bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of aortic valve regurgitation after continuous-flow left ventricular assist device implantation using artificial intelligence trained on acoustic spectra
Authors: Misumi Yusuke , Miyagawa Shigeru , Yoshioka Daisuke , Kainuma Satoshi , Kawamura Takuji , Kawamura Ai , Maruyama Yuichi , Ueno Takayoshi , Toda Koichi , Asanoi Hidetsugu , Sawa Yoshiki 
Published: February 2021

AbstractSignificant aortic regurgitation (AR) is a common complication after continuous-flow left ventricular assist device (LVAD) implantation. Using machine-learning algorithms, this study was designed to examine valuable predictors obtained from LVAD sound and to provide models for identifying AR. During a 2-year follow-up period of 13 patients with Jarvik2000 LVAD, sound signals were serially obtained from the chest wall above the LVAD using an electronic stethoscope for 1 min at 40,000 Hz, and echocardiography was simultaneously performed to confirm the presence of AR. Among the 245 echocardiographic and acoustic data collected, we found 26 episodes of significant AR, which we categorized as “present”; the other 219 episodes were characterized as “none”. Wavelet (time–frequency) analysis was applied to the LVAD sound and 19 feature vectors of instantaneous spectral components were extracted. Important variables for predicting AR were searched using an iterative forward selection method. Seventy-five percent of 245 episodes were randomly assigned as training data and the remaining as test data. Supervised machine learning for predicting concomitant AR involved an ensemble classifier and tenfold stratified cross-validation. Of the 19 features, the most useful variables for predicting concomitant AR were the amplitude of the first harmonic, LVAD rotational speed during intermittent low speed (ILS), and the variation in the amplitude during normal rotation and ILS. The predictive accuracy and area under the curve were 91% and 0.73, respectively. Machine learning, trained on the time–frequency acoustic spectra, provides a novel modality for detecting concomitant AR during follow-up after LVAD.
Effects of climate change on spatiotemporal patterns of tropical cyclone tracks and their implications for coastal agriculture in Myanmar
Authors: Hirano Akira 
Published: February 2021

AbstractImportant aspects for understanding the effects of climate change on tropical cyclones (TCs) are the frequency of TCs and their tracking patterns. Coastal areas are increasingly threatened by rising sea levels and associated storm surges brought on by TCs. Rice production in Myanmar relies strongly on low-lying coastal areas. This study aims to provide insights into the effects of global warming on TCs and the implications for sustainable development in vulnerable coastal areas in Myanmar. Using TC records from the International Best Track Archive for Climate Stewardship dataset during the 30-year period from 1983 to 2012, a hot spot analysis based on Getis-Ord (Gi*) statistics was conducted to identify the spatiotemporal patterns of TC tracks along the coast of Myanmar. The results revealed notable changes in some areas along the central to southern coasts during the study period. These included a considerable increase in TC tracks (pvalue < 0.01) near the Ayeyarwady Delta coast, otherwise known as “the rice bowl” of the nation. This finding aligns with trends in published studies and reinforced the observed trends with spatial statistics. With the intensification of TCs due to global warming, such a significant increase in TC experiences near the major rice-producing coastal region raises concerns about future agricultural sustainability.
Apple Sunburn Risk Detection—A Simple Model for Agricultural Decision Making and Some Fruit Temperature Measurements
Authors: Wittich Klaus-Peter 
Published: February 2021

