bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estrogen receptor β and treatment with a phytoestrogen are associated with inhibition of nuclear translocation of EGFR in the prostate
Authors: Wu Wan-fu , Wang Li , Spetsieris Nicholas , Boukovala Myrto , Efstathiou Eleni , Brössner Clemens , Warner Margaret , Gustafsson Jan-Ake 
Published: March 2021

Significance
Although PCa depends on AR signaling, the effect of androgen deprivation therapy is temporary and eventually leads to lethal castration-resistant prostate cancer (CRPC). The present study revealed that finasteride, abiraterone, and enzalutamide all increased EGFR nuclear translocation and increased proliferation. In men with BPH, treatment with finasteride led to nuclear expression of EGFR, and treatment with finasteride together with isoflavones (ERβ agonists) inhibited finasteride-induced nuclear EGFR. Of clinical significance is the increase in ERβ expression in advanced PCa upon short-term use of abiraterone, because it suggests a window in time when ERβ agonists may be effective in advanced PCa. Thus, ERβ agonists, by preventing EGFR nuclear translocation in PCa, might be useful in preventing development of tyrosine kinase driven cancer.
DNA hypomethylation in tetraploid rice potentiates stress-responsive gene expression for salt tolerance
Authors: Wang Longfei , Cao Shuai , Wang Peitong , Lu Kening , Song Qingxin , Zhao Fang-Jie , Chen Z. Jeffrey 
Published: March 2021

Significance
Polyploidy can stimulate genetic and epigenetic changes that enhance the potential for plant adaptation and fitness under extreme environments, but the molecular basis for this is poorly understood. Here we show that tetraploid rice is more tolerant to salinity than diploid rice. Tetraploidy induces DNA hypomethylation which potentiates genomic loci coexistent with stress-responsive genes including those in jasmonate biosynthesis and signaling pathways for rapid and robust responses under stress. After salt stress, elevated expression of salt-responsive genes can induce hypermethylation and suppress adjacent TEs. This feedback regulation between polyploidy-induced DNA hypomethylation in rapid and strong stress response and stress-induced hypermethylation to repress TEs and/or TE-associated genes may provide evolutionary advantages for selection to enhance adaptation in polyploid plants and crops.
Axonopus fissifolius.
Authors: Parker Chris 
Published: March 2021

Abstract

A. fissifolius is regarded as a useful pasture or turf grass on less fertile soils, and as such has been very widely introduced across Asia and the Pacific, but has proved unduly aggressive in many regions, competing with more desirable pasture species and threatening native flora, especially in Australia, Hawaii and other Pacific islands. It scored a high 16 in a risk assessment for Hawaii, based on the Australian system (PIER, 2012). Holm et al. (1979) classify A. fissifolius as a 'principal' weed in Brazil and Malaysia.
Stictococcus vayssierei (cassava brown root scale).
Authors: Beverley Claire 
Published: March 2021

Abstract

S. vayssierei is a scale insect found in Equatorial Africa. It feeds on the root system of cassava (Manihot esculenta), and can cause leaf-fall, wilting, tip dieback and ultimately death of cassava plants (Ngeve, 2003a; Williams et al., 2010). Plants that develop normally may exhibit small mature tuberous roots that become covered in scales, making them unsuitable for sale (Ngeve, 2003a). S. vayssierei can cause yield losses of up to 100% and could pose a major threat to cassava production in Central Africa if strong control measures are not taken to control its spread (Ngeve, 2003a; Lema et al., 2004). The species could also present a quarantine threat to other parts of the world where cassava is produced, such as parts of southern Asia.
Fimbristylis littoralis (lesser fimbristylis).
Authors: Rojas-Sandoval Julissa , Acevedo-Rodríguez Pedro 
Published: March 2021

