bluuebunny/crossref_metadata_2025 huggingface dataset:
Azobenzene molecular glasses with tuned glass transition temperatures: from optimal light-induced motion to self-erasable gratings
Authors: Diggins Austin , Dawson Eoin , Kamaliardakani Mahnaz , Pellerin Christian , Sabat Ribal Georges , Lebel Olivier
Published: April 2020

The rate of photomechanical formation of surface relief gratings (SRG) in thin films of azobenzene materials depends on their glass transition temperature (Tg), with self-erasable gratings being formed with materials with sub-ambient Tg.
Crystalline rubrene via a novel process and realization of a pyro-phototronic device with a rubrene-based film
Authors: Gogoi Deepshikha , Hussain Amreen A. , Biswasi Sweety , Pal Arup R.
Published: April 2020

A single-step solvent-free process for crystalline rubrene film where surface layer polarization results in the pyro-phototronic effect.
Differential effects of ‘resurrecting' Csp pseudoproteases during Clostridioides difficile spore germination
Authors: Donnelly M. Lauren , Forster Emily R. , Rohlfing Amy E. , Shen Aimee
Published: April 2020

Clostridioides difficile is a spore-forming bacterial pathogen that is the leading cause of hospital-acquired gastroenteritis. C. difficile infections begin when its spore form germinates in the gut upon sensing bile acids. These germinants induce a proteolytic signaling cascade controlled by three members of the subtilisin-like serine protease family, CspA, CspB, and CspC. Notably, even though CspC and CspA are both pseudoproteases, they are nevertheless required to sense germinants and activate the protease, CspB. Thus, CspC and CspA are part of a growing list of pseudoenzymes that play important roles in regulating cellular processes. However, despite their importance, the structural properties of pseudoenzymes that allow them to function as regulators remain poorly understood. Our recently solved crystal structure of CspC revealed that its pseudoactive site residues align closely with the catalytic triad of CspB, suggesting that it might be possible to ‘resurrect' the ancestral protease activity of the CspC and CspA pseudoproteases. Here, we demonstrate that restoring the catalytic triad to these pseudoproteases fails to resurrect their protease activity. We further show that the pseudoactive site substitutions differentially affect the stability and function of the CspC and CspA pseudoproteases: the substitutions destabilized CspC and impaired spore germination without affecting CspA stability or function. Thus, our results surprisingly reveal that the presence of a catalytic triad does not necessarily predict protease activity. Since homologs of C. difficile CspA occasionally carry an intact catalytic triad, our results indicate that bioinformatic predictions of enzyme activity may underestimate pseudoenzymes in rare cases.
Global warming and plant–pollinator mismatches
Authors: Gérard Maxence , Vanderplanck Maryse , Wood Thomas , Michez Denis
Published: April 2020

The mutualism between plants and their pollinators provides globally important ecosystem services, but it is likely to be disrupted by global warming that can cause mismatches between both halves of this interaction. In this review, we summarise the available evidence on (i) spatial or (ii) phenological shifts of one or both of the actors of this mutualism. While the occurrence of future spatial mismatches is predominantly theoretical and based on predictive models, there is growing empirical evidence of phenological mismatches occurring at the present day. Mismatches may also occur when pollinators and their host plants are still found together. These mismatches can arise due to (iii) morphological modifications and (iv) disruptions to host attraction and foraging behaviours, and it is expected that these mismatches will lead to novel community assemblages. Overall plant–pollinator interactions seem to be resilient biological networks, particularly because generalist species can buffer these changes due to their plastic behaviour. However, we currently lack information on where and why spatial mismatches do occur and how they impact the fitness of plants and pollinators, in order to fully assess if adaptive evolutionary changes can keep pace with global warming predictions.
Resource allocation algorithm for downlink MIMO‐OFDMA based cognitive radio networks in spectrum underlay scenario
Authors: Mohammadi Mahla , Hosseini Andargoli Seyed Mehdi
Published: April 2020

In this study, the sum throughput maximisation problem for cognitive radio networks (CRNs) based on the multiple‐input multiple‐output orthogonal frequency division multiple access (MIMO‐OFDMA) structure has been investigated. Hence, the intention is to maximise the downlink sum throughput of the CRN in a way that the sum power of the cognitive base station (CBS) remains below the given power limit and the induced interference on each subcarrier guarantees the interference threshold level predefined by primary users. Here, due to combinatorial constraints, the complex problem should be resolved. Hence, the core purpose of this study is to prepare a novel resource assignment algorithm that tries to fulfil these combinatorial constraints simultaneously. Therefore, this study makes progress towards solving the problem theoretically based on convex optimisation framework. An optimal solution has been implemented by proposing the iterative algorithm in which an optimal level of Lagrangian coefficients is obtained. Then, because of the optimal algorithm intricacy, the two low complicated algorithms are further suggested based on the solutions of two simplified versions of the original problem. Numerical results demonstrate that the suggested algorithms improve sum throughput considerably in comparison with classical algorithm. The proposed simplified algorithms converge to the optimal solutions’ performance while their complexities are desirable for practical implementation.
Copula function‐based analysis of outage probability and coverage region for wireless multiple access communications with correlated fading channels
Authors: Ghadi Farshad Rostami , Hodtani Ghosheh Abed
Published: April 2020

