Publications by authors named "Yanhui Guo"

68 Publications

A novel high-pressure phase of ScNwith higher stability predicted from first-principles calculations.

J Phys Condens Matter 2021 Sep 10;33(47). Epub 2021 Sep 10.

School of Physics and Optoelectronic Engineering, Shandong University of Technology, 250049, People's Republic of China.

For binary compounds of Sc-N, the stable structures and stoichiometries were studied from ambient condition to high pressure of 100 GPa, adopting CALYPSO method. The newly predicted2/c-ScNcompound was more energetically stable under high pressure= 62 GPa comparing with the three previously reported phases of1-ScN,-ScNand2/-ScN. Furthermore, the high-pressure phase of2/c-ScNwas dynamically stable at ambient condition, so the ambient-pressure recovery is possible. In this paper, the study suggested that the energetic polynitrides can be obtained in transition metal nitrides under high pressure. And we identified one novel 3D extended puckered poly-nitrogen network in the2/c-ScNstructure, which is similar to the2/-ScN. The decomposition of2/c-ScNto ScN and Nunder ambient pressure was estimated to release 5.02 eV energy per formula unit (f.u.), corresponding to 4.19 kJ gin energy density, which was expected to be highly exothermic. The present results can conduce to obtain more polynitrogen forms and theoretically encourages experimental discovery in these promising materials.
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http://dx.doi.org/10.1088/1361-648X/ac2119DOI Listing
September 2021

Effects of different doses of omega-3 polyunsaturated fatty acids on gut microbiota and immunity.

Food Nutr Res 2021 8;65. Epub 2021 Jul 8.

Department of Microecology, School of Basic Medical Science, Dalian Medical University, Dalian, China.

Background: Omega-3 polyunsaturated fatty acids (PUFAs) play beneficial roles in metabolism and health. Little is known about the effects of different doses of omega-3 PUFAs on gut microbiota.

Objective: In this study, we focus on the effects of different doses of omega-3 PUFAs on gut microbiota and immunity.

Design: BALB/c mice was first treated with ceftriaxone sodium for 7 days, and then they received saline or different doses of omega-3 PUFAs (30, 60 and 90 mg omega-3 PUFAs) via daily gavage for 21 days. Alterations of cecum microbiota; the tight junction proteins, zonula occludens 3 (ZO3) and occludin, in the ileal wall; serum lipopolysaccharide (LPS); Interleukin-10 (IL-10), interleukin-1β (IL-1β), and Tumour Necrosis Factor α (TNF-α) ; mucus SIgA levels were measured.

Results: Compared with the ceftriaxone sodium administration group, significant increases in bacterial richness and diversity were observed in the 60- and 90-mg omega-3 PUFA groups, while only a slight increase was observed in the 30-mg omega-3 PUFA group. A higher percentage of several genera, including , and , and a lower percentage of , and were observed in the 60- and 90-mg omega-3 PUFA groups when compared with those in the 30-mg group. The expression of ZO3 and occludin proteins increased in 60- and 90-mg omega-3 PUFA groups compared with the natural recovery group. The mucus SIgA and serum IL-10 levels were increased, and serum levels of LPS, IL-1β, and TNF-α were decreased in the 60- and 90-mg omega-3 PUFA groups when compared with those in the ceftriaxone sodium-treated group.

Conclusion: Different doses of omega-3 PUFAs have different therapeutic effects on the intestinal microbiota. The 60- and 90-mg omega-3 PUFA supplementation had better recovery effects on the gut microbiota and immunity than those of the 30 mg omega-3 PUFAs supplementation.
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http://dx.doi.org/10.29219/fnr.v65.6263DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8287659PMC
July 2021

Base-Promoted Three-Component Cascade Reaction of α-Hydroxy Ketones, Malonodinitrile, and Alcohols: Direct Access to Tetrasubstituted N-Pyrroles.

J Org Chem 2021 Jul 6;86(14):9610-9620. Epub 2021 Jul 6.

Key Laboratory of Functional Molecular Engineering of Guangdong Province, School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, People's Republic of China.

A base-promoted three-component cascade reaction of α-hydroxy ketones, malonodinitrile, and alcohols has been developed, providing a direct and efficient route to a range of structurally diverse and synthetically useful 2-alkyloxy-1-pyrrole-3-carbonitrile derivatives. The reaction involved three different bond (C-C, C-O, and C-N) formations in a single step, and its regioselectivity was depended on the structure of the α-hydroxy ketones employed. The use of easily available starting materials, wide substrate scope, good functional group tolerance, operational simplicity, and high atom economy are attractive features of the new method.
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http://dx.doi.org/10.1021/acs.joc.1c00882DOI Listing
July 2021

Molecular Targets and Biological Functions of cAMP Signaling in .

Biomolecules 2021 05 3;11(5). Epub 2021 May 3.

School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China.

Cyclic AMP (cAMP) is a pivotal signaling molecule existing in almost all living organisms. However, the mechanism of cAMP signaling in plants remains very poorly understood. Here, we employ the engineered activity of soluble adenylate cyclase to induce cellular cAMP elevation in plants and identify 427 cAMP-responsive genes (CRGs) through RNA-seq analysis. Induction of cellular cAMP elevation inhibits seed germination, disturbs phytohormone contents, promotes leaf senescence, impairs ethylene response, and compromises salt stress tolerance and pathogen resistance. A set of 62 transcription factors are among the CRGs, supporting a prominent role of cAMP in transcriptional regulation. The CRGs are significantly overrepresented in the pathways of plant hormone signal transduction, MAPK signaling, and diterpenoid biosynthesis, but they are also implicated in lipid, sugar, K, nitrate signaling, and beyond. Our results provide a basic framework of cAMP signaling for the community to explore. The regulatory roles of cAMP signaling in plant plasticity are discussed.
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http://dx.doi.org/10.3390/biom11050688DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147800PMC
May 2021

Hormetic responses of soil microbiota to exogenous Cd: A step toward linking community-level hormesis to ecological risk assessment.

J Hazard Mater 2021 08 26;416:125760. Epub 2021 Mar 26.

