bluuebunny/crossref_metadata_2025 huggingface dataset:
The inflammasome NLRP3 plays a dual role on mouse corpora cavernosa relaxation
Authors: Fais Rafael S. , Rodrigues Fernanda L. , Pereira Camila A. , Mendes Allan C. , Mestriner Fabíola , Tostes Rita C. , Carneiro Fernando S.
Published: November 2019

NLRP3 plays a role in vascular diseases. Corpora cavernosa (CC) is an extension of the vasculature. We hypothesize that NLRP3 plays a deleterious role in CC relaxation. Male C57BL/6 (WT) and NLRP3 deficient (NLRP3−/−) mice were used. Intracavernosal pressure (ICP/MAP) measurement was performed. Functional responses were obtained from CC strips of WT and NLRP3−/− mice before and after MCC950 (NLRP3 inhibitor) or LPS + ATP (NLRP3 stimulation). NLRP3, caspase-1, IL-1β, eNOS, nNOS, guanylyl cyclase-β1 (GCβ1) and PKG1 protein expressions were determined. ICP/MAP and sodium nitroprusside (SNP)-induced relaxation in CC were decreased in NLRP3−/− mice. Caspase-1, IL-1β and eNOS activity were increased, but PKG1 was reduced in CC of NLRP3−/−. MCC950 decreased non-adrenergic non-cholinergic (NANC), acetylcholine (ACh), and SNP-induced relaxation in WT mice. MCC950 did not alter NLRP3, caspase-1 and IL-1β, but reduced GCβ1 expression. Although LPS + ATP decreased ACh- and SNP-, it increased NANC-induced relaxation in CC from WT, but not from NLRP3−/− mice. LPS + ATP increased NLRP3, caspase-1 and interleukin-1β (IL-1β). Conversely, it reduced eNOS activity and GCβ1 expression. NLRP3 plays a dual role in CC relaxation, with its inhibition leading to impairment of nitric oxide-mediated relaxation, while its activation by LPS + ATP causes decreased CC sensitivity to NO and endothelium-dependent relaxation.
Reduced graphene oxide-gold nanoparticles-catalase-based dual signal amplification strategy in a spatial-resolved ratiometric electrochemiluminescence immunoassay
Authors: Cao Jun-Tao , Fu Xiao-Long , Liu Fu-Rao , Ren Shu-Wei , Liu Yan-Ming
Published: November 2019

A novel spatial-resolved electrochemiluminescent (ECL) ratiometry for cardiac troponin I (cTnI) analysis was developed using resonance energy transfer (RET) and a coreactant consumption strategy for signal amplification.
A safe, convenient liquid phase pre-sodiation method for titanium-based SIB materials
Authors: Cao Yang , Zhang Tianqi , Zhong Xingguo , Zhai Tianyou , Li Huiqiao
Published: November 2019

We develop a pre-sodiation method by simply immersing the electrode in a liquid sodium source to reduce irreversible capacity loss for titanium-based materials.
Synergistic bio-recognition/spatial-confinement for effective capture and sensitive photoelectrochemical detection of MCF-7 cells
Authors: Wu Dan , Zhang Zhonghai
Published: November 2019

A synergistic bio-recognition/spatial-confinement strategy is proposed for the effective capture of cancer cells and sensitive photoelectrochemical detection with the lowest limit of detection of 2 cells per mL.
3D cultures for modeling nanomaterial-based photothermal therapy
Authors: Darrigues Emilie , Nima Zeid A. , Griffin Robert J. , Anderson James M. , Biris Alexandru S. , Rodriguez Analiz
Published: November 2019

3D culture integrates key characteristics to advance and challenge Nanomedicine, supporting cancer diagnosis, imaging and treatment as photothermal therapy.
Acidic ion functionalized N-doped hollow carbon for esterification of levulinic acid
Authors: Zhang Qifang , Jiang Pingping , Nie Zhixin , Zhang Pingbo
Published: November 2019

Unique hollow carbon spheres with high acidity were used for the efficient catalytic synthesis of ethyl levulinate with good reusability.
Role of double interfaces in inspiring energy storage devices in CC@Ni(OH)Cl@NiO flexible electrodes
Authors: Fu Sixian , Li Liping , Meng Lingshen , Gao Mengyue , Xu Shuaikai , Wang Xiyang , Zhang Yuelan , Li Guangshe
Published: November 2019

The synergistic double interfaces in CC@Ni(OH)Cl@NiO flexible electrode stabilize Ni–O covalency and stimulate active electronic behavior for superior electrochemical performance.
Manipulating light trapping and water vaporization enthalpy via porous hybrid nanohydrogels for enhanced solar-driven interfacial water evaporation with antibacterial ability
Authors: Li Yaling , Zhao Mingyu , Xu Yunshi , Chen Leilei , Jiang Ting , Jiang Weicun , Yang Shuguang , Wang Yi
Published: November 2019

Porous MoS2 nanoflower-containing hydrogels are proposed as enhanced light trapping and antibacterial photothermal hotspots and are facilely deposited on a hydrophilic MCE substrate for highly efficient solar-driven interfacial water evaporation.
ZnS spheres wrapped by an ultrathin wrinkled carbon film as a multifunctional interlayer for long-life Li–S batteries
Authors: Yang Jin-Lin , Zhao Shi-Xi , Lu Yi-Ming , Zeng Xiang-Tian , Lv Wei , Cao Guo-Zhong
Published: November 2019

