bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of heated silver nanowires under surface modification
Authors: Khamla T , Petchsang N 
Published: March 2022

Abstract
Silver nanowires (Ag NWs) have received much attention and applied in many fields due to their excellent conductivity. Hence, Ag NWs were usually integrated with low conductive materials to enhance the conductivity of the overall system. In some conditions, the surface of Ag NWs need to be modified before combining with other materials. There are many ways to change and prepare the surface of Ag NWs, for example, ligand exchange which is a simple process. TOPO (trioctylphosphine oxide) is a robust coordinating ligand and is classified as an essential component for low-dimensional nanomaterials. In comparison, ODE (1-octadecene) is a noncoordinating ligand that is often used in quantum nanomaterials preparation. In this experiment, we investigated the surface attachment for ligand exchange of TOPO and ODE on the surface of Ag NWs under variations of reaction times at 150°C. The scanning electron microscope showed the rough surface when TOPO was added, and there was no noticeable change of surface when ODE was added. These results are promising for the preparation of heterostructure in the future.
Multi-value phase grating fabrication using direct laser writing for generating a two-dimensional focal spot array
Authors: Huang Yi , Li Minglong , Tu Pu , Zhu Haodong , Xia Junyu , He Guangqiang , Yang ZhenYu , Zhao Ming 
Published: March 2022

Abstract
As a beam splitter, multi-value phase grating (MVPG) has a higher diffraction efficiency than the traditional Damman grating (DG) due to its increased number of phase values within one period of the grating. In this paper, two MVPGs are numerically designed within a 120 μm × 120 μm area, which generate 4 * 4 and 5 * 5 focal spot arrays in the far field. Both gratings are fabricated by direct laser writing (DLW) technology. Their diffraction efficiencies reach 68.58% and 63.4%, respectively. To compare, DGs with the same size and focal spot arrays are designed and fabricated, whose diffraction efficiencies are tested to be 29.55% and 35.04%, respectively. The results demonstrate the better optical properties of multi-value phase gratings and the capability of DLW in three-dimensional nano-scale diffractive optical element fabrication.
Bound states in the continuum on flatbands of symmetry-broken photonic crystal slabs
Authors: Zeng Yixuan , Hu Guangwei , Cao Guangtao , Dong Shaohua , Liu Kaipeng , Tang Zhixiang , Qiu Cheng-Wei 
Published: March 2022

Abstract
Bound states in the continuum (BICs) are localized states despite in a radiation continuum, rendering the ultra-high quality factor for enhanced light–matter interactions and supporting exotic topological properties. So far, most of studied BICs in photonic crystal (PhC) slabs are only vertically localized, i.e. allowing propagations in the plane of slab therein but forbidding radiations, and the density of optical states (DOS) at their frequencies is limited due to the steep dispersion characteristics. Here, we report a BIC existing on a flatband of symmetry-broken PhC slab. The flatband, associated with largely reduced group velocity, significantly sharpens the DOS at the frequency of BIC, which can be realized via finely controlling broken vertical symmetry in the PhC slab. The effect of broken symmetry is revealed in a simple effective Hamiltonian near the second-order Γ point of such system. Our results show the simultaneous engineering of dispersion and leaky characteristics of modes, offering new opportunities to boost light–matter interactions and to enhance the performance of photonic devices.
Computer generated color rainbow holographic stereogram
Authors: Xu Fuyang , Yang Xin , Yu Wenjie , Jiang Yuyi , Song Qiang , Ma Guobin 
Published: March 2022

