1,279 research outputs found
The changing landscape of JIBS authorship
No full textIn this study, we examine the landscape of JIBS authorship over time to assess: (1) the accessibility of JIBS to new contributors, and (2) the diversity of authors contributing to JIBS. Our analysis of author data from 1972 to 2014 shows that JIBS is becoming more accessible, as indicated by the high and sustained proportion of first-time contributors to the journal. This is also evident from the recent decline in the share of authors with multiple past JIBS publications. With regard to diversity, our findings show that JIBS has a much wider geographic scope of authors on its landscape in comparison to previous decades. This may be attributed partly to increasing travel and communication in scholarly communities, and partly to the increased migration of scholars in the recent decades. Our analysis of migration patterns of JIBS authors suggests that about 51 % of prominent international business scholars are employed outside their country of birth. Of the 49 % employed in their country of birth, 12 % are return migrants. In our sample, China, South Korea and Canada have the highest number of returnees. The USA, the UK, Germany, the Netherlands and China have the highest number of natives, whose country of birth, country of PhD-granting institution and country of university affiliation are identical.Peer reviewe
A hierarchical spectral clustering and non-linear dimensionality reduction scheme for detection of prostate cancer from magnetic resonance spectroscopy:
No full textMagnetic Resonance Spectroscopy (MRS) is a unique non-invasive method which has recently been shown to have great potential in screening of prostate cancer (CaP). MRS provides functional information regarding the concentrations of different biochemicals present in the prostate at single or multiple locations within a rectangular grid of spectra superposed on the structural T2-weighted Magnetic Resonance Imaging (MRI). Changes in relative concentration of specific metabolites including choline, creatine and citrate compared to "normal" levels is highly indicative of the presence of CaP. Most previous attempts at developing computerized schemes for automated prostate cancer detection using MRS have been centered on developing peak area quantification algorithms. These methods seek to obtain area under peaks corresponding to choline, creatine and citrate which is then used to compute relative concentrations of these metabolites. However, manual identification of metabolite peaks on the MR spectra, let alone via automated algorithms, is a challenging problem on account of low SNR, baseline irregularity, peak-overlap, and peak distortion. In this thesis work a novel computer aided detection (CAD) scheme for prostate MRS is presented that integrates non-linear dimensionality reduction (NLDR) with an unsupervised hierarchical clustering algorithm to automatically identify cancerous spectra. The methodology comprises of two specific aims. Aim 1 is to first automatically localize the prostate region followed in Aim 2 by automated cancer detection on the prostate obtained in Aim 1. In Aim 1, a hierarchical spectral clustering algorithm is used to distinguish between informative and non-informative spectra in order to localize the region of interest (ROI) corresponding to the prostate. Once the prostate ROI is localized, in Aim 2, a non-linear dimensionality reduction (NLDR) scheme in conjunction with a replicated k-means clustering algorithm is used to automatically discriminate between 3 classes of spectra (normal, CaP, and intermediate tissue classes). Results of qualitative and quantitative evaluation of the methodology over 18 1.5 Tesla (T) in-vivo prostate T2-w and MRS studies obtained from the multi-site, multi-institutional ACRIN trial, for which corresponding histological ground truth of spatial extent of CaP is available, reveal that the CAD scheme has a high detection sensitivity (89.60) and specificity (78.98). Results further suggest that the CAD scheme has a higher detection accuracy compared to such commonly used MRS analysis schemes as z-score and PCA.M.S.Includes bibliographical references (p. 47-49).by Pallavi Tiwar
Insights into the beneficial effect of caloric/ dietary restriction for a healthy and prolonged life
No full textThe effect of mechanical strain on properties of lubricated tablets compacted at different pressures
No full textA full factorial design of experiments was used to study the effect of blend shear strain on the compaction process, relative density and strength of pharmaceutical tablets. The powder blends were subjected to different shear strain levels (integral of shear rate with respect to time) using an ad hoc Couette shear cell. Tablets were compressed at different compaction forces using an instrumented compactor simulator, and compaction curves showing the force-displacement profiles during compaction were obtained. Although the die-fill blend porosity (initial porosity) and the minimum in-die tablet porosity (at maximum compaction) decreased significantly with shear strain, the final tablet porosity was surprisingly independent of shear strain. The increase in the in-die maximum compaction with shear strain was, in fact, compensated during post-compaction relaxation of the tables, which also increased significantly with shear strain. Therefore, tablet porosity alone was not sufficient to predict tablet tensile strength. A decrease in the ‘work of compaction’ as a function of shear strain, and an increase in the recovered elastic work was observed, which suggested weaker particle-particle bonding as the shear strain in- creased. For each shear strain level, the Ryskewitch Duckworth equation was a good fit to the tensile strength as a function of tablet porosity, and the obtained asymptotic tensile strength at zero porosity exhibited a 60% reduction as a function of shear strain. This was consistent with a reduced bonding efficiency as the shear strain increased.Peer reviewed
