bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transmembrane adaptor protein WBP1L regulates CXCR4 signalling and murine haematopoiesis
Authors: Borna Simon , Drobek Ales , Kralova Jarmila , Glatzova Daniela , Splichalova Iva , Fabisik Matej , Pokorna Jana , Skopcova Tereza , Angelisova Pavla , Kanderova Veronika , Starkova Julia , Stanek Petr , Matveichuk Orest V. , Pavliuchenko Nataliia , Kwiatkowska Katarzyna , Protty Majd B. , Tomlinson Michael G. , Alberich‐Jorda Meritxell , Korinek Vladimir , Brdicka Tomas 
Published: December 2019

AbstractWW domain binding protein 1‐like (WBP1L), also known as outcome predictor of acute leukaemia 1 (OPAL1), is a transmembrane adaptor protein, expression of which correlates with ETV6‐RUNX1 (t(12;21)(p13;q22)) translocation and favourable prognosis in childhood leukaemia. It has a broad expression pattern in haematopoietic and in non‐haematopoietic cells. However, its physiological function has been unknown. Here, we show that WBP1L negatively regulates signalling through a critical chemokine receptor CXCR4 in multiple leucocyte subsets and cell lines. We also show that WBP1L interacts with NEDD4‐family ubiquitin ligases and regulates CXCR4 ubiquitination and expression. Moreover, analysis of Wbp1l‐deficient mice revealed alterations in B cell development and enhanced efficiency of bone marrow cell transplantation. Collectively, our data show that WBP1L is a novel regulator of CXCR4 signalling and haematopoiesis.
Monetary News Shocks
Authors: BEN ZEEV NADAV , GUNN CHRISTOPHER , KHAN HASHMAT 
Published: December 2019

AbstractWe pursue an empirical strategy to identify a monetary news shock in the U.S. economy. We use a monetary policy residual, along with other variables in a vector autoregression (VAR), and identify a monetary news shock as the linear combination of reduced‐form innovations that is orthogonal to the current residual and that maximizes the sum of contributions to its forecast error variance over a finite horizon. Real GDP declines in a persistent manner after a positive monetary news shock. This contraction in economic activity is accompanied by a fall in inflation and a rapid increase in the nominal interest rate.
Electron Compton scattering and the measurement of electron momentum distributions in solids
Authors: TALMANTAITE A. , HUNT M.R.C. , MENDIS B.G. 
Published: December 2019

SummaryElectron Compton scattering is a technique that gives information on the electron momentum density of states and is used to characterize the ground state electronic structure in solids. Extracting the momentum density of states requires us to assume the so‐called ‘impulse approximation’, which is valid for large energy losses. Here, the robustness of the impulse approximation in the low energy transfer regime is tested and confirmed on amorphous carbon films. Compared to traditional Compton measurements, this provides additional benefits of more efficient data collection and a simplified way to probe valence electrons, which govern solid state bonding. However, a potential complication is the increased background from the plasmon signal. To overcome this, a novel plasmon background subtraction routine is proposed for samples that are resistant to beam damage.Lay DescriptionProperties of solids depend on their electronic structure which can be studied using electron Compton scattering technique. Here, an electron beam is used to penetrate a very thin sample. During the interaction between the electrons in the beam and electrons in the sample, the former transfer a part of their energy to the latter, resulting in a measurable energy loss of the transmitted beam. The amount of the energy transfer depends on the angle of incidence between the beam and the sample. Typically, the experiments are carried out using high tilt angles and high energy transfer; however, in this work, we show that even smaller angles of incidence are suitable, which improve the signal quality and ease data processing procedures.
Shakespeare's Ariel versus Kālidāsa's Yaksha: Revisiting a comparative study from 19th century Bengal
Authors: Sarkar Abhishek 
Published: December 2019

