bluuebunny/crossref_metadata_2025_split huggingface dataset:
BioMedR: an R/CRAN package for integrated data analysis pipeline in biomedical study
Authors: Dong Jie , Zhu Min-Feng , Yun Yong-Huan , Lu Ai-Ping , Hou Ting-Jun , Cao Dong-Sheng 
Published: October 2019

Abstract

Background
With the increasing development of biotechnology and information technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these resources needs to be extracted and then transformed to useful knowledge by various data mining methods. However, a main computational challenge is how to effectively represent or encode molecular objects under investigation such as chemicals, proteins, DNAs and even complicated interactions when data mining methods are employed. To further explore these complicated data, an integrated toolkit to represent different types of molecular objects and support various data mining algorithms is urgently needed.

Results
We developed a freely available R/CRAN package, called BioMedR, for molecular representations of chemicals, proteins, DNAs and pairwise samples of their interactions. The current version of BioMedR could calculate 293 molecular descriptors and 13 kinds of molecular fingerprints for small molecules, 9920 protein descriptors based on protein sequences and six types of generalized scale-based descriptors for proteochemometric modeling, more than 6000 DNA descriptors from nucleotide sequences and six types of interaction descriptors using three different combining strategies. Moreover, this package realized five similarity calculation methods and four powerful clustering algorithms as well as several useful auxiliary tools, which aims at building an integrated analysis pipeline for data acquisition, data checking, descriptor calculation and data modeling.

Conclusion
BioMedR provides a comprehensive and uniform R package to link up different representations of molecular objects with each other and will benefit cheminformatics/bioinformatics and other biomedical users. It is available at: https://CRAN.R-project.org/package=BioMedR and https://github.com/wind22zhu/BioMedR/.
Is the Eurozone disintegrating? Macroeconomic divergence, structural polarisation, trade and fragility
Authors: Gräbner Claudius , Heimberger Philipp , Kapeller Jakob , Schütz Bernhard 
Published: October 2019

Abstract
This paper analyses macroeconomic developments in the Eurozone since its inception in 1999. In doing so, we document a process of divergence and polarisation among those countries that joined the Eurozone during its first two years. We find evidence for a ‘core–periphery’ pattern among Eurozone countries, that is, however, marked by substantial heterogeneity within these two clusters. We show how the polarisation process underlying this pattern first manifested in increasing current account imbalances, before it translated unto the level of general macroeconomic development when the crisis hit. Empirically, we demonstrate how this macroeconomic divergence is tied to a ‘structural polarisation’ in terms of the sectoral composition of Eurozone countries; specifically, the emergence of export-driven growth in core countries and debt-driven growth in the Eurozone periphery can be traced back to differences in technological capabilities and firm performance. Pushing for convergence within Europe requires the implementation of industrial policies aiming at a technological catch-up process in periphery countries in combination with public investment and progressive redistributional policies to sustain adequate levels of aggregate demand in all Eurozone countries.
Hierarchical Categorization and Review of Recent Techniques on Image Forgery Detection
Authors: Vinolin V , Sucharitha M 
Published: November 2019

Abstract
Information in the form of the image conveys more details than any other form of information. Several software packages are available to manipulate the images so that the authenticity of the images is being questioned. Several image processing approaches are available to create fake images without leaving any visual clue about the forging operation. So, proper image forgery detection tools are required to detect such forgery images. Over the past few years, several research papers were published in the digital image forensics domain for detecting fake images, thus escalating the legitimacy of the images. This survey paper attempts to review the recent approaches proposed for detecting image forgery. Accordingly, several research papers related to image forgery detection are reviewed and analyzed. The taxonomy of image forgery detection techniques is presented, and the algorithms related to each technique are discussed. The comprehensive analysis is carried out based on the dataset used, software used for the implementation and the performance achievement. Besides, the research issues associated with every approach were scrutinized together with the recommendation for future work.
Multi-Swarm Cuckoo Search Algorithm with Q-Learning Model
Authors: Li Juan , Xiao Dan-dan , Zhang Ting , Liu Chun , Li Yuan-xiang , Wang Gai-ge 
Published: October 2019

