bluuebunny/crossref_metadata_2025_split huggingface dataset:
Freestanding perovskite oxide monolayers as two-dimensional semiconductors
Authors: Xiao Xiang-Bo , Liu Bang-Gui 
Published: December 2020

Abstract
It is highly desirable to search for promising two-dimensional (2D) monolayer materials for obtaining deep insight of 2D materials and developing device applications. We use first-principles method to investigate tetragonal perovskite oxide monolayers as 2D materials, and find three stable freestanding 2D monolayer materials from important perovskite oxides (ABO3), namely SrTiO3, LaAlO3, and KTaO3, denoting them as STO-ML, LAO-ML, and KTO-ML. Such an oxide monolayer consists of one AO and one BO2 atomic layers. Further study shows that the three monolayers are 2D wide-gap semiconducotors, and there is a large electrostatic potential energy difference between the two sides, reflecting a large out-of-plane dipole, in each of the monolayers. We also investigate optical properties of the three monolayer semiconductors and compare them with graphene and MoS2 monolayer. These make a series of 2D monolayer materials, and should be useful in novel electronic and optoelectronic devices considering emerging phenomena in perovskite oxide heterostructures.
Evaluation for half-lives in α-decay chains of 309−312126 based on semi-empirical approaches
Authors: Ly N D , Duy N N , Chae K Y , Pham Vinh N T , Nhan-Hao T V 
Published: December 2020

Abstract
In this paper, we estimated half-lives using semi-empirical formulae for isotopes with Z = 100 − 126 in four α-decay chains, which can appear in the syntheses of the 309−312126 nuclei. The spontaneous fission half-lives were calculated using the Anghel, Karpov, and Xu models, whereas the α-decay ones were predicted using the Viola-Seaborg, Royer, Akrawy, Brown, modified formulae of Royer, Ni, and Qian approaches. We found that there are large differences among the spontaneous fission half-lives estimated using the Xu model and those calculated using the others, which are up to 50 orders of magnitude. The α-decay half-lives also have large uncertainties due to difference in either methods or uncertainties in nuclear mass and spin-parities. Subsequently, there is an argument in determination of α-emitters, especially for the 312126 isotope. On the other hand, the α-decay half-lives are in the range from a few microseconds (309−312126) to thousands of years (257−260Fm) in the decay chains. It was found that the half-lives are very sensitive to not only the shell closure but also the angular momentum in the α decay. For experiments, with relatively long half-lives (a few milliseconds), the 289−292Lv isotopes can be observed as evidences for syntheses of the unknown super-heavy 309−312126 nuclei. Furthermore, measurements for precise mass, fission barrier, and spin-parity are necessary to improve accuracy of half-life predictions for super-heavy nuclei.
Research on the photoluminescence of spectral broadening by rapid thermal annealing on InAs/GaAs quantum dots
Authors: Ning Dandan , Chen Yanan , Li Xinkun , Liang Dechun , Ma Shufang , Jin Peng , Wang Zhanguo 
Published: December 2020

Abstract
Photoluminescence (PL) test was conducted to investigate the effect of rapid thermal annealing (RTA) on the optical performance of self-assembled InAs/GaAs quantum dots (QDs) at the temperatures of 16 and 300 K. It was found that after RTA treatment, the PL spectrum of the QDs sample had a large blue-shift and significantly broadened at 300 K. Compared with the as-grown InAs QDs sample, the PL spectral width has increased by 44.68 meV in the InAs QDs sample RTA-treated at 800 °C. The excitation power-dependent PL measurements showed that the broadening of the PL peaks of the RTA-treated InAs QDs should be related to the emission of the ground state (GS) of different-sized InAs QDs, the InAs wetting layer (WL) and the In0.15Ga0.85As strain reduction layer (SRL) in the epitaxial InAs/GaAs layers.
The influence of total ionizing dose on the hot carrier injection of 22 nm bulk nFinFET
Authors: Wang Baoshun , Cui Jiangwei , Guo Qi , Zheng Qiwen , Wei Ying , Xi Shanxue 
Published: December 2020

