bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proposals on 3D parallel edge-preserving filtration for x-ray tomographic digital images of porous medium core plugs
Authors: Arsenyev-Obraztsov S S , Volkov E A , Plusch G O 
Published: November 2019

Abstract
Precise estimation of the effective petrophysical characteristics for the oil or gas-bearing reservoir plays a vital role in production control problems. It is preferable to use nondestructive measurement methods for porosity, conductivity, geomechanical modulus, and some other parameter fields. For the estimation of anisotropic permeability tensor flows in different directions need to be simulated in the core plug digital image void space, which is very difficult (if possible) to conduct with the real rock sample. The creation of the digital core image includes three stages: construction of its internal structure based on the computed tomography (CT) sinogram, filtration, and segmentation. Routine practice is the filtration of 2D slices pack of the core plug CT image because of a lack of computational power and memory limitations. Unfortunately, this can generate a directional orientation error orthogonal to the pack of slices. The total 3D edge-preserving filtration with the usage of two approaches: modified implicit anisotropic diffusion and discrete orthogonal transforms can reduce this error. Universal code based on the MPI+OpenAcc programming paradigm was tested on different high-performance computing systems incorporating various accelerators like GPGPU and heterogeneous processors such as Sunway 26010.
Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology
Authors: Antonic M , Solesa M , Zolotukhin A B , Rakic D , Aleksic M 
Published: November 2019

Abstract
SICLO (Source of data and information; Input data; Calculation/Analytic; Logic Analysis; Output/Value Delivery) methodology is an innovative concept for smart diagnostic, reservoir/well performance optimization and estimation of remaining reserves based on the integration of Petroleum Data Management System (PDMS) and expert rules. Implementation of SICLO methodology provides the best strategy on how to produce remaining reserves most profitably. PDMS is the foundation of SICLO methodology and provides structured and verified information that follows the Well Life Cycle. Within PDMS, data are organized and structured according to clearly defined principles and rules and filtered by different levels of quality control. Structured data allows integration of production and reservoir information with real-time data to achieve the maximum level of diagnosis of system operation performance according to reservoir and well potentials and system constraints. The built-in workflows and architecture of the whole process are automated and make the task accomplishment faster. SICLO methodology integrates expert-driven knowledge and pattern recognition tools improved by data-driven, artificial intelligence, neural network, and fuzzy logic technologies to deliver adaptive solutions for identifying locations of remaining reserves, optimizing oil and gas production, and minimizing associated operational costs.
Comparative study of wax inhibitor performance for pour-point reduction of oil from Sirikit Oilfield in Thailand
Authors: Maneeintr K , Jongkittinarukorn K , Boonpramote T 
Published: November 2019

Abstract
In petroleum industries, waxy crude oil is normally found in petroleum production. Wax formation and precipitation during pipeline transport of waxy crude oils can cause several challenges, including wax deposition and flow reduction which adversely impacts pipeline performance in oil and gas production. To overcome the wax deposition problem, the small amount of chemicals like wax inhibitors can provide an effective preventative measure. One of this mechanism is to reduce the pour point temperature. In this work, oil from Sirikit Oilfield in Thailand is selected for this study. The wax inhibitors are selected and studied the performance for pour-point reduction. These chemicals are Polyalkyl methacrylate (PAMA), Poly(maleic anhydride-alt-1-octadecane) (PMAO), Polyalkyl methacrylate-co-ethylene glycol (PAMAEG) and Copolymers of maleic anhydride (CPMA) with the concentration ranging from 100 to 1000 ppm. Also, n-pentane with the concentration of 5-20 % by weight is used as a solvent for wax inhibitors. The results from this study show that n-pentane can reduce the pour point to 39.41 % compared to the original oil. Furthermore, among the polymer group, PMAO can reduce the lowest pour point to 52.82 %. In addition, the mixed solvents of polymer with n-pentane can provide relatively less effect on pour-point reduction. The mixture of n-pentane with PMAO can lower the pour point to a certain level of 54.96 % compared to the original oil. This study can be applied to use in the real field to prevent wax deposition in the pipeline transportation for oil production.
Scalability and compatibility analyses of airborne wind technology for maritime transport
Authors: Domínguez Santana D A , El-Thalji I 
Published: November 2019

