bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovation as a driver of eco‐innovation in the firm: An approach from the dynamic capabilities theory
Authors: Arranz Nieves , Arroyabe Marta , Li Jun , Fernandez de Arroyabe Juan Carlos 
Published: January 2020

AbstractThe aim of this study is to investigate how innovative capabilities of the firm affect eco‐innovation from a dynamic capability lens. We build on OECD research to conceptualise eco‐innovation as the capacity with which firms modify, redesign, and create products, processes, procedures, and organisations in order to reduce environmental impact. We propose and test the temporal and relational properties of eco‐innovation as a capability. We demonstrate that eco‐innovation possesses two properties of innovative capabilities, namely, persistence over time and interrelation with other innovations. We thus shed new light on the mechanism through which firms engage in eco‐innovation. We also provide empirical evidence to the debate on the relationship between the “normal” innovation (technological or nontechnological) and eco‐innovation. We show that eco‐innovation and innovation are interrelated both simultaneously and sequentially. Moreover, we show that innovation capabilities and eco‐innovation are not only related, but they also have a complementary nature, which facilitates the development of future eco‐innovation.
How to Illuminate the Druggable Genome Using Pharos
Authors: Sheils Timothy , Mathias Stephen L. , Siramshetty Vishal B. , Bocci Giovanni , Bologa Cristian G. , Yang Jeremy J. , Waller Anna , Southall Noel , Nguyen Dac‐Trung , Oprea Tudor I. 
Published: January 2020

AbstractPharos is an integrated web‐based informatics platform for the analysis of data aggregated by the Illuminating the Druggable Genome (IDG) Knowledge Management Center, an NIH Common Fund initiative. The current version of Pharos (as of October 2019) spans 20,244 proteins in the human proteome, 19,880 disease and phenotype associations, and 226,829 ChEMBL compounds. This resource not only collates and analyzes data from over 60 high‐quality resources to generate these types, but also uses text indexing to find less apparent connections between targets, and has recently begun to collaborate with institutions that generate data and resources. Proteins are ranked according to a knowledge‐based classification system, which can help researchers to identify less studied “dark” targets that could be potentially further illuminated. This is an important process for both drug discovery and target validation, as more knowledge can accelerate target identification, and previously understudied proteins can serve as novel targets in drug discovery. Two basic protocols illustrate the levels of detail available for targets and several methods of finding targets of interest. An Alternate Protocol illustrates the difference in available knowledge between less and more studied targets. © 2020 by John Wiley & Sons, Inc.Basic Protocol 1: Search for a target and view detailsAlternate Protocol: Search for dark target and view detailsBasic Protocol 2: Filter a target list to get refined results
Study on modifying the Li/MnO2 battery by mixing with the carbon fluoride
Authors: Yang Kai , Shan Zhongqiang , Liu Xuesheng , Dong Meijing , Tian Jianhua , Wang Shirong 
Published: January 2020

AbstractMnO2 modified with CF
x as cathode electrode materials were investigated in order to improve the electrochemical performance of Li/MnO2 battery. The influences of addition amount of CF
x and thermal property of CF
x modified MnO2 electrode on the electrochemical performances were investigated. The results show that the increase of specific capacity is more powerful than the reduction of voltage platform in MnO2 mixed with CF
x electrodes. According to the results of thermal properties test in adiabatic environment, the heating power of Li/MnO2 battery goes up after mixed with CF
x, which agrees well with that of the discharging process. The heating power of CF
x is 1.15 W, which is almost four times than that of MnO2, but nevertheless, the Li/MnO2 battery with CF
x can be safely used by using forced convection, cooling fin or other heating transfer methods.
Two novel mutations of COL1A1 in fetal genetic skeletal dysplasia of Chinese
Authors: Li Ruibing , Wang Jianan , Wang Longxia , Lu Yanping , Wang Chengbin 
Published: January 2020

