bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feature selection for the accurate prediction of septic and cardiogenic shock ICU mortality in the acute phase
Authors: Aushev Alexander , Ripoll Vicent Ribas , Vellido Alfredo , Aletti Federico , Pinto Bernardo Bollen , Herpain Antoine , Post Emiel Hendrik , Medina Eduardo Romay , Ferrer Ricard , Baselli Giuseppe , Bendjelid Karim 
Published: June 2018

AbstractCirculatory shock is a life-threatening disease that accounts for around one-third of all admissions to intensive care units (ICU). It requires immediate treatment, which is why the development of tools for planning therapeutic interventions is required to deal with shock in the critical care environment. In this study, the ShockOmics European project original database is used to extract attributes capable of predicting mortality due to shock in the ICU. Missing data imputation techniques and machine learning models were used, followed by feature selection from different data subsets. Selected features were later used to build Bayesian Networks, revealing causal relationships between features and ICU outcome. The main result is a subset of predictive features that includes well-known indicators such as the SOFA and APACHE II scores, but also less commonly considered ones related to cardiovascular function assessed through echocardiograpy or shock treatment with pressors. Importantly, certain selected features are shown to be most predictive at certain time-steps. This means that, as shock progresses, different attributes could be prioritized. Clinical traits obtained at 24h. from ICU admission are shown to accurately predict cardiogenic and septic shock mortality, suggesting that relevant life-saving decisions could be made shortly after ICU admission.
Distributed leadership in organizations: an investigation of antecedent conditions
Authors: Fu Lihua , Liu Zhiying 
Published: June 2018

PurposeThis study aims to investigate antecedent conditions that lead to the development of distributed leadership (DL). The authors examine how the emergence of DL is affected by empowerment and internal context, which consists of shared purpose, social support and voice. The moderating effects of training are also investigated.Design/methodology/approachTo test the hypotheses, this empirical analysis of the relationship between the variables was based on the results of a questionnaire survey on 62 teams in high-tech enterprises of mainland China.FindingsResults indicate that empowerment and internal context in the team significantly predict the extent of DL and that training has positive moderating effects on the relationships.Practical implicationsThe results imply that firms must carefully analyze specific team conditions to ensure shared purpose, social support and voice in each team. This study also suggests the importance of empowerment. Moreover, enterprises can use training, a human resource tool, to enhance the positive effects of internal context and empowerment on DL.Originality/valueBy building on upper echelons theory and integrating insights from contingency theory, this study extends prior research by examining the direct effects of both empowerment managerial system and internal context on DL and the moderating effect of training.
An information privacy culture instrument to measure consumer privacy expectations and confidence
Authors: Da Veiga Adéle 
Published: June 2018

Purpose
This paper aims to propose an information privacy culture index framework (IPCIF) with a validated information privacy culture index instrument (IPCII) to measure information privacy culture across nations. The framework is based on consumers’ privacy expectations, their actual experiences when organisations process their personal information and their general privacy concerns.

Design/methodology/approach
A survey method was deployed to collect data in South Africa – the first participating country in the study – to start building a global information privacy culture index (IPCI) and to validate the questionnaire.

Findings
The IPCI revealed that there seems to be a disconnect between what consumers expect in terms of privacy and the way in which organisations are honouring (or failing to honour) those expectations, which results in a breach of trust and the social contract being violated.

Practical implications
Governments, information regulators and organisations can leverage the results of the privacy culture index to implement corrective actions and controls aimed at addressing the gaps identified from a consumer and compliance perspective. The validated IPCII can be used by both academia and industry to measure the information privacy culture of an institution, organisation or country to identify what to improve to address consumer privacy expectations and concerns.

Originality/value
The IPCIF and validated IPCII are the first tools that combine the concepts of consumer expectations and their confidence levels in whether organisations are meeting their privacy expectations, which are in line with the fair information practice principles and the privacy guidelines of the Organisation for Economic Cooperation and Development, to determine gaps and define improvement plans.
Using artificial intelligence to create value in insurance
Authors: Riikkinen Mikko , Saarijärvi Hannu , Sarlin Peter , Lähteenmäki Ilkka 
Published: June 2018

Purpose
Recent technological and digital developments have opened new avenues for customer data utilization in insurance services. One form of this data transformation is automated chatbots that provide convenient access to data leveraged through a discussion-like interface. The purpose of this paper is to uncover how insurance chatbots support customers’ value creation.

Design/methodology/approach
Three complementary theoretical perspectives – artificial intelligence, service logic, and reverse use of customer data – are briefly discussed and integrated into a conceptual framework. The suggested framework is further shown through illustrative case examples that characterize different ways of supporting customers’ value creation.

