bluuebunny/crossref_metadata_2025_split huggingface dataset:
Screening and Purification of Natural Products from Actinomycetes that Induce a “Rounded” Morphological Phenotype in Fission Yeast
Authors: Lewis Richard Alexander , Devi Jenileima , Green Katherine , Li Juanjuan , Hopkins Adam , Hayles Jacqueline , Nurse Paul , Errington Jeff , Allenby Nicholas Edward Ellis 
Published: April 2021

AbstractThis study was designed to identify and investigate bioactive natural product compounds that alter the cellular shape of the fission yeastSchizosaccharomyces pombeand induce a “rounded” or “small” cellular morphological phenotype. Bioassays using a range of antifungal agents against a multidrug-sensitive fission yeast strain, SAK950 showed that many induced a “rounded” phenotype. We then investigated whether 46 of the actinomycete strains identified in our previous study as inducing a similar phenotype produced antifungal agents of similar classes. We show that five of the strains produced streptothricin and that 26 strains produced polyenes, including fungichromin, filipin and candicidin, the last of which was produced by 24 strains. A taxonomic study of the strains indicated that the majority of the candicidin only producers wereStreptomyces hydrogenansandS. albidoflavuswhilst those that additionally produced streptothricin were related toS. enissocaesilis. A follow-up study to investigate the natural products made by related strains indicated that they followed a similar pattern. The identification of several compounds from the actinomycete strains similar to the antifungal agents initially tested confirm the validity of an approach using theS. pombemorphological phenotype and actinomycete taxonomy as a predictive tool for natural product identification.Graphic Abstract
Short-Term Prediction of Demand for Ride-Hailing Services: A Deep Learning Approach
Authors: Chen Long , Thakuriah Piyushimita , Ampountolas Konstantinos 
Published: April 2021

AbstractAs ride-hailing services become increasingly popular, being able to accurately predict demand for such services can help operators efficiently allocate drivers to customers, and reduce idle time, improve traffic congestion, and enhance the passenger experience. This paper proposesUberNet, a deep learning convolutional neural network for short-time prediction of demand for ride-hailing services. Exploiting traditional time series approaches for this problem is challenging due to strong surges and declines in pickups, as well as spatial concentrations of demand. This leads to pickup patterns that are unevenly distributed over time and space.UberNetemploys a multivariate framework that utilises a number of temporal and spatial features that have been found in the literature to explain demand for ride-hailing services. Specifically, the proposed model includes two sub-networks that aim to encode the source series of various features and decode the predicting series, respectively. To assess the performance and effectiveness ofUberNet, we use 9 months of Uber pickup data in 2014 and 28 spatial and temporal features from New York City. We use a number of features suggested by the transport operations and travel behaviour research areas as being relevant to passenger demand prediction, e.g., weather, temporal factors, socioeconomic and demographics characteristics, as well as travel-to-work, built environment and social factors such as crime level, within a multivariate framework, that leads to operational and policy insights for multiple communities: the ride-hailing operator, passengers, third-part location-based service providers and revenue opportunities to drivers, and transport operators such as road traffic authorities, and public transport agencies. By comparing the performance ofUberNetwith several other approaches, we show that the prediction quality of the model is highly competitive. Further,Ubernet’s prediction performance is better when using economic, social and built environment features. This suggests thatUbernetis more naturally suited to including complex motivators of travel behavior in making real-time demand predictions for ride-hailing services.
Mapping in unstructured natural environment: a sensor fusion framework for wearable sensor suites
Authors: Chahine Georges , Vaidis Maxime , Pomerleau François , Pradalier Cédric 
Published: April 2021

AbstractWe present a generalized mapping framework that can withstand the challenges incurred by working in unstructured outdoor environments, such as a snowy forest. The proposed method takes advantage of a sensor fusion scheme, where sensors such as cameras and lidars are used in order to reconstruct the surrounding natural environment. Although mapping techniques such as SLAM and ICP cannot themselves properly handle the complexity of natural scenes, they do have the potential to contribute to the global solution in a proposed sensor fusion scheme, based on a factor graph architecture. In this paper, we propose an innovative map registration scheme for visual maps, and show how it can improve the reconstruction quality after data fusion. We also analyze the behavior and sensitivity of factor graphs to uncertainties, by comparing the residual error with different parameter combinations such as variances, using an exhaustive grid search with ground truth comparison. Finally, we suggest an ICP-inferred loop closure, capable of compensating position and attitude drift. The experiments are carried out by recording in a snowy forest using a wearable sensor suite. In the experiments, ground truth was acquired using a millimeter-accurate total station. The proposed framework is shown to be robust and likewise capable of providing estimates that are otherwise unattainable using classic techniques, such as visual SLAM and ICP for lasers. Finally, a visible improvement in the map reconstruction quality is shown, and the proposed framework achieves a translation error of 0.36 m.
A systematic approach of lean supply chain management in shipbuilding
Authors: Chu Niansheng , Nie Xiang , Xu Jiang , Li Kunlin 
Published: April 2021