AbstractAs a response to strong radiative heating, the fruit temperature of apples may rise significantly above the air temperature. This may result in damage to the skin tissue and the epidermal and hypodermal cell layers. To avoid economic losses induced by sunburn symptoms on the skin, apple growers need forecasts of the fruit temperature, which will allow them to organize sun-protection measures in time.The temperatures of detached apples, which had been exposed to incident radiation and wind, were measured in order to quantify the extent of fruit heating under the climate conditions of northern Germany. On average, the daily maximum skin temperatures measured on the sunlit south side of the fruit during selected sunny and warm days were about 7 °C above the daily maximum air temperature. However, skin temperatures of more than 40 °C (the predefined warning threshold) were rarely detected, indicating that sunburn is still an uncommon phenomenon in northern Germany. Maximum apple-core temperatures were on average 4 °C higher than the maximum temperatures of ambient air.Based on energy balance principles, a simple model has been developed to predict the diurnal cycle of the sky- and ground-facing hemispherical apple temperatures. Focusing on fruit growers’ needs, daily temperature maxima of the modeled sky-facing hemisphere were compared with skin temperatures measured on the sunlit south side, resulting in a mean absolute error (MAE) of 1.7 °C. Comparison between daily maxima of total sphere temperatures and apple core temperatures provided better correlations (MAE = 0.8 °C).
Universities and start-up creation by Ph.D. graduates: the role of scientific and social capital of academic laboratories
Authors: Muscio Alessandro , Shibayama Sotaro , Ramaciotti Laura 
Published: February 2021

AbstractThis paper investigates how the characteristics of university laboratories influence the propensity of Ph.D. students to entrepreneurship, and thus, contribute to the transfer of academic knowledge to society. As determinants of Ph.D. entrepreneurship, we focus on the lab scientific and social capital as well as on the business experience that Ph.D. students acquire during their training period. The empirical exercise is based on questionnaire survey data of 5266 Ph.D. students in Italian universities in all subject areas. First, we find that 6.7% of the Ph.D. graduates engage in startup activities, and thus, Ph.D. training seems to contribute to knowledge transfer through entrepreneurship. Second, Ph.D. entrepreneurship is driven by business experience, in the forms of industry collaboration and industrially applicable research projects, during their training period. Third, the lab scientific capital is negatively associated with Ph.D. entrepreneurship, suggesting a conflict between scientific excellence and entrepreneurship, but this effect is mitigated if students acquire business experience. Fourth, the lab social capital increases the chance of startup when students have business experience. We further investigate the effects of lab environment by distinguishing between startups that are based on university research and startups that are not, finding different determinants.
When Opportunity Knocks: Confronting Theory and Empirics About Dynamics of Gender Wage Inequality
Authors: Tyrowicz Joanna , van der Velde Lucas Augusto 
Published: February 2021

AbstractWe present empirical evidence that large structural shocks are followed by changes in labor market inequality. Specifically, we study short-run fluctuations in adjusted gender wage gaps (unequal pay for equal work) following episodes of structural shocks in the labor markets, using several decades of individual data for a wide selection of transition countries. We find that for cohorts who entered the labor market after the onset of transition. Labor market shocks lead to significant declines in the gender wage gap. This decrease is driven mostly by episodes experienced among cohorts who enter the labor market during the transition. By contrast, we fail to find any significant relation for cohorts already active in the labor market at the time of transition. We provide plausible explanations based on sociological and economic theories of inequality.
Performance analysis of multi user massive MIMO hybrid beamforming systems at millimeter wave frequency bands
Authors: Dilli Ravilla 
Published: February 2021

AbstractMillimeter-wave (mmWave) and massive multi-input–multi-output (mMIMO) communications are the most key enabling technologies for next generation wireless networks to have large available spectrum and throughput. mMIMO is a promising technique for increasing the spectral efficiency of wireless networks, by deploying large antenna arrays at the base station (BS) and perform coherent transceiver processing. Implementation of mMIMO systems at mmWave frequencies resolve the issue of high path-loss by providing higher antenna gains. The motivation for this research work is that mmWave and mMIMO operations will be much more popular in 5G NR, considering the wide deployment of mMIMO in major frequency bands as per 3rd generation partnership project. In this paper, a downlink multi-user mMIMO (MU-mMIMO) hybrid beamforming communication system is designed with multiple independent data streams per user and accurate channel state information. It emphasizes the hybrid precoding at transmitter and combining at receiver of a mmWave MU-mMIMO hybrid beamforming system. Results of this research work give the tradeoff between multiple data streams per user and required number of BS antennas. It strongly recommends for higher number of parallel data streams per user in a mmWave MU-mMIMO systems to achieve higher order throughputs.
‘That’s What Art Does’: Disclosing Religious and Ethical Possibilities Through Film
Authors: Burley Mikel 
Published: February 2021

