Causal Analysis of Customer Churn Using Deep Learning

Customer churn describes terminating a relationship with a business or reducing customer engagement over a specific period. Two main business marketing strategies play vital roles to increase market share dollar- value: gaining new and preserving existing customers. Customer acquisition cost can be five to six times that for customer retention, hence investing in customers with churn risk is smart. Causal analysis of the churn model can predict whether a customer will churn in the foreseeable future and assist enterprises to identify effects and possible causes for churn and subsequently use that knowledge to apply tailored incentives. This paper proposes a framework using a deep feedforward neural network for classification accompanied by a sequential pattern mining method on high-dimensional sparse data. We also propose a causal Bayesian network to predict cause probabilities that lead to customer churn. Evaluation metrics on test data confirm the XGBoost and our deep learning model outperformed previous techniques. Experimental analysis confirms that some independent causal variables representing the level of super guarantee contribution, account growth, and customer tenure were identified as confounding factors for customer churn with a high degree of belief. This paper provides a real-world customer churn analysis from current status inference to future directions in local superannuation funds

Spectral weight transfer in a disorder-broadened Landau level

In the absence of disorder, the degeneracy of a Landau level (LL) is $N=BA/\phi_0$, where $B$ is the magnetic field, $A$ is the area of the sample and $\phi_0=h/e$ is the magnetic flux quantum. With disorder, localized states appear at the top and bottom of the broadened LL, while states in the center of the LL (the critical region) remain delocalized. This well-known phenomenology is sufficient to explain most aspects of the Integer Quantum Hall Effect (IQHE) [1]. One unnoticed issue is where the new states appear as the magnetic field is increased. Here we demonstrate that they appear predominantly inside the critical region. This leads to a certain ``spectral ordering'' of the localized states that explains the stripes observed in measurements of the local inverse compressibility [2-3], of two-terminal conductance [4], and of Hall and longitudinal resistances [5] without invoking interactions as done in previous work [6-8].Comment: 5 pages 3 figure

The correlates of urinary albumin to creatinine ratio (ACR) in a high risk Australian Aboriginal community

Background: Albuminuria marks renal disease and cardiovascular risk. It was estimated to contribute 75% of the risk of all-cause natural death in one Aboriginal group. The urine albumin/creatinine ratio (ACR) is commonly used as an index of albuminuria. This study aims to examine the associations between demographic factors, anthropometric index, blood pressure, lipid-protein measurements and other biomarkers and albuminuria in a cross-sectional study in a high-risk Australian Aboriginal population. The models will be evaluated for albuminuria at or above the microalbuminuria threshold, and at or above the "overt albuminuria" threshold with the potential to distinguish associations they have in common and those that differ

Structural Characterization of Mesoporous Silica Nanofibers Synthesized Within Porous Alumina Membranes

Mesoporous silica nanofibers were synthesized within the pores of the anodic aluminum oxide template using a simple sol–gel method. Transmission electron microscopy investigation indicated that the concentration of the structure-directing agent (EO20PO70EO20) had a significant impact on the mesostructure of mesoporous silica nanofibers. Samples with alignment of nanochannels along the axis of mesoporous silica nanofibers could be formed under the P123 concentration of 0.15 mg/mL. When the P123 concentration increased to 0.3 mg/mL, samples with a circular lamellar mesostructure could be obtained. The mechanism for the effect of the P123 concentration on the mesostructure of mesoporous silica nanofibres was proposed and discussed

Effects of an Alpha-4 Integrin Inhibitor on Restenosis in a New Porcine Model Combining Endothelial Denudation and Stent Placement

