bluuebunny/crossref_metadata_2025_split huggingface dataset:
Failures of once‐a‐week trimethoprim‐sulfamethoxazole prophylaxis in children undergoing allogeneic hematopoietic stem cell transplant
Authors: Castagnola Elio , Mesini Alessio , Saffioti Carolina , Moscatelli Andrea , Pierri Filomena , Giardino Stefano , Faraci Maura 
Published: December 2019

AbstractOnce‐a‐week cotrimoxazole is an effective prophylaxis for pneumocystosis during antineoplastic chemotherapy or autologous stem cell transplant. Following allogeneic stem cell transplant, this schedule is at risk of pneumocystosis or neurotoxoplasmosis, as demonstrated by these case reports. Therefore, a 3‐times‐a‐week schedule must be adopted in these patients.
Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops
Authors: Price Elliott J. , Drapal Margit , Perez‐Fons Laura , Amah Delphine , Bhattacharjee Ranjana , Heider Bettina , Rouard Mathieu , Swennen Rony , Becerra Lopez‐Lavalle Luis Augusto , Fraser Paul D. 
Published: December 2019

SummaryRoots, tubers, and bananas (RTB) are vital staples for food security in the world's poorest nations. A major constraint to current RTB breeding programmes is limited knowledge on the available diversity due to lack of efficient germplasm characterization and structure. In recent years large‐scale efforts have begun to elucidate the genetic and phenotypic diversity of germplasm collections and populations and, yet, biochemical measurements have often been overlooked despite metabolite composition being directly associated with agronomic and consumer traits. Here we present a compound database and concentration range for metabolites detected in the major RTB crops: banana (Musa spp.), cassava (Manihot esculenta), potato (Solanum tuberosum), sweet potato (Ipomoea batatas), and yam (Dioscorea spp.), following metabolomics‐based diversity screening of global collections held within the CGIAR institutes. The dataset including 711 chemical features provides a valuable resource regarding the comparative biochemical composition of each RTB crop and highlights the potential diversity available for incorporation into crop improvement programmes. Particularly, the tropical crops cassava, sweet potato and banana displayed more complex compositional metabolite profiles with representations of up to 22 chemical classes (unknowns excluded) than that of potato, for which only metabolites from 10 chemical classes were detected. Additionally, over 20% of biochemical signatures remained unidentified for every crop analyzed. Integration of metabolomics with the on‐going genomic and phenotypic studies will enhance ’omics‐wide associations of molecular signatures with agronomic and consumer traits via easily quantifiable biochemical markers to aid gene discovery and functional characterization.
Everywhere at Once
Authors: Abrams Michael 
Published: December 2019

Abstract
Some commuters discovered lightweight electric scooters were the perfect solution for commuting. For others, the things were an unasked-for nuisance, blocking sidewalks when parked and barreling down on pedestrians when in motion. To better serve the customers and disarm the naysayers, the shared scooter will have to change. How companies deploy scooters, how cities incorporate them, and how manufacturers make them, all need better engineering. This article delves deeper into what needs to be done to make electric scooters viable.
Day-Ahead Wind Power Forecast Through High-Resolution Mesoscale Model: Local Computational Fluid Dynamics Versus Artificial Neural Network Downscaling
Authors: Mana Matteo , Astolfi Davide , Castellani Francesco , Meißner Cathérine 
Published: December 2019

Abstract
The importance of accurately forecasting the power production of wind farms is boosting the development of meteorological models and their processing. This work is a discussion of different forecast configurations for predicting the day ahead production of a wind farm sited in a moderately complex terrain. The numerical weather prediction (NWP) model MetCoOp Ensemble Prediction System with 2.5 km resolution focusing on the wind farm area is dynamically downscaled by the computational fluid model (CFD) model WindSim. The transfer of the NWP model to the CFD model can be done using NWP results from various heights above ground and using all or parts of the nodes of the NWP model within the wind farm area. In this work, many different forecasting configurations are validated and the impact on the forecast performance is discussed. The NWP-CFD downscaling results are compared to a day ahead forecast obtained through ANN methods and to the observed production. The main result of this work is that a deterministic downscaling method like CFD simulations can perform as good or better than statistical approaches when using high-resolution NWP models and more NWP model data.
Calibration and Validation Framework for Selective Laser Melting Process Based on Multi-Fidelity Models and Limited Experiment Data
Authors: Olleak Alaa , Xi Zhimin 
Published: December 2019