AbstractMy article considers how a lesser‐known Bengali periodical essay of 1884 capitalises on the canonical eminence of Shakespeare's Ariel to establish by contrast the aesthetic and ethical merits of the unnamed yaksha, a semidivine being who forms the protagonist of Kālidāsa's poem Meghadūtam (4th–5th centuries CE). Comparison between Shakespeare and Kālidāsa, the classical Sanskrit poet and dramatist, has been a commonplace of Bengali literary criticism in the 19th century, with inputs from such luminaries as Bankimchandra Chattopadhyay (1887) and Rabindranath Tagore (1907). While the poet Hemchandra Bandyopadhyay eulogised Shakespeare with the aphorism Bhārater Kālidās, jagater tumi (“You are to the world what Kālidāsa is to India”), the other acts of comparison (including the essay's in question) are not so unqualified and effusive. The essay, entitled “Ariel o Yaksha” (Ariel and the Yaksha) and written by one Bishnucharan Chattopadhyay, plays a clever game in that it starts by accepting Shakespeare as a universal favourite and enlists his character Ariel as a yardstick for assessing the yaksha but it then goes on to expose tacitly the bestiality and impetuosity of Ariel when compared with what it finds to be the higher instincts of the yaksha. The essay thus engineers a reversal of the dominant critical opinion by puncturing the aura of nobility ascribed to Ariel and countering the allegation of base sensuality often levelled against Kālidāsa's lovesick yaksha. It attempts an ethical re‐evaluation of Kālidāsa's yaksha and shows Kālidāsa to be more edifying than is often suggested by commentators. The essay gestures towards a nativist and traditionalist agenda but does not fully enunciate it or subscribe to it, thus exemplifying the ambivalence inherent in the (post)colonial modernity of 19th‐century Bengal.
Artificial intelligence, machine learning and the pediatric airway
Authors: Matava Clyde , Pankiv Evelina , Ahumada Luis , Weingarten Benjamin , Simpao Allan 
Published: December 2019

AbstractArtificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and, in particular, airway management. The ability of artificial intelligence and machine learning algorithms to recognize patterns from large volumes of complex data makes them attractive for use in pediatric anesthesia airway management. The purpose of this review is to introduce artificial intelligence, machine learning, and deep learning to the pediatric anesthesiologist. Current evidence and developments in artificial intelligence, machine learning, and deep learning relevant to pediatric airway management are presented. We critically assess the current evidence on the use of artificial intelligence and machine learning in the assessment, diagnosis, monitoring, procedure assistance, and predicting outcomes during pediatric airway management. Further, we discuss the limitations of these technologies and offer areas for focused research that may bring pediatric airway management anesthesiology into the era of artificial intelligence and machine learning.
Incremental short maximal exercise increases urinary liver‐type fatty acid‐binding protein in adults without CKD
Authors: Kosaki Keisei , Kamijo‐Ikemori Atsuko , Sugaya Takeshi , Kumamoto Shota , Tanahashi Koichiro , Kumagai Hiroshi , Kimura Kenjiro , Shibagaki Yugo , Maeda Seiji 
Published: December 2019

Exercise‐induced redistribution of tissue blood flow decreases the renal blood flow in an exercise intensity‐dependent manner. However, the acute effects of incremental short maximal exercise on renal tubular conditions remain unknown. The purpose of this study was to investigate the acute effects of incremental short maximal exercise on the urinary liver‐type fatty acid‐binding protein, which is a highly sensitive tubular biomarker that correlates excellently with peritubular capillary blood flow. A total of 116 adults (aged 24‐83 years) without chronic kidney disease performed the incremental short maximal exercise using a cycling ergometer, wherein the exercise sequence consisted of commencing with a 2‐min workout period at 20 W (as a warm‐up period) and then followed by a 10‐20 W increase every 1 minute until termination criteria were reached. Urinary samples were gathered before and immediately after the exercise to evaluate the concentrations of urinary creatinine, albumin, and liver‐type fatty acid‐binding protein. Urinary excretion levels of albumin and liver‐type fatty acid‐binding protein were significantly increased post‐exercise (P < .001 and P = .008, respectively). Furthermore, the % change in urinary liver‐type fatty acid‐binding protein levels after exercise was found to correlate independently with age, estimated glomerular filtration rate at baseline, and the % change in urinary albumin (Model R2 = 0.451, P < .001). Our findings suggest that incremental short maximal exercise may lead to acute slightly adverse effects on tubular conditions, especially in young adults or adults with lower renal function, even without chronic kidney disease.
Reliability-Based Multifidelity Optimization Using Adaptive Hybrid Learning
Authors: Li Mingyang , Wang Zequn 
Published: December 2019