AbstractBackgroundSkeletal disorders, which have great genotypic and phenotypic varieties, are a considerable challenge to differentiate these diseases and provide a definitive prenatal diagnosis or pre‐implantation. The present study aims to identify the causative mutation in two unrelated outbred Han–Chinese families.MethodTwo short‐limb fetuses were referred to our hospital. Genomic DNA was extracted from the amniotic fluid of the short‐limb fetuses and from peripheral blood of their parents. To identify the causative gene, next‐generation‐based target capture sequencing was performed on these two fetuses, followed by Sanger Sequencing in unrelated healthy controls. Segregation analysis of the candidate variant was performed in parents by using Sanger sequencing. The mutations were analyzed by SIFT, PolyPhen and Provean.ResultsWe found that fetal genetic skeletal dysplasia was confirmed according to the correlations between genetic mutations and phenotypes in two Chinese families. Targeted next generation sequencing was performed to screen causative mutations in patients. Two novel heterozygous mutations COL1A1 c.1706 G > C (p. G569A) and c.3307 G > A (p. G1103S) were respectively identified. The results suggested that COL1A1 novel mutations were in highly conserved glycine residues present in the Gly‐X‐Y sequence repeats of the triple helical region of the collagen type I α chain, which was responsible for Osteogenesis Imperfecta. The presence of the missense mutation was also confirmed with the Sanger sequence. These two mutations were predicted to be pathogenic by SIFT, PolyPhen and Provean.ConclusionOur findings showed that the mutations of COL1A1 may play important roles in fetal genetic skeletal dysplasia in Chinese patients. Exome sequencing enhances the accurate diagnosis in utero then provides appropriate genetic counseling.
Wideband frequency selective absorber with high‐selective reflective‐band for RCS reduction applications
Authors: Han Ye , Xu Longjie 
Published: January 2020

AbstractThis article presents a wideband frequency selective absorber with a high selective reflective‐band for RCS reduction application. The proposed design consists of three metallic layers. With lossy resonance of the resistors‐loaded folded loop at the front layer, wide absorption performance is obtained. Then two independently lossless resonances are employed to introducing a flexible and high selective reflective‐band with full reflectance into the absorption band. The resultant absorbers have the thickness of only ~0.076 λL at the lowest operating frequencies and exhibit a whole operating bands of 126.3%. Two absorption band with bandwidth of 60.3% and 44.5% have been achieved. A prototype of the proposed structure has been fabricated, whose measured results show reasonable agreement with the simulated responses under normal incidence.
Technical Note: 3D localization of lung tumors on cone beam CT projections via a convolutional recurrent neural network
Authors: Wang Chuang , Hunt Margie , Zhang Lei , Rimner Andreas , Yorke Ellen , Lovelock Michael , Li Xiang , Li Tianfang , Mageras Gig , Zhang Pengpeng 
Published: January 2020

PurposeTo design a convolutional recurrent neural network (CRNN) that calculates three‐dimensional (3D) positions of lung tumors from continuously acquired cone beam computed tomography (CBCT) projections, and facilitates the sorting and reconstruction of 4D‐CBCT images.MethodUnder an IRB‐approved clinical lung protocol, kilovoltage (kV) projections of the setup CBCT were collected in free‐breathing. Concurrently, an electromagnetic signal‐guided system recorded motion traces of three transponders implanted in or near the tumor. Convolutional recurrent neural network was designed to utilize a convolutional neural network (CNN) for extracting relevant features of the kV projections around the tumor, followed by a recurrent neural network for analyzing the temporal patterns of the moving features. Convolutional recurrent neural network was trained on the simultaneously collected kV projections and motion traces, subsequently utilized to calculate motion traces solely based on the continuous feed of kV projections. To enhance performance, CRNN was also facilitated by frequent calibrations (e.g., at 10° gantry rotation intervals) derived from cross‐correlation‐based registrations between kV projections and templates created from the planning 4DCT. Convolutional recurrent neural network was validated on a leave‐one‐out strategy using data from 11 lung patients, including 5500 kV images. The root‐mean‐square error between the CRNN and motion traces was calculated to evaluate the localization accuracy.ResultThree‐dimensional displacement around the simulation position shown in the Calypso traces was 3.4 ± 1.7 mm. Using motion traces as ground truth, the 3D localization error of CRNN with calibrations was 1.3 ± 1.4 mm. CRNN had a success rate of 86 ± 8% in determining whether the motion was within a 3D displacement window of 2 mm. The latency was 20 ms when CRNN ran on a high‐performance computer cluster.ConclusionsCRNN is able to provide accurate localization of lung tumors with aid from frequent recalibrations using the conventional cross‐correlation‐based registration approach, and has the potential to remove reliance on the implanted fiducials.
A Transfer‐Learning Approach for Accelerated MRI Using Deep Neural Networks
Authors: Dar Salman Ul Hassan , Özbey Muzaffer , Çatlı Ahmet Burak , Çukur Tolga 
Published: January 2020