From practical and theoretical viewpoints, performance analysis of communications with correlated fading channels is important. In this study, the authors exploit a novel approach based on Copula function concept to investigate the impact of correlation of Rayleigh fading channels on communication performances. One of the most convenient ways to describe the dependence between several variables is using Copula functions. For this purpose, by applying the Farlie–Gumbel–Morgenstern Copula function, they derive closed‐form expressions for outage probability as well as coverage region in a wireless multiple access channel. It is shown that the fading correlation improves the outage probability and coverage region for negative dependence structure. Specifically, whenever the dependence structure tends to negative values, the outage and coverage region performance improvement is increased. Finally, the efficiency of the analytical results is illustrated numerically.
Event‐triggered leader‐following consensus for multi‐agent systems with external disturbances under fixed and switching topologies
Authors: Mu Rui , Wei Airong , Li Haitao , Wang Zi‐Ming
Published: April 2020

In this study, the event‐triggered leader‐following consensus problem for multi‐agent systems with external disturbances is addressed under fixed and switching topologies. First, based on an extended state observer, a novel distributed event‐triggered protocol is designed under a fixed topology to achieve consensus disturbance rejection and eliminate Zeno behaviour. Second, for the case of switching topologies which do not always have a directed spanning tree, an observer‐based event‐triggered protocol is proposed with topology‐dependent average dwell time. Moreover, both protocols presented are without the requirement of continuous information transmission among neighbouring agents. Finally, two numerical examples are provided to illustrate the effectiveness of the results.
Optimisation of both classifier and fusion based feature set for static American sign language recognition
Authors: C. Arun , Gopikakumari R.
Published: April 2020

Sign language recognition becomes a popular research field in human–computer interaction. Attention on hand signal analysis helps to make easy communication among computer and human for information sharing. Major focus of the gesture recognition system is to identify and recognise various gestures, by a computer. This study introduces optimisation of both classifier and feature set for static American sign language recognition. Initially, the hand part is segmented from other parts of the image through effective edge and skin colour detection. Thereafter, robust features are obtained using discrete cosine transform, Zernike moment, scale‐invariant feature transform, speeded‐up robust features, histogram of oriented gradients and binary object features from the segmented hand image. From these extracted features, an optimal feature set is selected by social ski driver optimisation algorithm. Deep Elman recurrent neural network classifier is then introduced for recognition purpose. Optimisation is performed on feature sets, derived by fusion of features obtained from the above methods, based on precision, accuracy, F‐measure and recall. Finally, optimised feature set and best classifier are used to recognise the hand gesture for classification purpose. The performance of this proposed method is evaluated and compared with existing literature.
Hyperspectral image classification using three‐dimensional geometric moments
Authors: Kumar Brajesh
Published: April 2020

Exploitation of both spectral and spatial information in hyperspectral imagery is important for effective classification. Considering the cubical arrangement of data, the three‐dimensional (3D) techniques could be effectively used to model hypespectral features. In this study, the 3D geometric moments are used to extract the rotation, scale, and translation invariant features. Unlike 2D moments, the 3D moments characterise the joint spectral–spatial properties. A classification method is proposed that uses the features derived from 3D geometric moments without vectorising or changing the original structure of the raw hyperspectral image. Unlike many other methods, the new method does not need a separate step for spectral feature extraction or dimensionality reduction. The moments are computed on the raw image that generate a comprehensive and smaller feature set. The experimental results from five benchmark airborne hyperspectral images demonstrate that the 3D moment based method yields good classification results better or comparable to several state‐of‐the‐art methods.
Multi‐frame image super resolution using spatially weighted total variation regularisations
Authors: V Abdu Rahiman , George Sudhish N.
Published: April 2020

Image super resolution refers to a class of signal processing algorithms to post‐process a captured image to obtain its high resolution version. Multi‐frame super resolution synthesises high resolution image from multiple low resolution observations. Performance of super resolution algorithms are adversely affected by the noise present in the input images. To develop a noise robust multi‐frame image super resolution, an objective function is formulated which contains a weighted data fidelity term and a regularisation term consisting of a bilateral total variation (BTV) term and structure tensor total variation (STV) term. Both BTV and STV are weighted appropriately in a per pixel basis in such a way that the BTV contributes more in smooth regions and STV contributes more on the edges. These terms ensure the continuity of edges and the smoothness of flat regions. An adaptive weighting scheme with the data fidelity term helps to select the reliable pixel alone in the reconstruction process. The proposed method is experimentally evaluated for its performance in real data and different types of noises.
Physics‐based dynamic texture analysis and synthesis model using GPU
Authors: Ghadekar Premanand Pralhad
Published: April 2020