Findings
Chatbots represent a new type of interaction through which companies can influence customers’ value creation by providing them with additional resources. Based on the proposed conceptual framework and the illustrative case examples, four metaphors are identified that characterize how insurance chatbots can support customers’ value creation.

Research limitations/implications
The study is conceptual in nature, and the case examples are used for illustrative purposes. No representative data from those users who will eventually determine whether chatbots are of value was used.

Practical implications
Using the suggested framework, which is aligned with provider service logic, insurance companies can consider what kind of a role they wish to play in customers’ value-creating processes.

Originality/value
Automated chatbots provide convenient access to data leveraged through a discussion-like interface. This study is among the earliest to address their value-creating potential in insurance.
The impact of servitization on firm performance: a meta-analysis
Authors: Wang Weijiao , Lai Kee-Hung , Shou Yongyi 
Published: June 2018

PurposeServitization has been recognized as an effective means for manufacturers to achieve superior performance. However, the servitization-performance relationship is controversial since prior empirical studies have provided inconsistent and even contradictory results. Hence, the purpose of this paper is to provide a quantitative review on the servitization-performance relationship based on research findings reported in the extant literature.Design/methodology/approachStudies from 41 peer-reviewed journal articles were sampled and analyzed. A meta-analytic approach was adopted to conduct a quantitative review on the relationship between servitization and firm performance.FindingsThe results confirm a positive servitization-performance relationship. In addition, the results reveal that the observed servitization-performance relationship is influenced by the operationalization of constructs (servitization and performance) and control variables (industry and region).Originality/valueAs the first meta-analysis on the servitization-performance relationship, this study contributes to the servitization literature and provides future research directions.
Empirical evidence of deep learning in learning communities
Authors: Smith Kara , Lovgren Robin 
Published: June 2018

Purpose
The purpose of this paper is to investigate whether learning communities (LCs), defined as a cohort of students jointly enrolled in two distinct courses, increase “deep learning” in either or both courses. This study focuses on the impact of learning communities in quantitative courses.

Design/methodology/approach
The hypothesis is tested using a unique data set including individual student performance and characteristics collected from students enrolled in an LC of Principles of Microeconomics and Elementary Statistics. The sample also includes students enrolled in each course separately which allows for testing between groups. The final exam in each course contained questions designed specifically to test deep learning. The design facilitates the use of multivariate regression analysis to examine the correlation between learning in communities and deep learning, holding constant other possible elements of student success.

Findings
Despite perceptions among the sample student population that learning increases in both courses as a result of the LC format, the empirical evidence does not reveal any statistically significant increase in deep learning as a result of learning in community. However, the sample is more introverted than the average college student which may meaningfully impact the results.

Research limitations/implications
There are a number of important motivations for implementing an LC program that are not measured here. These include an increased sense of community among students, breadth (rather than depth) of knowledge, and awareness of the interconnectedness of learning across disciplines. However, to the extent that university instructors are motivated to ensure learning in their own discipline, this resource-intensive strategy may not be the most suitable approach in quantitative courses.

Originality/value
Learning communities continue to be a popular pedagogical technique and curriculum requirement, particularly at teaching-focused universities. This research offers an empirical approach to measuring one aspect of their value which is typically left to conceptual or qualitative study.
Cointegration and causality in capital markets
Authors: Inci A. Can 
Published: June 2018

Purpose
The purpose of this paper is to study the efficiency of different oil and gas markets. Most previous studies examined the issue using low frequency date sampled at monthly, weekly, or daily frequencies. In this study, 30-minute intraday data are used to explore efficiency in energy markets.

Design/methodology/approach
Sophisticated statistical analysis techniques such as Granger-causality regressions, augmented Dickey-Fuller tests, cointegration tests, vector autoregressions are used to explore the transmission of information between oil and gas energy markets.

Findings
This study provides evidence for efficiency in energy markets. The new information that arrives either to futures markets or spot markets is digested correctly, completely, and in a fast manner, and is propagated to the other market. The evidence indicates high efficiency.

Originality/value
This study is one of the first papers that uses 30-minute interval intraday data to investigate efficiency in oil and gas commodity markets.
Evaluating sample size to estimate genetic management metrics in the genomics era
Authors: Flesch Elizabeth P. , Rotella Jay J. , Thomson Jennifer M. , Graves Tabitha A. , Garrott Robert A. 
Published: June 2018

