A new fuzzy classifier with triangular membership functions

Fuzzy logic is widely applied in control and modeling for its robustness, simplicity and clarity. It is also applied in classifier design with rules directly generated from numerical data. Some available rule generation methods, however, are either too complicated to implement or impractical for high dimensions. In this paper, we propose a new fuzzy classifier architecture. At the very beginning the training data is clustered at the input space. Fuzzy sets are then defined based on these clusters with triangular membership function. The outputs in the rule conclusion are initially determined by the “normalized vote” in the corresponding cluster. Fuzzy sets and conclusions can be adjusted through training. The proposed fuzzy system is simple in structure, and can be fast trained and easily implemented. Its classification performance is generally better than artificial neural network.published_or_final_versio

Neoproterozoic Mafic-Ultramafic Intrusions from the Fanjingshan Region, South China: Implications for Subduction-Related Magmatism in the Jiangnan Fold Belt

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A new fuzzy approach for pattern recognition with application to EMG classification

A fuzzy logic system with center average defuzzifier, product-inference rule, nonsingleton fuzzifier and Gauss membership function is discussed. The fuzzy sets are initially defined by the cluster parameters from the Basic ISO-DATA algorithm on input space. The system is then trained via back error propagation algorithm so that the fuzzy sets are fine-tuned. The system is applied to functional EMG classification and compared with its ANN counterpart. It is superior to the latter in at least three points: higher recognition rate; insensitive to over-training; and more consistent outputs thus having higher reliability.published_or_final_versio

Fuzzy EMG classification for prosthesis control

This paper proposes a fuzzy approach to classify single-site electromyograph (EMG) signals for multifunctional prosthesis control. While the classification problem is the focus of this paper, the ultimate goal is to improve myoelectric system control performance, and classification is an essential step in the control. Time segmented features are fed to a fuzzy system for training and classification. In order to obtain acceptable training speed and realistic fuzzy system structure, these features are clustered without supervision using the Basic Isodata algorithm at the beginning of the training phase, and the clustering results are used in initializing the fuzzy system parameters. Afterwards, fuzzy rules in the system are trained with the back-propagation algorithm. The fuzzy approach was compared with an artificial neural network (ANN) method on four subjects, and very similar classification results were obtained. It is superior to the latter in at least three points: slightly higher recognition rate; insensitivity to overtraining; and consistent outputs demonstrating higher reliability. Some potential advantages of the fuzzy approach over the ANN approach are also discussed.published_or_final_versio

Variations in subclinical left ventricular dysfunction, functional capacity, and clinical outcomes in different heart failure aetiologies

Aims: Patients with heart failure (HF) risk factors are described as being in Stage A of this condition (SAHF). Management is directed towards prevention of HF progression, but to date, no evidence has been described to align the intensity of this intervention to HF risk. We sought to what extent SAHF of Type 2 diabetes mellitus (T2DM) and other HF risks showed differences in subclinical left ventricular function, exercise capacity, and prognosis.Methods and Results: We recruited 551 elder asymptomatic SAHF patients (age 71 ± 5 years, 49% men, 290 T2DM) with at least one risk factor from a community-based population with preserved ejection fraction. All underwent a comprehensive echocardiogram including global longitudinal strain (GLS) and a 6 min walk test and were followed for 2 years. The primary endpoints were new-onset HF and all-cause mortality. The T2DM group was associated with reduced 6 min walk test distance (451 ± 111 vs. 493 ± 87 m, P P = 0.028), and impaired GLS (-17.7 ± 2.6% vs. -19.0 ± 2.6%, P P = 0.021). In Cox models, obesity [hazard ratio (HR) = 2.46; P = 0.007], atrial fibrillation (HR = 2.39; P = 0.028), 6 min walk distance (HR = 0.99; P = 0.034), and GLS (HR = 1.14; P = 0.033) were independently associated with the primary endpoint in T2DM-SAHF, independent of age and glycaemic control.Conclusions: The T2DM-SAHF has worse subclinical left ventricular function, exercise capacity, and prognosis than other-SAHF. Impaired GLS, atrial fibrillation, exercise capacity, and obesity are associated with a worse prognosis in T2DM-SAHF but not in other-SAHF

STM and RHEED study of the Si(001)-c(8x8) surface

The Si(001) surface deoxidized by short annealing at T~925C in the ultrahigh vacuum molecular beam epitaxy chamber has been in situ investigated by high resolution scanning tunnelling microscopy (STM) and reflected high energy electron diffraction (RHEED). RHEED patterns corresponding to (2x1) and (4x4) structures were observed during sample treatment. The (4x4) reconstruction arose at T<600C after annealing. The reconstruction was observed to be reversible: the (4x4) structure turned into the (2x1) one at T>600C, the (4x4) structure appeared again at recurring cooling. The c(8x8) reconstruction was revealed by STM at room temperature on the same samples. A fraction of the surface area covered by the c(8x8) structure decreased as the sample cooling rate was reduced. The (2x1) structure was observed on the surface free of the c(8x8) one. The c(8x8) structure has been evidenced to manifest itself as the (4x4) one in the RHEED patterns. A model of the c(8x8) structure formation has been built on the basis of the STM data. Origin of the high-order structure on the Si(001) surface and its connection with the epinucleation phenomenon are discussed.Comment: 26 pages, 12 figure