The texture is a repetition of a particular structure. Textures classified into static texture and dynamic texture. There are two approaches for synthesising dynamic textures: image‐based approach and physics‐based approach. In the proposed work, the synthesis of different dynamic textures is shown. The physics‐based approach is used to synthesise dynamic texture videos. Different mathematical models are proposed which are suitable to give appropriate motion to the dynamic textures. The raw frames are created, and these frames are further used to synthesise the dynamic textures using physics laws and mathematical formulae. The flexibility of each model is demonstrated. The proposed model has less specificity and less computational complexity. The proposed algorithms are implemented on the graphics processing unit to reduce the overall execution time and time complexity. High‐quality videos are produced, and the evaluation of every frame assures the quality.
Visual saliency based global–local feature representation for skin cancer classification
Authors: Xiao Feng , Wu Qiuxia
Published: April 2020

With the rapid increase in the cases of deadly skin cancer, the classification on different types of skin cancer has been emerging as one of the most significant issues in the field of medical image. Several approaches have been proposed to help in diagnosing the categories of the skin lesions by means of traditional features or leveraging the widely used deep learning models. However, there are lack of the integrated frameworks to combine the hand‐crafted traditional features and the deep Conv‐features. Furthermore, the effective way to extract global and local features is also conducive to distinguish the specific lesions from normal skin. Hence, in this study, the authors present an integrated model to acquire more representative global–local features including the traditional local binary pattern features and deep Conv‐features. In addition, several fusion strategies have conducted on the Global‐DNN and Local‐DNN for better performance. In order to extract more explicit features from the specific lesion areas, a target segmentation method based on visual saliency detection is employed to eliminate the background interference. Experimental results on ISIC‐2017 skin cancer dataset demonstrate that the proposed Global‐DNN and Global‐Local models can obtain more effective feature representation which achieve outperformed results for skin cancer classification.
Phase congruency and ODBTC based image retrieval
Authors: Gupta Shraddha , Modem Sudhakar , Thakre Vandana Vikas
Published: April 2020

In this study, the authors investigate content based image retrieval (CBIR) using ordered‐dither block truncation coding (ODBTC) and phase congruency feature (PCF). Relevant feature extraction plays a vital role for retrieving the image in CBIR. The unique reason to choose PCF with ODBTC is that it detects the edges and corners during variation of image while preserving image brightness and contrast. Combining the PCF and ODBTC features improves CBIR system usage in various visual data processing domains. Thus, yields a better CBIR system which assists in the reduction of storage space, decreases retrieval time and increases accuracy of the system. The precision and recall are used as performance metrics to evaluate the proposed method based on retrieval of relevant images. Extensive experimental results with Corel 1 K (1000 images), Corel 10 K (10000 images) and CALTECH 256 (30144 images) proves that the proposed method is more desirable than antecedent proposed CBIR system in terms of accuracy, precision and recall.
Vision‐based vehicle behaviour analysis: a structured learning approach via convolutional neural networks
Authors: Mou Luntian , Xie Haitao , Mao Shasha , Zhao Pengfei , Chen Yanyan
Published: April 2020

With the rapid development of artificial intelligence, the study of intelligent transportation is getting more and more attention and vision‐based vehicle behaviour analysis has become an active research field. Most existing methods label vehicle behaviours with discrete labels and then use the vehicle trajectories or motion characteristics to train classifiers which identify vehicle behaviours. However, a simple discrete label cannot contain detailed information about the vehicle behaviour. So, inspired by structured learning, the authors design a structured label which is used to characterise the instantaneous behavioural state based on the vehicle image, including behaviour trend and degree simultaneously. A structured convolutional neural networks model is constructed to learn and predict structured representation of transient vehicle behaviour and preliminary experimental results justify the feasibility of vehicle behaviour structural analysis model, but it achieves only 53.3% prediction accuracy. To reduce the risk of overfitting to small‐scale training data, the authors further propose an overfitting‐preventing deep neural network, which exploits transfer learning and multi‐task learning to achieve a much higher prediction accuracy of 91.1%.
Probabilistic indices for analysing the impact of penetration of distributed energy resources on system reliability
Authors: Paliwal Priyanka , Patidar Narayan Prasad , Nema Rajesh Kumar
Published: April 2020

Recent years have seen a steep increase in penetration of renewable energy sources (RES) based generators and storage devices; collectively referred as distributed energy resources (DERs). The traditional reliability indices used by utilities such as loss of load expectation, loss of energy expectation and loss of load probability are suitable for systems with conventional generators. However, they fail to acknowledge stochastic behaviour of RES based generators and energy limited capabilities of storage appropriately. In this study, new probabilistic reliability indices for investigating impact of penetration of DERs on system reliability have been proposed. In order to provide effective assessment, a reliability index referred as expectation of failure in grid connected mode (EFG) and three reliability indices viz. expectation of complete success in islanded mode, expectation of partial failure in islanded mode, expectation of complete failure in islanded mode have been proposed in grid connected mode and islanded mode, respectively. The mathematical formulation for proposed indices has been developed in probabilistic framework. The formulation has been implemented on a 33‐bus distribution feeder. Different penetration levels have been investigated to provide adequate justification for proposed indices. Parametric analyses with storage integration have also been carried out. The proposed reliability metrics will assist system planners to choose optimum penetration level with greater efficacy.
Application of an adaptive model predictive control algorithm on the Pelton turbine governor control
Authors: Beus Mateo , Pandžić Hrvoje
Published: April 2020