AbstractThe significance of narrative artworks as resources for, and possibly as instances of, philosophical thinking has increasingly been recognized over recent decades. Utilization of such resources in philosophy of religion has, however, been limited. Focusing on film in particular, this article develops an account of film’s importance for a ‘contemplative’ approach to philosophizing about religious ethics, an approach that prioritizes the elucidation ofpossibilities of senseover the evaluation of ‘truth claims’. TakingDead Man Walkingas a case in point, the article shows how this film facilitates an enhanced comprehension of specific concepts, most notably the concepts of faith, truth and love, as they feature within a characteristically Christian form of life.
Towards a network-based view of effective entrepreneurial ecosystems
Authors: Scott Stephanie , Hughes Mathew , Ribeiro-Soriano Domingo 
Published: February 2021

AbstractWe conceptualize entrepreneurial ecosystems as fundamentally reliant on networks and explore how and under what conditions inter-organizational networks lead an entrepreneurial ecosystem to form and evolve. It is widely accepted that entrepreneurial ecosystems possess a variety of symbiotic relationships. Research has focused considerable efforts in refining the structure and content of resources found within these networked relationships. However, merely focusing on actor-level characterizations dilutes the notion that social relationships change and are complex. There has been little conceptual treatment of the behavioral and governance factors that underpin how quality interactions composing an entrepreneurial ecosystem develop and change over time. In response, we provide a longitudinal ethnographic study examining how ecosystems are managed and evolve in their relational configurations and governance at critical junctures. Using mixed methods and data collected over 3 years, we reveal a cyclical process of relational development central to the initiation, development, and maintenance phases of a valuable entrepreneurial ecosystem. We contribute to a conceptualization of effective ecosystems as reliant on networks, we reveal the behavior and governance characteristics at play in the entrepreneurial ecosystem during each phase of its evolution.
Osteoarthritis: Insights Offered by the Study of Bone Mass Genetics
Authors: Hartley A. , Gregson C. L. , Paternoster L. , Tobias J. H. 
Published: February 2021

Abstract
Purpose of Review
This paper reviews how bone genetics has contributed to our understanding of the pathogenesis of osteoarthritis. As well as identifying specific genetic mechanisms involved in osteoporosis which also contribute to osteoarthritis, we review whether bone mineral density (BMD) plays a causal role in OA development.

Recent Findings
We examined whether those genetically predisposed to elevated BMD are at increased risk of developing OA, using our high bone mass (HBM) cohort. HBM individuals were found to have a greater prevalence of OA compared with family controls and greater development of radiographic features of OA over 8 years, with predominantly osteophytic OA. Initial Mendelian randomisation analysis provided additional support for a causal effect of increased BMD on increased OA risk. In contrast, more recent investigation estimates this relationship to be bi-directional. However, both these findings could be explained instead by shared biological pathways.

Summary
Pathways which contribute to BMD appear to play an important role in OA development, likely reflecting shared common mechanisms as opposed to a causal effect of raised BMD on OA. Studies in HBM individuals suggest this reflects an important role of mechanisms involved in bone formation in OA development; however further work is required to establish whether the same applies to more common forms of OA within the general population.
Ethical Issues in Consent for the Reuse of Data in Health Data Platforms
Authors: McKeown Alex , Mourby Miranda , Harrison Paul , Walker Sophie , Sheehan Mark , Singh Ilina 
Published: February 2021