Abstract
Most of the existing reliability-based design optimization (RBDO) are not capable of analyzing data from multifidelity sources to improve the confidence of optimal solution while maintaining computational efficiency. In this paper, we propose a novel reliability-based multifidelity optimization (RBMO) framework that adaptively integrates both low- and high-fidelity data for achieving reliable optimal designs. The Gaussian process (GP) modeling technique is first utilized to build a hybrid surrogate model by fusing data sources with different fidelity levels. To reduce the number of low- and high-fidelity data, an adaptive hybrid learning (AHL) algorithm is then developed to efficiently update the hybrid model. The updated hybrid surrogate model is used for reliability and sensitivity analyses in solving an RBDO problem, which provides a pseudo-optimal solution in the RBMO framework. An optimal solution that meets the reliability targets can be achieved by sequentially performing the adaptive hybrid learning at the iterative pseudo-optimal designs and solving RBDO problems. The effectiveness of the proposed framework is demonstrated through three case studies.
Novel Quantitative Risk Assessment Interface for Fixed Offshore Oil and Gas Exploration Platforms
Authors: Wang Chen , Ong Patrick , Wood Lincoln C. , Zou Fengqiu , Abdul-Rahman Hamzah 
Published: December 2019

Abstract
Light, sweet crude oils are depleting, forcing oil and gas companies to explore and operate in increasingly deeper waters, remote geographical locations, and harsher environmental conditions with higher safety risks. This paper analyzed the common misuse and errors of typical quantitative risk assessments (QRAs) during identification, assessment, approval, and project implementation stages of a project for the case of optimization of facilities and manning fixed offshore oil and gas platform, as well as the scenario of a gas leak from riser pipeline of a floating production platform. The lessons learned were then applied to design an optimized QRA process for a real case, preproject assessment for a proposed addition of a riser platform (R-A) to a fixed offshore oil and gas platform complex using individual risk per annum (IRPA) and potential loss of life (PLL) analyses. Findings reveal that applying the standard hazard and effects management process (HEMP) and as low as reasonably practicable (ALARP) guidelines and tools alone are insufficient. The application of practical lessons learned from the past oil and gas disasters using IRPA and PLL parameters has helped this research to produce an optimized QRA. The optimized QRA process is a live process which could be further improved with future lessons learned.
Burst Pressure Prediction of Cylindrical Vessels Using Artificial Neural Network
Authors: Zolfaghari Abolfazl , Izadi Moein 
Published: December 2019

Abstract
Pressure vessel plays an important role in wide range of applications to store gas or liquid substances. In order to design a pressure vessel safely, one of the main factors which has to be considered is selection of proper burst pressure perdition criterion. Due to large range of available materials in manufacturing of the vessels under different working conditions, several criteria to forecast burst pressure of the vessels have been developed and used by designers. Choosing the most proper criterion based on working condition and the material is a vital task to meet design requirements because inappropriate criterion may lead to unsafe vessel or over design. This issue makes not only pressure vessel design more complex but also maintenance planning, especially for designers who do not have enough experience, is a challenging task. Therefore, lack of a burst pressure predictor model, which is able to determine the pressure more accurately for wide range of materials and applications, has been remained unsolved. To evaluate machine learning techniques in prediction of burst pressure of pressure vessels, in this paper, a new model based on artificial neural network (ANN) has been proposed and developed. Input parameters of the model include internal and outer diameter, thickness, ultimate and yield strength; output is burst pressure. The obtained results showed that the constructed model has a good potential to be used as more applicable model compared to current models in design of pressure vessels.
Pressure Drop and Convective Heat Transfer in Different SiSiC Structures Fabricated by Indirect Additive Manufacturing
Authors: Rezaei Ehsan , Barbato Maurizio , Gianella Sandro , Ortona Alberto , Haussener Sophia 
Published: December 2019