Traditionally, hydro turbine governor applications mainly rely on classical proportional–integral–derivative controllers. A classical controller can perform optimally only at the operating point chosen during the controller design. Since hydro power plants are highly non‐linear systems alternative control approaches based on adaptive parameters are needed. Historically, due to the limited computation capabilities of microprocessors and programmable logic controllers (PLCs) used in hydro turbine governors, adaptive control schemes were not frequently applied. However, the latest generation of microprocessors and PLCs facilitate the application of adaptive control scheme based on predictive control algorithm for plants with faster dynamic behaviour. In that regard, this study introduces an adaptive controller based on model predictive control (MPC) algorithm developed and applied to a non‐linear simulation model of a laboratory hydro power plant. The applied MPC algorithm is based on a linear prediction model whose parameters are identified offline for different operating points across the plant's operating range. The adaptive control scheme updates the prediction model parameters depending on the current operating point. Furthermore, the predictive control algorithm applied in this study is set up as a quadratic programming (QP) optimisation problem that is solved online using a QP solver in a form of Hildreth's algorithm.
Removal of micro‐Doppler effect in ISAR imaging based on time recursive iterative adaptive approach
Authors: Wang Yong , Zhou Xingyu , Zhang Rongzheng
Published: April 2020

The signal separation method based on the short time Fourier transform (STFT) and the L‐statistics can effectively eliminate the interference of the micro‐Doppler effect on inverse synthetic aperture radar (ISAR) imaging. The insufficient frequency resolution of STFT will result in poor interference cancellation when the azimuth range between two adjacent scatterers is small. Then, a novel method for the elimination of micro‐Doppler effect in ISAR imaging based on the time recursive iterative adaptive approach (TRIAA) is proposed here. This method uses the TRIAA technique to improve the frequency resolution compared with STFT, thereby enhancing the ability to process the complicated signal. The ISAR imaging results for the simulation model and raw data illustrate the effectiveness of the algorithm here.
Deep Horizon: A machine learning network that recovers accreting black hole parameters
Authors: van der Gucht Jeffrey , Davelaar Jordy , Hendriks Luc , Porth Oliver , Olivares Hector , Mizuno Yosuke , Fromm Christian M. , Falcke Heino
Published: April 2020

Context. The Event Horizon Telescope recently observed the first shadow of a black hole. Images like this can potentially be used to test or constrain theories of gravity and deepen the understanding in plasma physics at event horizon scales, which requires accurate parameter estimations.

Aims. In this work, we present Deep Horizon, two convolutional deep neural networks that recover the physical parameters from images of black hole shadows. We investigate the effects of a limited telescope resolution and observations at higher frequencies.

Methods. We trained two convolutional deep neural networks on a large image library of simulated mock data. The first network is a Bayesian deep neural regression network and is used to recover the viewing angle i, and position angle, mass accretion rate Ṁ, electron heating prescription Rhigh and the black hole mass MBH. The second network is a classification network that recovers the black hole spin a.

Results. We find that with the current resolution of the Event Horizon Telescope, it is only possible to accurately recover a limited number of parameters of a static image, namely the mass and mass accretion rate. Since potential future space-based observing missions will operate at frequencies above 230 GHz, we also investigated the applicability of our network at a frequency of 690 GHz. The expected resolution of space-based missions is higher than the current resolution of the Event Horizon Telescope, and we show that Deep Horizon can accurately recover the parameters of simulated observations with a comparable resolution to such missions.
An Investigation of Mixed Reality Technology for Onsite Construction Assembly
Authors: DaValle Austin , Azhar Salman
Published: April 2020

The construction industry often falls short of other industries in terms of innovation; overall productivity within the construction industry has remained nearly flat for fifty years. As such, the industry is frequently exploring new technologies with the potential to increase its work efficiency as well as productivity. Mixed Reality (MR), which allows for the blending of real and virtual worlds, is one such technology that has a capability to improve productivity. The aim of this research study is to test MR’s potential as an onsite assembly tool in construction. The study more specifically determined if holographic BIM models, spatially anchored in 1:1 ratio over active construction sites, could provide trades’ sufficient information to assemble and install their work without using paper plans. A controlled experiment was designed to test if the electrical and plumbing components of a mock-bathroom could be installed only with MR. A total of 5 sub-groups, each consisting of two participants, took part in this experiment and the time is taken by each sub-group (i.e. the MR group) to complete the assembly was recorded. This was then compared with the time taken by a similar number of sub-groups (i.e. the Control group) to complete the same assembly using paper plans only. The analysis indicates that on average the MR group took approximately 9% less time as compared to the Control group. Qualitative analysis via a post-exercise questionnaire found several technological limitations that the MR must overcome before it sees widespread implementation as a tool for guiding construction assembly. The post-exercise questionnaire also gathered participants’ perceptions about MR potential in construction. This paper highlights the benefits and limitations of the MR technology in construction along with recommendations for improvement as well as future research.
Descarga de peso no pós-operatório de fratura de planalto tibial: Revisão sistemática da literatura
Authors: Alves Débora Pinheiro Lédio , Wun Paloma Yan Lam , Alves Andréia Lima , Christian Ralph Walter , Mercadante Marcelo Tomanik , Hungria José Octávio
Published: April 2020

