Cluster Analysis Based on Bipartite Network

Clustering data has a wide range of applications and has attracted considerable attention in data mining and artificial intelligence. However it is difficult to find a set of clusters that best fits natural partitions without any class information. In this paper, a method for detecting the optimal cluster number is proposed. The optimal cluster number can be obtained by the proposal, while partitioning the data into clusters by FCM (Fuzzy c-means) algorithm. It overcomes the drawback of FCM algorithm which needs to define the cluster number c in advance. The method works by converting the fuzzy cluster result into a weighted bipartite network and then the optimal cluster number can be detected by the improved bipartite modularity. The experimental results on artificial and real data sets show the validity of the proposed method

Semisupervised Community Detection by Voltage Drops

Many applications show that semisupervised community detection is one of the important topics and has attracted considerable attention in the study of complex network. In this paper, based on notion of voltage drops and discrete potential theory, a simple and fast semisupervised community detection algorithm is proposed. The label propagation through discrete potential transmission is accomplished by using voltage drops. The complexity of the proposal is OV+E for the sparse network with V vertices and E edges. The obtained voltage value of a vertex can be reflected clearly in the relationship between the vertex and community. The experimental results on four real networks and three benchmarks indicate that the proposed algorithm is effective and flexible. Furthermore, this algorithm is easily applied to graph-based machine learning methods

Artificial intelligence and data mining: algorithms and applications

Artificial intelligence and data mining techniques have been used in many domains to solve classification, segmentation, association, diagnosis, and prediction problems. The overall aim of this special issue is to open a discussion among researchers actively working on algorithms and applications. The issue covers a wide variety of problems for computational intelligence, machine learning, time series analysis, remote sensing image mining, and pattern recognition. After a rigorous peer review process, 20 papers have been selected from 38 submissions. The accepted papers in this issue addressed the following topics: (i) advanced artificial intelligence and data mining techniques; (ii) computational intelligence in dynamic and uncertain environments; (iii) machine learning on massive datasets; (iv) time series data analysis; (v) Spatial data mining: algorithms and applications

The Local Brain Abnormalities in Patients With Transient Ischemic Attack: A Resting-State fMRI Study

Background: Transient ischemic attack (TIA) is an important risk factor for stroke. Despite the transient episodes of clinical symptoms, brain alterations are still observed in patients with TIA. However, the functional mechanism of transient ischemia is still unclear. Here, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to explore the functional abnormalities in patients with TIA.Methods: 48 TIA patients and 41 age- and sex-matched healthy controls (HCs) were enrolled in the study. For each participant, we collected rs-fMRI data and clinical/physiological/biochemical data. Amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) were then calculated. Two sample t-tests were performed to compare the ALFF, ReHo, and DC maps between the two groups. Furthermore, a correlation analysis was performed to explore the relationship between local brain abnormalities and clinical/physiological/biochemical characteristics tests in TIA patients.Results: Compared with the HCs, the TIA patients exhibited decreased ALFF in the left middle temporal gyrus, decreased DC in the triangular part of right inferior frontal gyrus, and no significant statistical difference in ReHo. No correlation was found between local abnormalities and clinical/physiological/biochemical scores in the patients with TIA.Conclusion: Collectively, we found decreased ALFF and DC in patients with TIA which provide evidence for local brain dysfunctions and may help to understand the pathological mechanism for the disease

Adjustable single-incision mini-slings (Ajust®) versus other slings in surgical management of female stress urinary incontinence: a meta-analysis of effectiveness and complications

Abstract Background Adjustable single-incision mini-sling (SIMS) is a new category of SIMS for stress urinary incontinence (SUI). The aim of this study was to compare the efficacy and safety of adjustable single-incision mini-sling with other slings. Methods Literature search in databases such as Pubmed, and Conchrane Library was performed up to December, 2015. The outcomes including cure rate, operation time, postoperative pain score and complications were reanalyzed. The pooled relative risk (RR) and mean difference (MD) with their 95% confidence interval (95% CI) were calculated by RevMan v5.0. Results Eight studies with 1093 SUI female patients were included. There was no significant difference between adjustable SIMS and other slings (transobturator slings and MiniArc) in patients subjective cure rate and objective cure rate. In addition, adjustable SIMS was associated with a significantly shorter operative time and lower postoperative pain score when comparing adjustable SIMS with transobturator tape (MD = − 1.35; 95%CI: -2.24 to − 0.46, P = 0.003). For the complications, there was also no significant difference between adjustable SIMS and transobturator slings. Conclusions Adjustable SIMS had equally efficacy for SUI compared with transobturator slings and MiniArc. However, the significantly shorter operative time and lower postoperative pain score than transobturator tape supported the clinical application of adjustable SIMS

Safe and effective subcutaneous adipolysis in minipigs by a collagenase derivative.