Abstract
In this research, a fast method to calculate the color rainbow holographic stereogram (CRHS) by taking full advantage of the sparsity of the frequency domain is demonstrated. The CRHS is a novel color rainbow hologram containing a large number of elemental CRHSs, where each elemental CRHS only reproduces the color light field information of local 3D color object. The color of the reconstructed color 3D image perceived by the human eye is determined by the spectrum of the reproduced dispersion of different elemental CRHSs that enter the human eye. The calculation of the CRHS is implemented with parallel computing by inversely Fourier transforming the frequency of each elemental CRHS. With the proposed method, the computation time for a resolution of 200k × 200k pixels and size of 64 × 64 mm CRHS is only 15.4 min for a color 3D model with 406k object points. The optical reconstruction with a white LED light illumination proves the effectiveness of our proposed method, which can be applied to the field of color holographic 3D display, advertising or holographic packaging.
A modified spin-casting approach for scalable preparation of ultra-thick reduced graphene oxide films with high thermal conductivity
Authors: Liu Dapeng , Fu Huili , Yang Tingting , Wang Wenjing , Zhao Jingna , Wu Kunjie , Wu Cao , Yong Zhenzhong , Zhang Yongyi 
Published: March 2022

Abstract
With the fast development of high-power electronic devices in recent years, the demand for high-performance thermal dissipation films with high thermal conductivity and large thickness has dramatically increased. Graphene has shown great potential in thermal management due to its extremely high thermal conductivity. However, it remains a significant challenge to achieve high thermal conductivity in thick graphene films (≥100 μm). Herein, a scalable strategy combining a modified layer-by-layer ‘spin-casting’ solution deposition method and multi-step annealing post treatment was adopted for preparing ultra-thick, highly thermal conductive graphene films. The properties of the graphene films were characterized by SEM, XRD, Raman, and XPS, exhibiting excellent graphitic crystallinity, well aligned and dense packing assembly structure. These nearly ideal structural features endow the graphene films with high in-plane thermal conductivity of 1265 ± 46 W m−1 K−1 at a large thickness of 100 μm. The ultra-thick graphene films show superior thermal dissipation performance as compared with traditional Cu/Al foil, demonstrating their great potential in the field of highly-efficient heat spreader films for the next generation of high-power devices.
Computational study of pressurized tetragonal magnesium hydride (MgH4) as a potential candidate for high-temperature superconducting material
Authors: Gebreyohannes Muez Gebregiorgis , Geffe Chernet Amente , Singh Pooran 
Published: March 2022

Abstract
The dream of realizing room temperature superconductivity is one of the most challenging problems in condensed matter physics. Currently, materials with dense hydrogen contents at high pressures hold great promise for realizing room temperature superconductivity. In particular, pressurized alkaline earth metal hydrides received particular attention following the recently predicted sodalite-like calcium hydride (CaH6) with predicted Tc about 261 K above a pressure of 150 GPa; and magnesium hydride (MgH6) with predicted Tc about 270 K above 300 GPa. In this paper, we studied magnesium hydride (MgH4) with tetragonal (I4/mmm) type symmetry, and we found that this structure shows the highest

T

c

≅
313
K

at a pressure of 280 GPa which is higher than that of MgH6. Using density-functional perturbation theory (DFPT), the superconducting transition temperature, electron-phonon coupling, Eliashberg spectral function, and the logarithmic average frequency were computed. Our results reveal that, the computed values are reasonably in agreement with previous estimates.
Modeling dynamic recrystallization behavior of Al-Zn-Mg-Cu alloy during electroshock assisted tension based on cellular automata
Authors: Mei Manlin , Song Yanli , Lu Jue , Chuanchuan Hao , Lechun Xie 
Published: March 2022

Abstract
Electroshock assisted forming of high-strength aluminum alloy is a new type of plasticizing manufacturing method. To study the dynamic recrystallization (DRX) behavior of Al-Zn-Mg-Cu alloy during low-frequency electroshock assisted tension, a cellular automata (CA) model coupled electro-thermal-mechanical multi-field effect was proposed on the Matlab platform. In the established CA model, the effect of additional driving force generated by the electric pulse on the dynamic recrystallization nucleation and growth has been innovatively taken into account. The grain diameters obtained by the above CA model are consistent with that obtained by the electron back scatter diffraction (EBSD) tests, which verified the accuracy of the model. The effects of current density and electrical pulse period on grain morphology, average grain diameter, DRX fraction, and grain size distribution were analyzed. Additionally, the optimal parameters of electroshock assisted tensile (current density of 30 A·mm−2, pulse period of 5 s) were predicted by the CA method. At this time, the DRX fraction increased to 45.79% and the fracture elongation of unidirectional tensile specimen increased by 21.74%.
Deep-learning-based quantum imaging using NOON states
Authors: Li Fengrong , Sun Yifan , Zhang XiangDong 
Published: March 2022