As fraturas do planalto tibial constituem risco à integridade funcional do joelho, afetando o alinhamento axial e podendo levar à dor e à incapacidade do indivíduo. O suporte de carga e a mobilização articular precoce podem prevenir esses déficits e acelerar o processo de reabilitação. O objetivo do presente trabalho foi realizar uma revisão da literatura sobre estudos que citam o início, evolução e critérios de progressão do suporte de carga no pós-operatório das fraturas de planalto tibial. Foram selecionados artigos publicados nos últimos 12 anos, nos idiomas português e inglês, que descrevessem o tempo de início e progressão do suporte de carga, considerando a gravidade da fratura. Foram selecionados 36 artigos na literatura. Não há consenso na literatura quanto ao início e evolução do suporte de carga no pós-operatório das fraturas do planalto tibial. Contudo, observa-se relação entre a gravidade da fratura e o tempo de início da carga.
Impacto da campanha “Considere o Risco”, da Sociedade Brasileira de Ortopedia e Traumatologia, na percepção do risco e na utilização do checklist cirúrgico por ortopedistas brasileiros
Authors: Bähr Germana Lyra , Motta Filho Geraldo da Rocha
Published: April 2020

Objetivo Analisar o impacto das ações educacionais inseridas na campanha “Considere o Risco”, da Sociedade Brasileira de Traumatologia e Ortopedia (SBOT), para aumentar a percepção do risco envolvido na atividade cirúrgica e a utilização do checklist cirúrgico.

Métodos Realização de pesquisa comparativa, durante o 50° Congresso Brasileiro de Ortopedia e Traumatologia (50° CBOT), em novembro de 2018, utilizando questionário semelhante ao de duas versões anteriores.

Resultados O número de participantes foi de 730, correspondendo à 18,7% do total de 3903 inscritos no 50° CBOT. No total, 542 ortopedistas (74,2%) relataram já ter vivenciado erros dentro do centro cirúrgico e 218 (29,8%) cirurgias em locais errados; 624 participantes (85,5%) afirmaram marcar o local da cirurgia e 402 (55%) utilizar regularmente o checklist cirúrgico.

Conclusão Na amostra pesquisada, ficou evidenciado que os esforços da SBOT para a disseminação do conhecimento do protocolo da Organização Mundial de Saúde (OMS) foram efetivos, reduzindo a quantidade de ortopedistas que o desconheciam de 65,3% (em 2012) para 20,7% (em 2018), e ampliando sua utilização. Em 2018, 402 ortopedistas (55% da amostra) referiram fazer uso frequente do protocolo no ambiente cirúrgico, em comparação com 301 (40,2%) em 2014. Estes dados confirmam a necessidade de campanhas educacionais e treinamentos sistemáticos, não apenas para promover uma mudança de comportamento, como também, principalmente, uma mudança cultural.
O papel da ressonância magnética no diagnóstico da síndrome compartimental crônica do exercício
Authors: Nico Marcelo Astolfi Caetano , Carneiro Bruno Cerretti , Zorzenoni Fernando Ometto , Ormond Filho Alípio Gomes , Guimarães Julio Brandão
Published: April 2020

A síndrome compartimental crônica é uma condição comum e frequentemente subdiagnosticada, induzida pelo exercício, que corresponde em média a um quarto dos casos de dor crônica na perna relacionada ao exercício, e que perde em frequência apenas para o espectro fratura/reação ao estresse tibial. Tradicionalmente ocorre em jovens atletas corredores, embora estudos mais recentes tenham demonstrado uma prevalência considerável em praticantes de atividade física de baixo rendimento, mesmo em pacientes de meia-idade ou idosos. A lista de diagnósticos diferenciais é extensa, e por vezes é difícil fazer a distinção apenas pelos dados clínicos, sendo necessários exames subsidiários.

Classicamente, o diagnóstico é feito pelo quadro clínico, pela exclusão dos diferenciais, e pela medida pressórica intracompartimental. Embora a manometria por agulha seja considerada o padrão-ouro no diagnóstico, seu uso não é universalmente aceito, visto que existem algumas limitações importantes, além da disponibilidade restrita do equipamento com agulha no Brasil. Recentemente, novos protocolos de manometria têm sido propostos a fim suplantar a deficiência dos tradicionais, com algum deles inclusive recomendando o uso sistemático da ressonância magnética (RM) na exclusão dos diagnósticos diferenciais. O uso de sequências de RM sensíveis a líquido pós-esforço é uma ótima opção não invasiva à manometria por agulha no diagnóstico da síndrome compartimental crônica, uma vez que o aumento da intensidade de sinal pós-exercício é estatisticamente relevante quando comparados os valores pressóricos de manometria em pacientes com a síndrome e assintomáticos; portanto, o exame pode ser usado no critério diagnóstico. O tratamento definitivo é a fasciotomia, embora existam alternativas menos eficazes.
Mielopatia cervical secundária a gota: Relato de caso
Authors: Matos Thiago Dantas , Teixeira Kelsen de Oliveira , Fleury Rodrigo Barra Caiado , Costa Herton Rodrigo Tavares , Pádua Joel Del Bel , Defino Helton Luiz Aparecido
Published: April 2020