PurposeNeural networks have received recent interest for reconstruction of undersampled MR acquisitions. Ideally, network performance should be optimized by drawing the training and testing data from the same domain. In practice, however, large datasets comprising hundreds of subjects scanned under a common protocol are rare. The goal of this study is to introduce a transfer‐learning approach to address the problem of data scarcity in training deep networks for accelerated MRI.MethodsNeural networks were trained on thousands (upto 4 thousand) of samples from public datasets of either natural images or brain MR images. The networks were then fine‐tuned using only tens of brain MR images in a distinct testing domain. Domain‐transferred networks were compared to networks trained directly in the testing domain. Network performance was evaluated for varying acceleration factors (4‐10), number of training samples (0.5‐4k), and number of fine‐tuning samples (0‐100).ResultsThe proposed approach achieves successful domain transfer between MR images acquired with different contrasts (T1‐ and T2‐weighted images) and between natural and MR images (ImageNet and T1‐ or T2‐weighted images). Networks obtained via transfer learning using only tens of images in the testing domain achieve nearly identical performance to networks trained directly in the testing domain using thousands (upto 4 thousand) of images.ConclusionThe proposed approach might facilitate the use of neural networks for MRI reconstruction without the need for collection of extensive imaging datasets.
Mapping of fatty acid composition with free‐breathing MR spectroscopic imaging and compressed sensing
Authors: Rioux James A. , Hewlett Miriam , Davis Christa , Bowen Chris V. , Brewer Kimberly , Clarke Sharon E. , Beyea Steven D. 
Published: January 2020

Nonalcoholic fatty liver disease (NAFLD) is a growing health problem, and a major challenge in NAFLD management is identifying which patients are at risk of progression to more serious disease. Simple measurements of liver fat content are not strong predictors of clinical outcome, but biomarkers related to fatty acid composition (ie, saturated vs. unsaturated fat) may be more effective. MR spectroscopic imaging (MRSI) methods allow spatially resolved, whole‐liver measurements of chemical composition but are traditionally limited by slow acquisition times. In this work we present an accelerated MRSI acquisition based on spin echo single point imaging (SE‐SPI), which, using appropriate sampling and compressed sensing reconstruction, allows free‐breathing acquisition in a mouse model of fatty liver disease. After validating the technique's performance in oil/water phantoms, we imaged mice that had received a normal diet or a methionine and choline deficient (MCD) diet, some of which also received supplemental injections of iron to mimic hepatic iron overload. SE‐SPI was more resistant to the line‐broadening effects of iron than single‐voxel spectroscopy measurements, and was consistently able to measure the amplitudes of low‐intensity spectral peaks that are important to characterizing fatty acid composition. In particular, in the mice receiving the MCD diet, SE‐SPI showed a significant decrease in a metric associated with unsaturated fat, which is consistent with the literature. This or other related metrics may therefore offer more a specific biomarker of liver health than fat content alone. This preclinical study is an important precursor to clinical testing of the proposed method.MR‐based quantification of fatty acid composition may allow for improved characterization of non‐alcoholic fatty liver disease. A spectroscopic imaging method with appropriate sampling strategy allows whole‐liver mapping of fat composition metrics in a free‐breathing mouse model. Changes in metrics like the surrogate unsaturation index (UIs) are visible in mice receiving a diet which induces fat accumulation in the liver, as compared to a normal diet; such metrics may prove useful in future clinical studies of liver disease.
Eismonde von Jupiter und Saturn
Authors: Wagner Roland 
Published: January 2020

