bluuebunny/crossref_metadata_2025_split huggingface dataset:
Applying machine learning in motor activity time series of depressed bipolar and unipolar patients
Authors: Jakobsen Petter , Garcia-Ceja Enrique , Riegler Michael , Stabell Lena Antonsen , Nordgreen Tine , Torresen Jim , Fasmer Ole Bernt , Oedegaard Ketil Joachim 
Published: April 2020

ABSTRACTCurrent practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner physiological state expressed in behavior patterns. Alterations of motor activity are essential features of bipolar and unipolar depression. The aim was to investigate if objective measures of motor activity can aid existing diagnostic practice, by applying machine-learning techniques to analyze activity patterns in depressed patients and healthy controls. Random Forrest, Deep Neural Network and Convolutional Neural Network algorithms were used to analyze 14 days of actigraph recorded motor activity from 23 depressed patients and 32 healthy controls. Statistical features analyzed in the dataset were mean activity, standard deviation of mean activity and proportion of zero activity. Various techniques to handle data imbalance were applied, and to ensure generalizability and avoid overfitting a Leave-One-User-Out validation strategy was utilized. All outcomes reports as measures of accuracy for binary tests. A Deep Neural Network combined with random oversampling class balancing technique performed a cut above the rest with a true positive rate of 0.82 (sensitivity) and a true negative rate of 0.84 (specificity). Accuracy was 0.84 and the Matthews Correlation Coefficient 0.65. Misclassifications appear related to data overlapping among the classes, so an appropriate future approach will be to compare mood states intra-individualistic. In summary, machine-learning techniques present promising abilities in discriminating between depressed patients and healthy controls in motor activity time series.
A cryptic tubulin-binding domain links MEKK1 to microtubule remodelling
Authors: Filipčík Pavel , Latham Sharissa L. , Cadell Antonia L. , Day Catherine L. , Croucher David R. , Mace Peter D. 
Published: April 2020

ABSTRACTThe MEKK1 protein is a pivotal kinase activator of responses to cellular stress. Activation of MEKK1 can trigger various responses, including mitogen activated protein (MAP) kinases, NF-κB signalling, or cell migration. Notably, MEKK1 activity is triggered by microtubule-targeting chemotherapies, amongst other stressors. Here we show that MEKK1 contains a previously unidentified tumour overexpressed gene (TOG) domain. The MEKK1 TOG domain binds to tubulin heterodimers—a canonical function of TOG domains—but is unusual in that it appears alone rather than as part of a multi-TOG array, and has structural features distinct from previously characterised TOG domains. MEKK1 TOG demonstrates a clear preference for binding curved tubulin heterodimers, which exist in soluble tubulin and at sites of microtubule polymerisation and depolymerisation. Mutations disrupting tubulin-binding lead to destabilisation of the MEKK1 protein in cells, and ultimately a decrease in microtubule density at the leading edge of polarised cells. We also show that MEKK1 mutations at the tubulin-binding interface of the TOG domain recur in patient derived tumour sequences, suggesting selective enrichment of tumour cells with disrupted MEKK1–microtubule association. Together, these findings provide a direct link between the MEKK1 protein and tubulin, which is likely to be relevant to cancer cell migration and response to microtubule-modulating therapies.SIGNIFICANCE STATEMENTThe protein kinase MEKK1 activates stress response pathways in response to various cellular stressors, including chemotherapies that disrupt dynamics of the tubulin cytoskeleton. Filipčík et al., show that MEKK1 contains a previously uncharacterised domain that can preferentially bind to the curved tubulin heterodimer—which is found at sites of microtubule assembly and disassembly. Mutations that interfere with MEKK1-tubulin binding disrupt microtubule networks in migrating cells and are enriched in patient-derived tumour sequences. These results suggest that MEKK1-tubulin binding may be relevant to cancer progression, and the efficacy of microtubule-disrupting chemotherapies that require the activity of MEKK1.
How social exclusion and temporal distance influence product choices: the role of coping strategies
Authors: Xu Wei , Jin XiaoTong 
Published: April 2020