A gota é uma artropatia cristalina frequente na população; entretanto, a espondiloartropatia gotosa, também chamada de gota axial, é incomum. O presente relato de caso apresenta um caso raro de mielopatia cervical secundária a gota axial. Uma paciente de 50 anos de idade, sem patologias prévias, apresentou quadro de perda de força, alteração de sensibilidade e liberação piramidal há 2 anos. A tomografia computadorizada evidenciou imagem lítica no processo espinhoso de C7, e sinais de mielopatia com mielomalácia foram observados na ressonância magnética da coluna cervical. Após o procedimento cirúrgico e biópsia do material, o diagnóstico foi de gota, e o tratamento para a patologia foi iniciado, com melhora completa do quadro. O diagnóstico de gota axial deve ser incluído no espectro do diagnóstico diferencial das doenças que acometem a coluna vertebral. Apesar de a espondiloartrite gotosa ser incomum, há uma ocorrência subestimada devido a não investigação dos casos. O diagnóstico precoce e tratamento da patologia pode evitar que pacientes apresentem complicações da doença, como a relatada no presente estudo.
Hepatic Stellate Cell–Macrophage Crosstalk in Liver Fibrosis and Carcinogenesis
Authors: Matsuda Michitaka , Seki Ekihiro
Published: April 2020

Chronic liver injury due to viral hepatitis, alcohol abuse, and metabolic disorders is a worldwide health concern. Insufficient treatment of chronic liver injury leads to fibrosis, causing liver dysfunction and carcinogenesis. Most cases of hepatocellular carcinoma (HCC) develop in the fibrotic liver. Pathological features of liver fibrosis include extracellular matrix (ECM) accumulation, mesenchymal cell activation, immune deregulation, and angiogenesis, all of which contribute to the precancerous environment, supporting tumor development. Among liver cells, hepatic stellate cells (HSCs) and macrophages play critical roles in fibrosis and HCC. These two cell types interplay and remodel the ECM and immune microenvironment in the fibrotic liver. Once HCC develops, HCC-derived factors influence HSCs and macrophages to switch to protumorigenic cell populations, cancer-associated fibroblasts and tumor-associated macrophages, respectively. This review aims to summarize currently available data on the roles of HSCs and macrophages in liver fibrosis and HCC, with a focus on their interaction.
Manifold learning for organizing unstructured sets of process observations
Authors: Dietrich Felix , Kooshkbaghi Mahdi , Bollt Erik M. , Kevrekidis Ioannis G.
Published: April 2020

Data mining is routinely used to organize ensembles of short temporal observations so as to reconstruct useful, low-dimensional realizations of an underlying dynamical system. In this paper, we use manifold learning to organize unstructured ensembles of observations (“trials”) of a system’s response surface. We have no control over where every trial starts, and during each trial, operating conditions are varied by turning “agnostic” knobs, which change system parameters in a systematic, but unknown way. As one (or more) knobs “turn,” we record (possibly partial) observations of the system response. We demonstrate how such partial and disorganized observation ensembles can be integrated into coherent response surfaces whose dimension and parametrization can be systematically recovered in a data-driven fashion. The approach can be justified through the Whitney and Takens embedding theorems, allowing reconstruction of manifolds/attractors through different types of observations. We demonstrate our approach by organizing unstructured observations of response surfaces, including the reconstruction of a cusp bifurcation surface for hydrogen combustion in a continuous stirred tank reactor. Finally, we demonstrate how this observation-based reconstruction naturally leads to informative transport maps between the input parameter space and output/state variable spaces.
A clinically aligned experimental approach for quantitative characterization of patient-specific cardiovascular models
Authors: Narata Ana Paula , Silva de Moura Fernando , Patat Fréderic , Marzo Alberto , Larrabide Ignacio , Gregoire Jean-Marc , Perrault Cecile , Sennoga Charles A. , Bouakaz Ayache
Published: April 2020

Recent improvements in computational tools opened the possibility of patient-specific modeling to aid clinicians during diagnosis, treatment, and monitoring. One example is the modeling of blood flow for surgical planning, where modeling can help predict the prognosis. Computational analysis is used to extract hemodynamic information about the case; however, these methods are sensitive to assumptions on blood properties, boundary conditions, and appropriate geometry accuracy. When available, experimental measurements can be used to validate the results and, among the modalities, ultrasound-based methods are suitable due to their relative low cost and non-invasiveness. This work proposes a procedure to create accurate patient-specific silicone replicas of blood vessels and a power Doppler compatible experimental setup able to simulate and measure realistic flow conditions. The assessment of silicone model geometry shows small discrepancies between these and the target geometries (median of surface error lies within 57 µm and 82 μm). Power Doppler measurements were compared against computational fluid dynamics results, showing discrepancies within 10% near the wall. The experimental approach offers a setup to quantify flow in in vitro systems and provide more accurate results where other techniques (e.g., particle image velocimetry and particle tracking velocimetry) have shown limitations due to the interference of the interface.
First-principles study of anomalous Nernst effect in half-metallic iron dichloride monolayer
Authors: Syariati Rifky , Minami Susumu , Sawahata Hikaru , Ishii Fumiyuki
Published: April 2020

