bluuebunny/crossref_metadata_2025_split huggingface dataset:
flowAI: automatic and interactive anomaly discerning tools for flow cytometry data
Authors: Monaco Gianni , Chen Hao , Poidinger Michael , Chen Jinmiao , de Magalhães João Pedro , Larbi Anis 
Published: April 2016

Abstract
Motivation: Flow cytometry (FCM) is widely used in both clinical and basic research to characterize cell phenotypes and functions. The latest FCM instruments analyze up to 20 markers of individual cells, producing high-dimensional data. This requires the use of the latest clustering and dimensionality reduction techniques to automatically segregate cell sub-populations in an unbiased manner. However, automated analyses may lead to false discoveries due to inter-sample differences in quality and properties.
Results: We present an R package, flowAI, containing two methods to clean FCM files from unwanted events: (i) an automatic method that adopts algorithms for the detection of anomalies and (ii) an interactive method with a graphical user interface implemented into an R shiny application. The general approach behind the two methods consists of three key steps to check and remove suspected anomalies that derive from (i) abrupt changes in the flow rate, (ii) instability of signal acquisition and (iii) outliers in the lower limit and margin events in the upper limit of the dynamic range. For each file analyzed our software generates a summary of the quality assessment from the aforementioned steps. The software presented is an intuitive solution seeking to improve the results not only of manual but also and in particular of automatic analysis on FCM data.
Availability and implementation: R source code available through Bioconductor: http://bioconductor.org/packages/flowAI/
Contacts: mongianni1@gmail.com or Anis_Larbi@immunol.a-star.edu.sg
Supplementary information: Supplementary data are available at Bioinformatics online.
INPS-MD: a web server to predict stability of protein variants from sequence and structure
Authors: Savojardo Castrense , Fariselli Piero , Martelli Pier Luigi , Casadio Rita 
Published: April 2016

Abstract
Motivation: Protein function depends on its structural stability. The effects of single point variations on protein stability can elucidate the molecular mechanisms of human diseases and help in developing new drugs. Recently, we introduced INPS, a method suited to predict the effect of variations on protein stability from protein sequence and whose performance is competitive with the available state-of-the-art tools.
Results: In this article, we describe INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension), a web server for the prediction of protein stability changes upon single point variation from protein sequence and/or structure. Here, we complement INPS with a new predictor (INPS3D) that exploits features derived from protein 3D structure. INPS3D scores with Pearson’s correlation to experimental ΔΔG values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based INPS scores slightly lower than the structure-based INPS3D and both on the same blind test sets well compare with the state-of-the-art methods.
Availability and Implementation: INPS and INPS3D are available at the same web server: http://inpsmd.biocomp.unibo.it.
Supplementary information: Supplementary data are available at Bioinformatics online.
Contact: gigi@biocomp.unibo.it
Real-time prediction of inpatient length of stay for discharge prioritization
Authors: Barnes Sean , Hamrock Eric , Toerper Matthew , Siddiqui Sauleh , Levin Scott 
Published: April 2016

AbstractObjective Hospitals are challenged to provide timely patient care while maintaining high resource utilization. This has prompted hospital initiatives to increase patient flow and minimize nonvalue added care time. Real-time demand capacity management (RTDC) is one such initiative whereby clinicians convene each morning to predict patients able to leave the same day and prioritize their remaining tasks for early discharge. Our objective is to automate and improve these discharge predictions by applying supervised machine learning methods to readily available health information.Materials and Methods The authors use supervised machine learning methods to predict patients’ likelihood of discharge by 2 p.m. and by midnight each day for an inpatient medical unit. Using data collected over 8000 patient stays and 20 000 patient days, the predictive performance of the model is compared to clinicians using sensitivity, specificity, Youden’s Index (i.e., sensitivity + specificity – 1), and aggregate accuracy measures.Results The model compared to clinician predictions demonstrated significantly higher sensitivity ( P  &lt; .01), lower specificity ( P  &lt; .01), and a comparable Youden Index ( P  &gt; .10). Early discharges were less predictable than midnight discharges. The model was more accurate than clinicians in predicting the total number of daily discharges and capable of ranking patients closest to future discharge.Conclusions There is potential to use readily available health information to predict daily patient discharges with accuracies comparable to clinician predictions. This approach may be used to automate and support daily RTDC predictions aimed at improving patient flow.
First case of mixed infection with Cryptococcus deuterogattii and Cryptococcus neoformans VNI in an Ivorian HIV-positive patient
Authors: Kassi Fulgence K. , Bellet Virginie , Doumbia Adama , Krasteva Donika , Drakulovski Pascal , Kouakou Gisèle A. , Gatchitch François , Delaporte Eric , Reynes Jacques , Mallié Michèle , Menan Hervé I. E. , Bertout Sébastien 
Published: April 2016

Introduction:
Cryptococcal meningitis (CM) may be caused by several species of Cryptococcus.