Herein, a graphene-like wrinkled carbon film (WCF) wrapped zinc sulfide (ZnS) spheres hybrid interlayer material was fabricated. Li-S batteries coupled with ZnS@WCF interlayer showed excellent capacity retention and outstanding rate performance.
Significant increase in efficiency and limited toxicity of a solar cell based on Sb2Se3 with SnO2 as a buffer layer
Authors: Guo Huafei , Chen Zhiwen , Wang Xin , Cang Qingfei , Ma Changhao , Jia Xuguang , Yuan Ningyi , Ding Jianning
Published: November 2019

A Sb2Se3 device based on SnO2 with the highest efficiency has been obtained by adding ultrathin CdS between the FTO and SnO2 film.
An integrated self-healable and robust conductive hydrogel for dynamically self-adhesive and highly conformable electronic skin
Authors: Shao Changyou , Meng Lei , Cui Chen , Yang Jun
Published: November 2019

A novel dynamic self-adhesive and self-healable conductive hydrogel material that is applicable to highly conformal and ultrasensitive electronic skin devices.
Teaching Preschoolers With Down Syndrome Using Augmentative and Alternative Communication Modeling During Small Group Dialogic Reading
Authors: Quinn Emily D. , Kaiser Ann P. , Ledford Jennifer R.
Published: November 2019

Purpose

This study evaluated the effect of aided augmentative and alternative communication modeling (AAC-MOD) on the communication skills of children with Down syndrome (DS) during small group dialogic reading.

Method

Four children with DS between 3;1 and 5;3 (years;months;M= 4;5) and 5 typically developing peers between 3;5 and 5;9 (M= 4;3) participated. Effects were examined using a multiple probe across behaviors design with 4 children with DS. To simulate typical dialogic reading routines in inclusive classrooms, a strategy calledRead, Ask, Answer, Prompt(Binger, Kent-Walsh, Ewing, & Taylor, 2010) was applied during the baseline and intervention sessions.

Results

A functional relation was demonstrated between (a) AAC-MOD and percentage of correctly identified symbols for 3 participants, (b) AAC-MOD and rate of symbolic communication for 2 participants, and (c) AAC-MOD and number of different words for 2 participants. Increases in number of multiple word combinations occurred for 2 participants. All 4 children maintained their percentage of correctly identified symbols. Increases in rate of symbolic communication did not generalize to thematic play contexts, a distal measure of response generalization.

Conclusion

AAC-MOD is an effective strategy for teaching target vocabulary and increasing rate of symbolic communication in young children with DS.

Supplemental Material

https://doi.org/10.23641/asha.10093538
Adaptive preview control of single‐point path tracker for car‐like delivery service robot
Authors: Bae I. , Kim J.H. , Kim S.
Published: November 2019

The purpose of this research is to design a simple and intuitive path tracker to minimise the distance error of a car‐like delivery service robot using only a position sensor, i.e. global positioning system in outdoor environments. The authors proposed not only a single‐point preview path tracker (SPP), but also a curvature‐based preview control using a quadratic curve fitting technique. This method can provide flexibility in preview distance control even at a constant speed, and reduces the burden of an actuator for maintenance. Furthermore, the performance of the proposed adaptive SPP is considerably improved compared to that when using a fixed preview distance.
Magnet temperature estimation based on a novel frequency determination algorithm for the five‐phase PMa‐SynRM
Authors: Arafat AKM , Islam Md Khurshedul , Herbert Joseph , Choi Seungdeog
Published: November 2019

This study presents a novel frequency determination algorithm for the magnet temperature estimation of a five‐phase permanent magnet assisted synchronous reluctance motor (PMa‐SynRM) using the signal injection method. The signal injection method is a convenient and non‐invasive approach to determine the magnet temperature in permanent magnet motors by exploiting the temperature dependency of magnet resistance. However, its implementation as a magnet temperature estimation tool warrants an adaptive frequency determination method in order to ensure its effective employability under more pragmatic dynamic operations. The proposed method in this study proposes an analysis of the frequency spectrum to isolate the fundamental and fault frequencies and their respective harmonics to determine a range of available frequencies that may be employed in this method. The available frequencies are further concentrated based on the signal‐to‐noise ratio constraints. As an additional part of the contribution of this study, an innovative rotating hardware set‐up is developed which would transmit the magnet temperature data wirelessly to verify the accuracy of the proposed temperature estimation algorithm.
Computation of core losses in electrical sheets used in electrical machines
Authors: Szczygłowski Jan , Jabłoński Paweł
Published: November 2019

One of the most important quantities for magnetic materials is energy loss, usually expressed in terms of loss per mass unit and one cycle. From an engineering point of view, it would be desirable to have an accurate and simple model of energy losses in electrical sheets. This study presents a new approach to describing core losses in electrical sheets. The proposed approach allowed one obtaining a new formula for total losses in the material, in which only basic material coefficients such as material conductivity and magnetic permeability expressed in the form of a magnetic hysteresis loop are needed. The expressions used so far are semi‐empirical, whereas the proposed model clearly indicates how the material parameters affect the losses. This stays in contrary to the approach in which the hysteresis losses are obtained from measurements by extrapolation of the ratio of losses and frequency when the frequency tends to zero. The obtained expression for total losses in the material was compared with the commonly used expression proposed by Bertotti, and comparable approximation errors of prediction were obtained. The comparisons were made on the example of non‐oriented electrical sheets.
Low‐loss and lightweight magnetic material for electrical machinery
Authors: Ahmadi Farzad , Sozer Yilmaz , Donahue Michael J. , Tsukerman Igor
Published: November 2019