ZusammenfassungSeit 40 Jahren erforschen Sonden die Eismonde im äußeren Sonnensystem. Die Vielfalt dieser Körper, die mögliche Existenz von verborgenen Ozeanen und ihr Kryovulkanismus machen sie zu äußerst spannenden Himmelskörpern. Teil 1 dieses Zweiteilers stellt die Eismonde von Jupiter und Saturn vor. Jeder dieser Eismonde zeigt sich geologisch als eigene Welt. Bei den Jupitertrabanten ist die Oberfläche von Europa im Vergleich zu Ganymed geologisch sehr jung. Magnetfeldmessungen der Galileo‐Mission lassen unter der festen Eiskruste auf einen tiefen Ozean mit salzhaltigem Wasser schließen. Ein solcher Ozean existiert ebenfalls auf Callisto in größerer Tiefe, mutmaßlich auch auf Ganymed. Ganymed besitzt als einziger Eismond einen eisenhaltigen Kern, dessen starkes Magnetfeld das eines Ozeans überdeckt. Der Saturnmond Enceladus zeichnet sich durch aktiven Kryovulkanismus aus, der durch Gezeitenkräfte angetrieben ist.
Molecular mechanisms of vancomycin resistance
Authors: Stogios Peter J. , Savchenko Alexei 
Published: January 2020

AbstractVancomycin and related glycopeptides are drugs of last resort for the treatment of severe infections caused by Gram‐positive bacteria such as Enterococcus species, Staphylococcus aureus, and Clostridium difficile. Vancomycin was long considered immune to resistance due to its bactericidal activity based on binding to the bacterial cell envelope rather than to a protein target as is the case for most antibiotics. However, two types of complex resistance mechanisms, each comprised of a multi‐enzyme pathway, emerged and are now widely disseminated in pathogenic species, thus threatening the clinical efficiency of vancomycin. Vancomycin forms an intricate network of hydrogen bonds with the d‐Ala‐d‐Ala region of Lipid II, interfering with the peptidoglycan layer maturation process. Resistance to vancomycin involves degradation of this natural precursor and its replacement with d‐Ala‐d‐lac or d‐Ala‐d‐Ser alternatives to which vancomycin has low affinity. Through extensive research over 30 years after the initial discovery of vancomycin resistance, remarkable progress has been made in molecular understanding of the enzymatic cascades responsible. Progress has been driven by structural studies of the key components of the resistance mechanisms which provided important molecular understanding such as, for example, the ability of this cascade to discriminate between vancomycin sensitive and resistant peptidoglycan precursors. Important structural insights have been also made into the molecular evolution of vancomycin resistance enzymes. Altogether this molecular data can accelerate inhibitor discovery and optimization efforts to reverse vancomycin resistance. Here, we overview our current understanding of this complex resistance mechanism with a focus on the structural and molecular aspects.
An enhanced MAC protocol based on the IEEE 802.11 for data relay satellite systems
Authors: Wang Xingyu , Zhao Shanghong , Li Yongjun , Zhu Zhuodan , Zheng Yongxing , Yu Chen 
Published: January 2020

SummaryData relay satellite (DRS) systems play an important role in space information networks. Characterized by highly dynamic topology and discontinuous communication links, it is suggested that the IEEE 802.11 protocol employed in such a network could be more flexible. However, such a terrestrial network protocol could not be applied to DRS systems directly, nor supports a fast response due to the long propagation delay and severe packet collision. To address this challenge, we proposed an enhanced media access control (MAC) protocol based on the IEEE 802.11 protocol providing multiaccess for low earth orbit (LEO) distributed constellations. In this paper, we investigated the access delay performance of the proposed protocol in our model. Then, we derived a contention window adaption by using an iteration algorithm that can dynamically adjust the values of the contention window depending on the number of user satellites in the communication coverage. Simulation results show that the average access delay does not exceed 20 seconds, which is significantly lower than the standard protocol. Moreover, the traffic threshold is increased to 0.6, and the maximum throughput has doubled compared with the standard protocol. It is proved that the enhanced MAC protocol shows a better performance in DRS systems.
Two‐factor authentication using biometric based quantum operations
Authors: Sharma Mohit Kr , Nene Manisha J 
Published: January 2020