Abstract
As a novel swarm intelligence optimization algorithm, cuckoo search (CS) has been successfully applied to solve diverse problems in the real world. Despite its efficiency and wide use, CS has some disadvantages, such as premature convergence, easy to fall into local optimum and poor balance between exploitation and exploration. In order to improve the optimization performance of the CS algorithm, a new CS extension with multi-swarms and Q-Learning namely MP-QL-CS is proposed. The step size strategy of the CS algorithm is that an individual fitness value is examined based on a one-step evolution effect of an individual instead of evaluating the step size from the multi-step evolution effect. In the MP-QL-CS algorithm, a step size control strategy is considered as action, which is used to examine the individual multi-stepping evolution effect and learn the individual optimal step size by calculating the Q function value. In this way, the MP-QL-CS algorithm can increase the adaptability of individual evolution, and a good balance between diversity and intensification can be achieved. Comparing the MP-QL-CS algorithm with various CS algorithms, variants of differential evolution (DE) and improved particle swarm optimization (PSO) algorithms, the results demonstrate that the MP-QL-CS algorithm is a competitive swarm algorithm.
Qualitative insights into the opioid prescribing practices of Australian GP
Authors: Prathivadi Pallavi , Barton Chris , Mazza Danielle 
Published: October 2019

Abstract

Background
Over the last three decades, Australian opioid-prescribing rates and related morbidity and mortality have dramatically increased. Opioids are frequently prescribed by general practitioners (GPs) to manage chronic non-cancer pain, despite evidence-based recommendations from the Centre for Disease Control, National Institute for Health and Care Excellence and World Health Organization widely cautioning their use. Little is known about the factors influencing the opioid prescribing decisions of Australian GPs, especially when not evidence based.

Objective
To explore the opioid prescribing knowledge, attitudes and practices of Australian GPs.

Methods
Semi-structured interviews with 20 GPs recruited from the Monash University practice-based research network in metropolitan, southeastern Melbourne. Thematic analysis was used to identify emergent themes. Data were managed using QSR NVivo. Ethics approval was granted by Monash University.

Results
Three key themes emerged. GP attitudes towards opioid use for chronic pain varied by age of patient and goals for therapy. Use of opioids for elderly patients was positively perceived. GPs were reluctant to use opioids in younger patients due to fears of addiction and difficulty weaning. GPs felt obliged to prescribe opioids recommended by specialists, even if they believed the opioids were unsafe.

Conclusion
This study identified and described the patient-centred nature of GP opioid prescribing decisions. Patient age and perceived age-related opioid harm were important factors influencing prescribing decisions. Future work should inform interventions that value GP autonomy while still encouraging a collaborative inter-speciality approach to managing chronic pain patients with opioids.
Inversion of marine controlled source electromagnetic data using a parallel non-dominated sorting genetic algorithm
Authors: Ayani Mohit , MacGregor Lucy , Mallick Subhashis 
Published: October 2019

SUMMARY
We developed a multi-objective optimization method for inverting marine controlled source electromagnetic data using a fast-non-dominated sorting genetic algorithm. Deterministic methods for inverting electromagnetic data rely on selecting weighting parameters to balance the data misfit with the model roughness and result in a single solution which do not provide means to assess the non-uniqueness associated with the inversion. Here, we propose a robust stochastic global search method that considers the objective as a two-component vector and simultaneously minimizes both components: data misfit and model roughness. By providing an estimate of the entire set of the Pareto-optimal solutions, the method allows a better assessment of non-uniqueness than deterministic methods. Since the computational expense of the method increases as the number of objectives and model parameters increase, we parallelized our algorithm to speed up the forward modelling calculations. Applying our inversion to noisy synthetic data sets generated from horizontally stratified earth models for both isotropic and anisotropic assumptions and for different measurement configurations, we demonstrate the accuracy of our method. By comparing the results of our inversion with the regularized genetic algorithm, we also demonstrate the necessity of casting this problem as a multi-objective optimization for a better assessment of uncertainty as compared to a scalar objective optimization method.
Dining With Inflammatory Bowel Disease: A Review of the Literature on Diet in the Pathogenesis and Management of IBD
Authors: Gu Phillip , Feagins Linda A 
Published: October 2019