A low‐loss and lightweight core material, with applications in electrical machinery, is made of highly packed and insulated magnetic microwires (MWs). These MWs are aligned in such a way as to guide the flux in the rotor/stator, with the ultimate goal of increasing the efficiency and substantially reducing core losses. Commercial ‐based MWs with a 127 μm diameter and a 33 μm insulation coating are utilised. The magnetic measurements of the fabricated sample demonstrate the high permeability and low core loss in a wide range of frequencies. To prove the utility of this type of material, the authors used it in the rotor core of a prototype 25 W three‐phase synchronous reluctance machine. The core is lighter and the losses are significantly lower than in conventional core materials under the same torque density.
Mitigation of cogging torque in TFPM machines with flux concentrators and evaluation of the structures by using the SC method
Authors: Taravat Sajad , Kiyoumarsi Arash , Bracikowski Nicolas
Published: November 2019

In this study, the effect of adding of new stator and rotor slots on cogging torque of a transverse‐flux permanent‐magnet (TFPM) machine with flux concentrators is studied. To reduce the cogging torque, the widths and the positions of the slots of concern are improved through three‐dimensional finite element method (3D‐FEM). After that, to validate the 3D‐FEM results, cogging torque is determined by applying a Schwarz–Christoffel (SC) conformal mapping. To apply this transformation, the 3D TFPM structure with axially magnetised PM is converted into a 2D structure with radially magnetised PMs and cogging torque of the machine is predicted using both the analytical method and 3D‐FEM. The agreement in the obtained results through this SC mapping and the 3D‐FEM method is the indicative of the accuracy of the efforts.
Comparison and analysis of permanent magnet vernier motors for low‐noise in‐wheel motor application
Authors: Wu Zhanchuan , Fan Ying , Zhang Qiushi , Gao Dawei
Published: November 2019

In this study, the permanent magnet vernier motors (PMVMs) with different external rotor topologies are investigated and compared to obtain the optimal topology, which can reduce the vibroacoustic noise and keep the excellent output performance. Firstly, the unipolar and bipolar PMVM motors with V‐shape magnets are designed based on the torque and cost of the consequent‐pole PMVM (CPMVM), which have the reduced unbalanced magnetic force (UMF). Then to evaluate the performances of PMVMs comprehensively, the characteristics including flux density, back‐electromotive force, torque, the electromagnetic force and acoustic noise etc., are quantitatively investigated and compared by the finite element analysis (FEA). Finally, the modal parameters and acoustics noise spectrum of CPMVM are tested and compared with the noise FEA results, which verify the V‐shape magnet PMVMs can reduce the UMF and low‐frequency noise level by maintaining the output performance.
Design and performance analysis of various high torque segmented rotor HE‐FSM topologies for aircraft applications
Authors: Ali Hassan , Sulaiman Erwan , Kosaka Takashi
Published: November 2019

Electrical machines for aircraft applications require basic characteristics such as lightweight, high reliability, fault tolerance ability, and torque power and higher densities. Correspondingly, hybrid excitation flux switching machines (HE‐FSMs) are capable of producing significant characteristics of high torque and power by improving flux strengthening in the iron core. However, magnetic flux cancellation and leakage in HE‐FSMs cause the reduction of flux linkage created by permanent magnet (PM) and field excitation (FE), which leads to deterioration of electromagnetic torque. This study presents magnetic flux performance and comparison of various topologies of HE‐FSMs by employing different positions of PMs and FE coils on the stator core. The purpose of a segmented rotor is to deliver a well‐defined electromagnetic flux pathway for carrying magnetic flux to nearby armature coil on stator with rotor rotation to improve the flux strengthening. Moreover, magnetic performances of various proposed HE‐FSMs at different positions of PMs are investigated and compared based on 2D finite element analysis. Subsequently, the enhanced HE‐FSM III has successfully achieved flux strengthening of 22%, torque of 54% and power of 61% more than initial design of HE FSM I, respectively. In conclusion, the proposed HE‐FSM structures show the capability to match high torque and power for aircraft applications.
Rotor eddy current analysis and optimisation design of intermediate ring in novel double squirrel‐cage induction motor
Authors: Xu Wei , Bao Xiaohua , Cheng Shuai , Xu Yixiang , Lu Qinfen
Published: November 2019

The intermediate ring (IR) in the novel squirrel‐cage rotor is vulnerable to electrical faults for its relatively small dimension. With the investigation of IR current features, this study mainly proposes an optimisation design strategy of IR to avoid excessive thermal stress at a start‐up instant. The amplitude and phase relations of various rotor currents are reflected in the proposed current phasor diagram. In terms of the internal distribution of one concrete current, the circuit analysis theory is applied by dividing the whole conductor into multiple subconductors. The leakage flux around the conductors is simplified, respectively, according to the spatial symmetry. With reference to the existing bar design, the IR design scheme is mainly guided by two essential principles regarding the current‐related parameters. Finally, the validity of the designing process of IR is verified by the coupled simulations and temperature‐rise experiments. The surface temperature of the designed IR is not the highest, and the partial temperature difference is limited and reasonable.
Thrust force ripple reduction of H‐LVPMM based on dynamic harmonic current compensation
Authors: Chen Zhi , Kong Wubin , Zhou You , Qu Ronghai , Fedida Vincent
Published: November 2019

