bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian Networks established functional differences between breast cancer subtypes
Authors: Trilla-Fuertes Lucía , Zapater-Moros Andrea , Gámez-Pozo Angelo , Arevalillo Jorge M , Prado-Vázquez Guillermo , Díaz-Almirón Mariana , Ferrer-Gómez María , López-Vacas Rocío , Navarro Hilario , Espinosa Enrique , Maín Paloma , Vara Juan Ángel Fresno 
Published: May 2018

AbstractBreast cancer is a heterogeneous disease. In clinical practice, tumors are classified as hormonal receptor positive, Her2 positive and triple negative tumors. In previous works, our group defined a new hormonal receptor positive subgroup, the TN-like subtype, which has a prognosis and a molecular profile more similar to triple negative tumors. In this study, proteomics and Bayesian networks were used to characterize protein relationships in 106 breast tumor samples. Components obtained by these methods had a clear functional structure. The analysis of these components suggested differences in processes such as metastasis or proliferation between breast cancer subtypes, including our new subtype TN-like. In addition, one of the components, mainly related with metastasis, had prognostic value in this cohort. Functional approaches allow to build hypotheses about regulatory mechanisms and to establish new relationships among proteins in the breast cancer context.Author SummaryBreast cancer classification in the clinical practice is defined by three biomarkers (estrogen receptor, progesterone receptor and HER2) into hormone receptor positive, HER2+ and triple negative breast cancer (TNBC). Our group recently described a new ER+ subtype with molecular characteristics and prognosis similar to TNBC. In this study we propose a mathematical method, the Bayesian networks, as a useful tool to study protein interactions and differential biological processes in breast cancer subtypes, characterizing differences in relevant processes such as proliferation or metastasis and associated them with patient prognosis.
Identification of a host collagen inducing factor from the excretory secretory proteins ofTrichinella spiralisusing immunoscreening
Authors: Park Mi Kyung , Kim Hae-Jin , Cho Min Kyoung , Kang Shin Ae , Park So Young , Jang Se Bok , Yu Hak Sun 
Published: May 2018

AbstractBackgroundIn a previous study, we found thatTrichinella spiralisexcretory and secretory proteins (ES-P) most likely activate collagen synthesis via TGF-β/Smad signaling, and this event could influence collagen capsule formation.Methodology/Principal FindingsIn order to identify the specific collagen inducing factor, ES-P was fractionated by a Superdex 200 10/300 GL column. We obtained three large fractions, F1, F2, and F3, but only F3 had collagen gene inducing ability. After immunoscreening, 10 collagen inducing factor candidates were identified. Among them, TS 15-1 and TS 15-2 were identical to the putative trypsin ofT. spiralis. The deduced TS 15-1 (M.W. = 72 kDa) had two conserved catalytic motifs, an N-terminal Tryp_SPc domain (TS 15- 1n) and a C-terminal Tryp_SPc domain (TS 15-1c). To determine their collagen inducing ability, recombinant proteins (rTS 15-1n and rTS 15-1c) were produced using the pET-28a expression system. TS 15-1 is highly expressed during the muscle larval stage and has strong antigenicity. We determined that rTS 15-1c could elevate collagen I via activation of the TGF-β1 signaling pathwayin vitroandin vivo.Conclusion/SignificanceIn conclusion, we identified a host collagen inducing factor fromT. spiralisES-P using immunoscreening and demonstrated its molecular characteristics and functions.Author SummaryTrichinella spiraliscan make collagen capsules in host muscle cells during its life cycle, which encapsulates muscle stage larvae. Many investigators have tried to reveal the complex mechanism behind this collagen capsule architecture, and it has been suggested that several serine proteases in excretory-secretory proteins of the parasite are potential collagen capsule inducing factors. In addition, collagen synthesis is activated through the TGF-β/Smad signaling pathway and these events are closely related with protease activated receptor 2 which was activated by various serine proteases. In this study, we isolated and characterized a collagen gene expression inducer fromT. spiralisES-P using immunoscreening and investigated the candidate protein for its usefulness as a wound healing therapeutic agent.
Empirical single-cell tracking and cell-fate simulation reveal dual roles of p53 in tumor suppression
Authors: Rancourt Ann , Sato Sachiko , Satoh Masahiko S. 
Published: May 2018