Abstract
We investigate the hot carrier injection effect (HCI) and how X-ray radiation impacts the HCI of 22-nm nFinFETs as a function of device geometry and irradiation bias conditions in this paper. In the HCI test, the degradation of threshold voltage and saturation current decreases with the increase of fin number, which means that HCI weakens when the fin number increases. The reason is attributed to the coupling effect between fins. Moreover, irradiation is shown to weaken the degradation during the subsequent hot carrier test. The influence of irradiation on HCI is more obvious with ON bias than that of OFF bias and transmission gate bias. It is supposed that the Si–H bonds can be broken by irradiation before the HCI test, which is one reason for the irradiation influence on HCI. Besides, trapped charges are generated in the shallow trench isolation by the radiation, which could reduce the channel electric field, and then weaken the HCI.
Theoretical study of a group IV p–i–n photodetector with a flat and broad response for visible and infrared detection
Authors: Wu Jinyong , Huang Donglin , Ye Yujie , Wang Jianyuan , Huang Wei , Li Cheng , Chen Songyan , Ke Shaoying 
Published: December 2020

Abstract
We report a theoretical study of a broadband Si/graded-SiGe/Ge/Ge0.9Sn0.1 p–i–n photodetector with a flat response based on modulating thickness of the layers in the active region. The responsivity of the photodetector is about 0.57 A/W in the range of 700 to 1800 nm. This structure is suitable for silicon-based epitaxial growth. Annealing is technically applied to form the graded-SiGe. The photodetector reaches a cut-off wavelength at ~2300 nm and a low dark-current density under 3 V reverse bias about 0.17 mA/cm2 is achieved theoretical at room temperature. This work is of great significance for silicon-based detection and communication, from visible to infrared.
Re-assessing global water storage trends from GRACE time series
Authors: Vishwakarma B D , Bates P , Sneeuw N , Westaway R M , Bamber J L 
Published: December 2020

Abstract
Monitoring changes in freshwater availability is critical for human society and sustainable economic development. To identify regions experiencing secular change in their water resources, many studies compute linear trends in the total water storage (TWS) anomaly derived from the Gravity Recovery and Climate Experiment (GRACE) mission data. Such analyses suggest that several major water systems are under stress (Rodell et al 2009 Nature
460 999–1002; Long et al 2013 Geophys. Res. Lett.
40 3395–401; Richey et al 2015 Water Resour. Res.
51 5217–38; Voss et al 2013 Water Resour. Res.
49 904–14; Famiglietti 2014 Nat. Clim. Change.
4 945–8; Rodell et al 2018 Nature 557 651–9). TWS varies in space and time due to low frequency natural variability, anthropogenic intervention, and climate-change (Hamlington et al 2017 Sci. Rep.
7 995; Nerem et al 2018 Proc. Natl Acad. Sci.). Therefore, linear trends from a short time series can only be interpreted in a meaningful way after accounting for natural spatiotemporal variability in TWS (Paolo et al 2015 Science
348 327–31; Edward 2012 Geophys. Res. Lett. 39 L01702). In this study, we first show that GRACE TWS trends from a short time series cannot determine conclusively if an observed change is unprecedented or severe. To address this limitation, we develop a novel metric, trend to variability ratio (TVR), that assesses the severity of TWS trends observed by GRACE from 2003 to 2015 relative to the multi-decadal climate-driven variability. We demonstrate that the TVR combined with the trend provides a more informative and complete assessment of water storage change. We show that similar trends imply markedly different severity of TWS change, depending on location. Currently more than 3.2 billion people are living in regions facing severe water storage depletion w.r.t. past decades. Furthermore, nearly 36% of hydrological catchments losing water in the last decade have suffered from unprecedented loss. Inferences from this study can better inform water resource management.
Testing a simple formula for calculating approximate intensity-duration-frequency curves
Authors: Benestad Rasmus E , Lutz Julia , Dyrrdal Anita Verpe , Haugen Jan Erik , Parding Kajsa M , Dobler Andreas 
Published: December 2020