College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiangsu 210037, China; Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu 210037, China; National Positioning Observation Station of Hung-tse Lake Wetland Ecosystem in Jiangsu Province, Hongze, Jiangsu 223100, China. Electronic address:

We investigated hormetic responses of soil microbial communities to exogenous Cd by assessing microbial count, bacterial and fungal abundance, and microbial community diversity. We found that the bacterial count (BC) decreased (3-40%) by 0.2-40 mg Cdkg. Addition of 0.6-2.0 mgkg significantly increased fungal count (FC) by 7-42%, while addition of 4.0-40 mgkg Cd decreased FC by 29-51%, indicating a hormetic dose response. We also found that the FC/BC ratio increased by 0.6-2.0 mg Cdkg, with a maximum stimulation of 51%, and decreased (18-27%) by 4.0-40 mg Cdkg. Cd had no adverse effect on the α-diversity of bacterial or fungal communities. For relative abundances (RAs) of bacteria and fungi at phylum level, Bacteroidetes RA exhibited a biphasic dose-response curve, with an 18-24% increase at 0.6-4.0 mgkg and a 10% decrease at 40 mgkg compared with control. The results of FC, FC/BC, and Bacteroidetes RAs suggest that hormesis occurred at microbial community level, with positive effects occurring at 0.6-2.0 mgkg. This study can contribute to incorporating microbial community hormesis into the ecological risk assessments in the future.
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http://dx.doi.org/10.1016/j.jhazmat.2021.125760DOI Listing
August 2021

Iodine-Substituted Lithium/Sodium -Decaborates: Syntheses, Characterization, and Solid-State Ionic Conductivity.

ACS Appl Mater Interfaces 2021 Apr 6;13(15):17554-17564. Epub 2021 Apr 6.

Henan Key Laboratory of Boron Chemistry and Advanced Energy Materials, School of Chemistry and Chemical Engineering, Henan Normal University, Xinxiang, Henan 453007, China.

Solid-state electrolytes based on -decaborates have caught increasing interest owing to the impressive room-temperature ionic conductivity, remarkable thermal/chemical stability, and excellent deformability. In order to develop new solid-state ion conductors, we investigated the influence of iodine substitution on the thermal, structural, and ionic conduction properties of -decaborates. A series of iodinated -decaborates, M[BHI] (M = Li, Na; = 1, 2, 10), were synthesized and characterized by thermal analysis, powder X-ray diffraction, and electrochemical impedance spectroscopy; the stability and ionic conductivity of these compounds were studied. It was found that with the increase of iodine substitution on the -decaborate anion cage, the thermal decomposition temperature increases. All M[BHI] exhibit an amorphous structure. The ionic conductivity of Li[BHI] is higher than that of the Li[BH] parent compound. An ionic conductivity of 2.96 × 10 S cm with an activation energy of 0.23 eV was observed for Li[BI] at 300 °C, implying that iodine substitution can improve the ionic conductivity. However, the ionic conductivity of Na[BHI] is lower than that of Na[BH] and increases with the increase of iodine substitution, which could be associated with the increase of the electrostatic potential, mass, and volume of the iodinated anions. Moreover, Li[BI] offers a Li-ion transference number of 0.999, an electrochemical stability window of 3.3 V and good compatibility with the Li anode, demonstrating its potential for application in high-temperature batteries.
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http://dx.doi.org/10.1021/acsami.1c01659DOI Listing
April 2021

Persian sentiment analysis of an online store independent of pre-processing using convolutional neural network with fastText embeddings.

PeerJ Comput Sci 2021 5;7:e422. Epub 2021 Mar 5.

Computer Science, University of Illinois at Springfield, Springfield, IL, USA.

Sentiment analysis plays a key role in companies, especially stores, and increasing the accuracy in determining customers' opinions about products assists to maintain their competitive conditions. We intend to analyze the users' opinions on the website of the most immense online store in Iran; Digikala. However, the Persian language is unstructured which makes the pre-processing stage very difficult and it is the main problem of sentiment analysis in Persian. What exacerbates this problem is the lack of available libraries for Persian pre-processing, while most libraries focus on English. To tackle this, approximately 3 million reviews were gathered in Persian from the Digikala website using web-mining techniques, and the fastText method was used to create a word embedding. It was assumed that this would dramatically cut down on the need for text pre-processing through the skip-gram method considering the position of the words in the sentence and the words' relations to each other. Another word embedding has been created using the TF-IDF in parallel with fastText to compare their performance. In addition, the results of the Convolutional Neural Network (CNN), BiLSTM, Logistic Regression, and Naïve Bayes models have been compared. As a significant result, we obtained 0.996 AUC and 0.956 -score using fastText and CNN. In this article, not only has it been demonstrated to what extent it is possible to be independent of pre-processing but also the accuracy obtained is better than other researches done in Persian. Avoiding complex text preprocessing is also important for other languages since most text preprocessing algorithms have been developed for English and cannot be used for other languages. The created word embedding due to its high accuracy and independence of pre-processing has other applications in Persian besides sentiment analysis.
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http://dx.doi.org/10.7717/peerj-cs.422DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959661PMC
March 2021

Metal-Free Nanoassemblies of Water-Soluble Photosensitizer and Adenosine Triphosphate for Efficient and Precise Photodynamic Cancer Therapy.

ACS Nano 2021 03 12;15(3):4979-4988. Epub 2021 Mar 12.

Department of Chemistry, University of Texas at San Antonio, San Antonio, Texas 78249, United States.

Engineering photosensitizers into stimuli-responsive supramolecular nanodrugs allows enhanced spatiotemporal delivery and controllable release of photosensitizers, which is promising for dedicated and precise tumor photodynamic therapy. Complicated fabrication for nanodrugs with good tumor accumulation capability and the undesirable side-effects caused by the drug components retards the application of PDT . The fact that extracellular adenosine triphosphate (ATP) is overexpressed in tumor tissue has been overlooked in fabricating nanomedicines for tumor-targeting delivery. Hence, herein we present metal-free helical nanofibers formed in aqueous solution from the coassembly of a cationic porphyrin and ATP as a nanodrug for PDT. The easily accessible and compatible materials and simple preparation enable the nanodrugs with potential in PDT for cancer. Compared to the cationic porphyrin alone, the porphyrin-ATP nanofibers exhibited enhanced tumor-site photosensitizer delivery through whole-body blood circulation. Overexpressed extracellular ATP stabilizes the porphyrin-ATP nanodrug within tumor tissue, giving rise to enhanced uptake of the nanodrug by cancer cells. The enzyme-triggered release of photosensitizers from the nanodrugs upon biodegradation of ATP by intracellular phosphatases results in good tumor therapeutic efficacy. This study demonstrates the potential for employing the tumor microenvironment to aid the accumulation of nanodrugs in tumors, inspiring the fabrication of smart nanomedicines.
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http://dx.doi.org/10.1021/acsnano.0c09913DOI Listing
March 2021

The role of bacterial communities in shaping Cd-induced hormesis in 'living' soil as a function of land-use change.