PurposeWe examine how social exclusion and temporal distance (i.e. being socially excluded in the present or the anticipation of exclusion in the future) shape whether people choose hedonic or utilitarian products.Design/methodology/approachWe conduct four experiments to test the hypotheses. Study 1a and study 1b provide the initial evidence that consumers strategically engage in differentiation in response to social exclusion in the present and in the future. Study 2 and study 3 replicate the basic interaction effect of social exclusion and temporal distance on product choices and test the underlying mechanism.FindingsWe find that temporal distance affects consumer product choices through people’s coping strategies. When consumers are socially excluded, they are more likely to have a problem-solving tendency and more likely to choose utilitarian products. In contrast, when consumers imagine being socially excluded in the future, they are more likely to have to use emotions to solve problems and choose hedonic products.Originality/valueOur study contributes to the literature in several ways. First, it deepens our understanding of the psychological drivers of social exclusion in consumer research. Second, it offers insights into understanding prior findings that document both problem-solving and emotion-regulating behavior in response to social exclusion. Third, by showing that social exclusion and temporal distance can influence the type of products selected, our findings contribute to a new stream of work that examines the impact of people’s fundamental desire for control on consumer behavior.
Financing needs of micro-enterprises along their evolution
Authors: Prijadi Ruslan , Wulandari Permata , Desiana Putri Mega , Pinagara Fajar Ayu , Novita Maya 
Published: April 2020

Purpose
The purpose of this paper aims to investigate micro enterprises financing in Indonesia and examines how this financing differs, depending on the enterprise’s development stage. This research also identifies some structural problems related to micro-financing and provides workable solutions.

Design/methodology/approach
This research uses the entrepreneurial network model of Schutjens and Stam (2003) to examine how Indonesian micro and small enterprises (MSEs) evolve even before they become regular small businesses. Content analysis is used on 10 micro-enterprises from Jakarta, the capital city of Indonesia and its surroundings. Financing issues at each stage of enterprise development are identified and deeply examined.

Findings
This research not only confirms the significant financing problems micro-enterprises face but also clarifies that these problems are unique to each stage of the MSEs’ development. One insight is that most micro-enterprises do not use funding from formal institutions. That is, business owners rely more on funding from non-formal institutions. This is because these enterprises’ managers generally cannot prepare loans application and/or they are lack of knowledge/training on financing matters. They hesitate to borrow from formal financial institutions, as the rates are high but the processing time is longer than those of the loan sharks.

Originality/value
This research contributes to the field of entrepreneurial finance by identifying the structural problems inherent in micro-finance and providing workable solutions for overcoming these problems.
The multi-generation
Authors: Dorie Amy , Loranger David 
Published: April 2020

PurposeThe aim of this research is to advance the understanding of multi-channel behaviour in terms of different generational cohorts' usage and spending patterns.Design/methodology/approachBuilding on previous studies on multi-channel behaviour, differences in shopping channel usage and purchase amounts were investigated between baby boomers, Gen X, xennials and millennials.FindingsThere were significant differences found between the generations in terms of multi-channel behaviour regarding purchasing frequency and average purchase amounts via a) mobile phone, b) tablet, c) computer, d) social media and e) brick-and-mortar. Fewer differences were found amongst the generational cohorts in terms of amount spent per channel.Research limitations/implicationsThe research was successful in analysing variances in multi-channel behaviour amongst the baby boomer, Generation X, xennial and millennial cohorts, while updating the body of literature to consider generational channel usage of mobile and social media in multi-channel retailing.Practical implicationsMarketers should consider xennials’ channel behaviour and focus on converting sales through integrated programmes based on their channel usage. Retailers should also consider millennials' heavy engagement with social media in their lives but spend lower amounts via the medium, which may be an opportunity to use this medium as a viable stand-alone channel in targeting millennials' shopping dollars.Originality/valueThis study updates the body of research on multi-channel behaviour by considering generation as a factor in channel usage and spend amount.
Coworkers, supervisors and frontline restaurant employees: social judgments and the mediating effects of exhaustion and cynicism
Authors: Bufquin Diego 
Published: April 2020