Abstract
Wind energy is a source freely available in the oceans. New developments in the wind industry are towards high altitude wind turbines, known as Airborne Wind Energy Systems. The airborne wind technology is rapidly developing with several different design concepts, e.g. Skysail, Makani, KiteMill. There are mainly two types of airborne wind technology: propulsion-supporting and electricity-generating. Electricity generating airborne technology is mainly used for land-based buildings and fixed offshore structures and with small-scale airborne turbines. Thus, the applications of this technology in the maritime industry are limited to ship propulsion-support only and no scalable airborne wind turbine is used on board of a vessel. Therefore, the objective of this study is to explore the application of electricity-generating airborne turbines on the board of a ship. The exploration is mainly to determine how scalable these turbines shall be to satisfy a ship’s electricity needs and how compatible the design of these turbines can be with the ships design. . Therefore, a scalability analysis based on crosswind kite power model is applied to determine the technical requirements to scale up the existing airborne turbine to meet the electricity demand of a ship. Moreover, a compatibility analysis is applied to determine the technical interfaces and constrains between the airborne turbine configuration and the ship architecture. In this case, a commercial electricity-generating airborne turbine and a commercial floating storage unit are considered as part of the case study. The developed scalability model indicates that the traction force is the most critical design parameter to scale up a wind turbine. On the other hand, the developed compatibility model shows that there is a notorious complexity in merging airborne and ship technology due to their contexts. Consequently, this research appears to be relevant for both, the airborne technology industry and the maritime industry toward more innovative and cost-effective applications.
The effect of the intrinsic electrical matrix conductivity on the piezoelectric charge constant of piezoelectric composites
Authors: Stuber Vincent L , Mahon Tadhg R , van der Zwaag Sybrand , Groen Pim 
Published: November 2019

Abstract
Polymer-piezoceramic composites have drawn a lot of attention for sensor and energy harvesting applications. Poling such materials can be difficult due to the electric field getting mostly distributed over the low dielectric constant matrix. During this process, the electrical matrix conductivity plays a vital role. This work shows how two different polymer materials, loaded with various piezoelectric ceramic fillers, have very different poling efficiencies simply due to their intrinsic matrix conductivity. It is shown how temperature increases the matrix conductivity, and hence, increases the piezoelectric charge constant of the composites. By choosing the proper matrix material under the proper conditions, piezoelectric composites can be poled at electric fields as low as 2 kV mm−1, which is identical to that of bulk ceramic fillers. In addition, the matrix conductivity can be altered by aging the composites in a high humidity atmosphere, which can increase the piezoelectric charge constant in similar fashion. This is a simple method to increase the matrix conductivity, and hence the piezoelectric charge constant, without the need to add any conductive fillers into the composites, which increase complexity, and leads to an increased dielectric losses.
Simulation to fabrication—understanding the effect of NiAuCu alloy catalysts for controlled growth of graphene at reduced temperature
Authors: Zhan Huahan , Jiang Bin , Zietz Otto , Olson Samuel , Jiao Jun 
Published: November 2019

Abstract
It is a significant challenge to grow large-scale, high quality, monolayer graphene at low temperature for the applications in industry, especially for the complementary metal oxide semiconductor fabrication process. To overcome this difficulty, we simulated the decomposition of acetylene (C2H2) on (100) surfaces of primarily nickel (Ni) catalysts with small mol fractions of gold (Au) and copper (Cu), using a 4 × 4 × 4 periodic supercell model. Based on the calculation of the reaction energies to decompose the C-H or C≡C bonds on different catalyst surfaces, a differential energy is proposed to clearly scale the decomposition difficulties such that larger differential energy leads to easier control of the monolayer growth. It is observed that on the NiAuCu alloy surface with a mol fraction 0.0313 of both Au and Cu, the differential energy of the C-H bonds and the C≡C bond are both positive, showing an obvious modulation effect on the decomposition of C2H2 and the catalytic activites. The simulation result is consistent with the growth of uniform monolayer graphene on silicon dioxide substrate at 500°C by plasma enhanced chemical vapor deposition with C2H2 precursor and Ni alloy catalysts with 1 wt% Au and 1 wt% Cu.
Thickness effect on sensing properties of pure Cu2O thin films under sub-ppm O3 levels
Authors: Ben Nacer S , Labidi A , Touihri S , Aguir K 
Published: November 2019