Abstract
There are significant quality and reliability problems for components/products made by additive manufacturing (AM) due to various reasons. Selective laser melting (SLM) process is one of the popular AM techniques and it suffers from low quality and reliability issue as well. Among many reasons, the lack of accurate and efficient models to simulate the SLM process could be the most important one because reliability and quality quantification rely on accurate models; otherwise, a large number of experiments should be conducted for reliability and quality assurance. To date, modeling techniques for the SLM process are either computationally expensive based on finite element (FE) modeling or economically expensive requiring a significant amount of experiment data for data-driven modeling. This paper proposes the integration of FE and data-driven modeling with systematic calibration and validation framework for the SLM process based on limited experiment data. Multi-fidelity models are the FE model for the SLM process and a machine learning model constructed based on the FE model instead of real experiment data. The machine learning model, after incorporation of the learned physics from the FE model, is then further improved based on limited real experiment data through the calibration and validation framework. The proposed work enables the development of highly efficient and accurate models for melt pool prediction of the SLM process under various configurations. The effectiveness of the framework is demonstrated by real experiment data under 14 different printing configurations.
A Vision-Based Referencing Procedure for Cable-Driven Parallel Manipulators
Authors: Zavatta Michele , Chianura Mattia , Pott Andreas , Carricato Marco 
Published: December 2019

Abstract
In the last three decades, cable-driven parallel robots (CDPRs) have captured a growing attention in the robotics field. Indeed, they promise to bring automation in fields where it is not affirmed yet, granting ease of scaling and reconfigurability. For large-workspace cable robots, accuracy is an important issue. In this paper, a look-and-move procedure is proposed, based on a wireless camera, to refer the coordinate frame of the CDPR platform to another known coordinate frame. Two sample cases are studied and presented. In the first, the proposed vision-based system is employed to let the platform precisely attain its home position. In the second, the platform is referenced to an external coordinate frame, in order to accurately accomplish an assigned task. For both cases, experiments are successfully carried out.
Multiscale petrographic heterogeneity and their implications for the nanoporous system of the Wufeng-Longmaxi shales in Jiaoshiba area, Southeast China: Response to depositional-diagenetic process
Authors: Wang Yuxuan , Xu Shang , Hao Fang , Zhang Baiqiao , Shu Zhiguo , Gou Qiyang , Lu Yangbo , Cong Fuyun 
Published: December 2019