AbstractInbreeding and relationship metrics among and within populations are useful measures for genetic management of wild populations, but accuracy and precision of estimates can be influenced by the number of individual genotypes analysed. Biologists are confronted with varied advice regarding the sample size necessary for reliable estimates when using genomic tools. We developed a simulation framework to identify the optimal sample size for three widely used metrics to enable quantification of expected variance and relative bias of estimates and a comparison of results among populations. We applied this approach to analyse empirical genomic data for 30 individuals from each of four different free‐ranging Rocky Mountain bighorn sheep (Ovis canadensis canadensis) populations in Montana and Wyoming, USA, through cross‐species application of an Ovine array and analysis of approximately 14,000 single nucleotide polymorphisms (SNPs) after filtering. We examined intra‐ and interpopulation relationships using kinship and identity by state metrics, as well as FST between populations. By evaluating our simulation results, we concluded that a sample size of 25 was adequate for assessing these metrics using the Ovine array to genotype Rocky Mountain bighorn sheep herds. However, we conclude that a universal sample size rule may not be able to sufficiently address the complexities that impact genomic kinship and inbreeding estimates. Thus, we recommend that a pilot study and sample size simulation using R code we developed that includes empirical genotypes from a subset of populations of interest would be an effective approach to ensure rigour in estimating genomic kinship and population differentiation.
Agri‐environment schemes targeting farmland bird populations also provide food for pollinating insects
Authors: Ouvrard Pierre , Jacquemart Anne‐Laure 
Published: June 2018

Abstract
Farmland biodiversity has declined over the past few decades. European Common Agricultural Policy encourages farmers to set up agri‐environment schemes (AES) that support biodiversity and associated ecosystem services such as pollination. Although few AES are specifically devoted to pollinating insects, many AES could provide resources for pollinators. In Belgium, AES designed to provide seed resources for wild birds (bird‐strip AES) contain mixed‐plant communities that may benefit insects, although their ability to support pollinators has not yet been evaluated.
The present study aimed to assess the ability of bird‐strip AES to support pollinating insects. We identified and quantified floral resources, flower‐visiting insects and insect–flower interaction networks over 2 years on four bird strips located in intensive agro‐ecosystems in Belgium.
The bird strips contained plant species that were either purposely sown or established spontaneously. The spontaneous Cirsium species, with its high nectar production, offered floral resources that complemented those of the sown species Raphanus sativus and Phacelia tanacetifolia. Most of the flower‐visiting insects considered as pollinators belonged to the orders Hymenoptera and Diptera.
In conclusion, bird‐strip AES provided floral resources to pollinators, even in the absence of annual sowing.
Lymph nodes metastasis in cervical cancer: Incidences, risk factors, consequences and imaging evaluations
Authors: Du Rongxu , Li Lei , Ma Shuiqing , Tan Xianjie , Zhong Sen , Wu Ming 
Published: June 2018

AbstractAimThe aim of this study was to determine the incidence, risk factors, consequences and accuracy of imaging evaluation of lymph node (LN) metastasis in a cohort of 406 patients treated with radical hysterectomy (RH), lymphadenectomy of pelvic LN (PLN) and para‐aortic LN (PALN), which was performed primarily by one physician.MethodsFrom February 2001 to November 2015, patients with cervical cancer of FIGO stage IB were included, if they received RH of class III or type C performed by Dr. M. Wu in Peking Union Medical College Hospital. Follow‐up ended in December 2016. Incidences and accuracy of imaging evaluation of LN metastasis were described, and predictive factors of LN metastasis and its impact on survival outcomes were determined in univariate and multivariate models.ResultsAmong 406 patients with clinical stage IB, 57 (14.0%) had lymphatic metastasis. In multivariate model, positive parametrium was independent factor for general LN metastasis (odds ratio [OR] 5.1; 95% confidence interval [95% CI], 2.1–12.1) and PLN metastasis (OR 5.3; 95% CI, 2.2–12.8). Positive PLN was independent factor for metastasis to common iliac LN and PALN. After adjusted with clinico pathologic factors, general and site‐specific LN metastases were independent risk factors of progression‐free survival and overall survival (all P values <0.05). Preoperative imaging evaluation had low sensitivity but high specificity for predicting LN metastasis. Various imaging methods had similar predictive accuracy.ConclusionLymphatic metastasis was significantly related to the clinico pathologic characters and survival of cervical cancer. More sensitive preoperative evaluation is needed for predicting the LN metastasis.
Safety, tolerability and pharmacokinetics/pharmacodynamics of the adrenomedullin antibody adrecizumab in a first‐in‐human study and during experimental human endotoxaemia in healthy subjects
Authors: Geven Christopher , van Lier Dirk , Blet Alice , Peelen Roel , ten Elzen Bas , Mebazaa Alexandre , Kox Matthijs , Pickkers Peter 
Published: June 2018