AbstractTwo‐way authentication methods are utilized in every online user authentication transactions. Use of one time passwords (OTP) have proved to be more secure method, than one factor authentication when the two authentication schemes are carried out on different media. However, current use of OTP restricts authentication to the device itself rather than the user. The fraud cases with OTP based transactions have also increased due to growth of technology. Hence, there is a requirement of enhancing security of OTP based transactions. The study in this paper anchors on mathematically proven properties of quantum cryptography and utilizes the quantum entanglement property to generate quantum OTP (QOTP) for authenticating the user based on its biometrics. The proposed method takes into consideration various quantum computing capabilities of user, thus paving path for gradual upgradation of infrastructure. The work in the paper gives the outline of infrastructure required for implementing the proposed model and concludes by comparing security analysis of existing and proposed model against man‐in‐the‐middle attack (MITM) and user end vulnerabilities to bring forth the importance of QOTP. The practical implementation of the proposed model is envisaged as future research work due to evolving nature of quantum experiments.
Thermal CFTs in momentum space
Authors: Manenti Andrea 
Published: January 2020

AbstractWe study some aspects of conformal field theories at finite temperature in momentum space. We provide a formula for the Fourier transform of a thermal conformal block and study its analytic properties. In particular we show that the Fourier transform vanishes when the conformal dimension and spin are those of a “double twist” operator ∆ = 2∆ϕ+ℓ+ 2n. By analytically continuing to Lorentzian signature we show that the spectral density at high spatial momenta has support on the spectrum condition |ω| > |k|. This leads to a series of sum rules. Finally, we explicitly match the thermal block expansion with the momentum space Green’s function at finite temperature in several examples.
Assessing Google Street View Image Availability in Latin American Cities
Authors: Fry Dustin , Mooney Stephen J. , Rodríguez Daniel A. , Caiaffa Waleska T. , Lovasi Gina S. 
Published: January 2020

AbstractVirtual audits using Google Street View are an increasingly popular method of assessing neighborhood environments for health and urban planning research. However, the validity of these studies may be threatened by issues of image availability, image age, and variance of image age, particularly in the Global South. This study identifies patterns of Street View image availability, image age, and image age variance across cities in Latin America and assesses relationships between these measures and measures of resident socioeconomic conditions. Image availability was assessed at 530,308 near-road points within the boundaries of 371 Latin American cities described by the SALURBAL (Salud Urbana en America Latina) project. At the subcity level, mixed-effect linear and logistic models were used to assess relationships between measures of socioeconomic conditions and image availability, average image age, and the standard deviation of image age. Street View imagery was available at 239,394 points (45.1%) of the total sampled, and rates of image availability varied widely between cities and countries. Subcity units with higher scores on measures of socioeconomic conditions had higher rates of image availability (OR = 1.11 per point increase of combined index, p < 0.001) and the imagery was newer on average (− 1.15 months per point increase of combined index, p < 0.001), but image capture date within these areas varied more (0.59-month increase in standard deviation of image age per point increase of combined index, p < 0.001). All three assessed threats to the validity of Street View virtual audit studies spatially covary with measures of socioeconomic conditions in Latin American cities. Researchers should be attentive to these issues when using Street View imagery.
Gas Sensing and Power Harvesting Polyvinylidene Fluoride Nanocomposites Containing Hybrid Nanotubes
Authors: Ponnamma Deepalekshmi , Sharma Ashok K. , Saharan Priya , Al-Maadeed Mariam Al Ali 
Published: January 2020

AbstractGas sensing properties at room temperature and energy harvesting performances are realized for the polyvinylidene fluoride (PVDF) nanocomposites containing titanium dioxide (TiO2) nanotubes grown in the presence of carbon nanotubes (CNT). While hydrothermal reaction is practiced for the development of TiO2/CNT hybrid nanotubes, spin coating is done for the nanocomposite films to be deposited on sensing electrodes. Influence of various filler concentrations and the synergistic combination of fillers on the sensing characteristics are studied by recording the response times and the stability of the results. Upon exposure to liquefied petroleum gas, the PVDF/TiO2-CNT (2.5 wt.%) gas sensor shows a sensing response of 0.45 s (400 ppm LPG), approximately nine times higher than the composite containing 2.5 wt.% of TiO2 or 2.5 wt.% CNT. The piezoelectric response of the samples is also recorded and correlated with the synergistic influence of the filler materials. The current study can stimulate a good trend in fabricating self-powered gas sensors from PVDF nanocomposites.