Abstract
The phase sensitivity of photonic NOON states scales O(1/N), which reaches the Heisenberg limit and indicates a great potential in high-quality optical phase sensing. However, the NOON states with large photon number N are experimentally difficult both to prepare and to operate. Such a fact severely limits their practical use. In this article, we soften the requirements for high-quality imaging based on NOON states with large N by introducing deep-learning methods. Specifically, we show that, with the help of deep-learning network, the fluctuation of the images obtained by the NOON states when N = 2 can be reduced to that of the currently infeasible imaging by the NOON states when N = 8. We numerically investigate our results obtained by two types of deep-learning models—deep neural network and convolutional denoising autoencoders, and characterize the imaging quality using the root mean square error. By comparison, we find that small-N NOON state imaging data is sufficient for training the deep-learning models of our schemes, which supports its direct application to the imaging processes.
Evidence of decreasing diurnal temperature range in eastern Northern Hemisphere
Authors: Guan Xiaodan , Cao Chenyu , Zeng Xinrui , Sun Wen 
Published: March 2022

Abstract
As a key variable in the climate system, the diurnal temperature range (DTR) has received a lot of attention in the atmospheric science community. The majority of published papers interpret DTR change in terms of variables like water vapor, cloud cover, and enhanced vegetation index. In this study, we found that the DTR has an obvious decreasing trend in the semi-arid Northeastern Hemisphere, and the decreasing trend is mainly caused by the continuous release of CO2 closely associated with a drying process in the Northeastern Hemisphere. As a result of the continued high emission of CO2, such accelerated decline changes in DTR in drylands may become much more pronounced in the future, posing a series of environmental problems.
Tiling billiards and Dynnikov’s helicoid
Authors: Paris-Romaskevich O. 
Published: March 2022

Here are two problems. First, understanding the dynamics of a tiling billiard in a cyclic quadrilateral periodic tiling. Second, describing the topology of connected components of plane sections of a centrally symmetric subsurface

S
⊂

T

3

S \subset \mathbb {T}^3

of genus

3
3

. In this paper we show that these two problems are related via a helicoidal construction proposed recently by Ivan Dynnikov. The second problem is a particular case of a classical question formulated by Sergei Novikov. The exploration of the relationship between a large class of tiling billiards (periodic locally foldable tiling billiards) and Novikov’s problem in higher genus seems promising, as we show at the end of this paper.
The asymptotic behaviour of cocycles over flows
Authors: Lipatov M. 
Published: March 2022

In 1968, V. I. Oseledets formulated the question of the convergence in Birkhoff’s theorem and in the multiplicative ergodic theorem for measurable cocycles over flows, under the condition of integrability at any fixed time. In 2016, A. M. Stepin and the author of this paper established convergence along subsets of density 1 on the time axis. Here we show that, moreover, convergence takes place modulo subsets of finite measure of the time axis.
Invited Commentary: Toward a Better Understanding of Disparities in Overdose Mortality
Authors: Abdalla Salma M , Galea Sandro 
Published: March 2022