Case presentation:
We describe a fatal case of CM in a HIV-positive patient from Ivory Coast infected by Cryptococcus neoformans VNI and Cryptococcus
deuterogattii. Isolates were recovered from cerebrospinal fluid (CSF) prior to systemic antifungal treatment. Six isolates were studied (the entire culture plus five isolated colonies from it). Serotyping was performed via LAC 1 and CAP 64 gene amplification. Genotyping was performed using restriction fragment length polymorphism (RFLP) analysis of the URA5 gene, (GACA)4, (GTG)5 and M13 PCR fingerprinting. URA5-RFLP analysis identified the original culture with two different molecular type combinations. However, URA5-RFLP profiles of the five colonies isolated from the original sample revealed two different species. Four colonies were identified as C.
deuterogattii and the last isolate as C.
neoformans VNI. The in vitro susceptibility profile was determined using the standard method according to the CLSI M27-A3 protocol. The isolates were susceptible to the tested antifungals (fluconazole, flucytosine and amphotericin B). Treatment with fluconazole (1200  mg day−1) was initiated; however, the patient died 17 days after the onset of antifungal therapy.

Conclusion:
This is the first reported case of mixed infection with C. neoformans and C.
deuterogattii in a HIV-positive patient.
Unconscious integration of multisensory bodily inputs in the peripersonal space shapes bodily self-consciousness
Authors: Salomon Roy , Noel Jean-Paul , Łukowska Marta , Faivre Nathan , Metzinger Thomas , Serino Andrea , Blanke Olaf 
Published: April 2016

AbstractRecent studies have highlighted the role of multisensory integration as a key mechanism of self-consciousness. In particular, integration of bodily signals within the peripersonal space (PPS) underlies the experience of the self in a body we own (self-identification) and that is experienced as occupying a specific location in space (self-location), two main components of bodily self-consciousness (BSC). Experiments investigating the effects of multisensory integration on BSC have typically employed supra-threshold sensory stimuli, neglecting the role of unconscious sensory signals in BSC, as tested in other consciousness research. Here, we used psychophysical techniques to test whether multisensory integration of bodily stimuli underlying BSC may also occur for multisensory inputs presented below the threshold of conscious perception. Our results indicate that visual stimuli rendered invisible (through continuous flash suppression) boost processing of tactile stimuli on the body (Exp. 1), and enhance the perception of near-threshold tactile stimuli (Exp. 2), only once they entered peripersonal space. We then employed unconscious multisensory mechanisms to manipulate BSC. Participants were presented with tactile stimulation on their body and with visual stimuli on a virtual body, seen at a distance, which were either visible or rendered invisible. We report that if visuo-tactile stimulation was synchronized, participants self-identified with the virtual body (Exp. 3), and shifted their self-location toward the virtual body (Exp.4), even if visual stimuli were fully invisible. Our results indicate that multisensory inputs, even outside of awareness, are integrated and affect the phenomenological content of self-consciousness, grounding BSC firmly in the field of psychophysical consciousness studies.
Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer
Authors: Celik Safiye , Logsdon Benjamin A , Battle Stephanie , Drescher Charles W , Rendi Mara , David R Hawkins , Lee Su-In 
Published: April 2016

ABSTRACTBackground:Discovering patient subtypes and molecular drivers of a subtype are difficult and driving problems underlying most modern disease expression studies collected across patient populations. Expression patterns conserved across multiple expression datasets from independent disease studies are likely to represent important molecular events underlying the disease.Methods:We present the INSPIRE (INferringShared modules from multiPle gene expREssion datasets) method to infer highly coherent and robustmodulesof co-expressed genes and the dependencies among the modules from multiple expression datasets. Focusing on inferring modules and their dependencies conserved across multiple expression datasets is important for several reasons. First, using multiple datasets will increase the power to detect robust and relevant patterns (modules and dependencies among modules). Second, INSPIRE enables the use of multiple datasets that contain different sets of genes due to, e.g., the difference in microarray platforms. Many methods designed for expression data analysis cannot integrate multiple datasets with variable discrepancy to infer a single combined model, whereas INSPIRE can naturally model the dependencies among the modules even when a large proportion of genes are not observed on a certain platform.Results:We evaluated INSPIRE on synthetically generated datasets with known underlying network structure among modules, and gene expression datasets from multiple ovarian cancer studies. We show that the model learned by INSPIRE can explain unseen data better and can reveal prior knowledge on gene functions more accurately than alternative methods. We demonstrate that applying INSPIRE to nine ovarian cancer datasets leads to the identification of a new marker and potential molecular driver of tumor-associated stroma -HOPX. We also demonstrate that theHOPXmodule strongly overlaps with the genes defining the mesenchymal patient subtype identified in The Cancer Genome Atlas (TCGA) ovarian cancer data. We provide evidence for a previously unknown molecular basis of tumor resectability efficacy involving tumor-associated mesenchymal stem cells represented byHOPX.Conclusions:INSPIRE extracts a low-dimensional description from multiple gene expression data, which consists of modules and their dependencies. The discovery of a new tumor-associated stroma marker,HOPX,and its module suggests a previously unknown mechanism underlying tumor-associated stroma.
Third-generation sequencing and the future of genomics
Authors: Lee Hayan , Gurtowski James , Yoo Shinjae , Nattestad Maria , Marcus Shoshana , Goodwin Sara , Richard McCombie W. , Schatz Michael C. 
Published: April 2016