AbstractData platforms represent a new paradigm for carrying out health research. In the platform model, datasets are pooled for remote access and analysis, so novel insights for developing better stratified and/or personalised medicine approaches can be derived from their integration. If the integration of diverse datasets enables development of more accurate risk indicators, prognostic factors, or better treatments and interventions, this obviates the need for the sharing and reuse of data; and a platform-based approach is an appropriate model for facilitating this. Platform-based approaches thus require new thinking about consent. Here we defend an approach to meeting this challenge within the data platform model, grounded in: the notion of ‘reasonable expectations’ for the reuse of data; Waldron’s account of ‘integrity’ as a heuristic for managing disagreement about the ethical permissibility of the approach; and the element of the social contract that emphasises the importance of public engagement in embedding new norms of research consistent with changing technological realities. While a social contract approach may sound appealing, however, it is incoherent in the context at hand. We defend a way forward guided by that part of the social contract which requires public approval for the proposal and argue that we have moral reasons to endorse a wider presumption of data reuse. However, we show that the relationship in question is not recognisably contractual and that the social contract approach is therefore misleading in this context. We conclude stating four requirements on which the legitimacy of our proposal rests.
Molecular Pathology of Poorly Differentiated and Anaplastic Thyroid Cancer: What Do Pathologists Need to Know?
Authors: Volante Marco , Lam Alfred K. , Papotti Mauro , Tallini Giovanni 
Published: February 2021

AbstractThe molecular characterization of poorly and anaplastic thyroid carcinomas has been greatly improved in the last years following the advent of high throughput technologies. However, with special reference to genomic data, the prevalence of reported alterations is partly affected by classification criteria. The impact of molecular pathology in these tumors is multifaceted and bears diagnostic, prognostic, and predictive implications although its use in the clinical practice is not completely assessed. Genomic profiling data claim that genetic alterations in poorly differentiated and anaplastic thyroid carcinomas include “Early” and “Late” molecular events, which are consistent with a multi-step model of progression. “Early” driver events are mostly RAS and BRAF mutations, whereas “Late” changes include above all TP53 and TERT promoter mutations, as well as dysregulation of gene involved in the cell cycle, chromatin remodeling, histone modifications, and DNA mismatch repair. Gene fusions are rare but represent relevant therapeutic targets. Epigenetic modifications are also playing a relevant role in poorly differentiated and anaplastic thyroid carcinomas, with altered regulation of either genes by methylation/deacetylation or non-coding RNAs. The biological effects of epigenetic modifications are not fully elucidated but interfere with a wide spectrum of cellular functions. From a clinical standpoint, the combination of genomic and epigenetic data shows that several molecular alterations affect druggable cellular pathways in poorly differentiated and anaplastic thyroid carcinomas, although the clinical impact of molecular typing of these tumors in terms of predictive biomarker testing is still under exploration.
SEOM clinical guidelines for the treatment of malignant pleural mesothelioma (2020)
Authors: Nadal E. , Bosch-Barrera J. , Cedrés S. , Coves J. , García-Campelo R. , Guirado M. , López-Castro R. , Ortega A. L. , Vicente D. , de Castro-Carpeño J. 
Published: February 2021

AbstractMesothelioma is a rare and aggressive tumour with dismal prognosis arising in the pleura and associated with asbestos exposure. Its incidence is on the rise worldwide. In selected patients with early-stage MPM, a maximal surgical cytoreduction in combination with additional antitumour treatment may be considered in selected patients assessed by a multidisciplinary tumor board. In patients with unresectable or advanced MPM, chemotherapy with platinum plus pemetrexed is the standard of care. Currently, no standard salvage therapy has been approved yet, but second-line chemotherapy with vinorelbine or gemcitabine is commonly used. Novel therapeutic approaches based on dual immunotherapy or chemotherapy plus immunotherapy demonstrated promising survival benefit and will probably be incorporated in the future.
Consistent Poplar Clone Ranking Based on Leaf Phenology and Temperature Along a Latitudinal and Climatic Gradient in Northern Europe
Authors: Vico Giulia , Karacic Almir , Adler Anneli , Richards Thomas , Weih Martin 
Published: February 2021