Abstract

F. littoralis is a tufted leafy annual or short-lived herb (sedge) included in the Global Compendium of Weeds where it is listed as an agricultural and environmental weed (Randall, 2012). It has escaped from cultivation and become established along waterways and wetlands (Flora of China Editorial Committee, 2014). The species is of particular concern in rice plantations around the world (Holm et al., 1977). It shows allelopathic activity and once established it can change features of ecosystem functions including hydrological cycles, biophysical dynamics, nutrient cycles, and community composition (Holm et al., 1977; Holou et al., 2013).
Pseudococcus viburni (obscure mealybug).
Authors: Watson Gillian 
Published: March 2021

Abstract

P. viburni, commonly known as obscure mealybug, is an unarmoured scale insect and a common pest in the UK, Netherlands, Australia, New Zealand, the French Riviera, Iran, California and Chile. It can affect a number of fruit and nursery plants including apples, tomatoes, orchids and cacti and cause substantial damage to fruit orchards and vineyards. The degree of polyphagy of P. viburni, combined with its numerous economically important host-plants, have meant that it began to be carried on infested plant material between countries from an early date. The species was first recorded outside South America, in France by Signoret (1875), and its subsequent spread followed the trade routes between Europe and the rest of the world; the species is still increasing its geographical range. While obscure mealybug does not spread widely by its own means, human transport of infested plant material disseminates it over long distances very effectively. It has successfully adapted to life in a variety of ecological conditions and in the higher latitudes where it cannot survive winter outdoors, it thrives in greenhouses (Schoen and Martin, 1999).
Tapinoma melanocephalum (ghost ant).
Authors: Lester Philip 
Published: March 2021

Abstract

T. melanocephalum is a small ant species around 1.5 mm in length originating from the Old World tropics. It is considered an invasive and "tramp" ant species: widely associated with humans, it has been moved around the subtropical and tropical world by human activity. This ant is also recorded in heated buildings in areas such as Canada and Finland. It is primarily a household pest, nesting in housing and consuming household food. In areas such as Florida it is considered one of the most important house-infesting pests. However it has been known to affect agricultural production in situations such as greenhouses, especially if it tends honeydew-producing insects and protects these pests from biological control organisms. T. melanocephalum is thought to be capable of transporting pathogenic microbes and is often abundant in hospitals. Some people can suffer a slight, red irritation of the skin following contact with this ant. This ant is listed on the ISSG global invasive species database.
Interface effects in combined soft/hard ferrite permanent magnets
Authors: Tejera-Centeno Cesar , Gallego Silvia 
Published: March 2021

Abstract
We address the detailed description of the magnetic properties of the (001) and (111) interfaces between the hard CoFe2O4 (CFO) and soft NiFe2O4 spinel ferrites, used in bicomponent systems for permanent magnet applications. The similarity between the electronic properties, magnetic order and lattice structure of both oxides allows us to isolate the effect of ideal interface formation on the magnetism of the combined system based on density functional theory. While the magnetic moments and long-range magnetic order preserve bulk-like values, the magnetic anisotropy is reduced by the presence of the interface, and depends on the specific termination. Partial inversion of CFO is also relevant, as it enhances the net magnetization and alters both the magnitude and spatial dependence of the magnetic anisotropy.
Accuracy assessment of direct georeferencing UAV images with onboard global navigation satellite system and comparison of CORS/RTK surveying methods
Authors: Zeybek Mustafa 
Published: March 2021

Abstract
Inexpensive and small unmanned aerial vehicles (UAVs) provide high-accuracy positional data and enable users to collect high-resolution aerial images. The analysis of images captured using UAVs in a specific reference system is traditionally accomplished using the georeferencing method with high-accuracy ground control points (GCPs). This study aims to test and compare the benchmarks and point clouds’ positional accuracy produced on three consecutive days with different flight combinations at 75 and 100 m flight altitude by means of network-based continuously operating reference stations and differential-based real-time kinematic georeferencing systems without using GCPs. A root mean squared error values were obtained 1–3 cm for the horizontal accuracy and 4–6 cm for the vertical accuracy values. Thus, the proposed system proved an acceptable positional accuracy level. According to the results of the proposed approach, it can be said that the evaluation and use of UAV data without using GCPs is within an adequate range for various mapping purposes.
Atomic layer deposited nickel sulfide for bifunctional oxygen evolution/reduction electrocatalysis and zinc–air batteries
Authors: Yan Shihan , Li Hao , Zhu Jiahao , Xiong Wei , Lei Renbo , Wang Xinwei 
Published: March 2021