J Hazard Mater 2021 05 30;409:124996. Epub 2020 Dec 30.

College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiangsu 210037, China; Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu 210037, China. Electronic address:

Bacterial communities and soil physicochemical properties shape soil enzymes activities. However, how environmental factors and bacterial communities affect the relationship between increasing doses of soil pollutants and soil alkaline phosphatase (ALP), an index of soil microbiota activity, remains poorly understood. In this study, we investigated the response of soil ALP to 13 doses of Cd (0 and 0.01-100 mg/kg) under four land uses, viz. grassland (GL), natural forest (NF), plantation forest (PF), and wheat field (WF). We found that Cd commonly induced hormetic-like responses of soil ALP, with a maximum stimulation of 10.7%, 10.1%, 11.6%, and 14.5% in GL, NF, PF, and WF, respectively. The size of the hormetic zone (Hor), an integrated indicator of the stimulation phase and biological plasticity, was in the order GL > WF > PF > NF, and the hormetic zone occurred in the dose range of 5-10, 0.3-10, 0.8-3, and 3-5 mg/kg, respectively. These results indicate highly pleiotropic responses of 'living' soil system to promote resilience to Cd contamination, with soil microbiota potentially contributing to soil ALP's hormetic-like response under different land uses. The hormetic-like response of 'living' soil ALP in different land uses offers a new insight into the identification and minimization of the ecological risks of land-use change in Cd-contaminated lands.
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http://dx.doi.org/10.1016/j.jhazmat.2020.124996DOI Listing
May 2021

Cd induced biphasic response in soil alkaline phosphatase and changed soil bacterial community composition: The role of background Cd contamination and time as additional factors.

Sci Total Environ 2021 Feb 16;757:143771. Epub 2020 Nov 16.

College of Biological and Environment, Nanjing Forestry University, Nanjing, Jiangsu, China; Co-Innovation Center for the Sustainable Forestry in Southern Jiangsu Province, Nanjing, Jiangsu, China; National Positioning Observation Station of Hung-tse Lake Wetland Ecosystem in Jiangsu Province, Nanjing, Jiangsu, China. Electronic address:

Hormesis is an intriguing phenomenon characterized by low-dose stimulation and high-dose inhibition. The hormetic phenomena have been frequently reported in the past decades, but the researches on the biphasic responses of soil enzymes are still limited. The main objective of this study is to explore dose response of alkaline phosphatase (ALP) to Cd (0, 0.003, 0.03, 0.3, 3.0 and 30 mg/kg) in the presence of different levels of background Cd contamination (bulk soil with no added Cd, BS; low background Cd, LB; medium background Cd, MB; and high background Cd, HB). ALP activity at 0.003-0.3 mg Cd/kg was 13-39% higher than that of the control (0 mg Cd/kg) for HB after 7 d. Similarly, the enzyme activities at 0.003-0.03 mg Cd/kg were 2-25% and 14-17% higher than those of the controls for MB and HB after 60 d. After 90 d, ALP activities at 0.3-3.0 mg Cd/kg increased by 11-17% for LB. The dose-response curves had the shape of an inverted U, showing biphasic responses at days 7 (HB), 60 (MB and HB) and 90 (LB). After 60 days of exposure, total operational taxonomic units (OTU) numbers and unique species exposed to Cd stress displayed hormetic-response curve for MB. The relative abundances of Agrobacterium, Salinimicrobiums, Bacilllus, and Oceanobacillus displayed significantly positive correlations with ALP activity. This suggested that bacterial communities potentially contribute to ALP's hormesis. This study further provides new insights into the ecological mechanisms of pollutant-induced hormesis, and substantially contributes to the ecological risk assessment of Cd pollution.
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http://dx.doi.org/10.1016/j.scitotenv.2020.143771DOI Listing
February 2021

Effect of Shear Bands Induced by Asymmetric Rolling on Microstructure and Texture Evolution of Non-Oriented 3.3% Si Steel.

Materials (Basel) 2020 Oct 22;13(21). Epub 2020 Oct 22.

School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai 201418, China.

In the present work, the microstructure and texture of non-oriented 3.3% Si steel processed by asymmetric rolling (ASR) and subsequent annealing at different temperatures were compared with those obtained when using traditional symmetric rolling (SR). This work aims to reveal the effect of shear bands introduced by the ASR on the microstructure and texture evolution. The ASR sample reaches a recrystallization fraction of 62% at an annealing temperature of 650 °C, which is 32% higher than that of the SR sample annealed at the same temperature. This can be attributed to the abundant shear bands introduced by the ASR, which serve as the heterogeneous nucleation sites for the recrystallized grains. When increasing the annealing temperature to 750 °C, complete recrystallization could be observed in both asymmetric- and symmetric-rolled samples. When using an annealing temperature of 650 °C, the γ-oriented grains were dominant in the surface layer, while strong Goss-oriented grains could be observed in the center in the ASR sample. This is due to the fragmented small subgrains with different orientations in the surface layer inhibiting the nucleation of Goss- and cube-oriented grains during the annealing. In contrast, numerous Goss- and cube-oriented grains were formed in the surface layer after complete recrystallization when the ASR sample was annealed at a temperature of 750 °C. This may be related to the higher thermal energy, which benefits the nucleation of the Goss- and cube-oriented grains. In addition, ASR significantly increased the strength of η-fiber after complete recrystallization when compared with SR. This work might be helpful to design the rolling and the subsequent annealing processes.
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http://dx.doi.org/10.3390/ma13214696DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659486PMC
October 2020

Automatic myocardial infarction detection in contrast echocardiography based on polar residual network.

Comput Methods Programs Biomed 2021 Jan 8;198:105791. Epub 2020 Oct 8.

Institute for Sustainable Industries & Liveable Cities, Victoria University, SA.