AbstractInflammatory bowel diseases (IBDs) are chronic immune-related diseases hypothesized to be a sequela of an interplay of genetic predisposition and environmental exposures. The global incidence of IBD is increasing, and more patients are exploring diet as a means to explain and treat their IBD. In fact, many patients strongly believe diet plays a fundamental role in the onset and management of their IBD. However, a significant proportion of patients report limited nutritional education from their provider, and providers report limited nutritional resources to aid in discussions with patients. This imbalance between supply and demand likely reflects the previous paucity of available literature characterizing the influence of diet in IBD. To address this gap in knowledge, we review the available literature to characterize the role of diet in the pathogenesis, exacerbation, and treatment of IBD. We aim to provide patients and providers with resources to better understand and discuss the role of diet in IBD, with the overall goal of improving patient care and satisfaction.
Distribution and Antifungal Susceptibility of Candida Species Causing Candidemia in China: An Update From the CHIF-NET Study
Authors: Xiao Meng , Chen Sharon C-A , Kong Fanrong , Xu Xiu-Li , Yan Li , Kong Hai-Shen , Fan Xin , Hou Xin , Cheng Jing-Wei , Zhou Meng-Lan , Li Ying , Yu Shu-Ying , Huang Jing-Jing , Zhang Ge , Yang Yang , Zhang Jing-Jia , Duan Si-Meng , Kang Wei , Wang He , Xu Ying-Chun 
Published: November 2019

Abstract

Background
Candidemia is the most common, serious fungal infection and Candida antifungal resistance is a challenge. We report recent surveillance of candidemia in China.

Methods
The study encompassed 77 Chinese hospitals over 3 years. Identification of Candida species was by mass spectrometry and DNA sequencing. Antifungal susceptibility was determined using the Clinical and Laboratory Standards Institute broth microdilution method.

Results
In total, 4010 isolates were collected from candidemia patients. Although C. albicans was the most common species, non-albicans Candida species accounted for over two-thirds of isolates, predominated C. parapsilosis complex (27.1%), C. tropicalis (18.7%), and C. glabrata complex (12.0%). Most C. albicans and C. parapsilosis complex isolates were susceptible to all antifungal agents (resistance rate &lt;5%). However, there was a decrease in voriconazole susceptibility to C. glabrata sensu stricto over the 3 years and fluconazole resistance rate in C. tropicalis tripled. Amongst less common Candida species, over one-third of C. pelliculosa isolates were coresistant to fluconazole and 5-flucytocine, and &gt;56% of C. haemulonii isolates were multidrug resistance.

Conclusions
Non-albicans Candida species are the predominant cause of candidemia in China. Azole resistance is notable amongst C. tropicalis and C. glabrata. Coresistance and multidrug resistance has emerged in less common Candida species.
The Race to the Water for Offshore Renewable Energy: Assessing Cumulative and In-combination Impacts for Offshore Renewable Energy Developments
Authors: Caine Catherine Ann 
Published: October 2019

Abstract
Wind, wave and tidal energy are widely regarded as being the ‘good guys’ in energy production for their carbon neutral qualities. However, lurking in the shadow of this good reputation is the uncertainty about the impacts that this new technology will have on the marine environment. It could cause a potential conflict between carbon-neutral energy production and the protection of habitats, and the prevention of biodiversity loss. This article presents empirical data collected from three case studies in England and Scotland. This research indicates that the disjointed nature of the consenting processes for offshore renewables does not encourage full assessment of the cumulative impacts of offshore renewable developments as required by European Union environmental impact assessment legislation. The article identifies elements of the consenting processes, which fail to provide a full assessment of cumulative and in-combination impacts, and recommends changes to these processes in England and Scotland.
The impact of lymphadenectomy on prognosis and survival of clinically apparent early-stage malignant ovarian germ cell tumors
Authors: Qin Beijiao , Xu Wenyan , Li Yanfang 
Published: October 2019

Abstract

Objective
To determine the impact of lymphadenectomy (LND) on survival of clinically apparent early-stage malignant ovarian germ cell tumors (MOGCTs).

Methods
We retrospectively analyzed the survival of patients who were diagnosed with the three most common histopathology types of malignant ovarian germ cell tumors (yolk sac tumor, dysgerminoma and immature teratoma) and with clinical stage I and II disease, and treated at Sun Yat-sen University Cancer Center between 1 January 1970 and 30 September 2018.