PurposeThe current study assesses the relationships between the social judgments made by frontline restaurant employees toward their direct supervisors and coworkers and employees' cynicism, exhaustion and turnover intentions. The mediating effects of cynicism and exhaustion are also examined.Design/methodology/approachThe model was tested on 477 frontline restaurant employees using a questionnaire survey. Data were analyzed using descriptive statistics, confirmatory factor analysis and structural equation modeling, which included bootstrapping.FindingsResults indicate that the aforementioned social judgments significantly decrease frontline restaurant employees' exhaustion and cynicism, which are then positively related to turnover intentions. Furthermore, exhaustion and cynicism mediate the relationships between employees' evaluations of their supervisors and coworkers and turnover intentions.Originality/valueThis study is the first to analyze the effects of warmth, competence and morality – which represent fundamental social traits that people use to evaluate others – on turnover intentions via cynicism and exhaustion.
Smart library book sorting application with intelligence computer vision technology
Authors: Shi Xiaohua , Tang Kaicheng , Lu Hongtao 
Published: April 2020

PurposeBook sorting system is one of specific application in smart library scenarios, and it now has been widely used in most libraries based on RFID (radio-frequency identification devices) technology. Book identification processing is one of the core parts of a book sorting system, and the efficiency and accuracy of book identification are extremely critical to all libraries. In this paper, the authors propose a new image recognition method to identify books in libraries based on barcode decoding together with deep learning optical character recognition (OCR) and describe its application in library book identification processing.Design/methodology/approachThe identification process relies on recognition of the images or videos of the book cover moving on a conveyor belt. Barcode is printed on or attached to the surface of each book. Deep learning OCR program is applied to improve the accuracy of recognition, especially when the barcode is blurred or faded. The approach the authors proposed is robust with high accuracy and good performance, even though input pictures are not in high resolution and the book covers are not always vertical.FindingsThe proposed method with deep learning OCR achieves best accuracy in different vertical, skewed and blurred image conditions.Research limitations/implicationsMethods that the authors proposed need to cooperate and practice in different book sorting machine.Social implicationsThe authors collected more than 500 books from a library. These photos display the cover of more than 100 randomly picked books with backgrounds in different colors, each of which has about five different pictures captured from variety angles. The proposed method combines traditional barcode identification algorithm with the authors’ modification to locate and deskew the image. And deep learning OCR is involved to enhance the accuracy when the barcode is blurred or partly faded. Book sorting system design based on this method will also be introduced.Originality/valueExperiment demonstrates that the accuracy of the proposed method is high in real-time test and achieves good accuracy even when the barcode is blurred. Deep learning is very effective in analyzing image content, and a corresponding series of methods have been formed in video content understanding, which can be a greater advantage and play a role in the application scene of intelligent library.
The effect of housing type on householders' self-reported participation in recycling
Authors: du Toit Jacques , Wagner Claire 
Published: April 2020

PurposeThe purpose of this article is to examine the effect of housing type, relative to demographics, on householders' self-reported recycling across low-, medium- and high-density housing without recycling facilities by using the theory of planned behaviour.Design/methodology/approachA survey was conducted amongst 580 households across houses, townhouses and apartments in Pretoria, South Africa. The household member most responsible for recycling completed a self-administered questionnaire. Data were analysed using factor and reliability analyses, decision trees and multivariate analysis of variance.FindingsAge was the strongest predictor; the older the respondent, the more likely the household recycled. Housing type was the second strongest predictor with a significant increase in recycling in houses compared to townhouses and apartments. Subsequent analyses focussed on young respondents to control for age. Housing type had an overall non-significant effect on the factors behind recycling. Post hoc tests, however, suggest that young respondents in townhouses and apartments felt significantly less able to recycle, particularly because of lack of space and support from managing agencies.Practical implicationsFor recycling to be acceptable to young people in medium- and high-density housing, interior architects and site planners should find innovative ways to make individual and communal facilities as convenient and accessible as possible to tenants, owners and recycling companies. The role of managing agencies is also critical.Originality/valueThis study is one of the first to systematically examine recycling across three different housing types with recommendations for planning, design and further research.
Solving the delayed retirement puzzle … and creating win-win opportunities
Authors: Phillips Patti , Phillips Jack J. 
Published: April 2020

Purpose
The population across the industrialized world is aging to the extent never experienced before in history, living 10 years longer on average than the previous generation and nearly two decades longer than two generations ago.