Purpose: Heart disease is one of the leading causes of death. Among patients with cardiovascular diseases, myocardial infarction (MI) is the main reason. Precise and timely identification of MI is significant for early treatment. Myocardial contrast echocardiography (MCE) is widely used for the detection of MI in clinic practice. However, existing clinical exam using MCE is subjective and highly operator dependent and time-consuming. Hence an automatic computer-aided MI detection in MCE is necessary to improve the diagnosis performance and decrease the workload of clinicians.

Methods: In this study, a novel deep learning model, polar residual network (PResNet) is proposed to identify MI regions in MCE images which design a polar layer considering the ring shape of the myocardium. MCE images are fed into the PResNet and a newly defined polar layer is used to describe the myocardium with a ring shape. The whole polar images are evenly divided into several subsections and a residual network is improved to classify the subsection into normal and abnormal categories. Finally, the detection results are mapped back to the original image to illustrate the infarction regions' locations for the further process.

Results: To evaluate the proposed PResNet, a dataset is constructed via performing MCE on five mice, which underwent the left anterior descending artery ligation and receive erythropoietin or saline injection, and the area variation fraction is manually annotated by an experienced expert as golden standards. The results demonstrate that the proposed PResNet model accomplishes high classification precisions with 99.6% and 98.7%, and 0.999 and 0.996 of AUC (area under the receiver operator curve) values on two different testing sets, respectively. Results suggest that the proposed model could enable accurate infarct detection and diagnosis of the MCE images.

Conclusion: Those efficiency gains highlight the powerful ability to describe and interpret the MCE images using the polar layer and residual network. The proposed PResNet might aid the clinicians in fast and accurate assessing the infarcted myocardium on MCE.
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http://dx.doi.org/10.1016/j.cmpb.2020.105791DOI Listing
January 2021

Prediction of hepatitis E using machine learning models.

PLoS One 2020 17;15(9):e0237750. Epub 2020 Sep 17.

Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China.

Background: Accurate and reliable predictions of infectious disease can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task. However, for different data series, the performance of these models varies. Hepatitis E, as an acute liver disease, has been a major public health problem. Which model is more appropriate for predicting the incidence of hepatitis E? In this paper, three different methods are used and the performance of the three methods is compared.

Methods: Autoregressive integrated moving average(ARIMA), support vector machine(SVM) and long short-term memory(LSTM) recurrent neural network were adopted and compared. ARIMA was implemented by python with the help of statsmodels. SVM was accomplished by matlab with libSVM library. LSTM was designed by ourselves with Keras, a deep learning library. To tackle the problem of overfitting caused by limited training samples, we adopted dropout and regularization strategies in our LSTM model. Experimental data were obtained from the monthly incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE).

Results: By analyzing data, we took ARIMA(1, 1, 1), ARIMA(3, 1, 2) as monthly incidence prediction model and cases number prediction model, respectively. Cross-validation and grid search were used to optimize parameters of SVM. Penalty coefficient C and kernel function parameter g were set 8, 0.125 for incidence prediction, and 22, 0.01 for cases number prediction. LSTM has 4 nodes. Dropout and L2 regularization parameters were set 0.15, 0.001, respectively. By the metrics of RMSE, we obtained 0.022, 0.0204, 0.01 for incidence prediction, using ARIMA, SVM and LSTM. And we obtained 22.25, 20.0368, 11.75 for cases number prediction, using three models. For MAPE metrics, the results were 23.5%, 21.7%, 15.08%, and 23.6%, 21.44%, 13.6%, for incidence prediction and cases number prediction, respectively. For MAE metrics, the results were 0.018, 0.0167, 0.011 and 18.003, 16.5815, 9.984, for incidence prediction and cases number prediction, respectively.

Conclusions: Comparing ARIMA, SVM and LSTM, we found that nonlinear models(SVM, LSTM) outperform linear models(ARIMA). LSTM obtained the best performance in all three metrics of RSME, MAPE, MAE. Hence, LSTM is the most suitable for predicting hepatitis E monthly incidence and cases number.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0237750PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497991PMC
October 2020

An embedded novel compact feature profile image in speech signal for teledermoscopy system.

Health Inf Sci Syst 2020 Dec 25;8(1):23. Epub 2020 Jun 25.

Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt.

Background And Objectives: Teledermoscopy is a promising telemedicine service for remote diagnosis and treatment of skin diseases using dermoscopy images. It requires high quality transmission services, efficient utilization of channel bandwidth, effective storage, and security. Thus, this work develops an improved teledermoscopy system that guarantees the efficient and secure transmission of the dermoscopy images. It proposed a novel feature-based secure diagnostic system that supports the automated classification of malignant melanoma and benign nevus at the receiver side (i.e. medical facility).

Methods: To overcome the transmission of the original dermoscopy images having large size, a novel representation of the dermoscopy images is proposed, namely the compact feature profile (CFP). The proposed CFP represents the dermoscopy image only using its significant features. For security purpose, the CFP is embedded as a watermark in a speech signal using singular value decomposition (SVD) watermarking at the transmitter. Then, the de-embedding/reconstruction process is performed at the receiver end using a proposed modified SVD technique. Finally, the extracted CFP is fed into a classifier for diagnosis at the receiver. To evaluate the robustness of the proposed system, an additive white Gaussian noise (AWGN) attack was employed during the transmission process. To improve the immunity against the AWGN attack, a novel speech signal weight factor is proposed at the watermarking process. Moreover, a compensation factor is calculated at the training phase to compensate the effect of the channel AWGN attack at the receiver. In addition, the superior transform domain and embedding positions of the CFP in the speech signal were studied.

Results: The experimental results established that the proposed CFP diagnostic system achieved high classification accuracy, sensitivity, specificity, and F-measure for classifying the two skin cancer classes with the presence of signal-to-noise ratio (SNR) ranging from 10 to 25 dB.

Conclusion: This work established that the newly proposed CFP watermarked in speech signal using the DWT-based modified SVD followed by single-level decomposition Db1 with hard thresholding wavelet denoising achieved efficient diagnostic teledermoscopy system.
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http://dx.doi.org/10.1007/s13755-020-00113-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316950PMC
December 2020

Intuitionistic based segmentation of thyroid nodules in ultrasound images.

Comput Biol Med 2020 06 4;121:103776. Epub 2020 May 4.