AbstractThird-generation long-range DNA sequencing and mapping technologies are creating a renaissance in high-quality genome sequencing. Unlike second-generation sequencing, which produces short reads a few hundred base-pairs long, third-generation single-molecule technologies generate over 10,000 bp reads or map over 100,000 bp molecules. We analyze how increased read lengths can be used to address longstanding problems inde novogenome assembly, structural variation analysis and haplotype phasing.
Supply chain finance and financial contagion from disruptions - evidence from the automobile industry
Authors: Filbeck Greg , Kumar Sanjay , Liu Jiangxia , Zhao Xin 
Published: April 2016

Purpose
This research explores the effect of supply chain disruptions on competitors. Using companies in the automobile industry, we study the contagion effect in supply chains based on the affected firm and its competitors, whether the disruption occurs domestically or by a foreign-based firm, and within the context of economic market cycles.

Design/methodology/approach
Standard event study methodology is used to test the stock price reaction to supply chain disruptions. The purpose of this methodology is to determine whether the announcement of an event produces a “significant” stock price reaction around the time of the announcement. To conduct such tests, daily stock returns are measured around the announcement date and compared with the expected return. To further test whether the event study results can be explained by the business cycle, sample period, and stock characteristics, we use regression analysis. Our analysis is based on a data of 408 disruptions compiled from news announcements.

Findings
Supply chain disruptions have consequences for affected companies as well as competitors. The stock market impact from disruptions in automobile companies is affected by market cycle as well as the brand domicile. We observe that negative stock effect of disruptions occurs in bear markets but not in bull markets. American-brand automakers experience a larger stock price decline in bear markets compared to Japanese-brand automakers. Our results support a contagion effect as American-brand automakers experience negative stock reactions when a competitor announces disruptions. The contagion is more pronounced for American-brand automakers in bear markets when disruptions are announced by Japanese-brand automakers. We do not find evidence of a contagion effect for Japanese-brand automakers, indicating that they may be more resilient and are not affected by competitors’ supply chain performance.

Research limitations/implications
The U.S. automobile industry is dominated by five major firms. While our research is ground-breaking, the ability to generalizing to other industries that are less concentrated in leadership and competition may be limited.

Practical implications
Our study has implications for supply chain managers who make decisions regarding investments in disruptions mitigation. The results are also of interest to investors who may seek opportunities to take short positions on stocks within the automobile industry.

Originality/value
Our paper is the first to test the impact of supply chain disruptions on competitors. Additionally, we characterize the impact of disruptions based on market cycle and company domicile.
Reverse factoring in the supply chain: objectives, antecedents and implementation barriers
Authors: Liebl John , Hartmann Evi , Feisel Edda 
Published: April 2016

Purpose
Reverse factoring (RF) can generate win-win situations for buyers, banks and suppliers. However, the SCM literature generally tends to ignore financial influences and accounting support structures. Research in the area of reverse factoring is relatively new and considerably fragmented. To address this research gap this paper provides an analysis of the objectives, antecedents and barriers of implementation.

Design/methodology/approach
The study contributes fundamental new insights derived from eleven case studies. 28 interviews were conducted from the perspective of buyers, banks and suppliers and analyzed regarding influencing factors of different RF approaches.

Findings
Reverse factoring predominantly is used to extend days payable outstanding (DPO). However, secondary objectives such as the reduction of supplier default risk and process simplifications also play an important role. The number of integrated suppliers, dependence of suppliers on their buyers, spread between internal refinancing and RF costs and the diversity of target agreements strongly influence these objectives and therefore the configuration of RF solutions.