Abstract
Rechargeable Zn−air batteries are a promising type of metal-air batteries for high-density energy storage. However, their practical use is limited by the use of costly noble-metal electrocatalysts for the sluggish kinetics of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) occurred at the air electrode of the Zn−air batteries. This work reports a new non-precious bifunctional OER/ORR electrocatalyst of NiS
x
/carbon nanotubes (CNTs), which is made by atomic layer deposition (ALD) of nickel sulfide (NiS
x
) on CNTs, for the applications for the air electrode of the Zn−air batteries. The NiS
x
/CNT electrocatalyst on a carbon cloth electrode exhibits a low OER overpotential of 288 mV to reach 10 mA cm−2 in current density, and the electrocatalyst on a rotating disk electrode exhibits a half-wave ORR potential of 0.81 V in alkaline electrolyte. With the use of the NiS
x
/CNT electrocatalyst for the air electrode, the fabricated aqueous rechargeable Zn−air batteries show a fairly good maximum output power density of 110 mW cm−2, which highlights the great promise of the ALD NiS
x
/CNT electrocatalyst for Zn−air batteries.
A critical analysis of the ‘ponderomotive snowplow’ concept in direct laser acceleration of electrons
Authors: Robinson A P L 
Published: March 2021

Abstract
In this paper we critically examine a concept which we term the ‘ponderomotive snowplow’. It has been alluded to by a number of authors, but a complete description is given by Sazegari et al (2006 Phys. Plasmas
13 033102). In this paper we present a critical analysis of this concept. As a strictly model problem, this is a valid idea. However it does not account for the longitudinal electrostatic field that must be generated in an actual laser-plasma interaction. Both analytic and numerical investigations indicate that the effects of this are hard to neglect, and lead to an effective ponderomotive snowplow that works—as described by Sazegari—as an effective electron accelerator being hard to realize.
Empirical metal-oxide RRAM device endurance and retention model for deep learning simulations
Authors: Lammie Corey , Rahimi Azghadi Mostafa , Ielmini Daniele 
Published: March 2021

Abstract
Memristive devices including resistive random access memory (RRAM) cells are promising nanoscale low-power components projected to facilitate significant improvement in power and speed of Deep Learning (DL) accelerators, if structured in crossbar architectures. However, these devices possess non-ideal endurance and retention properties, which should be modeled efficiently. In this paper, we propose a novel generalized empirical metal-oxide RRAM endurance and retention model for use in large-scale DL simulations. To the best of our knowledge, the proposed model is the first to unify retention-endurance modeling while taking into account time, energy, SET-RESET cycles, device size, and temperature. We compare the model to state-of-the-art and demonstrate its versatility by applying it to experimental data from fabricated devices. Furthermore, we use the model for CIFAR-10 dataset classification using a large-scale deep memristive neural network (DMNN) implementing the MobileNetV2 architecture. Our results show that, even when ignoring other device non-idealities, retention and endurance losses significantly affect the performance of DL networks. Our proposed model and its DL simulations are made publicly available.
Quantum anonymous voting protocol based on single-particle
Authors: Liu Jiang-Shan , Li Yuan-Cheng , Wang Qing-Le , Hu Meng , Zhang Zhi-Chao 
Published: March 2021

Abstract
Anonymous voting is often one decision-making choice in many democracies. Facing the security threats from quantum computers, classical anonymous voting protocols based on computational complexity hypothesis have innovated to quantum anonymous voting protocols based on quantum mechanics. In this paper, we propose a quantum anonymous voting protocol by using high-dimension single particles. With the help of EA and T, the construction of our protocol makes each legitimate voter cast only one ballot, and all ballots open in a quite random rearrangement. Each voter can anonymously trace his/her vote by a private position index, thus our protocol achieving the precious properties of eligibility, privacy, no-reusability, verifiability and fairness. We also analyze that the protocol can successfully resist attacks from external eavesdroppers and internal participants, ensuring that our voting protocol is secure under ideal conditions. Designing mature quantum anonymous voting protocols is challenging.
Updated constraints on massive neutrino self-interactions from cosmology in light of the H0 tension
Authors: Choudhury Shouvik Roy , Hannestad Steen , Tram Thomas 
Published: March 2021