Department of Computer Science, University of Illinois at Springfield, Springfield, IL, USA. Electronic address:

Accurate delineation of thyroid nodules in ultrasound images is vital for computer-aided diagnosis. Most segmentation methods are semi-automated for thyroid nodules and require manual intervention, which increases the processing time and errors. We propose an automated intuitionistic fuzzy active contour method (IFACM) that integrates intuitionistic fuzzy clustering with an active contour for thyroid nodule segmentation using ultrasound images. Intuitionistic fuzzy clustering is used for the initialization of an active contour and estimation of the parameters required to automatically control the curve evolution. The IFACM was tested extensively on both artificial and real ultrasound images. The IFACM obtained a higher value of true positive (95.1% ± 2.86%), overlap metric (93.1 ± 2.95%), and dice coefficient (90.90 ± 3.08), indicating that the boundary delineated by the IFACM fits best to true nodules. Moreover, it obtained a lower value of false positive (04.1% ± 3.24%) and Hausdorff distance (0.50 ± 0.21 in pixels), further verifying the higher similarity of shape and boundary, respectively. According to the significance test, the results of the proposed method were more significant than those of the other segmentation methods. The main benefit of the IFACM is the automatic identification of nodules on the basis of image characteristics, which eliminates manual intervention. In all the experiments, all initial contours were automatically defined closer to the boundaries of the nodule, which is a benefit of the IFACM. Moreover, this method can segment multiple nodules in a single image efficiently.
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http://dx.doi.org/10.1016/j.compbiomed.2020.103776DOI Listing
June 2020

Deep learning of mammary gland distribution for architectural distortion detection in digital breast tomosynthesis.

Phys Med Biol 2021 01 30;66(3):035028. Epub 2021 Jan 30.

School of Data and Computer Science, Sun Yat-sen University, Guangzhou, People's Republic of China. Authors contributed equally to this work.

Computer aided detection (CADe) for breast lesions can provide an important reference for radiologists in breast cancer screening. Architectural distortion (AD) is a type of breast lesion that is difficult to detect. A majority of CADe methods focus on detecting the radial pattern, which is a main characteristic of typical ADs. However, a few atypical ADs do not exhibit such a pattern. To improve the performance of CADe for typical and atypical ADs, we propose a deep-learning-based model that used mammary gland distribution as prior information to detect ADs in digital breast tomosynthesis (DBT). First, information about gland distribution, including the Gabor magnitude, the Gabor orientation field, and a convergence map, were produced using a bank of Gabor filters and convergence measures. Then, this prior information and an original slice were input into a Faster R-CNN detection network to obtain the 2-D candidates for each slice. Finally, a 3-D aggregation scheme was employed to fuse these 2-D candidates as 3-D candidates for each DBT volume. Retrospectively, 64 typical AD volumes, 74 atypical AD volumes, and 127 normal volumes were collected. Six-fold cross-validation and mean true positive fraction (MTPF) were used to evaluate the model. Compared to an existing convergence-based model, our proposed model achieved an MTPF of 0.53 ± 0.04, 0.61 ± 0.05, and 0.45 ± 0.04 for all DBT volumes, typical + normal volumes, and atypical + normal volumes, respectively. These results were significantly better than those of 0.36 ± 0.03, 0.46 ± 0.04, and 0.28 ± 0.04 for a convergence-based model (p ≪ 0.01). These results indicate that employing the prior information of gland distribution and a deep learning method can improve the performance of CADe for AD.
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http://dx.doi.org/10.1088/1361-6560/ab98d0DOI Listing
January 2021

Lysobacter may drive the hormetic effects of Pb on soil alkaline phosphatase.

Environ Sci Pollut Res Int 2020 May 11;27(15):17779-17788. Epub 2020 Mar 11.

College of Biology and the Environment, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China.

It has become increasingly recognized that hormesis phenomena exist in soil ecosystem, but the research on the hormetic responses of soil enzymes are still limited. This study was conducted to investigate the hormetic effects of lead (Pb) on the activity of soil alkaline phosphatase (ALP) and the associated microbial groups. Soils were treated by adding Pb (NO) solution with 0, 10, 100, 500, 1000, 2000, 4000, and 5000 mg/kg of Pb, respectively. A moist heat sterilization method (121 °C × 30 min) was used to discriminate the microbial effect on soil ALP hormesis from other factors. The bacterial community composition and abundance in the control (CK) and Pb-treated soils were detected by the high-throughput sequencing technique. The ALP activity at doses of 500-1000 mg/kg of Pb was significantly higher than that of CK (0 mg/kg of Pb), showing a typical inverted U-shaped dose response with the stimulation magnitude of 9.8-10.3% within 48 h of incubation. In addition, ALP activity decreased by 80% on average after soil sterilization. Analysis of bacterial community composition indicated that the relative abundance of Lysobacter at 1000 mg Pb/kg was higher than that of CK at genus level, with the increase of 69.82%. The highly significant correlation between soil ALP activities and relative abundance of Lysobacter indicated that this bacterial genus could possibly contribute to the hormetic responses of soil ALP to added doses of Pb in soils.
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http://dx.doi.org/10.1007/s11356-020-08278-2DOI Listing
May 2020

Soil organic carbon pool and chemical composition under different types of land use in wetland: Implication for carbon sequestration in wetlands.

Sci Total Environ 2020 May 28;716:136996. Epub 2020 Jan 28.

College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China; National Positioning Observation Station of Hung-tse Lake Wetland Ecosystem in Jiangsu Province, Hongze 223100, China. Electronic address:

This study was conducted to understand how different wetland vegetation-land use types influenced the storage and stability of soil organic carbon (SOC) in surface soils. We determined the concentration and chemical composition of SOC in both density (including light fraction organic carbon (LFOC) and heavy fraction organic carbon (HFOC)) and particle size fractions (including <2 μm, 2-63 μm, 63-200 μm and 200-2000 μm) in four wetland land use types covered with different vegetation: lake-sedge, reed, willow and poplar wetlands. Results showed that the concentrations and stock of SOC and LFOC in willow and poplar wetlands were significantly higher than those in lake-sedge and reed. However, a higher proportion of alkyl-C and a lower proportion of O-alkyl-C were observed in lake-sedge and reed wetlands than in willow and poplar, suggesting that accumulated C in willow and poplar wetlands was less stable than that in lake-sedge and reed. For all particle-size fractions except the silt (2-63 μm), the SOC concentrations were highest in willow and lowest in reed wetland surface soils, while their alkyl-C/O-alkyl-C (A/O-A) and hydrophobic-C/hydrophilic-C ratios progressively decreased from lake-sedge and reed wetland surface soils to poplar and willow surface soils. Moreover, the ratios of A/O-A and hydrophobic-C/hydrophilic-C in surface soils generally decreased with increasing concentrations of SOC in particle-size fractions, with these stability indexes being lowest in the largest particle-size fraction. These results indicate that the wetland vegetation-land use types that could incorporate more C into finer particle-size fractions had a greater potential for sequestering more stable C in such wetland ecosystems. Different wetland vegetation-land use types resulted in significant changes in the concentration and chemical structure of SOC, which could affect soil C sequestration and dynamics, C cycling in wetland ecosystems. Although both willow and poplar forests could increase SOC stock, the stability of SOC in willow wetland was higher. Therefore, on balance (stock and stability) the land use of wetland for willow forest could be a more promising way for enhancing soil C sequestration in wetlands.
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http://dx.doi.org/10.1016/j.scitotenv.2020.136996DOI Listing
May 2020