Through the structural optimisation, the Halbach array‐linear vernier permanent magnet machine (H‐LVPMM) offers a higher force with extremely low ripple. However, thrust force ripple is minimised rather than eliminated and it reduces the precision of the control system. The thrust force ripple includes cogging force, end force and electromagnetic thrust ripple. Since the structural optimisation makes three phases balanced, the electromagnetic thrust ripple can be ignored. Here, a disturbance observer is proposed to observe and compensate the thrust force ripple by injecting the correspondent harmonic current into the closed‐loop controller in a feedforward method. It leads to second, fourth and sixth harmonic components in the q‐axis current. The closed‐loop current control with vector proportional and integral (VPI) regulator is applied to guarantee the current tracking accuracy of the harmonic components. Parameters are optimised according to the thrust force ripple harmonics and the open‐loop Bode diagram. The impact of thrust ripple is eliminated by the proposed control method. Experimental results show the validity of the disturbance observer and the VPI current controller.
Study on fault diagnosis of broken rotor bars in squirrel cage induction motors: a multi‐agent system approach using intelligent classifiers
Authors: Drakaki Maria , Karnavas Yannis L. , Karlis Athanasios D. , Chasiotis Ioannis D. , Tzionas Panagiotis
Published: November 2019

A critical factor in industrial production maintenance is decision‐making in fault diagnosis. Motor current signature analysis (MCSA) is an established condition‐based maintenance method to make fault diagnosis in induction motors (IMs). The occurrence of multiple interacting faults, as well as emergent behaviour, can be tackled efficiently especially when MCSA is combined with distributed problem‐solving artificial intelligence (AI) techniques. Therefore, in this study, an intelligent multi‐agent system (MAS) is presented to make decisions on the fault conditioning of a three‐phase squirrel cage IM. The incorporated agents represent different health conditions of the same IM, with faults that may occur in the rotor bars. All agents utilise an AI method, and use for training MCSA experimental data. A supervisor agent (SA) initially communicates with agents employing feed‐forward artificial neural networks trained with the back‐propagation algorithm and performs the final fault diagnosis by evaluating their responses. When a decision cannot be made on the fault type, the SA employs another agent that uses the k‐nearest neighbour rule. The proposed method achieves high fault diagnosis accuracy. Its performance is also compared with results previously obtained from the same motor when an adaptive neuro‐fuzzy inference system combined with a subtractive clustering method had been used.
Multiparameter identification for SPMSMs using NLMS adaptive filters and extended sliding‐mode observer
Authors: Kim Hyoung‐Woo , Kim Hong‐Joo , Choi Joon‐Young
Published: November 2019

The authors propose a parameter identification method for sequential identification of electrical and mechanical parameters of surface‐mounted permanent magnet synchronous motors (SPMSMs). Two normalised least mean square (NLMS) adaptive filters (AFs) are designed for identifying the electrical parameters, where the first AF identifies the stator inductance and the second AF identifies the stator resistance and rotor flux linkage. The NLMS AFs achieve faster transient responses than recursive least squares (RLS) AFs owing to lower computing load and smaller memory size. Regarding mechanical parameters, an extended sliding‐mode mechanical parameter observer (ESMMPO) is employed to estimate the system disturbance and angular velocity, from which the rotational inertia, viscous damping coefficient, and load torque are identified. The rotor flux linkage identified from the second NLMS AF is used for estimating the real‐time system disturbance of the ESMMPO, which enables the identification of mechanical parameters with higher accuracy. The proposed method effectively integrates the NLMS AFs and ESMMPO into a single framework to identify both electrical and mechanical parameters of the SPMSMs. The experimental results of the proposed method are compared with those of RLS AFs and the conventional ESMMPO, which demonstrates the faster response and less steady‐state parameter errors of the proposed method.
Application of random elements in ISS
Authors: Yan Xuehu , Lu Yuliang , Liu Lintao , Li Xia , Liu Jingju , Yang Guozheng
Published: November 2019

The ‐threshold image secret sharing (ISS) encodes a secret image into n shares. When k or more shares are obtained, the secret image can be decoded; however, less than k shares could decode none of the secret image. ISS primarily includes polynomial‐based ISS and visual secret sharing (VSS). In this study, the authors find that the random elements in ISS can be used not only to hide information but also to obtain more features such as multiple decryptions and comprehensible share. They have established an application model of random elements that is suitable for both polynomial‐based ISS and VSS. On the basis of the model, they have extended three algorithms to achieve information hiding, multiple decryptions and comprehensible share. Experiments indicate the effectiveness of these algorithms.
Effective key‐frame extraction approach using TSTBTC–BBA
Authors: Singh Yadwinder , Kaur Lakhwinder
Published: November 2019