Results
There were 227 stage I, 28 stage II and one stage IIIA cases after surgery. One hundred and twenty-six patients underwent lymphadenectomy and 130 did not. Only one lymph node metastasis (0.8%) was found in the lymphadenectomy group. Two hundred and twenty-four out of 256 patients (87.5%) received postoperative chemotherapy. There were five relapses (4.0%) in the lymphadenectomy group and four (3.1%) in the non-lymphadenectomy group. Median follow-up was 68 months (range, 1–388). The 10-year disease-free survival rate in the lymphadenectomy group and non-lymphadenectomy group were 88.2 and 96.4%, respectively (P = 0.412); the 10-year overall survival rate in the two groups were 95.7 and 98.2%; respectively (P = 0.798). The results showed that lymphadenectomy did not improve patient survival.

Conclusions
Lymphadenectomy may have little impact on survival in patients with clinically apparent early-stage malignant ovarian germ cell tumors and may be omitted in the surgical treatment.
Design of a Repellent Against Aedes aegypti (Diptera: Culicidae) Using in silico Simulations With AaegOBP1 Protein
Authors: Portilla-Pulido Johan Sebastián , Castillo-Morales Ruth Mariela , Barón-Rodríguez Mario Alberto , Duque Jonny Edward , Mendez-Sanchez Stelia Carolina 
Published: October 2019

Abstract
Skin irritation has been reported to be the main adverse effect of excessive use of N,N-diethyl-m-toluamide (DEET) and ethyl 3-acetyl(butyl)amino (IR3535) commercial repellents. Therefore, there is an interest in alternatives of natural origin such as essential oils (EOs) and major compounds, which have repellent effects but have no contraindications. The main purpose of the present study was to identify the repellent effect of selected terpenes on Aedes aegypti Linnaeus, 1762 (Diptera: Culicidae) by in silico analysis based on their affinity with the odorant protein AaegOBP1. The protein-metabolite interactions in 20 terpenes were analyzed using the SwissDock tool. Terpenes presenting the highest affinity compared with commercial repellents were selected to evaluate repellent activity at concentrations 0.1, 10, and 25% against Ae. aegypti. Different periods (0–2, 2–15, 15–60 min) were evaluated with DEET as a positive control. The toxicity of terpenes was verified through Osiris and Molinspiration Cheminformatics Software, and cytotoxicity assays in Vero and HepaRG cells were performed using the MTT method. Two formulations were prepared with polyethylene glycol to evaluate skin long-lasting in vivo assay. The results showed four terpenes: geranyl acetate, nerolidol, α-bisabolol, and nerol, with affinity to AaegOBP1 comparable with DEET and IR3535. Geranyl acetate, nerolidol, and their mixtures showed no cytotoxicity and protection percentages close to 100% during the test at concentrations 10 and 25%. Long-lasting assays with geranyl acetate and nerolidol formulate showed 3 h as maximum protection time with 100% protection percentage. These metabolites and their mixtures are candidates to repellent formulations with times and protection percentages similar to DEET.
HIV RNA, CD4+ Percentage, and Risk of Hepatocellular Carcinoma by Cirrhosis Status
Authors: Torgersen Jessie , Kallan Michael J , Carbonari Dena M , Park Lesley S , Mehta Rajni L , D’Addeo Kathryn , Tate Janet P , Lim Joseph K , Goetz Matthew Bidwell , Rodriguez-Barradas Maria C , Gibert Cynthia L , Bräu Norbert , Brown Sheldon T , Roy Jason A , Taddei Tamar H , Justice Amy C , Lo Re Vincent 
Published: October 2019

Abstract

Background
Despite increasing incidence of hepatocellular carcinoma (HCC) among HIV-infected patients, it remains unclear if HIV-related factors contribute to development of HCC. We examined if higher or prolonged HIV viremia and lower CD4+ cell percentage were associated with HCC.

Methods
We conducted a cohort study of HIV-infected individuals who had HIV RNA, CD4+, and CD8+ cell counts and percentages assessed in the Veterans Aging Cohort Study (1999–2015). HCC was ascertained using Veterans Health Administration cancer registries and electronic records. Cox regression was used to determine hazard ratios (HR, 95% confidence interval [CI]) of HCC associated with higher current HIV RNA, longer duration of detectable HIV viremia (≥500 copies/mL), and current CD4+ cell percentage less than 14%, adjusting for traditional HCC risk factors. Analyses were stratified by previously validated diagnoses of cirrhosis prior to start of follow-up.