Abstract
We have updated the constraints on flavour universal neutrino self-interactions mediated by a heavy scalar, in the effective 4-fermion interaction limit. We use the relaxation time approximation to modify the collisional neutrino Boltzmann equations, which is known to be very accurate for this particular scenario. Based on the latest CMB data from the Planck 2018 data release as well as auxiliary data we confirm the presence of a region in parameter space with relatively strong self-interactions which provides a better than naively expected fit. However, we also find that the most recent data, in particular high-ℓ polarisation data from the Planck 2018 release, disfavours this solution even though it cannot yet be excluded. Our analysis takes into account finite neutrino masses (parameterised in terms of ∑ mν) and allows for a varying neutrino energy density (parameterised in terms of N
eff), and we find that in all cases the neutrino mass bound inferred from cosmological data is robust against the presence of neutrino self-interactions. Finally, we also find that the strong neutrino self-interactions do not lead to a high value of H0 being preferred, i.e. this model is not a viable solution to the current H0 discrepancy.
Bioelectrical interfaces with cortical spheroids in three-dimensions
Authors: Kalmykov Anna , Reddy Jay W , Bedoyan Esther , Wang Yingqiao , Garg Raghav , Rastogi Sahil K , Cohen-Karni Devora , Chamanzar Maysamreza , Cohen-Karni Tzahi 
Published: March 2021

Abstract

Objective. Three-dimensional (3D) neuronal spheroid culture serves as a powerful model system for the investigation of neurological disorders and drug discovery. The success of such a model system requires techniques that enable high-resolution functional readout across the entire spheroid. Conventional microelectrode arrays and implantable neural probes cannot monitor the electrophysiology (ephys) activity across the entire native 3D geometry of the cellular construct. Approach. Here, we demonstrate a 3D self-rolled biosensor array (3D-SR-BA) integrated with a 3D cortical spheroid culture for simultaneous in vitro ephys recording, functional Ca2+ imaging, while monitoring the effect of drugs. We have also developed a signal processing pipeline to detect neural firings with high spatiotemporal resolution from the ephys recordings based on established spike sorting methods. Main results. The 3D-SR-BAs cortical spheroid interface provides a stable, high sensitivity recording of neural action potentials (<50 µV peak-to-peak amplitude). The 3D-SR-BA is demonstrated as a potential drug screening platform through the investigation of the neural response to the excitatory neurotransmitter glutamate. Upon addition of glutamate, the neural firing rates increased notably corresponding well with the functional Ca2+ imaging. Significance. Our entire system, including the 3D-SR-BA integrated with neuronal spheroid culture, enables simultaneous ephys recording and functional Ca2+ imaging with high spatiotemporal resolution in conjunction with chemical stimulation. We demonstrate a powerful toolset for future studies of tissue development, disease progression, and drug testing and screening, especially when combined with native spheroid cultures directly extracted from humans.
The Riemannian spatial pattern method: mapping and clustering movement imagery using Riemannian geometry
Authors: Larzabal Christelle , Auboiroux Vincent , Karakas Serpil , Charvet Guillaume , Benabid Alim-Louis , Chabardes Stephan , Costecalde Thomas , Bonnet Stéphane 
Published: March 2021