AbstractThis paper presents a systematic approach for lean supply chain management in shipbuilding industry based on analysis of the unique characters and processes of shipbuilding. The approach constantly improves productivity and retains low costs. The system that covers seven sub-systems on three different levels is created based on the lean thinking and supply chain management theory. In the lean supply chain management procedure, the operational data of the shipyard and suppliers are timely collected, monitored, and analyzed, and weaknesses in the supply chain are identified through performance measurement to suggest improvements. With this approach the entire shipbuilding supply chain can be continuously optimized and controlled. This approach is concluded and proofed functional with actual operation in a leading shipyard in China, Shanghai Waigaoqiao Shipbuilding Company, guided by Shipbuilding Modeling 2.0 Program of China state shipbuilding corporation.
Application of micro-computer tomography and inverse finite element analysis for characterizing the visco-hyperelastic response of bulk liver tissue using indentation
Authors: Resapu Rajeswara R. , Bradshaw Roger D. 
Published: April 2021

Abstract
In-vitro mechanical indentation experimentation is performed on bulk liver tissue of lamb to characterize its nonlinear material behaviour. The material response is characterized by a visco-hyperelastic material model by the use of 2-dimensional inverse finite element (FE) analysis. The time-dependent behaviour is characterized by the viscoelastic model represented by a 4-parameter Prony series, whereas the large deformations are modelled using the hyperelastic Neo-Hookean model. The shear response described by the initial and final shear moduli and the corresponding Prony series parameters are optimized using ANSYS with the Root Mean Square (RMS) error being the objective function. Optimized material properties are validated using experimental results obtained under different loading histories. To study the efficacy of a 2D model, a three dimensional (3D) model of the specimen is developed using Micro-CT of the specimen. The initial elastic modulus of the lamb liver obtained was found to 13.5 kPa for 5% indentation depth at a loading rate of 1 mm/sec for 1-cycle. These properties are able to predict the response at 8.33% depth and a loading rate of 5 mm/sec at multiple cycles with reasonable accuracy.

Article highlights

The visco-hyperelastic model accurately models the large displacement as well as the time-dependent behaviour of the bulk liver tissue.

Mapped meshing of the 3D FE model saves computational time and captures localized displacement in an accurate manner.

The 2D axisymmetric model while predicting the force response of the bulk tissue, cannot predict the localized deformations.
Consumer self-reported and testosterone responses to advertising of luxury goods in social context
Authors: Pozharliev Rumen , Verbeke Willem , De Angelis Matteo , Van Den Bos Ruud , Peverini Paolo 
Published: April 2021

AbstractDespite the growing demand for luxury goods, there is limited understanding about how consumers respond to luxury-goods advertising and how viewing advertising in different social contexts affects these responses. This study investigates the link between luxury goods advertising and expected utility from a biological perspective by looking at males’ hormonal responses to advertising of luxury versus non-luxury branded goods. Using traditional and consumer neuroscience methods, we collected salivary testosterone data pre- and post-ad viewing. Self-reported scores on social and quality value of the brands were compared to salivary testosterone levels from participants placed in different social conditions (Alone versus Together with another person). The results show that higher post-viewing testosterone levels were associated with higher scores on quality, but not on social value and only for branded goods viewed in the Together condition, compared to the Alone condition. These results suggest that changes in testosterone levels reflect a rewarding experience or activate social competitiveness when male consumers appraise the quality but not the social value of the advertised luxury goods and that social context modulates this effect.
Drilling the new 5G-5 branch hole at Vostok Station for collecting a replicate core of old meteoric ice
Authors: Turkeev Aleksei V. , Vasilev Nikolai I. , Lipenkov Vladimir Ya. , Bolshunov Alexey V. , Ekaykin Alexey A. , Dmitriev Andrei N. , Vasilev Dmitrii A. 
Published: April 2021