Abstract
A simple formula for estimating approximate values of return levels for sub-daily rainfall is presented and tested. It was derived from a combination of simple mathematical principles, approximations and fitted to 10 year return levels taken from intensity-duration-frequency (IDF) curves representing 14 sites in Oslo. The formula was subsequently evaluated against IDF curves from independent sites elsewhere in Norway. Since it only needs 24 h rain gauge data as input, it can provide approximate estimates for the IDF curves used to describe sub-daily rainfall return levels. In this respect, it can be considered as means of downscaling with respect to timescale, given an approximate power-law dependency between temporal scales. One clear benefit with this framework is that observational data is far more abundant for 24 h rain gauge records than for sub-daily measurements. Furthermore, it does not assume stationarity, and is well-suited for projecting IDF curves for a future climate.
On-chip high-definition bioprinting of microvascular structures
Authors: Dobos Agnes , Gantner Franziska , Markovic Marica , Van Hoorick Jasper , Tytgat Liesbeth , Van Vlierberghe Sandra , Ovsianikov Aleksandr 
Published: December 2020

Abstract
‘Organ-on-chip’ devices which integrate three-dimensional (3D) cell culture techniques with microfluidic approaches have the capacity to overcome the limitations of classical 2D platforms. Although several different strategies have been developed to improve the angiogenesis within hydrogels, one of the main challenges in tissue engineering remains the lack of vascularization in the fabricated 3D models. The present work focuses on the high-definition (HD) bioprinting of microvascular structures directly on-chip using two-photon polymerization (2PP). 2PP is a nonlinear process, where the near-infrared laser irradiation will only lead to the polymerization of a very small volume pixel (voxel), allowing the fabrication of channels in the microvascular range (10–30 µm in diameter). Additionally, 2PP not only enables the fabrication of sub-micrometer resolution scaffolds but also allows the direct embedding of cells within the produced structure. The accuracy of the 2PP printing parameters were optimized in order to achieve high-throughput and HD production of microfluidic vessel-on-chip platforms. The spherical aberrations stemming from the refractive index mismatch and the focusing depth inside the sample were simulated and the effect of the voxel compensation as well as different printing modes were demonstrated. Different layer spacings and their dependency on the applied laser power were compared both in terms of accuracy and required printing time resulting in a 10-fold decrease in structuring time while yielding well-defined channels of small diameters. Finally, the capacity of 2PP to create vascular structures within a microfluidic chip was tested with two different settings, by direct embedding of a co-culture of endothelial- and supporting cells during the printing process and by creating a supporting, cell-containing vascular scaffold barrier where the endothelial cell spheroids can be seeded afterwards. The functionality of the formed vessels was demonstrated with immunostaining of vascular endothelial cadherin (VE-Cadherin) endothelial adhesion molecules in both static and perfused culture.
Broadband absorption of infrared dielectric resonators for passive radiative cooling
Authors: Liu Yanning , Weng Xiaolong , Zhang Peng , Li Wenxin , Gong Yu , Zhang Li , Zhou Peiheng , Deng Longjiang 
Published: December 2020

Abstract
Infrared resonator metamaterials, exhibiting spectral selective absorption of light, have recently been of great interest for passive radiative cooling. In this approach, coolers radiate power passively, with emissivity equals to its absorptivity. However, high-efficient energy dissipation requires radiation windows of broad bandwidth, i.e. 8–14 μm, that challenges the narrow-band feature of resonators. Here, we numerically realize the broadband absorption (above 80% in 8–11 μm) for dielectric resonators over a wide incident angle range (0°–60°), predicting 12 °C cooling below the ambient temperature at nighttime. The electromagnetically resonating eigenmodes of the dielectric resonators are perturbated by losses to reshape the dispersion relation in radiation windows, which are implemented by two methods: inserting metal components and coating lossy dielectrics. Retrieval constitutive parameters, as well as S parameters, map the reshaping process for broadband considerations. Additionally, ideal transparency (nearly 100%) above the wavelength of 0.5 mm is achieved. These crucial features offer an effective solution to the microwave signals shielding problem generally encountered in previous radiative coolers, regarding applied scenes such as buildings and cars.
A multiscale optimization framework for reconstructing binary images using multilevel PCA-based control space reduction
Authors: Koolman Priscilla M , Bukshtynov Vladislav 
Published: December 2020