We performed first-principles simulations to elucidate the transverse thermoelectric effect (anomalous Nernst effect) of the half-metallic FeCl2 monolayer. We analyzed its thermoelectricity based on the semiclassical transport theory including the effect of Berry curvature and found that carrier-doping induced a large anomalous Nernst effect that was ∼6.65 μV/K at 100 K if we assumed 10 fs for the relaxation time. This magnitude originates in a large Berry curvature at the K-point of a hexagonal Brillouin zone. These results suggest that two-dimensional ferromagnetic half-metallic materials can potentially be used in thermoelectric devices.
Physics of the implosion up until the time of ignition in a revolver (triple-shell) capsule
Authors: Keenan Brett D. , Taitano William T. , Molvig Kim
Published: April 2020

A revolver is designed to have two dynamical fuel implosion stages to reach ignition: a shock phase in which the fuel is pre-heated up until the shock collapses at the capsule center, followed by an adiabatic compression phase to ignition. This picture assumes ideal hydrodynamics. Employing the state-of-the-art, hybrid (kinetic-ion/fluid electron), multi-ion Vlasov-Fokker-Planck code, iFP, along with semi-analytic predictions from ideal hydrodynamics in spherical geometry, we confirm this two phase picture—resolving some outstanding questions in Revolver design along the way. Although we find that shock kinetic effects and non-ideality are present in the course of the implosion, these effects do not change the overall dynamics (which is well described by ideal hydrodynamics theory). Additionally, we put the assumption of adiabaticity, for the post-collapse phase, to the test. Finally, we verify the ideal hydro-conjecture that the shock collapse (fuel) convergence is ∼2.12 given a single shock, and we confirm that the convergence is about 2.5 in the case of two shocks—in agreement with previous radiation-hydrodynamics simulations.
Anti-symmetric representation of the extended magnetohydrodynamic equations
Authors: Halpern Federico D.
Published: April 2020

We introduce the anti-symmetric representation of the extended magnetohydrodynamic (MHD) equations. In this representation, the use of the anti-symmetric flux operator (∇·v+v·∇) results in conservation theorems with discrete analogs. Inherently robust numerical applications are achieved with little effort, and conservation to machine precision is possible with simple numerical schemes. Starting from the two-fluid equations, we construct a single-fluid MHD model based on generalized center-of-mass variables for the mass (ρ), momentum (ρv), and pressure (p). This model is shown to possess identical conservation properties to the two-fluid system, with the only restriction being the use of a single temperature. Common approximations to the Braginskii heat fluxes and to the gyroviscous stress tensor are cast into our representation for convenience. The discrete conservation properties are verified using the classic Orszag–Tang vortex problem. In addition to the favorable mass, momentum, and energy conservation properties, the time reversibility of the simulations is demonstrated.
Diamond nanocrystal thin films: Case study on surface texture and power spectral density properties
Authors: Solaymani Shahram , Ţălu Ştefan , Nezafat Negin Beryani , Rezaee Sahar , Kenari Mahboubeh Fathi
Published: April 2020

Analyzing diamond nanocrystal (DNC) thin film morphology produced by the HFCVD technique is the main objective of the present work. Stereometric analysis of three-dimensional surface microtextures was carried out based on data obtained through atomic force microscopy (AFM), while the ISO 25178-2:2012 standard was applied to characterize surface topography. The Abbott–Firestone curve, peak count histograms, and Cartesian graphs, which were extracted through AFM images, gave valuable statistical information. As can be seen, the most isotropic sample was the Au catalyst (etched) deposited by the hot filament chemical vapor deposition method. Moreover, by increasing the time of DNC growth from 15 min to 60 min, the surface roughness was increased. In addition, the average power spectral density was calculated and furrows were determined for all samples.
Labyrinthine acoustic metastructures enabling broadband sound absorption and ventilation
Authors: Kumar Sanjay , Lee Heow Pueh
Published: April 2020

There is growing interest in the development of path coiling-based labyrinthine acoustic metamaterials for realizing extraordinary acoustical properties such as low-to-mid frequency sound absorption. We present a subwavelength labyrinthine acoustic metastructure (≤3 cm) exhibiting a superior sound absorption with a high bandwidth (more than one octave in the range of 400–1400 Hz). The metastructure is orchestrated of multiple labyrinthine unit cells of different configurations in a hexagonal array, and broadband absorption has been achieved by the dissipation of incident propagating sound waves inside the labyrinthine zigzag channels. Furthermore, the unique design of the metastructure allows for simultaneous air circulation for facilitating natural ventilation and sound absorption. The proposed unique designs may find potential applications in architectural acoustics and noise shielding where simultaneous natural ventilation and noise mitigation are required.
Developing workplace Skills
Authors: Lee Gary , Knight Peter , Errington Sharyn , Traynor Peter
Published: April 2020

The business of science education; Training science students in communication; Presentation skills
Embracing astrobiology
Authors: Walter Malcolm
Published: April 2020