Video summarisation and key‐frame extraction play a vital role in video processing and content‐based video analysis. Key‐frame extraction facilitates rapid browsing and proficient video ordering in numerous applications such as multimedia, gaming etc. The application of ‘effective key‐frame extraction’ can be used in the field of object detection and tracking, and it is found to be helpful in providing some sort of signal to visually impaired persons. In this study, the advantages of Thepade's sorted ternary block truncation coding (TSTBTC) along with binary bat algorithm (BBA) are used to overcome the limitations by extracting an effective key frame from the videos. Static images in the form of frames are extracted from input video database and processed through TSTBTC algorithm for calculating similarity measures amongst two consecutive frames. The input data is processed using four colour spaces, namely red–green–blue colour space, Kekre's LUV colour space, YCbCr colour space, YUV colour space and BBA are used to optimise the threshold value. Furthermore, five similarity measures indices are used to calculate the number of frames, and the result obtained shows that TSTBTC–BBA algorithm deployed in YUV colour space provides better results compared with other existing techniques regarding precision, F‐measure and colour spaces.
Left ventricular segmentation based on a parallel watershed transformation towards an accurate heart function evaluation
Authors: Mahmoudi Ramzi , Ben Ameur Narjes , Ammari Asma , Akil Mohamed , Saouli Rachida , Hmida Badii , Bedoui Momahed Hedi
Published: November 2019

Magnetic resonance imaging (MRI) has emerged as the golden reference for cardiac examination. This modality allows the assessment of human cardiovascular morphology, functioning, and perfusion. Although a couple of challenging issues, such as the cardiac magnetic resonance (MR) image's features and the large variability of images among several patients, still influences the cardiac cavities’ segmentation and needs to be carried out. In this study, the authors have profoundly reviewed and fully compared semi‐automated segmentation methods performed on cardiac cine‐MR short‐axis images for the evaluation of the left ventricular functions. However, the number of parameters handled by the synthesised works is limited if not null. For the sake of ensuring the highest coverage of the left ventricle parameters computing, they have introduced a parallel watershed‐based approach to segment the left ventricular allowing hence the computation of six parameters (end‐diastolic volume, end‐systolic volume, ejection fraction, cardiac output, stroke volume, and left ventricular mass). An algorithm is associated with the main considered measurements. The experimental results that were obtained through studying 20 patients’ MRI data base demonstrate their approach's accuracy in estimating real values of the parameters’ set thanks to a faithful segmentation of the myocardium.
Image denoising using 2D orthogonal locality preserving discriminant projection
Authors: Shikkenawis Gitam , Mitra Suman K.
Published: November 2019

Image denoising using a combination of non‐local self‐similarity and transformed domain techniques has become popular in past few years. Instead of working on independent pixels, patches extracted from the noisy image are grouped together based on structural similarity and noise elimination is performed in transformed domain. Orthogonal locality preserving projection and its variant that processes the images directly in matrix format have been used for image denoising recently. Locality preserving nature of these techniques takes care of similarity within image patches while learning the basis, hence reducing the task of grouping patches explicitly. Non‐local self‐similarity based image denoising approaches perform patch grouping based on structural similarity. Discriminant information, if considered can play pivotal role in achieving superior clustering of data and thereby is expected to enhance the quality of denoising. With this aim in mind, two‐dimensional (2D) orthogonal locality preserving discriminant projection is formulated in this study. While learning the basis, along with the similarity, proposed approach also takes into account dissimilarity between patches. A global basis thus learnt from the noisy image is used for denoising and comparable denoising performance is shown relative to the state‐of‐the‐art methods.
Low light image enhancement with adaptive sigmoid transfer function
Authors: Srinivas Kankanala , Bhandari Ashish Kumar
Published: November 2019

Low light image enhancement algorithms intent to produce visually pleasant images and target to extract valuable information for computer vision applications. The task of improving the quality of low light images is a challenging one. The existing methods for quality improvement undeniably annoy the visual aesthetics and suffer the major drawback of high computational complexity and less efficiency. To improve the visual quality and lower the distortions, a simple and computationally efficient low light image enhancement framework is presented in this study. To achieve this, an adaptive sigmoid transfer function (ASTF) is used and is derived from the sigmoid activation function of neural networks. By combining ASTF with a Laplacian operator, colour and contrast‐enhanced images are obtained. Experiments show the effectiveness of the proposed method with state‐of‐the‐art methods.
Identification of wool and mohair fibres with texture feature extraction and deep learning
Authors: Yildiz Kazim
Published: November 2019

Wool and mohair fibres are both animal‐based fibres and having circular scales on their microscopic images from the longitudinal view. Although they look very similar in their microscopic view, they show different physical/chemical properties which determine their usage area. Thus, in textile industry, they need to be separated carefully from each other. The separation of wool/mohair fibres is an important issue and can be performed with human eye by using the microscopic images, that is not time/cost effective and not objective. The novelty of the presented study is to design an objective, easy, rapid, time and cost‐effective method in order to separate wool fibre from mohair fibre by using a texture analysis based identification method. For this purpose, microscopic images of both wool and mohair fibres were preprocessed as the texture images. Local binary pattern‐based feature extraction process and deep learning were separately used to get determinative information from the fibres. In order to identify the samples, the classification based method was completed. Experimental results indicated that an accurate texture analysis for this kind of animal fibres is possible to identify wool and mohair fibres by using deep learning and machine learning with 99.8% and 90.25% accuracy rates, respectively.
Medical fusion framework using discrete fractional wavelets and non‐subsampled directional filter banks
Authors: Kaur Gurpreet , Singh Sukhwinder , Vig Renu
Published: November 2019