Results
Among 35 659 HIV-infected patients, 302 (0.8%) developed HCC over 281 441 person-years (incidence rate = 107.3 per 100 000 person-years). Among patients without baseline cirrhosis, higher HIV RNA (HR = 1.25, 95% CI = 1.12 to 1.40, per 1.0 log10 copies/mL) and 12 or more months of detectable HIV (HR = 1.47, 95% CI = 1.02 to 2.11) were independently associated with higher risk of HCC. CD4+ percentage less than 14% was not associated with HCC in any model. Hepatitis C coinfection was a statistically significant predictor of HCC regardless of baseline cirrhosis status.

Conclusion
Among HIV-infected patients without baseline cirrhosis, higher HIV RNA and longer duration of HIV viremia increased risk of HCC, independent of traditional HCC risk factors. This is the strongest evidence to date that HIV viremia contributes to risk of HCC in this group.
(-)-Loliolide, the most ubiquitous lactone, is involved in barnyardgrass-induced rice allelopathy
Authors: Li Lei-Lei , Zhao Huan-Huan , Kong Chui-Hua 
Published: November 2019

Abstract
Neighbor detection and allelochemical response are important mediators in plant-plant interactions. Despite increasing knowledge of plant allelochemicals in response to the presence of competitors involved in the neighbor-derived signaling chemicals, less is known about which signaling chemicals are responsible for the neighbor-induced allelochemical response. Here, we experimentally demonstrated (-)-loliolide, a carotenoid metabolite, as a signaling chemical in barnyardgrass-rice allelopathic interactions. The production of rice allelochemicals momilactone B and tricin was increased in the presence of five biotypes of barnyardgrass. (-)-Loliolide was found in all biotypes of barnyardgrass and their root exudates and rhizosphere soils. There were significant positive relationships between rice allelechemicals and (-)-loliolide concentrations across biotypes of barnyardgrass. Furthermore, (-)-loliolide elicited the production of momilactone B and tricin. Comparative transcriptome analysis showed regulation of (-)-loliolide on diterpenoid and flavonoid biosynthesis pathway. The expression of key genes involved in the biosynthesis of momilactone B (CPS4, KSL4 and MAS) and tricin (CYP75B3 and CYP75B4) was up-regulated by (-)-loliolide. These findings suggest that (-)-loliolide as a signaling chemical participates in barnyardgrass-rice allelopathic interactions. Through the signaling chemical, allelopathic rice plants can detect competing barnyardgrass and respond by increasing allelochemical levels to provide an advantage for their own growth.
Determining the origin of the building blocks of the Ice Giants based on analogue measurements from comets
Authors: Mandt K E , Mousis O , Treat S 
Published: November 2019

ABSTRACT
The abundances of the heavy elements and isotopic ratios in the present atmospheres of the giant planets can be used to trace the composition of volatiles that were present in the icy solid material that contributed to their formation. The first definitive measurements of noble gas abundances and isotope ratios at comet 67P/Churyumov–Gerasimenko (67P/C–G) were recently published by Marty et al. (2017) and Rubin et al. (2018, 2019). The implications of these abundances for the formation conditions of the 67P/C–G building blocks were then evaluated by Mousis et al. (2018a). We add here an analysis of the implications of these results for understanding the formation conditions of the building blocks of the Ice Giants and discuss how future measurements of Ice Giant atmospheric composition can be interpreted. We first evaluate the best approach for comparing comet observations with giant planet composition, and then determine what would be the current composition of the Ice Giant atmospheres based on four potential sources for their building blocks. We provide four scenarios for the origin of the Ice Giants building blocks based on four primary constraints for building block composition: (1) the bulk abundance of carbon relative to nitrogen, (2) noble gas abundances relative to carbon and nitrogen, (3) abundance ratios Kr/Ar and Xe/Ar, and (4) Xe isotopic ratios. In situ measurements of these quantities by a Galileo-like entry probe in the atmosphere(s) of Uranus and/or Neptune should place important constraints on the formation conditions of the Ice Giants.