ABSTRACTThe tumor suppressor p53 regulates various stress responses via increasing its cellular levels. The lowest p53 levels occur in unstressed cells; however, the functions of these low levels remain unclear. To investigate the functions, we used empirical single-cell tracking of p53-expressing (Control) cells and cells in which p53 expression was silenced by RNA interference (p53 RNAi). Here we show that p53 RNAi cells underwent more frequent cell death and cell fusion, which further induced multipolar cell division to generate aneuploid progeny. Those results suggest that the low levels of p53 in unstressed cells indeed have a role in suppressing the induction of cell death and the formation of aneuploid cells. We further investigated the impact of p53 silencing by developing an algorithm to simulate the fates of individual cells. Simulation of the fate of aneuploid cells revealed that these cells could propagate to create an aneuploid cell population. In addition, the simulation also revealed that more frequent induction of cell death in p53 RNAi cells under unstressed conditions conferred a disadvantage in terms of population expansion compared with Control cells, resulting in faster expansion of Control cells compared with p53 RNAi cells, leading to Control cells predominating in mixed cell populations. In contrast, the expansion of Control cells, but not p53 RNAi cells, was suppressed when the damage response was induced, allowing p53 RNAi cells to expand their population compared with the Control cells. These results suggest that, although p53 could suppress the formation of aneuploid cells, which could have a role in tumorigenesis, it could also allow the expansion of cells lacking p53 expression when the damage response is induced. p53 may thus play a role in both the suppression and the promotion of malignant cell formation during tumorigenesis.
Prediction of Mutations to Control Pathways Enabling Tumour Cell Invasion with the CoLoMoTo Interactive Notebook (Tutorial)
Authors: Levy Nicolas , Naldi Aurélien , Hernandez Céline , Stoll Gautier , Thieffry Denis , Zinovyev Andrei , Calzone Laurence , Paulevé Loïc 
Published: May 2018

AbstractBoolean and multi-valued logical formalisms are increasingly used to model complex cellular networks. To ease the development and analysis of logical models, a series of software tools have been proposed, often with specific assets. However, combining these tools typically implies a series of cumbersome software installation and model conversion steps. In this respect, the CoLoMoTo Interactive Notebook provides a joint distribution of several logical modelling software tools, along with an interactive web Python interface easing the chaining of complementary analyses. In this protocol, we demonstrate the assets of this approach through the analysis of a computational model of biological network. Our computational workflow combines (1) the importation of a GINsim model and its display, (2) its format conversion using the Java library BioLQM, (3) the formal prediction of mutations using the OCaml software Pint, (4) the model checking using the C++ software NuSMV, (5) quantitative stochastic simulations using the C++ software MaBoSS, and (6) the visualisation of results using the Python library matplotlib. Starting with a recent Boolean model of the signalling network controlling tumour cell invasion and migration, our model analysis culminates with the prediction of sets of mutations presumably involved in a metastatic phenotype.
Using the learning curve theory in the investigation of on-site craft gangs’ blockwork construction productivity
Authors: Ugulu Rex Asibuodu , Allen Stephen 
Published: May 2018

Purpose
The purpose of this paper is to investigate how on-site blockwork craft gangs’ learning impacts productivity within the production environment on-site to optimise their productivity.

Design/methodology/approach
The research is adopting a quantitative method with the observation of seven craft gangs’ blockwork with an average of five members in each gang, using the learning curve model application in a 17-storey tri-tower construction project in Nigeria. The linear regression method was employed in the analysis stage of this study using labour-recorded productivity time input as the dependent variables.

Findings
The paper provides empirical insights about the significance of on-site craft gangs’ learning. The overall blockwork craft gangs learning observed at the site level shows an average learning rate of 94.21 per cent resulting in 5.79 per cent improvement gains.

Research limitations/implications
Due to the nature of the study and the research question, the observations in this research study were limited to FCDA construction project in Nigeria. The limitation of this scenario is that the research results may lack generalisability. Therefore, there is the need for further study on the learning rate.

Practical implications
This research study includes the implications for the development of on-site blockwork craft gangs learning; the significant impact of learning rate of 94.21 per cent resulting in 5.79 per cent improvement gain can be used in the planning and to fast track the productivity of craft gangs’ construction.

Originality/value
This paper identified the need to improve construction productivity through craft gangs’ on-site learning with the application of the learning curve theory.
Energy efficiency practices for Malaysian green office building occupants
Authors: Ohueri Chukwuka Christian , Enegbuma Wallace Imoudu , Kenley Russell 
Published: May 2018

Purpose
Green building construction was adopted as a strategy to reduce energy consumption and the overall impact of the built environment on our natural environment. However, in Malaysia, previous studies have reaffirmed that green office buildings consume a substantial amount of energy, compared to their counterparts in Singapore. Moreover, there is still a significant performance gap between predicted energy measurements and actual operational energy consumption of green office buildings in Malaysia, due to occupants’ behavioural discrepancies. Therefore, the purpose of this paper is to develop energy efficiency practices for occupants of green office buildings in Malaysia. The developed practices integrate technology, organisation policy, and occupants’ behavioural strategies, in order to reduce the energy consumption of green office buildings in Malaysia.