Image fusion in neuro diagnosis is intimidating due to its complexity. The heterogeneous natures of the original brain images make intermodal transmission difficult during fusion. Medical image fusion using complementary modalities results in loss of vital salient information. Poor fusion, colour deficiencies result due to similar processing for both the modalities. A dual technique is proposed using discrete fractional wavelet transform (FRWT) and non‐subsampled directional filter banks for better extraction of salient image elements for improved diagnosis. The sparsity character of the coefficients FRWT is controlled by optimising the parity operator using Grey Wolf optimisation algorithm. Four sets of neurological multimodal magnetic resonance imaging and single photon emission computed tomography (CT) brain images are used from benchmark database for validation. The objective evaluation has been conducted using five metrics. The main values obtained from objective metrics based on the proposed technique are 6.3213 for Shannon entropy, mutual information is computed to be 2.7582, fusion factor is 1.9095, standard deviation is 0.1310, and edge strength is 0.76122 indicating improved diagnostic information and superior image quality. Subjective evaluation by a medico validates the findings with finer visual output and enhanced contrast in comparison with recent and state‐of‐the‐art methods.
Regionalisation of islanded microgrid considering planning and operation stages
Authors: Ashfaq Sara , Zhang Daming , Zhang Cuo , Dong Zhao Yang
Published: November 2019

To harmonise the operation of renewable and conventional power generation, the radial distribution network of islanded microgrids (MGs) has been regionalised into two types of regions namely conventional generation dominant regions (CGRs) and renewable generation dominant regions (RGRs). RGRs will operate on constant frequency control methodology and CGRs will operate using conventional control techniques. A framework starting from the planning stage where sensitivity analysis‐based approach has been implemented for regionalisation and then optimisation of distributed generation (DG) units has been carried out for regionalised MGs (RMGs) is proposed in this study. At operation stage, a short‐term dispatch framework has been proposed based on the forecasted wind power generation scenarios with a battery energy storage system in the RMGs. A power exchange strategy with a scheduled pattern between the regions has also been developed to make the scheme more dispatchable and reliable. Multi‐objective optimisation algorithms have been developed for DGs planning and power dispatch in RMGs. The performance of the proposed RMGs has been studied by implementing it with four different modes of operation by converting IEEE 15‐bus radial distribution system into an islanded MG.
Efficient algorithm for big data clustering on single machine
Authors: Alguliyev Rasim M. , Aliguliyev Ramiz M. , Sukhostat Lyudmila V.
Published: November 2019

Big data analysis requires the presence of large computing powers, which is not always feasible. And so, it became necessary to develop new clustering algorithms capable of such data processing. This study proposes a new parallel clustering algorithm based on the k‐means algorithm. It significantly reduces the exponential growth of computations. The proposed algorithm splits a dataset into batches while preserving the characteristics of the initial dataset and increasing the clustering speed. The idea is to define cluster centroids, which are also clustered, for each batch. According to the obtained centroids, the data points belong to the cluster with the nearest centroid. Real large datasets are used to conduct the experiments to evaluate the effectiveness of the proposed approach. The proposed approach is compared with k‐means and its modification. The experiments show that the proposed algorithm is a promising tool for clustering large datasets in comparison with the k‐means algorithm.
Bone Defect Management with Vascularized Fibular Grafts in the Treatment of Grade III-IV Osteomyelitis
Authors: Antonini Andrea , Rossello Carlo , Salomone Carlo , Iacoviello Paolo , Chiarlone Francesco , Burastero Giorgio
Published: November 2019

Purpose This study is a retrospective analysis of our experience in microsurgical bone transfers for complex limb reconstructions. The aim of this study is to evaluate reliability of the vascularized fibula technique: infection recurrence, hypertrophy, time to bone union, complications, and time to healing in severe osteomyelitis (Cierny-Mader III and IV) cases over a 38 to 93 month follow-up.

Patients and Methods From March 2010 until December 2015, 18 patients’ limbs (6 females and 1 2 males; mean age 48.7 years) were reconstructed with 10 free fibula flaps, 5 pedicled fibula flaps, 3 peroneus brevis osteomuscular flaps. We reconstructed 2 radiuses, 2 ulnae, 4 femurs, 4 tibiae, 1 acetabulum and 3 fibular malleoli.

Results We considered as successful results all cases where patients had successful functional bone reconstruction with no recurrence of infection during the follow up (mean time 63.6 months). We obtained 14 complete functional reconstructions, 2 limb salvages with impaired function, and 2 failures which underwent major amputations. In only one case there was an infection recurrence.

Conclusions The bone defect reconstruction with vascularized fibula grafts in severe bone infections is an effective option, but requires a well trained multidisciplinary team to manage the high rate of complications. Complications, in our series, were demonstrated to be significantly associated to patients defined as B-hosts according to Cierny-Mader’s classification (P < 0.05), and caliber discrepancy between fibula and reconstructed bones such as Tibia and Femur (P < 0.005). Furthermore, stress fractures in the grafted fibulae were prognostic indicators for overall treatment failure (P < 0.05).
Urokinase Plasminogen Activator Overexpression Reverses Established Lung Fibrosis
Authors: Horowitz Jeffrey C. , Tschumperlin Daniel J. , Kim Kevin K. , Osterholzer John J. , Subbotina Natalya , Ajayi Iyabode O. , Teitz-Tennenbaum Seagal , Virk Ammara , Dotson Megan , Liu Fei , Sicard Delphine , Jia Shijing , Sisson Thomas H.
Published: November 2019

Introduction Impaired plasminogen activation (PA) is causally related to the development of lung fibrosis. Prior studies demonstrate that enhanced PA in the lung limits the severity of scarring following injury and in vitro studies indicate that PA promotes matrix degradation and fibroblast apoptosis. These findings led us to hypothesize that increased PA in an in vivo model would enhance the resolution of established lung fibrosis in conjunction with increased myofibroblast apoptosis.