Abstract

Objective. Over the last decade, Riemannian geometry has shown promising results for motor imagery classification. However, extracting the underlying spatial features is not as straightforward as for applying common spatial pattern (CSP) filtering prior to classification. In this article, we propose a simple way to extract the spatial patterns obtained from Riemannian classification: the Riemannian spatial pattern (RSP) method, which is based on the backward channel selection procedure. Approach. The RSP method was compared to the CSP approach on ECoG data obtained from a quadriplegic patient while performing imagined movements of arm articulations and fingers. Main results. Similar results were found between the RSP and CSP methods for mapping each motor imagery task with activations following the classical somatotopic organization. Clustering obtained by pairwise comparisons of imagined motor movements however, revealed higher differentiation for the RSP method compared to the CSP approach. Importantly, the RSP approach could provide a precise comparison of the imagined finger flexions which added supplementary information to the mapping results. Significance. Our new RSP method illustrates the interest of the Riemannian framework in the spatial domain and as such offers new avenues for the neuroimaging community. This study is part of an ongoing clinical trial registered with ClinicalTrials.gov, NCT02550522.
Deep learning for design metamaterial electromagnetic induction transparent device
Authors: Wei Ziming , Zhang Zeyulin , Huang Wei , Yin Shan , Zhang Wentao 
Published: March 2021

Abstract
In this paper, we propose a deep learning model that can be used to reverse design metamaterial electromagnetic induction transparent (EIT) devices. This is a problem that is difficult to achieve with traditional numerical calculation methods. We use the coordinates of six specific points on the EIT transmission spectrum as the input of the neural network, and then the network can predict the structural parameters of the corresponding EIT device. We cite an example to prove that our method can be used to efficiently reverse design the structure of EIT devices. We believe that this method will open up a new way for the structural design of EIT devices and has great potential for expanding the application of terahertz EIT metamaterials.
Design and implementation of graft database on MSME information system using Neo4j
Authors: Sholeh M , Rachmawati R Y , Susanti E 
Published: March 2021

Abstract
This study aims to implement a database of information systems for small and medium enterprises (MSME) using database graphs. In the conducted application development, the used database mostly uses the relational database. With the development of large amounts of data, the tendency of ever increasing data volume has an impact on the increasingly large table size and the number of merging data on the query (JOIN) has an impact on the time of accessing the query. This data speed is a problem in the relational database, and one solution is to use the noSQL database. In this research, the implementation of noSQL used a graph database and used the Neo4j application. The research methodology and database development carried out in this study is by collecting and analyzing, conceptual, logical, physical level databases on data related to the needs of MSME information systems such as MSME locations, MSME actors and MSME products. The data is then carried out conceptual level database design and proceed with logical level database design. This research resulted in a graft database that stored the MSME data. The results of the node from the graph database implementation were the nodes of city, sub-district MSME, and product and connector of the sub-district_entrance node which connecting the MSME location (sub-village) with the sub-district, the node connector of industrial_typed_entrance which connecting the MSME actors with the industry types.
The technology of augmented reality based on 3D modeling to improve special skills for vocational students in the era of industrial revolution 4.0
Authors: Tuwoso  , Putra A B N R , Mukhadis A , Purnomo  , Bin Mahamad Abd. Kadir , Subandi M S 
Published: March 2021

Abstract
Currently, the development of virtual learning technology continues to increase. Virtual technology such as augmented reality is becoming a sophisticated learning innovation. On the other hand, the special abilities of vocational education graduates have decreased relatively. This study aims to: 1) map the components of the need to improve special skills in vocational education graduate students; 2) develop 3D-modeling based augmented reality learning technology; and 3) testing the attractiveness of the 3D-modeling based augmented reality learning technology. The method used is the research and development (R&D) method. Requirement component map data was taken using qualitative methods through questionnaires and observations. Informants at this stage were students in the field of vocational education at State Universities in East Java. Furthermore, expert tests were conducted by material experts in the field of vocational education and online learning media experts. The results of this study include 1) map of the components of the need to improve special skills in vocational education student graduates consisting of idea development (78%), utilization of infrastructure (82%), deepening knowledge (90%), professional organization (88%), and mental stimulation (90 %); 2) the developed 3D-modeling based augmented reality learning technology has an excellent level of attractiveness and feasibility based on online learning media experts and material experts; and 3) learning technology products based on 3D-modeling augmented reality which is developed can increase the special skills of graduate vocational education students.