Design/methodology/approach
To date, this rapidly growing segment of the population is not always addressed in inclusion and diversity plans and has often been overlooked as a source of competitive advantage, rather seen as a cost and a burden in some organizations.

Findings
Leaders in industrial nations agree that to continue strong economic growth, it is vital to support people to live healthier lives and stay in the workforce for longer. By doing so, we can not only improve well-being and enable people to remain active and economically productive but also reduce dependency, bringing down the burdens on health, pensions and social systems.

Originality/value
When this challenge is addressed, important motivational and productivity benefits will result from the seasoned talent segment staying a little longer with the organization. They will stay longer because they want to, not because they cannot afford to retire.
Impact of health warning labels communicating the risk of cancer on alcohol selection: an online experimental study
Authors: Clarke Natasha , Pechey Emily , Mantzari Eleni , Blackwell Anna K.M. , De‐loyde Katie , Morris Richard W. , Munafò Marcus R. , Marteau Theresa M. , Hollands Gareth J. 
Published: April 2020

ABSTRACTAimsEvidence from tobacco research suggests that health warning labels (HWLs) depicting the adverse consequences of consumption change smoking behaviours, with image‐and‐text (also known as ‘pictorial’ or ‘graphic’) HWLs most effective. There is an absence of evidence concerning the potential impact of HWLs placed on alcohol products on selection of those products. This study aimed to obtain a preliminary assessment of the possible impact of (i) image‐and‐text, (ii) text‐only, and (iii) image‐only HWLs on selection of alcoholic versus non‐alcoholic drinks.DesignA between‐subjects randomised experiment with a 2 (image: present versus absent) × 2 (text: present versus absent) factorial design.SettingThe study was conducted on the online survey platform Qualtrics.ParticipantsParticipants (n = 6024) were adults over the age of 18 who consumed beer or wine regularly (i.e. at least once a week), recruited through a market research agency.InterventionsParticipants were randomised to one of four groups varying in the HWL displayed on the packaging of alcoholic drinks: (i) image‐and‐text HWL; (ii) text‐only HWL; (iii) image‐only HWL; and (iv) no HWL. HWLs depicted bowel cancer, breast cancer and liver cancer, which were each displayed twice across six alcoholic drinks. Each group viewed six alcoholic and six non‐alcoholic drinks and selected one drink that they would like to consume.MeasurementsThe primary outcome was the proportion of participants selecting an alcoholic versus a non‐alcoholic drink.FindingsAlcoholic drink selection was lower for all HWL types compared with no HWL (image‐and‐text: 56%; image‐only: 49%; text‐only: 61%; no HWL: 77%), with selection lowest for HWLs that included an image. Image‐and‐text HWLs reduced the odds of selecting an alcoholic drink compared with text‐only HWLs (OR = 0.80, 95% CI = 0.69, 0.92), but increased the odds of selecting an alcoholic drink compared with image‐only HWLs (OR = 1.34, 95% CI = 1.16, 1.55).ConclusionsHealth warning labels communicating the increased risk of cancers associated with alcohol consumption reduced selection of alcoholic versus non‐alcoholic drinks in a hypothetical choice task in an online setting; labels displaying images had the largest effect. Their impact in laboratory and real‐world field settings using physical products awaits investigation.
The association of criminal justice supervision setting with overdose mortality: a longitudinal cohort study
Authors: Binswanger Ingrid A. , Nguyen Anh P. , Morenoff Jeffrey D. , Xu Stanley , Harding David J. 
Published: April 2020