Abstract
The microstructure of porous materials has a significant effect on their transport properties. Engineered cellular ceramics can be designed to exhibit properties at will, thanks to the advances in additive manufacturing. We investigated the heat and mass transport characteristics of SiSiC lattices produced by three-dimensional (3D) printing and replication, with three different morphologies: rotated cube (RC), Weaire–Phelan (WPh), and tetrakaidecahedron (TK) lattices, and a commercially available ceramic foam. The pressure gradients were measured experimentally for various velocities. The convective heat transfer coefficients were determined through a steady-state experimental technique in combination with numerical analysis. The numerical model was a volume-averaged model based on a local thermal nonequilibrium (LTNE) assumption of the two homogeneous phases. The results showed that for TK and WPh structures, undesirable manufacturing anomalies (specifically window clogging) led to unexpectedly higher pressure drops across the samples and increased thermal dispersion. Compared to the TK and WPh structures the manufactured RC lattice and the random foam had lower heat transfer rates but also lower pressure drops. These lower values for the RC lattice and foam are also a result of their lower specific surface areas.
Estimation of the Bubble Influence on the Imbibed Liquid Measurement During Tight Rock Continuous Imbibition
Authors: Meng Mianmo , Ge Hongkui , Shen Yinghao , Ji Wenming , Li Longlong , Yu Jiayao , Li Qinyu , Liu Tongyuan , Li Yunfeng 
Published: December 2019

Abstract
Bubble influence makes the measured liquid content in rock become less during continuous imbibition because it attaches to the surface of the tight sand increasing the buoyancy of rock in liquid. The imbibition experiment was performed to research this influence. The experiment has two parts. One is the repeated measurement of imbibition with the same sample to investigate the repeatability of the imbibition experiment under the bubble influence. The other part includes the measurement with bubble influence and without bubble influence of the same sample. The results are listed as follows. The repeated measurement of the same rock imbibition reflects a similar characteristic with the bubble influence. The water content is very close with the corresponding imbibition time. This characteristic presents that tight sand imbibition has the characteristic of repeatability, which was the basis for the other experiment. Some different characteristics appear during the measurement of the liquid content with and without bubble influence in the same sample. The liquid content without bubble influence is apparently larger than the liquid content with bubble influence. The difference between the liquid content in these two conditions is small at the end of imbibition time. It becomes larger in the middle imbibition time. The error can reach 50%. It severely influences the accurate evaluation of the imbibition capacity of tight sand. Our research contributes to the acquaintance of liquid imbibition in the formation during hydraulic fracturing and is also conducive to better measure the liquid content through the laboratory experiment.
Experimental Investigation on Airflow and Water Production in the Integrated Rooftop Solar Thermal System
Authors: Sivaram P. M. , Dinesh Kumar S. , Premalatha M. , Sivasankar T. , Arunagiri A. 
Published: December 2019

Abstract
Solar chimney is a passive renewable technology, adopted and followed widely for the application of room ventilation and power production. It requires a wide space for operation. Hence, an effective heat transfer mechanism is required within the available space to improve the performance. The solar chimney is integrated with a solar still using an external condenser to effectively utilize the energy released during the condensation of water vapor in the external condenser. The external condenser acts as an additional heat source besides the solar collector in the solar chimney. The experiments were conducted with the solar chimney of heights 1 m and 2 m, by considering the effects of an external condenser in both summer and winter. Heat transfer studies on the external condenser are also made to determine the effectiveness and the number of transfer units. The temperature and mass flow rate of vapor in the still are the influential parameters on the effectiveness of the external condenser. The condensation energy released from the external condenser increased the daily average air velocity by 14.9% and 22.4% in summer and winter, respectively. However, the overall solar chimney efficiency was improved by 37.1% in summer and 14.5% in winter for the integrated system with the chimney of height 2 m.
Modeling and Optimization of a New Configuration of Heat Pipe Parabolic Trough Collector for Solar Water Heating
Authors: Janan Moulay Ahmed , Taqi Mohamed , Chakir Hamid 
Published: December 2019