Adipocytes attached to the extracellular matrix (ECM) mainly consist of collagen in adipose tissues, while the degradation of ECM by collagenase induces the apoptosis of adipocytes, leading to a decrease in local subcutaneous adipose. To achieve this goal, we are developing a mutant collagenase H (ColH) to remove local subcutaneous fat such as submental fat (SMF). Three vectors were constructed for expressing rColH(FM, mutant for fat melting, with 6xHis tag), rColH(WT, wild-type, with 6xHis tag), and rColH(E451D, E451D mutant, without 6xHis tag) in Escherichia coli. rColH(FM) & rColH(WT) were purified by Ni Sepharose on a laboratory scale, while rColH(E451D) was purified by five chromatography purification steps on a large scale. Then, the stability of rColH(FM) and rColH(WT) was tested by SDS-PAGE to investigate the influence of the E451D mutation on stability. Afterwards, the enzyme kinetics of ColH (mutant or wild-type, with or without His tag) were investigated and compared. Finally, the adipolysis of rColH(E451D) at various doses was tested in vitro and in vivo. The ultrasound results in minipigs suggested that effective adipolysis was induced by rColH(E451D) compared with the negative control, and the histological results suggest dose-dependent fibrosis, necrosis, inflammation and cholesterol cleft formation. These findings indicate the possibility of rColH(E451D) becoming a new injectable drug to safely remove subcutaneous adipose

Adsorption isotherm, mechanism, and geometry of Pb(II) on magnetites substituted with transition metals

Iron oxides are abundant in natural waters and soils and have high capacities for scavenging Pb(II) by adsorption, which affects the transport and fate of Pb on the earth's surface. We investigated the adsorption of Pb (II) on magnetites substituted with commonly incorporated transition metals such as Cr, Mn, Co, and Ni. The adsorption capacity, mechanism, and local coordination of Pb(II) were investigated by traditional macroscopic studies, i.e., acid-base titration and batch adsorption experiment, complemented with X-ray absorption fine structure (XAFS) spectrum analysis and surface complexation model (SCM). The substitution increased the surface site density, while pHpzc did not vary. Pb(II) adsorption was not suppressed by the presence of background electrolyte and improved as pH increased. The isotherms were well fit to the Langmuir adsorption model. The XAFS analysis demonstrated that Pb(II) ions were adsorbed on magnetite surface predominantly via innersphere complexation, where the adsorbed Pb(II) species was in bidentate binuclear corner-sharing geometry, independent of the adsorption capacity. This adsorption geometry can be applied to fit the experimental adsorption data well with the diffuse layer model (DLM). The substitutions improved the adsorption capacity in the following order: Cr > Ni > Mn > Co, and were discussed regarding the measured values of active site density and local coordination of adsorbed Pb(II). This study is the first documentation of Pb(II) adsorption on magnetite with different substitutions. The obtained results are of great significance for the understanding of Pb(II) surface complexation reactions on magnetite surface

Comparison of Serum Soluble Corin Levels among Stroke Subtypes

Background: Serum soluble corin was decreased not only in some cardiac diseases, but also in stroke. Cardiogenic sources play a critical role in ischemic stroke. Serum soluble corin level in stroke subtypes has not been studied. Here we aimed to study corin level in 4 stroke subtypes: hemorrhagic, thrombotic, embolic and lacunar stroke.Methods: 116 hemorrhagic stroke, 320 thrombotic stroke patients, 48 embolic stroke patients and 102 lacunar stroke patients were studied. Serum soluble corin was measured and some conventional risk factors of stroke were collected. We compared corin level among different types of stroke in men and women respectively.Results: Serum soluble corin level was significantly higher in ischemic stroke patients than hemorrhagic stroke patients in men (log-corin, mean±SD:7.53±0.34 vs. 7.42±0.28; P =0.013) and women (log-corin, mean±SD:7.22±0.27 vs. 7.12±0.31; P = 0.044). Then we studied serum soluble corin in subtypes of ischemic stroke. Unadjusted analysis failed to show a significant difference in logtransformed serum soluble corin among different ischemic stroke subtypes in both men and women. However, after adjustment for the covariables, the mean level of log-transformed serum soluble corin was significantly increased in embolic stroke patients compared with other subtypes in men (P &lt;0.05). In women, embolic stroke patients also had the highest mean level of log-transformed serum soluble corin but with no significant difference. After excluding patients with a history of coronary heart disease, the mean level of serum soluble corin was still the highest in embolic stroke patients among men and women however with no significance.Conclusions: Serum soluble corin was higher in ischemic stroke than hemorrhagic stroke and thehighest in embolic stroke. Our findings indicated that corin may be a candidate biomarker used in thedifferentiate diagnosis of embolism from the heart.</p