Abstract
The sub-ppm ozone (O3) sensitivity of pure cuprous (Cu2O) thin films based sensors have been investigated by utilizing conductivity measurements at different temperatures varies from 150 to 200 °C. The structural and morphological properties of Cu2O sensitive layers have been investigated by the scanning electron microscope (SEM) and x-ray diffraction (XRD) respectively. The detection properties of Cu2O layers have been strongly altered by the electrode geometries and sensitive layer thickness. The sensors’ responses and structural investigations revealed that the ozone sensitivity has improved with the increase in the degree of crystallinity along the preferential direction (111). Ab-initio calculation shows that O3 adsorption mechanism could be semi- dissociative of O3 molecule on the Cu2O (111) surface, giving O2 molecule remaining in interaction with the surface and an adsorbed oxygen Oads.
Effect of Li doping on conductivity and band gap of nickel oxide thin film deposited by spin coating technique
Authors: J Arunodaya , Sahoo Trilochan 
Published: November 2019

Abstract
Nickel oxide, a stable inorganic p-type semiconductor with wide bandgap is an attractive hole transport material for the perovskite-based solar cells. Doping the nickel oxide with group-1 elements such as lithium, sodium, and potassium is found to increase the conductivity of the film. In the present work lithium doped and undoped nickel oxide thin films are coated on the glass substrate by spin coating method under ambient conditions, and the effects of doping are investigated. The structural, electrical and optical properties have been studied for different doping concentrations. X-ray diffraction confirms the formation of single-phase cubic nickel oxide. It is found that the conductivity increases nine times as the lithium concentration increases. The UV–vis spectroscopy measurement modulates the bandgap with the increase in the lithium-ion concentration.
Predicting drug-induced hepatotoxicity based on biological feature maps and diverse classification strategies
Authors: Su Ran , Wu Huichen , Liu Xinyi , Wei Leyi 
Published: November 2019

AbstractIdentifying hepatotoxicity as early as possible is significant in drug development. In this study, we developed a drug-induced hepatotoxicity prediction model taking account of both the biological context and the computational efficacy based on toxicogenomics data. Specifically, we proposed a novel gene selection algorithm considering gene’s participation, named BioCB, to choose the discriminative genes and make more efficient prediction. Then instead of using the raw gene expression levels to characterize each drug, we developed a two-dimensional biological process feature pattern map to represent each drug. Then we employed two strategies to handle the maps and identify the hepatotoxicity, the direct use of maps, named Two-dim branch, and vectorization of maps, named One-dim branch. The two strategies subsequently used the deep convolutional neural networks and LightGBM as predictors, respectively. Additionally, we here for the first time proposed a stacked vectorized gene matrix, which was more predictive than the raw gene matrix. Results validated on both in vivo and in vitro data from two public data sets, the TG-GATES and DrugMatrix, show that the proposed One-dim branch outperforms the deep framework, the Two-dim branch, and has achieved high accuracy and efficiency. The implementation of the proposed method is available at https://github.com/RanSuLab/Hepatotoxicity.
Ifosfamide nephrotoxicity in adult patients
Authors: Ensergueix Gaël , Pallet Nicolas , Joly Dominique , Levi Charlène , Chauvet Sophie , Trivin Claire , Augusto Jean-Francois , Boudet Rémi , Aboudagga Hail , Touchard Guy , Nochy Dominique , Essig Marie , Thervet Eric , Lazareth Hélène , Karras Alexandre 
Published: November 2019

AbstractBackgroundIfosfamide, a widely prescribed antineoplasic agent, is frequently associated with kidney dysfunction. Its nephrotoxicity is well documented in children, but data are lacking in adult patients.MethodsThe aim of this retrospective study was to describe the clinical, biological and histological characteristics of ifosfamide nephrotoxicity.ResultsWe report 34 patients (median age: 41 years) admitted in six French nephrology departments for kidney failure and/or tubular dysfunction. Fifteen patients (44.1%) received cisplatin as part of their chemotherapy. In 6 patients (17.7%), ifosfamide nephrotoxicity was revealed by a proximal tubular dysfunction (PTD), in 5 patients (14.4%) by an acute kidney injury (AKI), in 6 patients (17.7%) by a chronic kidney disease (CKD) and in 17 patients (49.7%) by an association of PTD and AKI. Fourteen renal biopsies (41.2%) were performed and revealed acute tubular necrosis (85.7%), vacuolation (78.6%) and nuclear atypias (71.4%) of renal epithelial cells, interstitial inflammation (71.4%) and fibrosis (57.1%). Electron microscopy showed mitochondrial enlargement and dysmorphic changes suggestive of mitochondrial toxicity. Ten patients (29.4%) progressed to Stage 5 CKD, six (17.6%) required haemodialysis and six patients died during a median follow-up period of 31 months. Risk factors for Stage 5 CKD were age and cisplatin co-administration.
A Multivariate Blind Ring Signature Scheme
Authors: Hoang Duong Dung , Susilo Willy , Tran Ha Thanh Nguyen 
Published: November 2019