AbstractIn Northern Europe, poplars (Populus) can provide biomass for energy and material use, but most available clones were developed for lower latitudes and are unlikely to be well adapted to higher latitudes, even under warmer climates. We thus need to understand how clones respond to climatic conditions and photoperiod, and how these responses can be predicted. We answer these questions exploiting leaf phenological data ofPopulusclones, grown in six sites across the Baltic region, in Northern Europe, for 2 years with contrasting climatic conditions. Regarding the effects of climatic conditions and photoperiod, within each site, higher temperatures advanced the timing and enhanced the speed of spring and autumn phenology, but reduced the effective growing season length. Across sites, latitude affected the timing of spring and autumn phenology, the speed of spring phenology, and the effective growing season length; clone affected only the timing of phenology. Regarding the predictability of clone response to growing conditions, the growing degree day (GDD) model could not predict spring phenology, because the growing degree day threshold for a specific phenological stage was not only clone-, but also latitude- and year-specific. Yet, this GDD threshold allowed a robust ranking of clones across sites and years, thus providing a tool to determine the relative differences across clones, independently of latitude and temperature. A similar, but not as strong, pattern was observed in the timing of spring and autumn phenological stages. Hence, while prediction of spring phenology remains elusive, the ranking of clones based on observations of their phenology in a single location can provide useful indications on the clones’ relative performance under different latitudes and climates.
Computed Tomography Angiography for the Diagnosis of Coronary Artery Disease Among Patients Undergoing Transcatheter Aortic Valve Implantation
Authors: Meier David , Depierre Arnaud , Topolsky Antoine , Roguelov Christan , Dupré Marion , Rubimbura Vladimir , Eeckhout Eric , Qanadli Salah Dine , Muller Olivier , Mahendiran Thabo , Rotzinger David , Fournier Stephane 
Published: February 2021

Abstract
Background
Computed tomography angiography (CTA) is used to plan TAVI procedures. We investigated the performance of pre-TAVI CTA for excluding coronary artery disease (CAD).

Methods
In total 127 patients were included. CTA images were analyzed for the presence of ≥ 50% (significant CAD) and ≥ 70% (severe CAD) diameter stenoses in proximal coronary arteries. Results were compared with invasive coronary angiography (ICA) at vessel and patient levels. Primary endpoint was the negative predictive value (NPV) of CTA for the presence of CAD.

Results
A total of 342 vessels were analyzable. NPV of CTA was 97.5% for significant CAD and 96.3% for severe CAD. Positive predictive value and accuracy were 44.8% and 87.1% for significant CAD and 56.3% and 94.4% for severe CAD. At patient level, NPV for significant CAD was 88.6%.

Conclusion
Pre-TAVI CTA shows good performance for ruling out CAD and could be used as a gatekeeper for ICA in selected patients.

Graphical abstract
Using neural nets to predict transportation mode choice: Amsterdam network change analysis
Authors: Buijs Ruurd , Koch Thomas , Dugundji Elenna 
Published: February 2021

AbstractIn the Amsterdam metropolitan area, the opening of a new metro line along the north–south axis of the city has introduced a significant change in the region’s public transportation network. Mode choice analysis can help in assessment of changes in traveler behavior that occurred after the opening of the new metro line. As it is known that artificial neural nets excel at complex classification problems, this paper aims to investigate an approach where the traveler’s transportation mode is predicted through a neural net, trained on choice sets and user specific attributes inferred from the data. The method shows promising results. It is shown that such models perform better when it is asked to predict the choice of mode for trips which take place on the same underlying transportation network as the data with which the model is trained. This difference in performance is observed to be especially high for trips from and to certain areas that were impacted by the introduction of the north–south line, indicating possible changes in behavioural patterns, entailing interesting possible directions for further research.