrete information.

Findings
The performance evaluation of MHSs has been carried out under concert of individual fiscal criteria excluding ecological criteria in past researches. Moreover the previous developed DSS tackled sole approach under individual fiscal criteria. The authors found the broad applications of fuzzy sets except Grey set theory in the same context for measuring the performance of MHS alternatives. Aforesaid research gaps have been transformed into research objectives by incorporating the module for both fiscal cum ecological criteria. This research embraces a robust DSS, which has been explored to select the admirable MHS alternative.

Originality/value
An empirical case study has been carried out in order to demonstrate the legitimacy of holistic Grey-MCDM method, implemented over multi criteria MHS hierarchical module. Proposed DSS seems to be the best for organisations, which believe to appraise and select the MHS including fiscal as well as ecological criteria excluding individual fiscal criteria. Moreover, subjective cum objective or individual subjective or objective criteria can be extended with respect to varieties of MHSs.
Improved parameter optimization method for complex assembly process in robotic manufacturing
Authors: Chen Heping , Xu Jing , Zhang Biao , Fuhlbrigge Thomas 
Published: January 2017

Purpose
High precision assembly processes using industrial robots require the process parameters to be tuned to achieve desired performance such as cycle time and first time through rate. Some researchers proposed methods such as design-of-experiments (DOE) to obtain optimal parameters. However, these methods only discuss how to find the optimal parameters if the part and/or workpiece location errors are in a certain range. In real assembly processes, the part and/or workpiece location errors could be different from batch to batch. Therefore, the existing methods have some limitations. This paper aims to improve the process parameter optimization method for complex robotic assembly process.

Design/methodology/approach
In this paper, the parameter optimization process based on DOE with different part and/or workpiece location errors is investigated. An online parameter optimization method is also proposed.

Findings
Experimental results demonstrate that the optimal parameters for different initial conditions are different and larger initial part and/or workpiece location errors will cause longer cycle time. Therefore, to improve the assembly process performance, the initial part and/or workpiece location errors should be compensated first, and the optimal parameters in production should be changed once the initial tool position is compensated. Experimental results show that the proposed method is very promising in reducing the cycle time in assembly processes.

Research limitations/implications
The proposed method is practical without any limitation.

Practical implications
The proposed technique is implemented and tested using a real industrial application, a valve body assembly process. Hence, the developed method can be directly implemented in production.

Originality/value
This paper provides a technique to improve the assembly efficiency by compensating the initial part location errors. An online parameter optimization method is also proposed to automatically perform the parameter optimization process without human intervention. Compared with the results using other methods, the proposed technology can greatly reduce the assembly cycle time.
Development of an environment characterization methodology for optimal design of an agricultural robot
Authors: Bloch Victor , Bechar Avital , Degani Amir 
Published: January 2017

Purpose
The purpose of this paper is to describe a methodology for characterization of the robot environment to help solve such problem as designing an optimal agricultural robot for a specific agricultural task.

Design/methodology/approach
Defining and characterizing a task is a crucial step in the optimization of a task-specific robot. It is especially difficult in the agricultural domain because of the complexity and unstructured nature of the environment. In this research, trees are modeled from orchards and are used as the robot working environment, the geometrical features of an agricultural task are investigated and a method for designing an optimal agricultural robot is developed. Using this method, a simplified characteristic environment, representing the actual environment, is developed and used.

Findings
Case studies showing that the optimal robot, which is designed based on the characteristic environment, is similar to the optimal robot, which is designed based on the actual environment (less than 4 per cent error), is presented, while the optimization run time is significantly shorter (up to 22 times) when using the characteristic environment.

Originality/value
This paper proposes a new concept for solving the robot task-based optimization by the analysis of the task environment and characterizing it by a simpler artificial task environment. The methodology decreases the time of the optimal robot design, allowing to take into account more details in an acceptable time.
Design and experiment of a modular multisensory hand for prosthetic applications
Authors: Zeng Bo , Fan Shaowei , Jiang Li , Liu Hong 
Published: January 2017

Purpose
This paper aims to present the design and experiment of a modular multisensory prosthetic hand for applications. Design and experiment of a modular multisensory hand for prosthetic applications.

Design/methodology/approach
This paper reveals more details focusing on the appearance, mechanism design, electrical design and control of the prosthetic hand considering anthropomorphism, dexterity, sensing and controllability. The finger is internally integrated with the actuator, the transmission mechanism, the sensors and the controller as a modular unit. Integrated with multiple sensors, the prosthetic hand can not only perceive the position, the contact force and the temperature of the environment like a human hand but also provide the foundation for the practical control.

Findings
The experiments show that the prosthetic hand can accurately control the contact force to achieve stable grasps based on the sensors feedback and a simple and effective force-tracking impedance control algorithm. In addition, the experiments based on the cosmesis validate not only the cosmesis functionality but also the control performance for a prosthesis–cosmesis system.

Practical implications
Because of the small size, low weight, high integration, modularity and controllability, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the finger as a modular unit is easy to be fixed, maintained and applied to a partial upper-limb amputee.

Originality/value
Each modular finger of the prosthetic hand integrated with the actuator, the transmission mechanism, the sensors and the controller as a whole can independently control the position and the force. The cosmetic glove design can provide pretty appearance without compromising the control performance.
Pick-place of dynamic objects by robot manipulator based on deep learning and easy user interface teaching systems
Authors: Hossain Delowar , Capi Genci , Jindai Mitsuru , Kaneko Shin-ichiro 
Published: January 2017

Purpose
Development of autonomous robot manipulator for human-robot assembly tasks is a key component to reach high effectiveness. In such tasks, the robot real-time object recognition is crucial. In addition, the need for simple and safe teaching techniques need to be considered, because: small size robot manipulators’ presence in everyday life environments is increasing requiring non-expert operators to teach the robot; and in small size applications, the operator has to teach several different motions in a short time.

Design/methodology/approach
For object recognition, the authors propose a deep belief neural network (DBNN)-based approach. The captured camera image is used as the input of the DBNN. The DBNN extracts the object features in the intermediate layers. In addition, the authors developed three teaching systems which utilize iPhone; haptic; and Kinect devices.

Findings
The object recognition by DBNN is robust for real-time applications. The robot picks up the object required by the user and places it in the target location. Three developed teaching systems are easy to use by non-experienced subjects, and they show different performance in terms of time to complete the task and accuracy.

Practical implications
The proposed method can ease the use of robot manipulators helping non-experienced users completing different assembly tasks.

Originality/value
This work applies DBNN for object recognition and three intuitive systems for teaching robot manipulators.