AbstractRecent studies have shown that stratigraphically disturbed meteoric ice bedded at Vostok Station between 3318 and 3539 m dates back to 1.2 Ma BP and possibly beyond. As part of the VOICE (Vostok Oldest Ice Challenge) initiative, a new deviation from parent hole 5G-1 was made at depths of 3270–3291 m in the 2018/19 austral season with the aim of obtaining a replicate core of the old ice. Sidetracking was initiated using the standard KEMS-132 electromechanical drill routinely employed for deep ice coring at Vostok, without significant changes to its initial design. Here we describe the method and operating procedures for replicate coring at a targeted depth in an existing slant hole, involving the use of a cable-suspended electromechanical drill. The design of the milling cutter head used for sidetracking is presented. The performance characteristics and the experience of drilling branch-hole 5G-5 at Vostok are described and discussed.
How exclusion from the public and private realm can negatively effect adolescents’ sense of community belonging
Authors: Barron C. 
Published: April 2021

Objectives:This paper discusses the issue of adolescent exclusion from the public (playgrounds, beaches, roads) and private realm (homes) and its link to their sense of community belonging, identity, and mental health.Methods:This research project employed a rights-based approach, and such a methodology focuses on researchwith, rather than researchabout, children and adolescents. In line with this philosophy, a wide range of qualitative participatory methodologies were employed with children and adolescents. In total, 411 children and adolescents (3–17 years) took part in consultation workshops across the county.Results:From the age of 11 onwards, children report a sense of ‘not belonging’ to recognised ‘children’s places’ such as playgrounds. Young adolescents report being actively excluded from public and private spaces. The effects of this exclusion are examined in relation to their sense of belonging, identity, and well-being.Conclusions:Exclusionary practices appear to be increasing and impacting on younger children in both private and public spaces. This forced exclusion of children and adolescents from the public and private realm challenges their sense of belonging or connectedness which is associated with low self-esteem, high levels of anxiety, depression, and suicidal ideation. A more inclusive, rights-based approach should be employed in all aspects of public realm design that actively seeks and incorporates the views of children and adolescents as well as the more dominant voice of the adult.
The Government and Pharmaceutical Innovation: Looking Back and Looking Ahead
Authors: Sampat Bhaven N. 
Published: April 2021

AbstractCurrent debates about the roles of the public and private sectors in pharmaceutical innovation have a long history. The extent to which, and ways in which, the public sector supports drug innovation has implications for assessments of the returns to public research funding, taxpayer rights in drugs, the argument the high prices are needed to support drug innovation, and the desirability of patenting publicly funded research.
Opportunities and Challenges in Translational Research: The Development of Photodynamic Therapy and Anti-Vascular Endothelial Growth Factor Drugs
Authors: Marko Christina Kaiser , Miller Joan W. 
Published: April 2021

AbstractThe development of photodynamic therapy and anti-vascular endothelial growth factor agents have revolutionized the treatment of retinal diseases, transforming the retina subspecialty by ushering in an age of pharmacological treatments for a wide range of diseases, including age-related macular degeneration (AMD).
Controls on range shifts of coastal Californian bivalves during the peak of the last interglacial and baseline predictions for today
Authors: Orzechowski Emily A. , Finnegan Seth 
Published: April 2021

AbstractAs the most recent time in Earth history when global temperatures were warmer than at present, the peak of the last interglacial (Marine Isotope Substage [MIS] 5e; ~120,000 years ago) can serve as a pre-anthropogenic baseline for a warmer near-future world. Here we use a new compilation of 22 fossil localities in California that have been reliably dated to MIS 5e to establish baseline expectations for contemporary bivalve species movements by identifying and analyzing bivalve species with “extralimital” ranges, that is, species that occupied the California region during MIS 5e but are now restricted to adjacent regions. We find that 15% of species (n= 142) found in MIS 5e localities have extralimital ranges and currently occupy warmer waters to the south of the California region. The majority of extralimital occurrences occur in paleo-embayments, suggesting that these sheltered habitats were more suitable habitats for warm-water species than exposed coasts during the MIS 5e. We further find that extralimital species now tend to occur in cooler, more seasonally productive coastal waters and to occupy more offshore islands when compared with the broader species pool immediately south of California. These findings suggest that high dispersal potential and preexisting tolerances to environmental conditions similar to California's comparatively cool and seasonally productive environments may have enabled extralimital bivalves to colonize the California region during MIS 5e.
A method for simulating risk profiles of wheat yield in data-sparse conditions
Authors: Bracho-Mujica G. , Hayman P.T. , Sadras V.O. , Ostendorf B. 
Published: April 2021

AbstractProcess-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.
Impaired executive function exacerbates neural markers of posttraumatic stress disorder
Authors: Jagger-Rickels Audreyana , Stumps Anna , Rothlein David , Park Hannah , Fortenbaugh Francesca , Zuberer Agnieszka , Fonda Jennifer R. , Fortier Catherine B. , DeGutis Joseph , Milberg William , McGlinchey Regina , Esterman Michael 
Published: April 2021