A novel weighted compressive sensing using L1-magic recovery technique in medical image compression.

Health Inf Sci Syst 2020 Dec 23;8(1). Epub 2019 Dec 23.

1Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt.

Recent technological advancement in computing technology, communication systems, and machine learning techniques provides opportunities to biomedical engineers to achieve the requirements of clinical practice. This requires storage and/or transmission of medical images with the conservation of the medical information over the communication channel. Accordingly, medical compression is necessary for efficient channel bandwidth utilization. To solve the trade-off between the compression ratio and the preservation of significant information, compressed sensing (CS) can be used. During image recovery in CS, an optimization algorithm is used, such as greedy pursuit, convex relaxation, and Bayesian framework. In the present work, a convex relaxation optimization called L1-magic is employed, where the objective function can be relaxed to the nearest convex norm, i.e., ℓ1-norm. In addition, the discrete cosine transform is used for recovery by transforming the image from time- to frequency-domain. To improve the medical image recovery, a weighted L1-magic is proposed using a threshold based on the image content, where high weight is given to the significant details in the image. Thus, the significant information in the image (values greater than the threshold) is multiplied by a weight factor according to the image characteristics for a successful recovery process. A comparative study of the proposed weighted L1-magic and orthogonal matching pursuit (OMP), one of the greedy algorithms, was conducted. Different metrics were measured, including the Structural Similarity Index Measure and Peak Signal-to-Noise Ratio (PSNR) to evaluate CS performance using the proposed weighted L1-magic as well as the weighted OMP and the principal component analysis (PCA) as a traditional compression method at different compression ratios (CR). The experimental results on diabetic retinopathy images dataset proved the superiority of the weighted L1-magic method, where for example as 0.4 CR, average PSNR is 19.37, 17.95, and 15.64 using the weighted L1-magic, weighted OMP, and PCA, respectively.
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http://dx.doi.org/10.1007/s13755-019-0093-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928178PMC
December 2020

Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation.

Med Hypotheses 2020 Jan 14;134:109431. Epub 2019 Oct 14.

Department of Electrical and Electronics Engineering, Technology Faculty, Firat University, Elazig, Turkey. Electronic address:

Liver and hepatic tumor segmentation remains a challenging problem in Computer Tomography (CT) images analysis due to its shape variation and vague boundary. The general hypothesis says that deep learning methods produce improved results on medical image segmentation. This paper formulates the segmentation of liver tumor in CT abdominal images as a classification problem, and then solves it using a cascaded classifier framework based on deep convolutional neural networks. Two deep encoder-decoder convolutional neural networks (EDCNN) were constructed and trained to cascade segments of both the liver and lesions in CT images with limited image quantity. In other words, an EDCNN segments the liver image as the input for the training of a second EDCNN. The second EDCNN then segments the tumor regions within the liver ROI regions as predicted by the first EDCNN. Segmenting the hepatic tumor inside the liver ROI also significantly reduces false-positives. The proposed model was then tested using a public dataset (3DIRCADb), and several metrics were used in order to quantitatively evaluate its performance. The proposed method produced an average DICE score of 95.22% for the test set of CT images. The proposed method was then compared with some of the existing methods. The experimental results demonstrated that the proposed EDCNN achieved improved performance in segmentation accuracy over some existing methods.
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http://dx.doi.org/10.1016/j.mehy.2019.109431DOI Listing
January 2020

Pediatric population health analysis of southern and central Illinois region: A cross sectional retrospective study using association rule mining and multiple logistic regression.

Comput Methods Programs Biomed 2019 Sep 18;178:145-153. Epub 2019 Jun 18.

Office of Population Science and Policy, Southern Illinois University School of Medicine, United States. Electronic address:

Background: Southern Illinois University School of Medicine (SIUSOM) collects large amounts of data every day. SIUSOM and other similar healthcare systems are always looking for better ways to use the data to understand and address population level problems. The purpose of this study is to analyze the administrative dataset for pediatric patients served by Southern Illinois University School of Medicine (SIUSOM) to uncover patterns that correlate specific demographic information to diagnoses of pediatric diseases. The study uses a cross-sectional database of medical billing information for all pediatric patients served by SIUSOM between June 2013 and December 2016. The dataset consists of about 980.9K clinical visits for 65.4K unique patients and includes patient demographic identifiers such as their sex, date of birth, race, anonymous zipcode and primary and secondary insurance plan as well as the related pediatric diagnosis codes. The goal is to find unknown correlations in this database.

Method: We proposed a two step methodology to derive unknown correlations in SIUSOM administrative database. First, Class association rule mining was used as a well-established data mining method to generate hypothesis and derive associations of the form D → M, where D is diagnosis code of a pediatric disease and M is a patient demographic identifier (age,sex, anonymous zipcode, insurance plan, or race). The resulting associations were pruned and filtered using measures such as lift, odds ratio, relative risk, and confidence. The final associations were selected by a pediatric doctor based on their clinical significance. Second,each association rule in the final set was further validated and adjusted odds ratios were obtained using multiple logistic regression.

Results: Several associations were found correlating specific patients' residential zip codes with the diagnosis codes for viral hepatitis carrier, exposure to communicable diseases, screening for mental and developmental disorder in childhood, history allergy to medications, disturbance of emotions specific to childhood, and acute sinusitis. In addition, the results show that African American patients are more likely to be screened for mental and developmental disorders compared to White patients for SIUSOM pediatric population (Odds Ratio (OR):3.56, 95% Confidence Interval (CI):[3.29,3.85]).