Abstract
Blind signatures are an important and useful tool in designing digital cash schemes and electronic voting protocols. Ring signatures on the other hand provide the anonymity of the signer within the ring of users. In order to fit to some real-life applications, it is useful to combine both protocols to create a blind ring signature scheme, which utilizes all of their features. In this paper, we propose, for the first time, a post-quantum blind ring signature scheme. Our scheme is constructed based on multivariate public key cryptography, which is one of the main candidates for post-quantum cryptography.
Segmentectomy or lobectomy for early-stage non-small-cell lung cancer: a systematic review and meta-analysis
Authors: Winckelmans Thomas , Decaluwé Herbert , De Leyn Paul , Van Raemdonck Dirk 
Published: November 2019

Abstract

OBJECTIVES
The role of segmentectomy in early-stage non-small-cell lung cancer (NSCLC) remains a matter of debate. We performed a meta-analysis to evaluate the oncological outcomes following segmentectomy versus lobectomy for stage I, stage IA only and stage IA &lt;2 cm only.

METHODS
We systematically searched the literature for articles reporting on overall survival (OS), cancer-specific survival (CSS) or recurrence-free survival (RFS). The hazard ratios (HRs) were retrieved and pooled using an inverse variance-weighted approach.

RESULTS
Twenty-eight studies were included in the analysis. In stage I, segmentectomy was found to be inferior to lobectomy for all 3 outcomes with HR: 1.25 (P = 0.01) for OS, 1.59 (P = 0.02) for CSS and 1.40 (P &lt; 0.001) for RFS. In stage IA, the differences were significant for OS and CSS, though not for RFS with HR: 1.31 (P = 0.04), 1.56 (P = 0.02) and 1.22 (P = 0.11), respectively. In stage IA &lt;2 cm, no significant differences were found between segmentectomy and lobectomy with HR: 1.13 (P = 0.37) for OS, 1.02 (P = 0.95) for CSS and 1.24 (P = 0.11) for RFS.

CONCLUSIONS
For stages I and IA, lobectomy showed superior results whereas for tumours &lt;2 cm, our study did not find significant differences in oncological outcomes between both groups. These results suggest that segmentectomy might be a valuable alternative to lobectomy for NSCLC in tumours &lt;2 cm.
External validity of a model to predict postoperative atrial fibrillation after thoracic surgery
Authors: Smith Heather , Li Heidi , Brandts-Longtin Olivier , Yeung Ching , Maziak Donna , Gilbert Sebastien , Villeneuve Patrick James , Sundaresan Sudhir , Passman Rod , Shamji Farid , Seely Andrew J E 
Published: November 2019

Abstract

OBJECTIVES
A prediction model developed by Passman et al. stratifies patients’ risk of postoperative atrial fibrillation (POAF) after major non-cardiac thoracic surgery using 3 simple factors (sex, age and preoperative resting heart rate). The model has neither undergone external validation nor proven to be relevant in current thoracic surgery practice.

METHODS
A retrospective single-centre analysis of all patients who underwent major non-cardiac thoracic surgery (2008–2017) with prospective documentation of incidence and severity of POAF was used for external validation of Passman’s derivation sample (published in 2005 with 856 patients). The model calibration was assessed by evaluating the incidence of POAF and patients’ risk scores (0–6).