Methods Transgenic C57BL/6 mice with doxycycline inducible lung-specific urokinase plasminogen activator (uPA) expression or littermate controls were treated (day 0) with bleomycin or saline. Doxycycline was initiated on days 1, 9, 14, or 21. Lung fibrosis, stiffness, apoptosis, epithelial barrier integrity, and inflammation were assessed.

Results Protection from fibrosis with uPA upregulation from day 1 through day 28 was associated with reduced parenchymal stiffness as determined by atomic force microscopy. Initiation of uPA expression beginning in the late inflammatory or the early fibrotic phase reduced stiffness and fibrosis at day 28. Induction of uPA activity in mice with established fibrosis decreased lung collagen and lung stiffness while increasing myofibroblast apoptosis. Upregulation of uPA did not alter lung inflammation but was associated with improved epithelial cell homeostasis.

Conclusion Restoring intrapulmonary PA activity diminishes lung fibrogenesis and enhances the resolution of established lung fibrosis. This PA-mediated resolution is associated with increased myofibroblast apoptosis and improved epithelial cell homeostasis. These studies support the potential capacity of the lung to resolve existing scar in murine models.
Pseudo-Cerebrospinal Fluid Leaks of the Anterior Skull Base: Algorithm for Diagnosis and Management
Authors: Constanzo Felipe , Pinto Jaime , Sedaghat Sahba , Schmidt Thomas
Published: November 2019

Objective Pseudo-cerebrospinal fluid (CSF) leaks are a rare cause of unilateral, watery rhinorrhea. We proposed a step-wise approach to evaluate these cases.

Design It involves a single-center retrospective cohort study.

Setting The setting is that of a tertiary academic medical center.

Participants Ten patients with diagnosis of pseudo-CSF leak over a 21-year period were evaluated using our proposed algorithm that includes computed tomography, magnetic resonance imaging, nasal endoscopy, β-2 transferrin, intrathecal fluorescein, and surgical exploration of the anterior cranial base.

Main Outcome Measures The occurrence of intracranial infection and resolution of the symptoms were evaluated at a mean follow-up of 94.4 months.

Results Eight patients had history of skull base fracture or surgery. In all patients computed tomography, magnetic resonance imaging, and nasal endoscopy did not show signs of CSF leak. Beta-2 transferrin testing was performed in five patients, being negative in all of them. Intrathecal fluorescein was performed in seven patients, being negative in five and inconclusive in two. Surgical exploration was performed in five patients, definitively ruling out CSF leak. Six patients were treated with intranasal ipratropium, resolving the symptoms in all cases.

Conclusion The presented algorithm provides a step-wise approach for patients with unilateral watery rhinorrhea, allowing to safely ruling out CSF leak.
Soliton-effect optical pulse compression in CMOS-compatible ultra-silicon-rich nitride waveguides
Authors: Choi Ju Won , Sohn Byoung-Uk , Chen George F. R. , Ng Doris K. T. , Tan Dawn T. H.
Published: November 2019

The formation of optical solitons arises from the simultaneous presence of dispersive and nonlinear properties within a propagation medium. Chip-scale devices that support optical solitons harness high field confinement and flexibility in dispersion engineering for significantly smaller footprints and lower operating powers compared to fiber-based equivalents. High-order solitons evolve periodically as they propagate and experience a temporal narrowing at the start of each soliton period. This phenomenon allows strong temporal compression of optical pulses to be achieved. In this paper, soliton-effect temporal compression of optical pulses is demonstrated on a CMOS-compatible ultra-silicon-rich nitride (USRN) waveguide. We achieve 8.7× compression of 2 ps optical pulses using a low pulse energy of ∼16 pJ, representing the largest demonstrated compression on an integrated photonic waveguide to date. The strong temporal compression is confirmed by numerical calculations of the nonlinear Schrödinger equation to be attributed to the USRN waveguide’s large nonlinearity and negligible two-photon absorption at 1550 nm.
Early sarcomere and metabolic defects in a zebrafish
pitx2c
cardiac arrhythmia model
Authors: Collins Michelle M. , Ahlberg Gustav , Hansen Camilla Vestergaard , Guenther Stefan , Marín-Juez Rubén , Sokol Anna M. , El-Sammak Hadil , Piesker Janett , Hellsten Ylva , Olesen Morten S. , Stainier Didier Y. R. , Lundegaard Pia R.
Published: November 2019

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. The major AF susceptibility locus 4q25 establishes long-range interactions with the promoter of
PITX2
, a transcription factor gene with critical functions during cardiac development. While many AF-linked loci have been identified in genome-wide association studies, mechanistic understanding into how genetic variants, including those at the 4q25 locus, increase vulnerability to AF is mostly lacking. Here, we show that loss of
pitx2c
in zebrafish leads to adult cardiac phenotypes with substantial similarities to pathologies observed in AF patients, including arrhythmia, atrial conduction defects, sarcomere disassembly, and altered cardiac metabolism. These phenotypes are also observed in a subset of
pitx2c