Conclusion: Class association rule mining is an effective method for detecting signals in a large patient administrative database and generating hypotheses which correlate patients' demographics with diagnosis of pediatric diseases. A post processing of the hypotheses generated by this method is necessary to prune spurious associations and select a set of clinically relevant hypotheses.
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http://dx.doi.org/10.1016/j.cmpb.2019.06.020DOI Listing
September 2019

Magnitude of the mixture hormetic response of soil alkaline phosphatase can be predicted based on single conditions of Cd and Pb.

Ecotoxicology 2019 Sep 16;28(7):790-800. Epub 2019 Jul 16.

College of Biology and the Environment, Nanjing Forestry University, 210037, Nanjing, Jiangsu, People's Republic of China.

In soil ecosystems, it is very challenging to predict mixture hormesis effects. In the present study, soil alkaline phosphatase (ALP) was selected to investigate and predict its potential hormetic responses under Cd and Pb stresses. Typical reverse U-shaped dose-response relationships between ALP activities and the single and combined Cd and Pb were observed, showing a hormetic response of soil itself. The maximum stimulatory magnitudes ranged in 8.0 - 8.6% under 0.004 - 0.2 mg/kg Cd and 80 - 400 mg/kg Pb, respectively. An enhanced stimulation of 15.7% occurred under the binary mixtures of 0.6 mg/kg Cd and 200 mg/kg Pb. In addition, a dosage-independent binary linear regression model was proposed based on an assumption of a linear relationship between the single and combined hormetic responses under Cd and Pb. Our model can well predict ALP's responses in the presence of the two metals' mixtures (p < 0.1). Our findings provided new understandings to hormesis in soil.
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http://dx.doi.org/10.1007/s10646-019-02077-3DOI Listing
September 2019

A Radiomic feature-based Nipple Detection Algorithm on Digital Mammography.

Med Phys 2019 Oct 9;46(10):4381-4391. Epub 2019 Aug 9.

School of Data and Computer Science, Sun Yat-sen University, Guangzhou, 510006, China.

Purpose: In the diagnosis and detection of breast lesions, the nipple is an important anatomical landmark which can be used for the registration on multiview mammograms. In this study, we propose a new detection algorithm for nipples on digital mammography (DM) by applying pixel classification based on geometric and radiomic features extracted from breast boundary regions.

Methods: The imaging characteristics of nipples are closely related to the visibility on mammograms. To locate the nipple on mammogram, a searching area is first determined based on the breast boundary and chest wall orientation. Two different approaches are developed for obvious and subtle nipples, respectively. For obvious nipples, top hat transformation is employed to detect the nipple region, whose geometric center is regarded as the nipple position. For subtle nipples, the curved searching area near the breast boundary is mapped onto a Cartesian plane through a revised rubber band straightening transformation. On the straightened searching area, the geometric and radiomic features are calculated along the normal direction of the breast boundary, and a random forest classifier is trained for subtle nipple localization.

Results: Seven hundred and twenty-one DMs were collected for the evaluation of the proposed algorithm. The locations of nipples are manually identified by an experienced radiologist as the reference standard. The average Euclidean distance between the computed nipple position and the reference standard was 2.69 mm (obvious) and 7.81 mm (subtle), respectively. A total of 97.61% of the obvious nipples (613/628) and 88.17% of the subtle nipples (82/93) were detected within a 10-mm radius centered from the reference standard.

Conclusions: The evaluation results show that the proposed method is effective for nipple detection on DM, especially for subtle nipple detection.
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http://dx.doi.org/10.1002/mp.13684DOI Listing
October 2019

Time-Dependent Hormetic Response of Soil Alkaline Phosphatase Induced by Cd and the Association with Bacterial Community Composition.

Microb Ecol 2019 Nov 5;78(4):961-973. Epub 2019 Apr 5.

College of Biology and the Environment, Nanjing Forestry University, No.159 Longpan Road, Nanjing, Jiangsu, 210037, People's Republic of China.

Hormetic dose-response that involved Cd in soils is increasingly paid attentions for risk assessment of Cd toxicity, but insufficient studies were conducted to define the temporary modification of soil enzyme and the potential microbial responses. The present study chooses soil alkaline phosphatase (ALP) as endpoint to uncover the time-dependent hormetic responses to low doses of Cd and its association with bacterial community composition. The results showed that addition of 0.01-3.0 mg kg Cd significantly increased ALP's activities with maximum stimulatory magnitude of 11.4-27.2%, indicating a typical hormesis. The response started at 12 h after Cd addition and maintained about 24 h. This demonstrated that the hormetic response is time-dependent and transient. Changes of soil bacterial community composition showed that, at 6 h, relative abundances (RAs) of Proteobacteria and Firmicutes at phylum and Pontibacter, Bacillaceae-Bacillus, Bacillaceae1-Bacillus, and Paenisporosarcina at genus significantly correlated with ALP's activities at 12-36 h (P < 0.05). This suggests that soil bacteria likely showed an earlier response to Cd and potentially contributes to the subsequent soil enzyme's hormesis. In addition, it was found that Gram-negative bacteria other than Gram-positive bacteria are prone to exhibiting a hormetic response under Cd stress. Our findings provide much insight into ecotoxicological risk assessment for soil Cd pollution.
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http://dx.doi.org/10.1007/s00248-019-01371-1DOI Listing
November 2019

Domino C-H Sulfonylation and Pyrazole Annulation for Fully Substituted Pyrazole Synthesis in Water Using Hydrophilic Enaminones.

J Org Chem 2019 Mar 12;84(5):2984-2990. Epub 2019 Feb 12.

College of Chemistry and Chemical Engineering , Jiangxi Normal University , Nanchang 330022 , P. R. China.

The cascade reactions between NH-functionalized enaminones and sulfonyl hydrazines have been developed for the synthesis of fully substituted pyrazoles. By making use of the hydrophilic primary amino group in the enaminones, the reactions proceed well in the medium of pure water in the presence of molecular iodine, TBHP, and NaHCO via cascade C-H sulfonylation and pyrazole annulation. The cleavage of the C-N bond in enaminones is confirmed by the experiment using N-labeled enaminone.
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http://dx.doi.org/10.1021/acs.joc.8b02897DOI Listing
March 2019

Facile Synthesis of Unsolvated Alkali Metal Octahydrotriborate Salts MB H (M=K, Rb, and Cs), Mechanisms of Formation, and the Crystal Structure of KB H.