Abstract
The organic matter-rich shales in Wufeng-Longmaxi Formation, Jiaoshiba area, Southeast China, are showing a notable petrographic heterogeneity characteristic within the isochronous stratigraphic framework, which lead to vast differences in the mineral composition and organic matter abundance in the adjacent sections of the shale reservoir. The studied shale has been divided into three systems tracts: a transgressive systems tract (TST), an early highstand systems tract (EHST), and a late highstand systems tract (LHST). Multiple-scale petrographic observation and detailed mineralogical and geochemical analyses were combined to investigate the manifestation, origin, and the ways by which the shale heterogeneity is affected. The results indicate that polytropic depositional environments lead to different components in sediment. Subsequently, these differences among shale sections become more apparent through different diagenetic pathways. During the deposition of the section TST, the Hirnantian glaciation and regional volcanism played a crucial role, contributing to the abundant accumulation of fine-grained intrabasinal silica and organic matter. In diagenesis stage, authigenic quartz aggregates derived from siliceous organisms are formed. They filled in primary interparticle pores, forming a rigid particle-bracing structure that provide effective resistivity against the compaction and spaces for organic matter migration and occlusion. Finally, the migrated organic matter left plenty of newly created pore spaces that constituted a great portion of the total porosity of shale reservoir. The depositional process of section EHST is strongly influenced by contour current, which brings about more extrabasinal influx and impoverishes organic matter. In diagenesis stage, the rigid particle-bracing structure could only be preserved in limited areas, since insufficient siliceous supply could not produce enough authigenic quartz. Primary interparticle pores are significantly reduced owing to compaction, leaving less space for later organic matter migration and occlusion. As a result, the total porosity of shale reservoir declines in this section. In a rapid tectonic-uplifting background, the deposition of section LHST is associated with a rapid increase in terrigenous clay minerals, which further dilutes organic matter. Ductile clay experienced strong compaction and then occupies most of the primary interparticle space. Rigid particles are wrapped by a large number of clays, which has destroyed the particle-bracing structure. As a result, the nanoporous system in the shale could not be well preserved.
Redistribution of germanium during dynamic recrystallization of sphalerite
Authors: Cugerone Alexandre , Cenki-Tok Bénédicte , Oliot Emilien , Muñoz Manuel , Barou Fabrice , Motto-Ros Vincent , Le Goff Elisabeth 
Published: December 2019

Abstract
Rare metals are essential to the development of the “green” technologies that are at the core of low-carbon societies. In nature, these metals are frequently present in trace amounts scattered in base metal ore deposits, but the physico-chemical processes that are responsible for their concentration into strategic minerals are still poorly understood. Based on laser-induced breakdown spectroscopy (LIBS), coupled with electron backscattered diffraction (EBSD) analysis, this study shows that plastic deformation and subsequent syntectonic recrystallization of sphalerite (zinc sulfide, ZnS) led to the spatial redistribution of germanium (Ge): from a background level of a few hundreds of parts per million in undeformed primary sphalerite to tens of weight-percent in neocrystallized Ge minerals. During dynamic recrystallization, Ge is likely released from the crystal lattice of parent sphalerite and subsequently concentrated in Ge minerals, leaving behind a Ge-depleted, recrystallized sphalerite matrix. Identifying how rare metals concentrate through deformation and syntectonic recrystallization at the mineral scale is essential to understand the spatial redistribution and localization at the deposit scale. This study highlights the importance of coupling in situ chemical mapping analysis with macro- and microstructural characterization when targeting rare metals in deformed ore.
Effects of feeding strategy and duration of the dry period on the rumen microbiota of dairy cows
Authors: Khazanehei H. , Li S. , Khafipour E. , Plaizier J.C. 
Published: December 2019

The composition of rumen microbiota during late gestation and early lactation was compared between cows receiving a close-up diet (1.43 Mcal net energy of lactation (NEl) kg−1 dry matter (DM)) throughout a 40 d dry period (SHORT) and cows receiving a far-off diet (1.28 Mcal NEl kg−1 DM) as well as the close-up diet (as above) for 39 and 21 d, respectively, during a conventional 60 d dry period (CONV). Rumen fluid was collected at weeks −2, −1, +1, +2, and +7 relative to calving. Extracted DNA was analyzed for taxonomic composition of the rumen microbiome using MiSeq Illumina sequencing of the V4 region of the 16S rRNA gene. At week +1, this composition differed (P < 0.05) between treatments. In cows under the CONV treatment, this composition only differed (P < 0.05) between weeks −1 and +1. For SHORT cows, this composition tended to differ between weeks +1 and +2 (P = 0.09) as well as between weeks +2 and +7 (P < 0.03). The change of the taxonomic composition of the rumen microbiota after calving, mainly consisting of increases in the abundance of Firmicutes and decreases in that of Bacteroidites, was comparatively slower and less favourable under the SHORT treatment. This may have been due to more excessive grain intake before calving of cows on the latter treatment.
Preferences for Return of Genetic Results Among Participants in the Jackson Heart Study and Framingham Heart Study
Authors: Joffe Steven , Sellers Deborah E. , Ekunwe Lynette , Antoine-Lavigne Donna , McGraw Sarah , Levy Daniel , Splansky Greta Lee 
Published: December 2019

Background:
Surveys suggest that most research participants desire access to secondary (incidental) genomic findings. However, few studies clarify whether preferences vary by the nature of the finding.