Abstract
This work reports the design, numerical modeling, and optimization of a new solar water heater using a heat pipe parabolic trough collector (HPPTC) with low concentration ratio. The heat pipe evaporator is positioned on the focal axis of the reflector, while the condenser section is completely immersed in the water cylindrical tank. The copper wire mesh wick is used as the capillary structure, and the working fluid is distillated water. The proposed model operates in transitory regime under the weather conditions of Casablanca city in Morocco. The intensity of direct solar radiation was estimated by the Kasten model assuming a total sun tracking. The finite difference method has been used to solve governing equations. Several optimization types have been investigated and proved that the optimal configuration is obtained by correctly choosing the geometrical and physical parameters of the system. The thermal efficiency for this configuration with a single heat pipe is about 68.45%. This high performance show that the incorporation of a heat pipe as absorber in a PTC may be a better alternative than conventional heating systems.
Low-Cost Fabrication of Polyvinyl Alcohol-Based Personalized Vascular Phantoms for In Vitro Hemodynamic Studies: Three Applications
Authors: Annio Giacomo , Franzetti Gaia , Bonfanti Mirko , Gallarello Antonio , Palombi Andrea , De Momi Elena , Homer-Vanniasinkam Shervanthi , Wurdemann Helge A. , Tsang Victor , Diáz-Zuccarini Vanessa , Torii Ryo , Balabani Stavroula , Burriesci Gaetano 
Published: December 2019

Abstract
Vascular phantoms mimicking human vessels are commonly used to perform in vitro hemodynamic studies for a number of bioengineering applications, such as medical device testing, clinical simulators, and medical imaging research. Simplified geometries are useful to perform parametric studies, but accurate representations of the complexity of the in vivo system are essential in several applications as personalized features have been found to play a crucial role in the management and treatment of many vascular pathologies. Despite numerous studies employing vascular phantoms produced through different manufacturing techniques, an economically viable technique, able to generate large complex patient-specific vascular anatomies, accessible to nonspecialist laboratories, still needs to be identified. In this work, a manufacturing framework to create personalized and complex phantoms with easily accessible and affordable materials and equipment is presented. In particular, three-dimensional (3D) printing with polyvinyl alcohol (PVA) is employed to create the mold, and lost core casting is performed to create the physical model. The applicability and flexibility of the proposed fabrication protocol is demonstrated through three phantom case studies—an idealized aortic arch, a patient-specific aortic arch, and a patient-specific aortic dissection model. The phantoms were successfully manufactured in a rigid silicone, a compliant silicone, and a rigid epoxy resin, respectively; using two different 3D printers and two casting techniques, without the need of specialist equipment.
Reconstruction and Analysis of Freak Waves Generated From Unidirectional Random Waves
Authors: Ma Yuxiang , Yuan Changfu , Ai Congfang , Dong Guohai 
Published: December 2019

AbstractThe generation of two freak waves in a broadband and a narrowband random series registered in the experiments of Li, J. X., Li, P. F., and Liu, S. X. (2013, “Observations of Freak Waves in Random Wave Field in 2D Experimental Wave Flume,” China Ocean Eng., 27(5), pp. 659–670) is precisely reconstructed using a fully non-hydrostatic water wave model. The simulation results indicate that even when the background spectral bandwidths are different, the evolution processes of the two freak waves are similar. Both freak waves emerge quickly during the transition from normal states to extreme events. The freak waves can persist over a long distance, i.e., approximately 5 peak wavelengths. The reconstructed time series in both the backward and forward locations at which the freak waves were recorded reveal that the largest freak wave crests were not captured in the experiment. The freak waves gradually emerged from an intense wave group. The waves developed quickly during the transition from a normal state to an extreme event. Very deep troughs were also formed in the evolution process. The two freak waves were actually generated via different spectral bandwidth processes, but the generation mechanisms of the rogue waves were similar. By analyzing the time series of the freak wave groups, the formation of the freak waves is found to result from the combined effect of the dispersive focusing, the third-order resonant wave interactions, and the higher harmonics.