Angew Chem Int Ed Engl 2019 Feb 1;58(9):2720-2724. Epub 2019 Feb 1.

School of Chemistry and Chemical Engineering, Henan Key Laboratory of Boron Chemistry and Advanced Energy Materials, Henan Normal University, Xinxiang, Henan, 453007, China.

A facile synthesis of heavy alkali metal octahydrotriborates (MB H ; M=K, Rb, and Cs) has been developed. It is simply based on reactions of the pure alkali metals with THF⋅BH , does not require the use of electron carriers or the addition of other reaction media such as mercury, silica gel, or inert salts as for previous procedures, and delivers the desired products at room temperature in very high yields. However, no reactions were observed when pure Li or Na was used. The reaction mechanisms for the heavy alkali metals were investigated both experimentally and computationally. The low sublimation energies of K, Rb, and Cs were found to be key for initiation of the reactions. The syntheses can be carried out at room temperature because all of the elementary reaction steps have low energy barriers, whereas reactions of LiBH /NaBH with THF⋅BH have to be carried out under reflux. The high stability and solubility of KB H were examined, and a crystal structure thereof was obtained for the first time.
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http://dx.doi.org/10.1002/anie.201812795DOI Listing
February 2019

An optimized Mamdani FPD controller design of cardiac pacemaker.

Health Inf Sci Syst 2019 Dec 28;7(1). Epub 2018 Nov 28.

1Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt.

Cardiac pacemaker is a standard implantable medical electronic device for management and treatment of the heart rhythm disorders aiming to improved healthcare. Developing a new pacemaker based heart stimulation techniques has a vital role in preserving the patient's life. This target inspired the present work to design a new Mamdani fuzzy proportional-derivative (FPD) controller of a cardiac pacemaker, where Mamdani algorithm is the most common algorithm to deal with the human signals. The electrical pulses have closed features to the Sino atrial node pulses, which are delivered to the patient's heart chamber model using the FPD controller to regulate and recover a normal heart rate (HR) precisely. The FPD controller is considered an integration of conventional proportional-integral-derivative (PID) controller and the fuzzy techniques to realize precise, controlled and regulated HR that follows the desired set point. Furthermore, an optimization technique is used to determine the optimally tuned gains of the controller. The proposed model is designed, tested, and simulated along with tuning the controller gains using Matlab/Simulink software. The simulation results confirmed the impact of the proposed controller to achieve the optimal HR adaptation to the desired patient's physiological needs at rest compared to the existing PID, fuzzy and fuzzy PID control algorithms. The output response has a closed and regulated pacing rate with a rapid rise time of 0.5 s, the rapid settling time of 2 s, and very small error of 0.5% with overshooting of 0.4%.
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http://dx.doi.org/10.1007/s13755-018-0063-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261926PMC
December 2019

Li(NH)BH: a new ionic liquid octahydrotriborate.

Chem Commun (Camb) 2019 Jan;55(3):408-411

Department of Materials Science, Fudan University, Shanghai, 200433, China.

We report a strategy of using small cations to construct ionic liquid octahydrotriborate. The novel liquid Li(NH3)B3H8, prepared by a facile reaction of NH4B3H8 with LiH, froze below -33.4 °C and crystallized into a monoclinic unit cell with lattice parameters of a = 8.813(1) Å, b = 8.8626(1) Å, c = 8.2076(1) Å, and β = 110.1046(5)°, providing a promising functional liquid octahydrotriborate with the highest B3H8- content and lowest freezing temperature.
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http://dx.doi.org/10.1039/c8cc08300bDOI Listing
January 2019

A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Comput Methods Programs Biomed 2018 Dec 30;167:43-48. Epub 2018 Oct 30.

Electrical and Electronics Engineering Department, Firat University, Elazig, Turkey.

Background And Objective: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detection is still a challenging problem due to variations in morphology of the vessels on noisy and low contrast fundus images.

Methods: In this paper, we formulate the detection task as a classification problem and solve it using a multiple classifier framework based on deep convolutional neural networks. The multiple deep convolutional neural network (MDCNN) is constructed and trained on fundus images with limited image quantity. The MDCNN is trained using an incremental learning strategy to improve the networks' performance. The final classification results are obtained from the voting procedure on the results of MDCNN.

Results: The MDCNN achieves better performance and significantly outperforms the state-of-the-art for automatic retinal vessel segmentation on the DRIVE dataset with 95.97% and 96.13% accuracy and 0.9726 and 0.9737 AUC (area below the operator receiver character curve) score on training and testing sets, respectively. Another public dataset, STARE, is also used to evaluate the proposed network. The experimental results demonstrate that the proposed MDCNN network achieves 95.39% accuracy and 0.9539 AUC score in STARE dataset. We further compare our result with several state-of-the-art methods based on AUC values. The comparison is shown that our proposal yields the third best AUC value.

Conclusions: Our method yields the better performance in the compared the state of the art methods. In addition, our proposal has no preprocessing stage, and the input color fundus images are fed into the CNN directly.
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http://dx.doi.org/10.1016/j.cmpb.2018.10.021DOI Listing
December 2018

Ensemble of subspace discriminant classifiers for schistosomal liver fibrosis staging in mice microscopic images.

Health Inf Sci Syst 2018 Dec 1;6(1):21. Epub 2018 Nov 1.

3Department of Radiology, University of Michigan Medical School, Ann Arbor, USA.

Schistosomiasis is one of the dangerous parasitic diseases that affect the liver tissues leading to liver fibrosis. Such disease has several levels, which indicate the degree of fibrosis severity. To assess the fibrosis level for diagnosis and treatment, the microscopic images of the liver tissues were examined at their different stages. In the present work, an automated staging method is proposed to classify the statistical extracted features from each fibrosis stage using an ensemble classifier, namely the subspace ensemble using linear discriminant learning scheme. The performance of the subspace/discriminant ensemble classifier was compared to other ensemble combinations, namely the boosted/trees ensemble, bagged/trees ensemble, subspace/KNN ensemble, and the RUSBoosted/trees ensemble. The simulation results established the superiority of the proposed subspace/discriminant ensemble with 90% accuracy compared to the other ensemble classifiers.
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http://dx.doi.org/10.1007/s13755-018-0059-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6212370PMC
December 2018
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