Abstract
The United States has been in the grip of an epidemic of drug overdose mortality for the past few decades, and deaths from drug overdose increased dramatically during the coronavirus disease 2019 pandemic. Townsend et al. (Am J Epidemiol. 2022;191(4):599–612) add to the growing literature highlighting the steep rise of drug overdose mortality among racial and ethnic minorities in the country. Using data from National Center for Health Statistics death certificates and employing principles of small-area estimation and a Bayesian hierarchical model to stabilize the estimates of smaller racial/ethnic groups and states, the authors found that combinations of opioid/stimulant drug overdose deaths saw a steep increase among racial and ethnic minorities, particularly Black Americans, between 2007 and 2019. The results from their analysis highlight the need to change the narrative around opioid deaths, to invest in targeted policies that address the growing burden of drug overdose faced by racial/ethnic minorities, and the importance of using innovative methods to address limitations to data disaggregation. The paper also demonstrates the importance of a holistic view of the challenges to the health of the American public.
Virtual clinical pharmacy services: A model of care to improve medication safety in rural and remote Australian health services
Authors: Chambers Brett , Fleming Cristen , Packer Anna , Botha Louis , Hawthorn Gerard , Nott Shannon 
Published: March 2022

Abstract

Purpose
To describe a virtual clinical pharmacy service as a model of care to support rural and remote Australian hospitals that otherwise would not have access to onsite pharmacists.

Summary
Many small hospitals in Australia do not have an onsite hospital pharmacist and struggle to support and optimize patient care. To increase access to a hospital pharmacist’s specialized skills and medication knowledge, a virtual clinical pharmacy service was designed and implemented in 8 hospitals across rural New South Wales, Australia in 2020. The virtual clinical pharmacy service focuses on the core role of hospital pharmacists, including obtaining a best possible medication history, medication reconciliation at transitions of care, medication review, interprofessional team meetings, provision of patient-friendly medication lists, antimicrobial stewardship, and patient and clinician education. The model is aligned with recognized standards of practice for the delivery of clinical pharmacy services in Australian hospitals. This article details a model of care for translation across other settings. It provides the necessary details on clinical services, processes, supporting structures, an evaluation framework, and other important considerations for implementing virtual pharmacy services.

Conclusion
This research provides policymakers, health service planners, and practitioners with a model for providing comprehensive clinical pharmacy services virtually to increase the safe and effective use of medicines. Future publication of the findings of a formal evaluation of the model’s acceptability and effectiveness is planned.
Heterogeneous multi-scale neighbor topologies enhanced drug–disease association prediction
Authors: Xuan Ping , Meng Xiangfeng , Gao Ling , Zhang Tiangang , Nakaguchi Toshiya 
Published: March 2022

AbstractMotivationIdentifying new uses of approved drugs is an effective way to reduce the time and cost of drug development. Recent computational approaches for predicting drug–disease associations have integrated multi-sourced data on drugs and diseases. However, neighboring topologies of various scales in multiple heterogeneous drug–disease networks have yet to be exploited and fully integrated.ResultsWe propose a novel method for drug–disease association prediction, called MGPred, used to encode and learn multi-scale neighboring topologies of drug and disease nodes and pairwise attributes from heterogeneous networks. First, we constructed three heterogeneous networks based on multiple kinds of drug similarities. Each network comprises drug and disease nodes and edges created based on node-wise similarities and associations that reflect specific topological structures. We also propose an embedding mechanism to formulate topologies that cover different ranges of neighbors. To encode the embeddings and derive multi-scale neighboring topology representations of drug and disease nodes, we propose a module based on graph convolutional autoencoders with shared parameters for each heterogeneous network. We also propose scale-level attention to obtain an adaptive fusion of informative topological representations at different scales. Finally, a learning module based on a convolutional neural network with various receptive fields is proposed to learn multi-view attribute representations of a pair of drug and disease nodes. Comprehensive experiment results demonstrate that MGPred outperforms other state-of-the-art methods in comparison to drug-related disease prediction, and the recall rates for the top-ranked candidates and case studies on five drugs further demonstrate the ability of MGPred to retrieve potential drug–disease associations.
Digital Diasporas: Staying with the Trouble
Authors: Candidatu Laura , Ponzanesi Sandra 
Published: March 2022