Design/methodology/approach
To achieve the research goal, a mixed (quantitative and qualitative) research method was used to collect data from the research population. In total, 53 respondents working in a green office building complex in Kuala Lumpur Malaysia were surveyed using a questionnaire. Additionally, three top management staff of the green office building and two Malaysian construction professionals were interviewed. The study adopted convenience sampling technique in selecting the research respondents. The data from the questionnaire were analysed using SPSS software (version 22) while the interview data were analysed via thematic content analysis.

Findings
The findings suggest that the integration of technological strategy (use of BIM tools, sustainable building materials, etc.); organisational strategy (develop, implement and evaluate action plans, use of monitor/control systems, etc.); and occupants behavioural strategy (training, incentives, occupants energy efficiency guide, etc.) will critically reduce energy consumption of green office buildings in Malaysia.

Originality/value
Based on the findings, energy efficiency practices are developed to guide occupants in reducing the energy consumption of green office buildings in Malaysia. This strategy will contribute to reducing the performance gap that exists between predicted energy and actual energy use of green office buildings in Malaysia. However, the developed energy efficiency practices need to be validated to ascertain its workability in the green office building context.
The impact of gender and profit margin on the duration of hiring process for professional service firms
Authors: Agrawal Vikas , Hartman Leigh , Rasberry Clayton , Arbogast Gordon 
Published: May 2018

PurposeThe purpose of this paper is to explore the impact of recruiter gender and profit margin on the duration of the hiring process in professional services firms (PSFs).Design/methodology/approachIn evaluating over 500 recruiting transactions in a PSF, a factorial ANOVA was performed to determine if there is a significant interaction between recruiter gender and profit margin on days it take to fill an open position.FindingsThe results suggest a significant interaction exists between the recruiter gender and profit margin variables in effect on days that it takes to fill an open position. At lower job position profit margins, female recruiters were found to outperform their male counterparts. Conversely, at higher job position profit margins, male recruiters appear to outperform female recruiters.Research limitations/implicationsThis research is focused on the duration of the recruiting process and does not address the quality of candidate selection. An evaluation of the quality of candidate selection contrasted with the time it takes to hire should be an essential consideration for future research.Practical implicationsIf job vacancies remain vacant at client firms for an extended period, this could adversely impact the financial and reputational health of small PSFs. By focusing on key variables that impact the recruiting timeline, management may be able to consider interventions that would improve both the recruiting process and firm’s financial health.Originality/valueThis study provides a unique contribution by focusing on the recruiting timeline, recruiter gender, profit margin, and the resulting ability of a PSF to proactively manage its revenue.
Improved 2D laser grid mapping by solving mirror reflection uncertainty in SLAM
Authors: Singh Ravinder , Nagla Kuldeep Singh 
Published: May 2018

Purpose
Accurate perception of the environment using range sensors such as laser scanner, SONAR, infrared, vision, etc., for the application, such as path planning, localization, autonomous navigation, simultaneously localization and mapping, is a highly challenging area. The reliability of the perception by range sensors relies on the sensor accuracy, precision, sensor model, sensor registration, resolution, etc. Laser scanner is even though accurate and precise but still the efficient and consistent mapping of the environment is yet to be attained because laser scanner gives error as the extrinsic and intrinsic parameters varied which cause specular reflection, refraction, absorption, etc., of the laser beam. The paper aims to discuss this issue.

Design/methodology/approach
This paper presents an error analysis in sensory information of laser scanner due to the effect of varying the scanning angle with respect to the optical axis and surface reflectivity or refractive index of the targets. Uncertainties caused by these parameters are reduced by proposing a new technique, tilt mounting system (TMS) with designed filters of tilting the angular position of a laser scanner with the best possible selection of range and scanning angle for the robust occupancy grid mapping. Various experiments are performed in different indoor environments, and the results are validated after the implementation of the TMS approach with designed filters.

Findings
After the implementation of the proposed TMS approach with filters, the errors in the laser grid map are reduced by 15.6 percent, which results in 62.5 percent reduction in the collision of a mobile robot during autonomous navigation in the laser grid map.

Originality/value
The TMS approach with designed filter reduces the effect of variation in intrinsic and extrinsic parameters to generate efficient laser occupancy grid map to achieve collision-free autonomous navigation.
Human motion analysis from UAV video
Authors: Perera Asanka G. , Law Yee Wei , Al-Naji Ali , Chahl Javaan 
Published: May 2018

Purpose
The purpose of this paper is to present a preliminary solution to address the problem of estimating human pose and trajectory by an aerial robot with a monocular camera in near real time.