Abstract
An efficient computational approach for optimal reconstructing parameters of binary-type physical properties for models in biomedical applications is developed and validated. The methodology includes gradient-based multiscale optimization with multilevel control space reduction by using principal component analysis (PCA) coupled with dynamical control space upscaling. The reduced dimensional controls are used interchangeably at fine and coarse scales to accumulate the optimization progress and mitigate side effects at both scales. Flexibility is achieved through the proposed procedure for calibrating certain parameters to enhance the performance of the optimization algorithm. Reduced size of control spaces supplied with adjoint-based gradients obtained at both scales facilitate the application of this algorithm to models of higher complexity and also to a broad range of problems in biomedical sciences. This technique is shown to outperform regular gradient-based methods applied to fine scale only in terms of both qualities of binary images and computing time. Performance of the complete computational framework is tested in applications to 2D inverse problems of cancer detection by the electrical impedance tomography (EIT). The results demonstrate the efficient performance of the new method and its high potential for minimizing possibilities for false positive screening and improving the overall quality of the EIT-based procedures.
A hybrid quantum regression model for the prediction of molecular atomization energies
Authors: Reddy Pranath , Bhattacherjee Aranya B 
Published: December 2020

Abstract
Quantum machine learning is a relatively new research field that aims to combine the dramatic performance advantage offered by quantum computing and the ability of machine learning algorithms to learn complex distributions of high-dimensional data. The primary focus of this domain is the implementation of classical machine learning algorithms in the quantum mechanical domain and study of the speedup due to quantum parallelism, which could enable the development of novel techniques for solving problems such as quantum phase recognition and quantum error correction optimization. In this paper, we propose a hybrid quantum machine learning pipeline for predicting the atomization energies of various molecules using the nuclear charges and atomic positions of the constituent atoms. Firstly, we will be using a deep convolutional auto-encoder model for the feature extraction of data constructed from the eigenvalues and eigenvector centralities of the pairwise distance matrix calculated from atomic positions and the unrolled upper triangle of each Coulomb matrix calculated from nuclear charges, and we will then be using a quantum regression algorithm such as quantum linear regression, quantum radial basis function neural network and, a quantum neural network for estimating the atomization energy. The hybrid quantum neural network models do not seem to provide any speedup over their classical counterparts. Before implementing a quantum algorithm, we will also be using state-of-the-art classical machine learning and deep learning models such as XGBoost, multilayer perceptron, deep convolutional neural network, and a long short-term memory network to study the correlation between the extracted features and corresponding atomization energies of molecules.
Accurate, scalable cohort variant calls using DeepVariant and GLnexus
Authors: Yun Taedong , Li Helen , Chang Pi-Chuan , Lin Michael F , Carroll Andrew , McLean Cory Y 
Published: December 2020

Abstract

Motivation
Population-scale sequenced cohorts are foundational resources for genetic analyses, but processing raw reads into analysis-ready cohort-level variants remains challenging.

Results
We introduce an open-source cohort-calling method that uses the highly accurate caller DeepVariant and scalable merging tool GLnexus. Using callset quality metrics based on variant recall and precision in benchmark samples and Mendelian consistency in father-mother-child trios, we optimize the method across a range of cohort sizes, sequencing methods and sequencing depths. The resulting callsets show consistent quality improvements over those generated using existing best practices with reduced cost. We further evaluate our pipeline in the deeply sequenced 1000 Genomes Project (1KGP) samples and show superior callset quality metrics and imputation reference panel performance compared to an independently generated GATK Best Practices pipeline.

Availability and implementation
We publicly release the 1KGP individual-level variant calls and cohort callset (https://console.cloud.google.com/storage/browser/brain-genomics-public/research/cohort/1KGP) to foster additional development and evaluation of cohort merging methods as well as broad studies of genetic variation. Both DeepVariant (https://github.com/google/deepvariant) and GLnexus (https://github.com/dnanexus-rnd/GLnexus) are open-source, and the optimized GLnexus setup discovered in this study is also integrated into GLnexus public releases v1.2.2 and later.