Massively Parallel Sequencing Reveals the Complex Structure of an Irradiated Human Chromosome on a Mouse Background in the Tc1 Model of Down Syndrome

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and presents a complex phenotype that arises from abnormal dosage of genes on this chromosome. However, the individual dosage-sensitive genes underlying each phenotype remain largely unknown. To help dissect genotype – phenotype correlations in this complex syndrome, the first fully transchromosomic mouse model, the Tc1 mouse, which carries a copy of human chromosome 21 was produced in 2005. The Tc1 strain is trisomic for the majority of genes that cause phenotypes associated with DS, and this freely available mouse strain has become used widely to study DS, the effects of gene dosage abnormalities, and the effect on the basic biology of cells when a mouse carries a freely segregating human chromosome. Tc1 mice were created by a process that included irradiation microcell-mediated chromosome transfer of Hsa21 into recipient mouse embryonic stem cells. Here, the combination of next generation sequencing, array-CGH and fluorescence in situ hybridization technologies has enabled us to identify unsuspected rearrangements of Hsa21 in this mouse model; revealing one deletion, six duplications and more than 25 de novo structural rearrangements. Our study is not only essential for informing functional studies of the Tc1 mouse but also (1) presents for the first time a detailed sequence analysis of the effects of gamma radiation on an entire human chromosome, which gives some mechanistic insight into the effects of radiation damage on DNA, and (2) overcomes specific technical difficulties of assaying a human chromosome on a mouse background where highly conserved sequences may confound the analysis. Sequence data generated in this study is deposited in the ENA database, Study Accession number: ERP000439

Putting the pieces together: Integration for forest landscape restoration implementation

© 2019 John Wiley & Sons, Ltd. The concept of forest landscape restoration (FLR) is being widely adopted around the globe by governmental, non-governmental agencies, and the private sector, all of whom see FLR as an approach that contributes to multiple global sustainability goals. Originally, FLR was designed with a clearly integrative dimension across sectors, stakeholders, space and time, and in particular across the natural and social sciences. Yet, in practice, this integration remains a challenge in many FLR efforts. Reflecting this lack of integration are the continued narrow sectoral and disciplinary approaches taken by forest restoration projects, often leading to marginalisation of the most vulnerable populations, including through land dispossessions. This article aims to assess what lessons can be learned from other associated fields of practice for FLR implementation. To do this, 35 scientists came together to review the key literature on these concepts to suggest relevant lessons and guidance for FLR. We explored the following large-scale land use frameworks or approaches: land sparing/land sharing, the landscape approach, agroecology, and socio-ecological systems. Also, to explore enabling conditions to promote integrated decision making, we reviewed the literature on understanding stakeholders and their motivations, tenure and property rights, polycentric governance, and integration of traditional and Western knowledge. We propose lessons and guidance for practitioners and policymakers on ways to improve integration in FLR planning and implementation. Our findings highlight the need for a change in decision-making processes for FLR, better understanding of stakeholder motivations and objectives for FLR, and balancing planning with flexibility to enhance social–ecological resilience.The Frank Jackson Foundatio

Postdialysis blood pressure rise predicts long-term outcomes in chronic hemodialysis patients: a four-year prospective observational cohort study

<p>Abstract</p> <p>Background</p> <p>The blood pressure (BP) of a proportion of chronic hemodialysis (HD) patients rises after HD. We investigated the influence of postdialysis BP rise on long-term outcomes.</p> <p>Methods</p> <p>A total of 115 prevalent HD patients were enrolled. Because of the fluctuating nature of predialysis and postdialysis BP, systolic BP (SBP) and diastolic BP before and after HD were recorded from 25 consecutive HD sessions during a 2-month period. Patients were followed for 4 years or until death or withdrawal.</p> <p>Results</p> <p>Kaplan-Meier estimates revealed that patients with average postdialysis SBP rise of more than 5 mmHg were at the highest risk of both cardiovascular and all-cause mortality as compared to those with an average postdialysis SBP change between -5 to 5 mmHg and those with an average postdialysis SBP drop of more than 5 mmHg. Furthermore, multivariate Cox regression analysis indicated that both postdialysis SBP rise of more than 5 mmHg (HR, 3.925 [95% CI, 1.410-10.846], <it>p </it>= 0.008) and high cardiothoracic (CT) ratio of more than 50% (HR, 7.560 [95% CI, 2.048-27.912], <it>p </it>= 0.002) independently predicted all-cause mortality. We also found that patients with an average postdialysis SBP rise were associated with subclinical volume overload, as evidenced by the significantly higher CT ratio (<it>p </it>= 0.008).</p> <p>Conclusions</p> <p>A postdialysis SBP rise in HD patients independently predicted 4-year cardiovascular and all-cause mortality. Considering postdialysis SBP rise was associated with higher CT ratio, intensive evaluation of cardiac and volume status should be performed in patients with postdialysis SBP rise.</p