Originality/value
Most studies fall short of exploring the mechanism of reverse factoring from all of the different perspectives of buyers, banks and suppliers. This approach allows new insights regarding prerequisites and different motivations behind RF.
Supply chain finance: a literature review
Authors: Gelsomino Luca Mattia , Mangiaracina Riccardo , Perego Alessandro , Tumino Angela 
Published: April 2016

Purpose
The purpose of this paper is twofold: to classify the research to-date on Supply Chain Finance (SCF) according to the main themes and methods, and to propose directions for future research.

Design/methodology/approach
The review is based on 119 papers mainly published from 2000 to 2014 in international peer-reviewed journals and in the proceedings of international conferences.

Findings
The articles that provide a definition of SCF reflect two major perspectives: the ‘finance oriented’ perspective - focused on short-term solutions provided by financial institutions, addressing accounts payable and receivable - and the ‘supply chain oriented’ perspective - which might not involve a financial institution, and is focused on working capital optimisation in terms of accounts payable, receivable, inventories, and sometimes even on fixed asset financing.

Research limitations/implications
While efforts were made to be all-inclusive, significant research efforts may have been inadvertently omitted. However, the authors believe that this review is an accurate representation of the body of research on SCF published during the specified timeframe, and feel that confidence may be placed on the resulting assessments.

Originality/value
The paper presents a comprehensive summary of previous research on this topic and identifies the most important issues that need to be addressed in future research. On the basis of the identified gaps in the literature, four key issues have been highlighted which should be addressed in future research.
Prescribed consumption and consumers' decision-making styles: a cross-cultural comparison between Europe and Asia
Authors: Lamour Corinne , De La Robertie Catherine 
Published: April 2016

PurposeThe goal of this research is 1) to check if shopping prescription consciousness is a fundamental decision-making characteristic, 2) to know its weight and position into consumer decision-making styles (DMS), and 3) to compare results between France and China.Design/methodology/approachA quantitative survey using the Consumer Styles Inventory (Sproles and Kendall, 1986) is done with 308 French and 221 Chinese pet food buyers. Factorial, multivariance, clustering and discriminant analyses are run.FindingsFindings reveal that shopping prescription consciousness is a fundamental decision-making characteristic. Although this concept scores the same in both cultures, correlations between shopping prescription and other characteristics vary from a culture to another, showing a different prescription follower profile. In addition, opposite to our expectations prescription consciousness has a discriminant role on DMS in France but not in China. Finally, culture impacts overall DMS.Research limitations/implicationsThe Chinese sample is weak. This study must be replicated in more product categories and involve more countries. This paper attempts to enrich prescribed consumption knowledge in a cross-cultural context.Practical implicationsThis paper 1) enriches academic understanding of the decision delegation concept, in a cross-cultural context, and 2) encourages organizations involved in complex products to set up loyalty qualitative programs and prescriber networks to ease shopping decision and consequently increase sales.Originality/valueThis is the first time that decision delegation and prescription is studied according to decision-making styles in a cross-cultural context.
Material modelling of tensile steel component under impulsive loading
Authors: Ribeiro Joao , Santiago Aldina , Rigueiro Constança 
Published: April 2016

Purpose
Characterization and modelling of the material properties, as well as the fracture simulation needed for the numerical analysis of bolted T-stub connection under impulsive loads. The strain rate effects are considered on the material law; fracture simulation is explored following “element deletion” technique for a given level of ductile damage.

Design/methodology/approach
The T-stub model is used in Eurocode 3 – part 1.8 as part of the “component method” for the representation of steel connection’s tension zone and is usually responsible for providing ductility to the connection. Looking forward to establish the “T-stub’s” maximum displacement capacity under impact loading, i) fracture simulation of steel elements is here explored following “element deletion” technique for a given level of ductile damage; ii) material softening and triaxial stress state dependency are assessed by finite element analysis of common uniaxial tension tests, and iii) strain rates effects are used based on results from Split-Hopkinson Bar tests, through the incorporation of the Johnson-Cook’s elevated strain rate law for material strain-hardening description. Numerical predictions of the model describing the “T-stub” behaviour and displacement capacity are compared against experimental results.

Findings
The FE model developed was found reliable in the description of the T-stub response subject to static and impact loads. Particularly, the strain rate sensitive material hardening following a calibrated Johnson-Cook law proved accurate in the description of the enhancement of the material strength. It was observed that when subject to impact loading regimes, the force-displacement response of T-stubs is: i) enhanced due to elevated strain rate effects, avoiding rupture when subject to a load equal the maximum static; ii) less ductile plastic failure modes in deformable T-stubs are expected, whilst the development of higher strains in the bolt may lead to a reduction in its ductility capacity.

Originality/value
A non-linear dynamic FE model of simple T-stub configuration using a strain rate effect on the material law and fracture simulation, providing insight of stress, strain, strain rate and damage contours developments, when exposed to impact loading.