AimsAdrenomedullin (ADM) is an important regulator of endothelial barrier function and vascular tone, and may represent a novel treatment target in sepsis. The non‐neutralizing ADM antibody adrecizumab has shown promising results in preclinical sepsis models. In the present study, we investigated the safety, tolerability and pharmacokinetics (PK)/pharmacodynamics of adrecizumab in a first‐in‐man study and in a second study during experimental human endotoxaemia.MethodsForty‐eight healthy male volunteers were enrolled in two randomized, double‐blind, placebo‐controlled phase I studies. In both studies, subjects received placebo or one of three doses of adrecizumab (n = 6 per group). In the second study, a bolus of 1 ng kg–1 endotoxin was followed by infusion of 1 ng kg–1 h–1 endotoxin for 3 h to induce systemic inflammation, and the study medication infusion started 1 h after endotoxin bolus administration.ResultsAdrecizumab showed an excellent safety profile in both studies. PK analyses showed proportional increases in the maximum plasma concentration of adrecizumab with increasing doses, a small volume of distribution, a low clearance rate and a terminal half‐life of ~14 days. adrecizumab elicited a pronounced increase in plasma ADM levels, whereas levels of mid‐regional pro‐adrenomedullin remained unchanged, indicating that de novo synthesis of ADM was not influenced. In the second study, no effects of adrecizumab on cytokine clearance were observed, whereas endotoxin‐induced flu‐like symptoms resolved more rapidly.ConclusionsAdministration of adrecizumab is safe and well tolerated in humans, both in the absence and presence of systemic inflammation. These findings pave the way for further investigation of adrecizumab in sepsis patients.
The biomedical challenge of neurodegenerative disorders: an opportunity for cannabinoid‐based therapies to improve on the poor current therapeutic outcomes
Authors: Fernández‐Ruiz Javier 
Published: June 2018

At the beginning of the 21st century, the therapeutic management of neurodegenerative disorders remains a major biomedical challenge, particularly given the worldwide ageing of the population over the past 50 years that is expected to continue in the forthcoming years. This review will focus on the promise of cannabinoid‐based therapies to address this challenge. This promise is based on the broad neuroprotective profile of cannabinoids, which may cooperate to combat excitotoxicity, oxidative stress, glia‐driven inflammation and protein aggregation. Such effects may be produced by the activity of cannabinoids through their canonical targets (e.g. cannabinoid receptors and endocannabinoid enzymes) and alsovianon‐canonical elements and activities in distinct cell types critical for cell survival or neuronal replacement (e.g. neurons, glia and neural precursor cells). Ultimately, the therapeutic events driven by endocannabinoid signalling reflect the activity of an endogenous system that regulates the preservation, rescue, repair and replacement of neurons and glia.Linked ArticlesThis article is part of a themed section on 8thEuropean Workshop on Cannabinoid Research. To view the other articles in this section visithttp://onlinelibrary.wiley.com/doi/10.1111/bph.v176.10/issuetoc
ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content
Authors: Marnerides D. , Bashford‐Rogers T. , Hatchett J. , Debattista K. 
Published: June 2018

AbstractHigh dynamic range (HDR) imaging provides the capability of handling real world lighting as opposed to the traditional low dynamic range (LDR) which struggles to accurately represent images with higher dynamic range. However, most imaging content is still available only in LDR. This paper presents a method for generating HDR content from LDR content based on deep Convolutional Neural Networks (CNNs) termed ExpandNet. ExpandNet accepts LDR images as input and generates images with an expanded range in an end‐to‐end fashion. The model attempts to reconstruct missing information that was lost from the original signal due to quantization, clipping, tone mapping or gamma correction. The added information is reconstructed from learned features, as the network is trained in a supervised fashion using a dataset of HDR images. The approach is fully automatic and data driven; it does not require any heuristics or human expertise. ExpandNet uses a multiscale architecture which avoids the use of upsampling layers to improve image quality. The method performs well compared to expansion/inverse tone mapping operators quantitatively on multiple metrics, even for badly exposed inputs.
Fast Fluid Simulations with Sparse Volumes on the GPU
Authors: Wu Kui , Truong Nghia , Yuksel Cem , Hoetzlein Rama 
Published: June 2018

AbstractWe introduce efficient, large scale fluid simulation on GPU hardware using the fluid‐implicit particle (FLIP) method over a sparse hierarchy of grids represented in NVIDIA® GVDB Voxels. Our approach handles tens of millions of particles within a virtually unbounded simulation domain. We describe novel techniques for parallel sparse grid hierarchy construction and fast incremental updates on the GPU for moving particles. In addition, our FLIP technique introduces sparse, work efficient parallel data gathering from particle to voxel, and a matrix‐free GPU‐based conjugate gradient solver optimized for sparse grids. Our results show that our method can achieve up to an order of magnitude faster simulations on the GPU as compared to FLIP simulations running on the CPU.