Methods:
We surveyed members of the JHS (Jackson Heart Study, n=960), the FHS (Framingham Heart Study; n=955), and African American members of the FHS Omni cohort (n=160) who had consented to genomic studies. Each factorial survey included 3 vignettes, randomly selected from a set of 64, that described a secondary genomic result. Vignettes varied systematically by 5 factors identified by expert panels as salient: phenotype severity, actionability (preventability), reproductive significance, and relative and absolute risk of the phenotype. Respondents indicated whether they would want to receive the result. Data were analyzed separately by cohort using generalized linear mixed models.

Results:
Response rates ranged from 67% to 73%. Across vignettes, 88% to 92% of respondents would definitely or probably want to learn the result. In multivariate analyses among JHS respondents, desire for results was associated with positive attitudes towards genetic testing, lower education, higher subjective numeracy, and younger age, but not with any of the 5 factors. Among FHS respondents, desire for results was associated with higher absolute risk, preventability, reproductive risk, and positive attitudes towards genetic testing. Among FHS Omni respondents, desire for results was associated with positive attitudes towards genetic testing and younger age.

Conclusions:
Most genetic research participants desire return of secondary genetic results. Several factors identified by expert panels as salient are associated with preferences among FHS, but not JHS or FHS Omni, participants.
Élite Folktales: Munes-nāma, Ketāb-e dāstān, and Their Audiences
Authors: Askari Nasrin 
Published: December 2019

Abstract
Drawing on evidence from the texts, illustrations, and contexts of production of two Persian manuscripts, the present paper points to the role of female élites as both audiences and protagonists of the two works, and argues that both works functioned as advisory literature for the female élites of medieval Persian royal courts. It also draws attention to the strong connection of both works to the two realms of élite and folk literature and calls for a designation and defining criteria for a body of works that occupies the zone between the high and low ends of the wide spectrum of Persian literature.
The Donation of the Extremely Wealthy in China
Authors: Zhang (张丛丛) Congcong , Huang (黄建忠) Chien-Chung 
Published: December 2019

Abstract
As trends in increasing private wealth around the world continue, understanding the charitable contributions of the extremely wealthy is important. Using the Forbes China Rich Lists and the Forbes China Charity Lists from 2013 to 2017, this study examines the social and economic factors present in the donations of the extremely wealthy whose net worth equals at least 649 million (all amounts expressed in U.S. dollars unless otherwise noted) in China. The results indicate that net worth, social status, political connection, and source of wealth are important factors in these donations. Specifically, extremely wealthy individuals with high net worth, social status, and political connections are more likely to be and more frequently on the Charity Lists than extremely wealthy individuals without above characteristics, particularly those in the real estate industry. However, the real estate industry’s effect on the dollar amount of donations is not significant. In contrast, the extremely wealthy individuals in professional, scientific, and technical areas donated significantly more money than their counterparts in other areas.
A temporal visualization of chronic obstructive pulmonary disease progression using deep learning and unstructured clinical notes
Authors: Tang Chunlei , Plasek Joseph M. , Zhang Haohan , Kang Min-Jeoung , Sheng Haokai , Xiong Yun , Bates David W. , Zhou Li 
Published: December 2019

Abstract
Background
Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients with COPD and to generate a temporal visualization that describes signs and symptoms during different stages of COPD progression.