Restenosis remains the main complication of balloon angioplasty and/or stent implantation. Preclinical testing of new pharmacologic agents preventing restenosis largely rely on porcine models, where restenosis is assessed after endothelial abrasion of the arterial wall or stent implantation. We combined endothelial cell denudation and implantation of stents to develop a new clinically relevant porcine model of restenosis, and used this model to determine the effects of an α4 integrin inhibitor, ELN 457946, on restenosis. Balloon-angioplasty endothelial cell denudation and subsequent implantation of bare metal stents in the left anterior descending coronary, iliac, and left common carotid arteries was performed in domestic pigs, treated with vehicle or ELN 457946, once weekly via subcutaneous injections, for four weeks. After 1 month, histopathology and morphometric analyses of the arteries showed complete healing and robust, consistent restenotic response in stented arteries. Treatment with ELN 457946 resulted in a reduction in the neointimal response, with decreases in area percent stenosis between 12% in coronary arteries and 30% in peripheral vessels. This is the first description of a successful pig model combining endothelial cell denudation and bare metal stent implantation. This new double injury model may prove particularly useful to assess pharmacological effects of drug candidates on restenosis, in coronary and/or peripheral arteries. Furthermore, the ELN 457946 α4 integrin inhibitor, administered subcutaneously, reduced inflammation and restenosis in stented coronary and peripheral arteries in pigs, therefore representing a promising systemic therapeutic approach in reducing restenosis in patients undergoing angioplasty and/or stent implantation

Epstein-Barr Virus Infection and Sporadic Breast Cancer Risk: A Meta-Analysis

BACKGROUND: A large number of epidemiological studies have evaluated the association between Epstein-Barr virus infection and breast carcinoma risk but results have been inconsistent. METHODOLOGY: Research using the polymerase chain reaction technique for detecting the Epstein-Barr virus was selected; 24 studies and 1535 cases were reviewed. Information on the study populations, sample types, publication calendar period and histological types of breast carcinoma were collected. An unconditional logistic regression model was used to analyze potential parameters related to the Epstein-Barr virus prevalence. A Kappa test was used to evaluate the consistency in detecting different Epstein-Barr virus DNA regions. Nine studies that included control groups and 1045 breast cancer cases were adopted in this meta-analysis. CONCLUSIONS: We found that 29.32% of the patients with breast carcinoma were infected with the Epstein-Barr virus. The prevalence of Epstein-Barr was highest in Asia (35.25%) and lowest in the USA (18.27%). Statistical analysis revealed a trend that showed lobular breast carcinoma might have the strongest association with Epstein-Barr virus infection. This meta-analysis showed a significant increase in breast malignancy risk in patients testing positive for the Epstein-Barr virus (OR = 6.29, 95% CI = 2.13-18.59). This result suggests that an Epstein-Barr virus infection is statistically associated with increased breast carcinoma risk

NMR methods to monitor the enzymatic depolymerization of heparin

Heparin and the related glycosaminoglycan, heparan sulfate, are polydisperse linear polysaccharides that mediate numerous biological processes due to their interaction with proteins. Because of the structural complexity and heterogeneity of heparin and heparan sulfate, digestion to produce smaller oligosaccharides is commonly performed prior to separation and analysis. Current techniques used to monitor the extent of heparin depolymerization include UV absorption to follow product formation and size exclusion or strong anion exchange chromatography to monitor the size distribution of the components in the digest solution. In this study, we used 1H nuclear magnetic resonance (NMR) survey spectra and NMR diffusion experiments in conjunction with UV absorption measurements to monitor heparin depolymerization using the enzyme heparinase I. Diffusion NMR does not require the physical separation of the components in the reaction mixture and instead can be used to monitor the reaction solution directly in the NMR tube. Using diffusion NMR, the enzymatic reaction can be stopped at the desired time point, maximizing the abundance of larger oligosaccharides for protein-binding studies or completion of the reaction if the goal of the study is exhaustive digestion for characterization of the disaccharide composition. In this study, porcine intestinal mucosa heparin was depolymerized using the enzyme heparinase I. The unsaturated bond formed by enzymatic cleavage serves as a UV chromophore that can be used to monitor the progress of the depolymerization and for the detection and quantification of oligosaccharides in subsequent separations. The double bond also introduces a unique multiplet with peaks at 5.973, 5.981, 5.990, and 5.998 ppm in the 1H-NMR spectrum downfield of the anomeric region. This multiplet is produced by the proton of the C-4 double bond of the non-reducing end uronic acid at the cleavage site. Changes in this resonance were used to monitor the progression of the enzymatic digestion and compared to the profile obtained from UV absorbance measurements. In addition, in situ NMR diffusion measurements were explored for their ability to profile the different-sized components generated over the course of the digestion