+/−

fish, mimicking the situation in humans. Most notably, the onset of these phenotypes occurs at an early developmental stage. Detailed analyses of
pitx2c
loss- and gain-of-function embryonic hearts reveal changes in sarcomeric and metabolic gene expression and function that precede the onset of cardiac arrhythmia first observed at larval stages. We further find that antioxidant treatment of
pitx2c

−/−

larvae significantly reduces the incidence and severity of cardiac arrhythmia, suggesting that metabolic dysfunction is an important driver of conduction defects. We propose that these early sarcomere and metabolic defects alter cardiac function and contribute to the electrical instability and structural remodeling observed in adult fish. Overall, these data provide insight into the mechanisms underlying the development and pathophysiology of some cardiac arrhythmias and importantly, increase our understanding of how developmental perturbations can predispose to functional defects in the adult heart.
Algorithms for i-optimal designs for ordinal response: a literature approach
Authors: Hamim Wigena Aji , Erfiani  , Mohamad Soleh Agus , Dyah Syafitri Utami
Published: November 2019

In many cases, the reseachers face the problem how to design the experiment which deal with the real situation. This is because the designs on literature do not suit the case. To solve the problem, optimal design can be an alternative. There are two approaches on optimal design: an analytical and a computational approach. An algorithm in the computational approach is needed to find an optimal design. The optimal design is a part of experimental design which seeks the design based on a certain criterion. The criterion which focuses on presicion of prediction variance is I-optimality criterion. Limited literatures address the I- optimality criterion for ordinal response. Most of literatures address to developing algorithms of other optimality criteria for General Linear Model. As the response is ordinal, hence the ordinal response belongs to non-linear model.
Value of perfect information in stock picking
Authors: Rosha Media
Published: November 2019

Portfolio picking is an important aspect in investmtent management. Before deciding what stock to pick, an investor will consider many aspect of the stock, the fundamental and the trend of the market. Knowing what to expect is an important science and art in investment. Expected value of perfect information – EVPI is the difference between two payoff that predicted to be the best of some certain condition. For portfolio management, we could employ Capital Asset Pricing Model to provide clearer view of each securities and using treynor ratio to optimize the investment result. Description in this paper about performance analysis of stocks in LQ-45 index in Indonesian Stock Index in 1-st quartil period of 2015, based on return and risk to reach the group of stocks which optimum using the model of Capital Asset Pricing Model (CAPM). Our finding suggests that using CAPM and Treynor Ratio analysis could optimize the portfolio outcome, while changing business and economic environment create limitation on the portfolio.
Fuzzy c-means and gath-geva methods in clustering districts based on human development index (hdi) in south sulawesi
Authors: Annas S , Nyompa S , Arisandi R , Nusrang M , Eka S
Published: November 2019

District grouping in South Sulawesi based on the Human Development Index (HDI) indicators needs to be done as a material for planning and evaluating the targets of government work programs. This grouping is based on dominant indicators of the high and low HDI. The value of the HDI indicator needs to be considered so that the achievement of each indicator is known. Statistical analysis that can be used to group districts that have similarities is cluster analysis. The method that is currently developing is fuzzy clustering analysis, which classifies objects using certain membership degrees. Fuzzy clustering algorithm that can be used is Fuzzy C-means (FCM). Another method of fuzzy clustering analysis developed further is Gath Geva (GG), which is able to detect groups with different forms. In this study, the fuzzy clustering process on the FCM and GG methods with the same parameters and shows that the GG method is better than the FCM method. This conclusion is based on a total of 1000 iterations. The GG method gives an objective function value smaller than FCM, besides it gives a faster- conferencing iteration result.
An analysis of the relevancy between mathematics and productive subject in computer and network engineering program at vocational high school
Authors: Silvia Wahyuni , Armiati
Published: November 2019

The fast development of science and technology and the workforce competition in this globalization era, require education academy to produce a competent and good quality of human resources in their field. Vocational high school is an education academy that is expected to create professional and productive human resources to fulfil every skill pursuit that is needed in the workforce.Computer and network engineering program and mathematics have a role in science and technology development and in the workforce competition.Productive subject in computer and network engineering will produce productive and professional graduates that can compete in the workforce.Since the activity that include mathematics could develop logical reasoning, logical thinking, systematic, critical, neat and objective, mathematics could help computer and network engineering graduates in solving the problem in the workforce. This paper will deliver the relevancy between mathematics and productive subject in computer and network engineering program at vocational high school.
D-optimal design for ordinal responses in mixture experiments
Authors: Rahayu W D , Syafitri U D , Soleh A M
Published: November 2019

A mixture experiment is an experiment in which the response depends on the ingredients proportions. In organoleptic test, the response is ordinal. This research focused on how to generate the D-optimal design of ordinal response. The model belongs to Generalized Linear Model (GLM) with logit as the link function. To find the D-optimal design which is seeking the design that minimizing the covariance of parameter model, the point-exchange algorithm was constructed. There were three ingredients of a cookies recipe which were needed to mix meanwhile other ingredients were fixed. The D-optimal design of the three ingredients consisted of seven design points.