Methods
We present a two-step approach for visualizing COPD progression at the level of unstructured clinical notes. We included 15,500 COPD patients who both received care within Partners Healthcare’s network and died between 2011 and 2017. We first propose a four-layer deep learning model that utilizes a specially configured recurrent neural network to capture irregular time lapse segments. Using those irregular time lapse segments, we created a temporal visualization (the COPD atlas) to demonstrate COPD progression, which consisted of representative sentences at each time window prior to death based on a fraction of theme words produced by a latent Dirichlet allocation model. We evaluated our approach on an annotated corpus of COPD patients’ unstructured pulmonary, radiology, and cardiology notes.

Results
Experiments compared to the baselines showed that our proposed approach improved interpretability as well as the accuracy of estimating COPD progression.

Conclusions
Our experiments demonstrated that the proposed deep-learning approach to handling temporal variation in COPD progression is feasible and can be used to generate a graphical representation of disease progression using information extracted from clinical notes.
Evolving trends in infective endocarditis in a developing country: a consequence of medical progress?
Authors: Sunil Mohamed , Hieu Huynh Quoc , Arjan Singh Ramesh Singh , Ponnampalavanar Sasheela , Siew Kelvin S. W. , Loch Alexander 
Published: December 2019

AbstractBackgroundStaphylococcus has replaced streptococcus as the most common cause of infective endocarditis (IE) in developed health care systems. The trend in developing countries is less clear.AimTo examine the epidemiological trends of infective endocarditis in a developing nation.MethodsSingle-centre, retrospective study of patients admitted with IE to a tertiary hospital in Malaysia over a 12-year period.ResultsThe analysis included 182 patients (n = 153 Duke’s definite IE, n = 29 possible IE). The mean age was 51 years. Rheumatic heart disease was present in 42%, while 7.6% were immunocompromised. IE affected native valves in 171 (94%) cases. Health-care associated IE (HCAIE) was recorded in 68 (37.4%). IE admission rates increased from 25/100,000 admissions (2012) to 59/100,000 admissions (2017). At least one major complication on admission was detected in 59 (32.4%) patients. Left-sided IE was more common than right-sided IE [n = 159 (87.4%) vs. n = 18 (9.9%)]. Pathogens identified by blood culture were staphylococcus group [n = 58 (40.8%)], streptococcus group [n = 51 (35.9%)] andEnterococcusspecies [n = 13 (9.2%)]. staphylococcus infection was highest in the HCAIE group. In-hospital death occurred in 65 (35.7%) patients. In-hospital surgery was performed for 36 (19.8%) patients. At least one complication was documented in 163 (85.7%).ConclusionStaphylococcus is the new etiologic champion, reflecting the transition of the healthcare system. Streptococcus is still an important culprit organism. The incidence rate of IE appears to be increasing. The rate of patients with underlying rheumatic heart disease is still high.
A review on strategies to optimize metabolic stages of anaerobic digestion of municipal solid wastes towards enhanced resources recovery
Authors: Richard Edwin N. , Hilonga Askwar , Machunda Revocatus L. , Njau Karoli N. 
Published: December 2019

AbstractRecently, there are increased efforts by municipals and researchers to investigate the potential of utilizing municipal solid wastes (MSW) for resources recovery. In many parts of developing countries, MSW is mostly collected for disposal with little emphasis on resources recovery. However, the MSW has high organic and moisture contents, and are suitable substrates for anaerobic digestion (AD) process to recover biogas for energy and digestate which can be used as fertilizers or for soil amendments. Resources recovery from the AD process consists of four metabolic stages; hydrolysis, acidogenesis, acetogenesis, and methanogenesis. These metabolic stages can be affected by several factors such as the nature of substrates, accumulation of volatile fatty acids, and ammonia inhibition. In this review, different optimization strategies towards resources recoveries such as pre-treatment, co-digestion, trace elements supplementation, optimization of key parameters and the use of granular activated carbon are discussed. The review reveals that the currently employed optimization strategies fall short in several ways and proposes the need for improvements.