RESULTS
A total of 2054 patients were included. Among them, POAF occurred in 164 (7.9%), compared to 147 (17.2%) in Passman’s study. Differences in our sample compared to Passman’s sample included mean heart rate (75.7 vs 73.7 bpm, P &lt; 0.001), proportion of patients with hypertension (46.1 vs 29.4%, P &lt; 0.001), proportion of extensive lung resections, particularly pneumonectomy (6.1 vs 21%, P &lt; 0.001) and proportion of minimally invasive surgeries (56.6% vs 0%). The model demonstrated a positive correlation between risk scores and POAF incidence (risk score 1.2% vs 6.16%).

CONCLUSIONS
The POAF model demonstrated good calibration in our population, despite a lower overall incidence of POAF compared to the derivation study. POAF rates were higher among patients with a higher risk score and undergoing procedures with greater intrathoracic dissection. This tool may be useful in identifying patients who are at risk of POAF when undergoing major thoracic surgery and may, therefore, benefit from targeted prophylactic therapy.
Arctic tundra soil bacterial communities active at subzero temperatures detected by stable isotope probing
Authors: Gadkari Preshita S , McGuinness Lora R , Männistö Minna K , Kerkhof Lee J , Häggblom Max M 
Published: November 2019

ABSTRACT
Arctic soils store vast amounts of carbon and are subject to intense climate change. While the effects of thaw on the composition and activities of Arctic tundra microorganisms has been examined extensively, little is known about the consequences of temperature fluctuations within the subzero range in seasonally frozen or permafrost soils. This study identified tundra soil bacteria active at subzero temperatures using stable isotope probing (SIP). Soils from Kilpisjärvi, Finland, were amended with 13C-cellobiose and incubated at 0, −4 and −16°C for up to 40 weeks. 16S rRNA gene sequence analysis of 13C-labelled DNA revealed distinct subzero-active bacterial taxa. The SIP experiments demonstrated that diverse bacteria, including members of Candidatus Saccharibacteria, Melioribacteraceae, Verrucomicrobiaceae, Burkholderiaceae, Acetobacteraceae, Armatimonadaceae and Planctomycetaceae, were capable of synthesising 13C-DNA at subzero temperatures. Differences in subzero temperature optima were observed, for example, with members of Oxalobacteraceae and Rhizobiaceae found to be more active at 0°C than at −4°C or −16°C, whereas Melioribacteriaceae were active at all subzero temperatures tested. Phylogeny of 13C-labelled 16S rRNA genes from the Melioribacteriaceae, Verrucomicrobiaceae and Candidatus Saccharibacteria suggested that these taxa formed subzero-active clusters closely related to members from other cryo-environments. This study demonstrates that subzero temperatures impact active bacterial community composition and activity, which may influence biogeochemical cycles.
A multi-day and multi-band dataset for a steady-state visual-evoked potential–based brain-computer interface
Authors: Choi Ga-Young , Han Chang-Hee , Jung Young-Jin , Hwang Han-Jeong 
Published: November 2019

Abstract

Background
A steady-state visual-evoked potential (SSVEP) is a brain response to visual stimuli modulated at certain frequencies; it has been widely used in electroencephalography (EEG)-based brain–computer interface research. However, there are few published SSVEP datasets for brain–computer interface. In this study, we obtained a new SSVEP dataset based on measurements from 30 participants, performed on 2 days; our dataset complements existing SSVEP datasets: (i) multi-band SSVEP datasets are provided, and all 3 possible frequency bands (low, middle, and high) were used for SSVEP stimulation; (ii) multi-day datasets are included; and (iii) the EEG datasets include simultaneously obtained physiological measurements, such as respiration, electrocardiography, electromyography, and head motion (accelerator).

Findings
To validate our dataset, we estimated the spectral powers and classification performance for the EEG (SSVEP) datasets and created an example plot to visualize the physiological time-series data. Strong SSVEP responses were observed at stimulation frequencies, and the mean classification performance of the middle frequency band was significantly higher than the low- and high-frequency bands. Other physiological data also showed reasonable results.

Conclusions
Our multi-band, multi-day SSVEP datasets can be used to optimize stimulation frequencies because they enable simultaneous investigation of the characteristics of the SSVEPs evoked in each of the 3 frequency bands, and solve session-to-session (day-to-day) transfer problems by enabling investigation of the non-stationarity of SSVEPs measured on different days. Additionally, auxiliary physiological data can be used to explore the relationship between SSVEP characteristics and physiological conditions, providing useful information for optimizing experimental paradigms to achieve high performance.