AbstractBackgroundA major obstacle in understanding and treating posttraumatic stress disorder (PTSD) is its clinical and neurobiological heterogeneity. To address this barrier, the field has become increasingly interested in identifying subtypes of PTSD based on dysfunction in neural networks alongside cognitive impairments that may underlie the development and maintenance of symptoms. The current study aimed to determine if subtypes of PTSD, based on normative-based cognitive dysfunction across multiple domains, have unique neural network signatures.MethodsIn a sample of 271 veterans (90% male) that completed both neuropsychological testing and resting-state fMRI, two complementary, whole-brain functional connectivity analyses explored the link between brain functioning, PTSD symptoms, and cognition.ResultsAt the network level, PTSD symptom severity was associated with reduced negative coupling between the limbic network (LN) and frontal-parietal control network (FPCN), driven specifically by the dorsolateral prefrontal cortex and amygdala Hubs of Dysfunction. Further, this relationship was uniquely moderated by executive function (EF). Specifically, those with PTSD and impaired EF had the strongest marker of LN-FPCN dysregulation, while those with above-average EF did not exhibit PTSD-related dysregulation of these networks.ConclusionThese results suggest that poor executive functioning, alongside LN-FPCN dysregulation, may represent a neurocognitive subtype of PTSD.
Sample size, sample size planning, and the impact of study context: systematic review and recommendations by the example of psychological depression treatment
Authors: Schuster Raphael , Kaiser Tim , Terhorst Yannik , Messner Eva Maria , Strohmeier Lucia-Maria , Laireiter Anton-Rupert 
Published: April 2021

AbstractBackgroundSample size planning (SSP) is vital for efficient studies that yield reliable outcomes. Hence, guidelines, emphasize the importance of SSP. The present study investigates the practice of SSP in current trials for depression.MethodsSeventy-eight randomized controlled trials published between 2013 and 2017 were examined. Impact of study design (e.g. number of randomized conditions) and study context (e.g. funding) on sample size was analyzed using multiple regression.ResultsOverall, sample size during pre-registration, during SSP, and in published articles was highly correlated (r's ≥ 0.887). Simultaneously, only 7–18% of explained variance related to study design (p = 0.055–0.155). This proportion increased to 30–42% by adding study context (p = 0.002–0.005). The median sample size was N = 106, with higher numbers for internet interventions (N = 181; p = 0.021) compared to face-to-face therapy. In total, 59% of studies included SSP, with 28% providing basic determinants and 8–10% providing information for comprehensible SSP. Expected effect sizes exhibited a sharp peak at d = 0.5. Depending on the definition, 10.2–20.4% implemented intense assessment to improve statistical power.ConclusionsFindings suggest that investigators achieve their determined sample size and pre-registration rates are increasing. During study planning, however, study context appears more important than study design. Study context, therefore, needs to be emphasized in the present discussion, as it can help understand the relatively stable trial numbers of the past decades. Acknowledging this situation, indications exist that digital psychiatry (e.g. Internet interventions or intense assessment) can help to mitigate the challenge of underpowered studies. The article includes a short guide for efficient study planning.
Enacting citizenship through participation in a technological society: a longitudinal three-year study among people with dementia in Sweden
Authors: Gaber Sophie Nadia , Nygård Louise , Malinowsky Camilla , Brorsson Anna , Kottorp Anders , Hedman Annicka 
Published: April 2021

AbstractThe role of Everyday Technology (ET) use is presented as subsidiary or neutral in policy for age- and dementia-friendly communities; and yet, research suggests that older people, especially those with dementia, experience increased challenges using ET in their everyday lives. Through the lens of micro-citizenship, the study aims to deepen the knowledge about how use of ET outside the home, including portable ETs, relates to participation in places visited within public space among people with dementia over time. Using a longitudinal study design, 35 people with dementia were recruited at baseline and followed over three years. Data were collected through semi-structured interviews using standardised questionnaires: the Participation in ACTivities and Places OUTside Home Questionnaire (ACT-OUT) and the Everyday Technology Use Questionnaire (ETUQ). Random intercept modelling and descriptive statistics were used to analyse the data. Throughout the three-year study, decreasing use of ET outside the home, including portable ETs, was associated with decreasing participation in places visited within public space, in a statistically significant way when controlling for age (F= 7.59,p= 0.01). The findings indicate that facilitating access and use of ET outside the home, among people with dementia, should be integral to promoting and maintaining participation in age- and dementia-friendly communities.