Consumer behaviour in E-Commerce : Millennials in the USA, Washington D.C area

The target of this thesis was to understand consumer behaviour in e-commerce. The target area is the Washington DC area USA from amongst young adults between 21-34 years of age classified as millennials. The impact of technology changes and variables influencing the selection process of an e-retailer among the millennials was studied. A research with help of a survey to total 285 participants in four different shopping malls was performed in the Washington D.C. metropolitan area conducted between April 1st and May 31st 2015. The findings of the survey show that both the number of consumers who use the Internet for both assessing a product and retailers that are selling via Internet is growing in the area of this research. Consumers are also purchasing with more frequency on the Internet and as such the importance of the Internet is becoming a crucial aspect to understand consumer behaviour. The items purchased on the Internet range from small purchase items of iPhone cases to large purchase of vessels and work trucks with prices ranging on the thousands of dollars. Trust is imperative on the Internet and along increasing competition it is the all more important to have a strict control of what goes in the Internet and what goes out to the Internet in regards to ones business. On a personal note, I had an experience purchasing a truck replacement part from a farm ways out in Pennsylvania farmland. The seller at the conclusion of the transaction re-marked how without “this Internet” we would have never met or known we existed. I believe that simple remark summarizes all the importance of E-Commerce

Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruning

Predictive pattern mining is an approach used to construct prediction models when the input is represented by structured data, such as sets, graphs, and sequences. The main idea behind predictive pattern mining is to build a prediction model by considering substructures, such as subsets, subgraphs, and subsequences (referred to as patterns), present in the structured data as features of the model. The primary challenge in predictive pattern mining lies in the exponential growth of the number of patterns with the complexity of the structured data. In this study, we propose the Safe Pattern Pruning (SPP) method to address the explosion of pattern numbers in predictive pattern mining. We also discuss how it can be effectively employed throughout the entire model building process in practical data analysis. To demonstrate the effectiveness of the proposed method, we conduct numerical experiments on regression and classification problems involving sets, graphs, and sequences

The Impact of KRAS Mutation in Patients With Sporadic Nonampullary Duodenal Epithelial Tumors

INTRODUCTION: The genomic characterization of primary nonampullary duodenal adenocarcinoma indicates a genetic resemblance to gastric and colorectal cancers. However, a correlation between the clinical and molecular characteristics of these cancers has not been established. This study aimed to elucidate the clinicopathological features of sporadic nonampullary duodenal epithelial tumors, including their molecular characteristics and prognostic factors. METHODS: One hundred forty-eight patients with sporadic nonampullary duodenal epithelial tumors were examined in this study. Patient sex, age, TNM stage, tumor location, treatment methods, histology, KRAS mutation, BRAF mutation, Fusobacterium nucleatum, mucin phenotype, and programmed death-ligand 1 (PD-L1) status were evaluated. KRAS and BRAF mutations, Fusobacterium nucleatum, mucin phenotype, and PD-L1 status were analyzed by direct sequencing, quantitative polymerase chain reaction, and immunochemical staining. RESULTS: The median follow-up duration was 119.4 months. There were no deaths from duodenal adenoma (the primary disease). Kaplan-Meier analysis for duodenal adenocarcinoma showed a significant effect of TNM stage (P DISCUSSION: Only KRAS mutation was a significant prognostic factor in primary sporadic nonampullary duodenal adenocarcinoma in cases in which TNM stage was considered

J-CKD-DB: a nationwide multicentre electronic health record-based chronic kidney disease database in Japan

The Japan Chronic Kidney Disease (CKD) Database (J-CKD-DB) is a large-scale, nation-wide registry based on electronic health record (EHR) data from participating university hospitals. Using a standardized exchangeable information storage, the J-CKD-DB succeeded to efficiently collect clinical data of CKD patients across hospitals despite their different EHR systems. CKD was defined as dipstick proteinuria ≥1+ and/or estimated glomerular filtration rate <60 mL/min/1.73 m² base on both out- and inpatient laboratory data. As an initial analysis, we analyzed 39, 121 CKD outpatients (median age was 71 years, 54.7% were men, median eGFR was 51.3 mL/min/1.73 m²) and observed that the number of patients with a CKD stage G1, G2, G3a, G3b, G4 and G5 were 1, 001 (2.6%), 2, 612 (6.7%), 23, 333 (59.6%), 8, 357 (21.4%), 2, 710 (6.9%) and 1, 108 (2.8%), respectively. According to the KDIGO risk classification, there were 30.1% and 25.5% of male and female patients with CKD at very high-risk, respectively. As the information from every clinical encounter from those participating hospitals will be continuously updated with an anonymized patient ID, the J-CKD-DB will be a dynamic registry of Japanese CKD patients by expanding and linking with other existing databases and a platform for a number of cross-sectional and prospective analyses to answer important clinical questions in CKD care

Prevalence of anemia in patients with chronic kidney disease in Japan: A nationwide, cross-sectional cohort study using data from the Japan Chronic Kidney Disease Database (J-CKD-DB)