Design/methodology/approach
The distinguishing feature of the solution is a dynamic classifier selection architecture. Each video frame is corrected for perspective using projective transformation. Then, a silhouette is extracted as a Histogram of Oriented Gradients (HOG). The HOG is then classified using a dynamic classifier. A class is defined as a pose-viewpoint pair, and a total of 64 classes are defined to represent a forward walking and turning gait sequence. The dynamic classifier consists of a Support Vector Machine (SVM) classifier C64 that recognizes all 64 classes, and 64 SVM classifiers that recognize four classes each – these four classes are chosen based on the temporal relationship between them, dictated by the gait sequence.

Findings
The solution provides three main advantages: first, classification is efficient due to dynamic selection (4-class vs 64-class classification). Second, classification errors are confined to neighbors of the true viewpoints. This means a wrongly estimated viewpoint is at most an adjacent viewpoint of the true viewpoint, enabling fast recovery from incorrect estimations. Third, the robust temporal relationship between poses is used to resolve the left-right ambiguities of human silhouettes.

Originality/value
Experiments conducted on both fronto-parallel videos and aerial videos confirm that the solution can achieve accurate pose and trajectory estimation for these different kinds of videos. For example, the “walking on an 8-shaped path” data set (1,652 frames) can achieve the following estimation accuracies: 85 percent for viewpoints and 98.14 percent for poses.
Fuzzy adaptive extended Kalman filter for robot 3D pose estimation
Authors: Deilamsalehy Hanieh , Havens Timothy C. 
Published: May 2018

Purpose
Estimating the pose – position and orientation – of a moving object such as a robot is a necessary task for many applications, e.g., robot navigation control, environment mapping, and medical applications such as robotic surgery. The purpose of this paper is to introduce a novel method to fuse the information from several available sensors in order to improve the estimated pose from any individual sensor and calculate a more accurate pose for the moving platform.

Design/methodology/approach
Pose estimation is usually done by collecting the data obtained from several sensors mounted on the object/platform and fusing the acquired information. Assuming that the robot is moving in a three-dimensional (3D) world, its location is completely defined by six degrees of freedom (6DOF): three angles and three position coordinates. Some 3D sensors, such as IMUs and cameras, have been widely used for 3D localization. Yet, there are other sensors, like 2D Light Detection And Ranging (LiDAR), which can give a very precise estimation in a 2D plane but they are not employed for 3D estimation since the sensor is unable to obtain the full 6DOF. However, in some applications there is a considerable amount of time in which the robot is almost moving on a plane during the time interval between two sensor readings; e.g., a ground vehicle moving on a flat surface or a drone flying at an almost constant altitude to collect visual data. In this paper a novel method using a “fuzzy inference system” is proposed that employs a 2D LiDAR in a 3D localization algorithm in order to improve the pose estimation accuracy.

Findings
The method determines the trajectory of the robot and the sensor reliability between two readings and based on this information defines the weight of the 2D sensor in the final fused pose by adjusting “extended Kalman filter” parameters. Simulation and real world experiments show that the pose estimation error can be significantly decreased using the proposed method.

Originality/value
To the best of the authors’ knowledge this is the first time that a 2D LiDAR has been employed to improve the 3D pose estimation in an unknown environment without any previous knowledge. Simulation and real world experiments show that the pose estimation error can be significantly decreased using the proposed method.
Consumer sensitivity to delivery lead time: a furniture retail case
Authors: Marino Gaetano , Zotteri Giulio , Montagna Francesca 
Published: May 2018

PurposeShort delivery time is a feature that can influence consumers’ purchasing decisions and that retailers compete over fiercely. Accordingly, evaluating the effect of delivery time on demand and identifying marketing-mix variables that alter this relationship may influence retailers’ strategies and impact supply chain (SC) performance. The paper aims to discuss these issues.Design/methodology/approachThis study was performed in collaboration with the largest furniture retailer in Italy, which provided its sales and inventory data for 19,000 units sold over a six-month period in 32 stores throughout Italy. Data were analysed using logistic regression with fixed effects.FindingsThe value of delivery time for consumers, even in an industry generally characterised by long delivery lead times, is surprisingly high. The evidence reveals that when the delivery time changes from two days to seven days, demand is reduced by 37.5 per cent, although variables related to location and the marketing mix moderate this relationship.Practical implicationsRetailers can use the findings presented herein to drive their inventory and facility planning decisions and support investments in SC integration.Originality/valueSupply chain management (SCM) studies consider the value of delivery time anecdotally and have neglected empirical estimations of the magnitude of the effects of delivery time on consumer demand. Further, SCM studies have not explored the factors moderating this relationship, although intertemporal choice and service management studies have demonstrated the existence of such factors.