AbstractThis commentary proposes a reorientation of diaspora studies towards new configurations of participation and identification. Digital media affordances in this sense are just such new configurations that enable, sustain and multiply diasporic encounters through social media platforms, digital devices and infrastructures. The emerging digital diasporas do not oppose or replace traditional diasporas, but on the contrary further expand and transform their agency in the digital age Mihaela Nedelcu (2018). In our thinking, we are inconversation with, as well as departing from, previous notions of diaspora. In this commentary, we briefly establish the complex and non-linear genealogy of the term, as partaking in multiple disciplinary takes and discursive orientations, and then migrating to the new realm of technology and digital connectedness.
Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of self versus other
Authors: Chiou Rocco , Cox Christopher R , Lambon Ralph Matthew A 
Published: March 2022

AbstractResearch of social neuroscience establishes that regions in the brain’s default-mode network (DN) and semantic network (SN) are engaged by socio-cognitive tasks. Research of the human connectome shows that DN and SN regions are both situated at the transmodal end of a cortical gradient but differ in their loci along this gradient. Here we integrated these 2 bodies of research, used the psychological continuity of self versus other as a “test-case,” and used functional magnetic resonance imaging to investigate whether these 2 networks would encode social concepts differently. We found a robust dissociation between the DN and SN—while both networks contained sufficient information for decoding broad-stroke distinction of social categories, the DN carried more generalizable information for cross-classifying across social distance and emotive valence than did the SN. We also found that the overarching distinction of self versus other was a principal divider of the representational space while social distance was an auxiliary factor (subdivision, nested within the principal dimension), and this representational landscape was more manifested in the DN than in the SN. Taken together, our findings demonstrate how insights from connectome research can benefit social neuroscience and have implications for clarifying the 2 networks’ differential contributions to social cognition.
The global division of labour as enduring archipelago: thinking through the spatiality of ‘globalisation in reverse’
Authors: van Meeteren Michiel , Kleibert Jana 
Published: March 2022

AbstractContemporary globalisation faces several challenges, for instance related to climate change, technological disruption and shifting geopolitics, that have repercussions for the organisation of value chains and the global division of labour. Analysing the long-term geographies of globalisation we observe how successive reconfigurations of ‘new’ and ‘newer’ global divisions of labour share an archipelagic socio-spatial structure. The paper theorizes the articulations of this archipelago spatial figure as a combination of de/bordering, dis/connecting and dis/association. We apply this framework to provide a nuanced assessment of how global capitalism might restructure when some processes that defined globalisation during the last decades kick in reverse.
Adaptive temporal patterns of echolocation and flight behaviors used to fly through varied-sized windows by 2 species of high duty cycle bats
Authors: Ding Jianan , Zhang Yu , Han Fujie , Jiang Tingting , Feng Jiang , Lin Aiqing , Liu Ying 
Published: March 2022

AbstractAs actively sensing animals guided by acoustic information, echolocating bats must adapt their vocal–motor behavior to various environments and behavioral tasks. Here, we investigated how the temporal patterns of echolocation and flight behavior were adjusted in 2 species of bats with a high duty cycle (HDC) call structure, Rhinolophus ferrumequinum and Hipposideros armiger, when they flew along a straight corridor and then passed through windows of 3 different sizes. We also tested whether divergence existed in the adaptations of the 2 species. Both H. armiger and R. ferrumequinum increased their call rates by shortening the pulse duration and inter-pulse interval for more rapid spatial sampling of the environment when flying through smaller windows. Bats produced more sonar sound groups (SSGs) while maintaining a stable proportion of calls that made up SSGs during approaches to smaller windows. The 2 species showed divergent adjustment in flight behavior across 3 different window sizes. Hipposideros armiger reduced its flight speed to pass through smaller windows while R. ferrumequinum increased its flight speed. Our results suggest that these 2 species of HDC bats adopt similar acoustic timing patterns for different tasks although they performed different flight behaviors.