Background: The Japan Chronic Kidney Disease Database (J-CKD-DB) is a nationwide clinical database of patients with chronic kidney disease (CKD) based on electronic health records. The objective of this study was to assess the prevalence of anemia and the utilization rate of erythropoiesis-stimulating agents (ESAs) in Japanese patients with CKD. Methods: In total, 31, 082 adult outpatients with estimated glomerular filtration rates of 5–60 ml/min/1.73 m2 in seven university hospitals were included this analysis. The proportions of patients with CKD stages G3b, G4, and G5 were 23.5%, 7.6%, and 3.1%, respectively. Results: The mean (standard deviation) hemoglobin level of male patients was 13.6 (1.9) g/dl, which was significantly higher than the mean hemoglobin level of female patients (12.4 (1.6) g/dl). The mean (standard deviation) hemoglobin levels were 11.4 (2.1) g/dl in patients with CKD stage G4 and 11.2 (1.8) g/dl in patients with CKD stage G5. The prevalences of anemia were 40.1% in patients with CKD stage G4 and 60.3% in patients with CKD stage G5. Logistic regression analysis showed that diagnoses of CKD stage G3b (adjusted odds ratio [95% confidence interval]: 2.32 [2.09–2.58]), G4 (5.50 [4.80–6.31]), and G5 (9.75 [8.13–11.7]) were associated with increased prevalence of anemia. The utilization rates of ESAs were 7.9% in patients with CKD stage G4 and 22.4% in patients with CKD stage G5. Conclusions: We determined the prevalence of anemia and utilization rate of ESAs in Japanese patients with CKD using data from a nationwide cohort study

Results of the search for inspiraling compact star binaries from TAMA300's observation in 2000-2004

We analyze the data of TAMA300 detector to search for gravitational waves from inspiraling compact star binaries with masses of the component stars in the range 1-3Msolar. In this analysis, 2705 hours of data, taken during the years 2000-2004, are used for the event search. We combine the results of different observation runs, and obtained a single upper limit on the rate of the coalescence of compact binaries in our Galaxy of 20 per year at a 90% confidence level. In this upper limit, the effect of various systematic errors such like the uncertainty of the background estimation and the calibration of the detector's sensitivity are included.Comment: 8 pages, 4 Postscript figures, uses revtex4.sty The author list was correcte

Observation results by the TAMA300 detector on gravitational wave bursts from stellar-core collapses

We present data-analysis schemes and results of observations with the TAMA300 gravitational-wave detector, targeting burst signals from stellar-core collapse events. In analyses for burst gravitational waves, the detection and fake-reduction schemes are different from well-investigated ones for a chirp-wave analysis, because precise waveform templates are not available. We used an excess-power filter for the extraction of gravitational-wave candidates, and developed two methods for the reduction of fake events caused by non-stationary noises of the detector. These analysis schemes were applied to real data from the TAMA300 interferometric gravitational wave detector. As a result, fake events were reduced by a factor of about 1000 in the best cases. The resultant event candidates were interpreted from an astronomical viewpoint. We set an upper limit of 2.2x10^3 events/sec on the burst gravitational-wave event rate in our Galaxy with a confidence level of 90%. This work sets a milestone and prospects on the search for burst gravitational waves, by establishing an analysis scheme for the observation data from an interferometric gravitational wave detector

The Quiescent Intracluster Medium in the Core of the Perseus Cluster

Clusters of galaxies are the most massive gravitationally-bound objects in the Universe and are still forming. They are thus important probes of cosmological parameters and a host of astrophysical processes. Knowledge of the dynamics of the pervasive hot gas, which dominates in mass over stars in a cluster, is a crucial missing ingredient. It can enable new insights into mechanical energy injection by the central supermassive black hole and the use of hydrostatic equilibrium for the determination of cluster masses. X-rays from the core of the Perseus cluster are emitted by the 50 million K diffuse hot plasma filling its gravitational potential well. The Active Galactic Nucleus of the central galaxy NGC1275 is pumping jetted energy into the surrounding intracluster medium, creating buoyant bubbles filled with relativistic plasma. These likely induce motions in the intracluster medium and heat the inner gas preventing runaway radiative cooling; a process known as Active Galactic Nucleus Feedback. Here we report on Hitomi X-ray observations of the Perseus cluster core, which reveal a remarkably quiescent atmosphere where the gas has a line-of-sight velocity dispersion of 164+/-10 km/s in a region 30-60 kpc from the central nucleus. A gradient in the line-of-sight velocity of 150+/-70 km/s is found across the 60 kpc image of the cluster core. Turbulent pressure support in the gas is 4% or less of the thermodynamic pressure, with large scale shear at most doubling that estimate. We infer that total cluster masses determined from hydrostatic equilibrium in the central regions need little correction for turbulent pressure.Comment: 31 pages, 11 Figs, published in Nature July