?Astrobiology? is a term popularised in 1998 by a decision of the US space agency NASA to establish the NASA Astrobiology Institute (NAI). The then Administrator of NASA, Daniel Goldin, declared that ?biology will be the science of the 21st century?. The NAI was established to promote research aimed at gaining a fundamental understanding of the full potential of living systems. Its goal is to understand how life begins and evolves, whether life exists elsewhere in the universe, and what the future holds for life on Earth and beyond. While such broadly interdisciplinary research is not entirely new, the NAI was to give it new vigour and new resources. And it has.
Viruses in the placenta
Authors: C Munro Sian
Published: April 2020

Many different viruses can infect placental cells and are associated with congenital infection (Table 1). Viruses such as rubella, cytomegalovirus (CMV) and parvovirus are recognised as infectious agents of the placenta and foetus. Herpes simplex virus (HSV), varicella, human immunodeficiency virus (HIV), hepatitis B virus (HBV) and enterovirus occasionally infect the placenta and foetus, but are more commonly known as perinatal pathogens. Other viruses such as adenovirus and adeno-associated virus (AAV) have been found to infect the placenta, but a causative link between viral infection and poor pregnancy outcome has not yet been definitively established.
Cryptococcosis in Australian Wildlife
Authors: Krockenberger Mark , Stalder Kathryn , Malik Richard , Canfield Paul
Published: April 2020

Cryptococcosis is the most important systemic fungal disease to affect mammalian hosts in Australia. Although recent taxonomic developments have somewhat confused the nomenclature of the causative agents, it is now generally accepted that the Cryptococcus neoformans complex may be divided into two separate species, namely C. neoformans and C. gattii.
Vertical Transmission, August 2005
Authors: Rood Julian
Published: April 2020

Associate Professor Keryn Christiansen, who is the Director of the Department of Microbiology and Infectious Diseases at Royal Perth Hospital, has been elected unopposed as President-elect of ASM. A/Prof Christiansen will take up her position after the Annual General Meeting in Canberra in September. She will then assume the office of President of the ASM from July 2006 for a two year term. A/Prof Christiansen is responsible for the Gram Positive Typing and Research Unit in Western Australia, which has a strong research interest in MRSA including genetics, epidemiology and virulence determinants. Her other areas of interest include antibiotic resistance, pharmacodynamics and infection control. Keryn brings a wealth of experience to her new role in ASM. She is currently President of the International Society for Infectious Diseases, President of the Australian Society for Antimicrobials, a Member of the National Health and Medical Research Committee (NHMRC) Expert Advisory Committee on Antimicrobial Resistance and a member of the World Health Organisation Working Party to develop the Framework for the WHO Global Strategy for the Containment of Antimicrobial Resistance. I am sure that she will prove to be an outstanding President and I very much look forward to working with her over the next few years.
Connecting industry and the Bioresource Collection and Research Center (BCRC) in Taiwan
Authors: Chen Yu-Fen , Yuan Gwo-Fang , Liao Chii-Cherng
Published: April 2020

The Bioresource Collection and Research Center (BCRC) aims to connect with industry in Taiwan. Intellectual property and quality management systems are integrated to BCRC?s management accordingly.
Point of care using simple/rapid HIV tests
Authors: Learmonth Kate , McPhee Dale , M Dax Elizabeth
Published: April 2020

Movement of HIV testing to point of care (POC) has been facilitated by the availability of simple/rapid anti-HIV immunoassays. These assays have been used at health centres in the United States, Canada and at voluntary counselling and testing centres in developing countries. While this approach has revolutionised HIV screening in some areas, there are ethical, legal and quality assurance considerations that must be addressed before POC HIV testing is universally accepted.
Bacterial gene regulation: an overview
Authors: K Davies John , I Rood Julian
Published: April 2020

Bacteria are highly efficient and metabolically flexible organisms, with their genomes providing them with the ability to adapt to many different environmental conditions. For example, pathogens like Escherichia coli and Clostridium perfringens grow and survive very well in water and soil, respectively, but are also highly adapted to growth in the human body
Influenza: achievements and challenges An historical snapshot
Authors: W Hampson Alan
Published: April 2020

I have worked with influenza over a period of 40 years and, with each passing year, I have become more aware of its impact and more intrigued by the fascinating biology and natural history of the causative viruses. Influenza wasn?t my first experience in virology, having worked initially in a poliomyelitis vaccine R&D programme following the introduction of Salk vaccine into Australia by Val Bazeley. I had something of a jaundiced view when my next project was to assist in applying the virus dissociation methods of Laver & Webster to the production of an improved, less reactogenic influenza vaccine. Although William Farr had alerted the medical profession as early as 1847 to the excess mortality associated with influenza outbreaks, like many others, I regarded influenza as little more than a winter season inconvenience.
Pandemic planning: the Australian response
Authors: McKinnon Moira
Published: April 2020

If the world comes face to face with a rapidly spreading novel virus like the one that emerged in 1918, then the rapid detection of human to human transmission, early and intensive implementation of containment measures, and the development and deployment of effective vaccine are our best strategy for responding.