AbstractBackground and AimsDespite the high prevalence of substance use among people in the US criminal justice system, little is known about the incidence of overdose mortality by use patterns, drug convictions and supervision setting. We examined the associations between these characteristics and overdose mortality.DesignRetrospective cohort study.Setting and participantsIndividuals sentenced to prison, jail, probation or jail plus probation for a felony conviction in Michigan, USA from 2003 to 2006.MeasurementsUsing the National Death Index, we assessed overdose mortality to December 2012. We calculated overdose mortality rates by pre‐sentence opioid use, drug convictions and supervision setting. Multivariable analyses were conducted using competing risks regression with time‐varying covariates.FindingsAmong 140 266 individuals followed over a mean of 7.84 years [standard deviation (SD) = 1.52], 14.9% of the 1131 deaths were due to overdose (102.8 per 100 000 person‐years). Over the follow‐up, more than half of overdose deaths occurred in the community (57.7%), nearly a third (28.8%) on probation and 12.8% on parole. The adjusted risk of overdose death was lower on probation [hazard ratio (HR) = 0.71, 95% confidence interval (CI) = 0.60, 0.85] than in the community without probation or parole (HR = 1.00) but not significantly different on parole (HR = 1.13, 95% CI = 0.87, 1.47). Pre‐sentence daily opioid use (HR = 3.54, 95% CI = 3.24, 3.87) was associated with an increased risk. Drug possession (HR = 1.11, 95% CI = 0.93, 1.31) and delivery convictions (HR = 0.92, 95% CI = 0.77, 1.09) were not significantly associated with overdose mortality.ConclusionsBased on the absolute or relative risk, parole, probation and community settings are appropriate settings for enhanced overdose prevention interventions. Ensuring that individuals with pre‐sentence opioid use have access to harm reduction and drug treatment services may help to prevent overdose among people involved with the criminal justice system.
Battling COVID‐19: critical care and peri‐operative healthcare resource management strategies in a tertiary academic medical centre in Singapore
Authors: Lee C. C. M. , Thampi S. , Lewin B. , Lim T. J. D. , Rippin B. , Wong W. H. , Agrawal R. V. 
Published: April 2020

SummaryIn December 2019, a cluster of atypical pneumonia cases were reported in Wuhan, China, and a novel coronavirus elucidated as the aetiologic agent. Although most initial cases occurred in China, the disease, termed coronavirus disease 2019, has become a pandemic and continues to spread rapidly with human‐to‐human transmission in many countries. This is the third novel coronavirus outbreak in the last two decades and presents an ensuing healthcare resource burden that threatens to overwhelm available healthcare resources. A study of the initial Chinese response has shown that there is a significant positive association between coronavirus disease 2019 mortality and healthcare resource burden. Based on the Chinese experience, some 19% of coronavirus disease 2019 cases develop severe or critical disease. This results in a need for adequate preparation and mobilisation of critical care resources to anticipate and adapt to a surge in coronavirus disease 2019 case‐load in order to mitigate morbidity and mortality. In this article, we discuss some of the peri‐operative and critical care resource planning considerations and management strategies employed in a tertiary academic medical centre in Singapore in response to the coronavirus disease 2019 outbreak.
Generalised regression estimation via the bootstrap
Authors: Booth James G. , Welsh Alan H. 
Published: April 2020

SummaryA generalised regression estimation procedure is proposed that can lead to much improved estimation of population characteristics, such as quantiles, variances and coefficients of variation. The method involves conditioning on the discrepancy between an estimate of an auxiliary parameter and its known population value. The key distributional assumption is joint asymptotic normality of the estimates of the target and auxiliary parameters. This assumption implies that the relationship between the estimated target and the estimated auxiliary parameters is approximately linear with coefficients determined by their asymptotic covariance matrix. The main contribution of this paper is the use of the bootstrap to estimate these coefficients, which avoids the need for parametric distributional assumptions. First‐order correct conditional confidence intervals based on asymptotic normality can be improved upon using quantiles of a conditional double bootstrap approximation to the distribution of the studentised target parameter estimate.