Supplementary information
Supplementary data are available at Bioinformatics online.
Decoding Music-Evoked Emotions in the Auditory and Motor Cortex
Authors: Putkinen Vesa , Nazari-Farsani Sanaz , Seppälä Kerttu , Karjalainen Tomi , Sun Lihua , Karlsson Henry K , Hudson Matthew , Heikkilä Timo T , Hirvonen Jussi , Nummenmaa Lauri 
Published: December 2020

Abstract
Music can induce strong subjective experience of emotions, but it is debated whether these responses engage the same neural circuits as emotions elicited by biologically significant events. We examined the functional neural basis of music-induced emotions in a large sample (n = 102) of subjects who listened to emotionally engaging (happy, sad, fearful, and tender) pieces of instrumental music while their hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). Ratings of the four categorical emotions and liking were used to predict hemodynamic responses in general linear model (GLM) analysis of the fMRI data. Multivariate pattern analysis (MVPA) was used to reveal discrete neural signatures of the four categories of music-induced emotions. To map neural circuits governing non-musical emotions, the subjects were scanned while viewing short emotionally evocative film clips. The GLM revealed that most emotions were associated with activity in the auditory, somatosensory, and motor cortices, cingulate gyrus, insula, and precuneus. Fear and liking also engaged the amygdala. In contrast, the film clips strongly activated limbic and cortical regions implicated in emotional processing. MVPA revealed that activity in the auditory cortex and primary motor cortices reliably discriminated the emotion categories. Our results indicate that different music-induced basic emotions have distinct representations in regions supporting auditory processing, motor control, and interoception but do not strongly rely on limbic and medial prefrontal regions critical for emotions with survival value.
Salinity increases growth and pathogenicity of water mold to cause mortality and early hatching in Rana sylvatica embryos
Authors: Coughlan Megan P , Waters Theresa R , Touchon Justin C 
Published: December 2020

ABSTRACT
Amphibian embryos often suffer increased mortality and altered hatching when exposed to road deicing salt runoff or pathogens such as water molds. However, the combined effects of such contaminants on embryos remain understudied. To test how pond salinization interacts with water mold (Saprolegniasp.) to influence hatching timing and survival, we first measured pond water conductivity and temperature and quantified the prevalence and abundance of water mold in four ponds in an ecological preserve. Second, we experimentally placed wood frog (Rana sylvatica) embryos in the presence or absence of water mold, crossed with environmentally realistic salt concentrations (100, 300 or 600 μS). Lastly, we quantified growth and colonization of water mold in this range of salinities. Our results demonstrate that salt had synergistic effects with water mold exposure that affected hatching time, though water mold had less of an effect at higher salinities. Water mold significantly reduced egg survival whereas salt did not. Higher salinities also increased water mold growth and colonization on new substrates. These results indicate that road salt runoff may enhance colonization of amphibian eggs by water molds increasing mortality and premature hatching of surviving embryos, which may in turn have detrimental effects on amphibian communities.
Ancient Mnemonic in New Format—Episodic Memory Training With the Method of Loci in a Smart Phone Application
Authors: Sandberg Petra , Boraxbekk Carl-Johan , Zogaj Idriz , Nyberg Lars 
Published: December 2020

AbstractObjectivesEpisodic memory is age-sensitive but can be strengthened by targeted training interventions. The method of loci (MoL) is a classic mnemonic which if successfully implemented greatly improves memory performance. We developed and investigated the effects of a MoL training program implemented in a smart phone application (app) with the aim of studying usage of the application, training effect and its modifiability by age, predictors for MoL proficiency, transfer effects to a face-name memory task, and perceived benefit in everyday memory.MethodA total of 359 adults participated. Instruction and training of the MoL, transfer test (face-name paired associates cued recall task), and surveys were performed in an in-house developed app.ResultsThe app interested people across the adult life span. Older adults practiced the most, whereas younger and young-old participants showed the highest level of MoL proficiency. Level of proficiency was modulated by amount of practice, but in the oldest participants this effect was less pronounced. Greater self-rated health was associated with higher level of proficiency. No transfer effect was observed. Among those who answered the survey, about half expressed that MoL training had benefitted memory in their everyday life.DiscussionApp-based memory training in the MoL can be delivered successfully via an app across the adult life span. Level of performance reached in training is variable but generally high, and mainly influenced by amount of training and age of the participants. Our data suggest plasticity across the life span, but to a lesser degree for adults between 70 and 90 years.