Quantitative integration of imaging and non-imaging data: application to integrating multi-parametric MRI for prostate cancer diagnosis, grading and treatment evaluation
No full textThe problem of data integration involving imaging and non-imaging modalities is largely unexplored in the biomedical eld, mainly due to the challenges in quantitatively combining such heterogeneous modalities existing in diff erent dimensions and scales. Although several methods have been proposed in the literature involving quantitative integration of multi-protocol imaging, there has been a paucity of similar biomedical tools for quantitative integration of imaging and non-imaging data. In this work, we present novel data integration schemes to overcome the aforementioned challenges limiting the integration of imaging and non-imaging modalities, and hence improve disease characterization. Our novel data integration methods are applied to integration of multi-parametric Magnetic Resonance (MR) imaging (MP-MRI)-structural MR imaging with metabolic spectroscopic information (non-imaging) for improved prostate cancer (CaP) diagnosis, grading, and treatment evaluation post-radiation therapy (RT). To this end, we have developed novel data integration schemes such as, Multimodal Wavelet Embedding Representation for data Combination (MaWERiC), and Semi-Supervised Multi-Kernel (SeSMiK) Graph Embedding, which fi rst uniformly represent individual data modalities into a common framework using dimensionality reduction and kernel embedding techniques, followed by a seamless integration of imaging and non-imaging data in the common framework. The integrated quantitative signatures thus obtained are shown to be signifi cantly more diagnostically informative as compared to any single modality. Similar improvement in results was observed using integrated MP-MRI signatures for evaluating radiation therapy related changes in CaP patients, with an aim to identify (a) pre-RT disease extent along with extra capsule spread (if any) and (b) residual disease on post-RT MP-MRI.Ph. D.Includes bibliographical referencesIncludes vitaby Pallavi Tiwar
D.H. Lawrence is the Harbinger of New Psycho Dynamics in the Modern Literature: Tyagi Pallavi
No full textThe psychodynamic model is founded on the ideas of Sigmund Freud. Freud’s writings have a greater influence on the development of psychology. Central to his approach is the assumption that biological drives and inborn instincts towards self-preservation direct behavior. Thus we are dominated by sexual and aggressive urges, catching the infant or young child in a crosscurrent. Though we are the mercy of our inherited urges and early parental training experiences, we survive by imposing rational control over these basic conflicts. Behavior that does not appear to make sense, or to be based on logic, is analyzed as a symptom of unconscious motives. According to psycho dynamic model, human nature is fully determined by heredity and early life experiences. In accordance of Freud’s belief, Lawrence as an author pours in his own unconscious into the characters and situations depicted in his works more specifically in his novels. Freudian interpretation of literature applied to Lawrence’s works becomes convincing and ingenious in explaining the “return of the repressed”. His novels besides portraying the psychology of characters are also taken as the conscious or ‘Overt’ interpretation of the ‘covert’ or the unconscious of the author himself. The critical analysis of the psycho dynamics revealing itself through abstract impulses, feelings, and instincts, mythical or materialistic symbols has been attempted in the present study
A hierarchical spectral clustering and nonlinear dimensionality reduction scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS)
No full textIn this article the authors present a novel CAD scheme that integrates nonlinear dimensionality reduction (NLDR) with an unsupervised hierarchical clustering algorithm to automatically identify suspicious regions on the prostate using MRS and hence avoids the need to explicitly identify metabolite peaks.The published version of this article is available at: http://scitation.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=MPHYA6000036000009003927000001&idtype=cvips&prog=normalThis work was made possible via grants from the Wallace H. Coulter Foundation, New Jersey Commission on Cancer Research, National Cancer Institute (Grant Nos. R01CA136535-01, ARRA-NCl-3 R21CA127186–02S1, R21CA127186–01, and R03CA128081-01), the Society for Imaging Informatics in Medicine (SIIM), The Cancer Institute of New Jersey, and the Life Science Commercialization Award from Rutgers University
Improved Clustering Technique in Marketing Sector
No full textCluster analysis divides data into meaningful or useful groups clusters . One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behaviour for investment decisions. Clustering techniques that are being used in Data Mining is presented. Data mining adds to clustering the complications of very large datasets with very many attributes of different types. This imposes unique computational requirements on relevant clustering algorithms with k means method is one of the clustering techniques. Data mining facilitates marketing sector by classifying customer demographic that can be used to predict which customer will respond to a mailing or buy a particular product and it is very much helpful in growth of business. K means method proposed that will improved in marketing sector and also discuss how to support clustering technique in marketing sector. Experimental results show difference between clustered and non clustered data of marketing product that represent in graphically and theoretically. These results help customer to choose the products and also it saves the time. Pallavi R. Wankhade | Prof. Rajeshri R. Shelke "Improved Clustering Technique in Marketing Sector" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: https://www.ijtsrd.com/papers/ijtsrd98.pd
sj-docx-1-jtt-10.1177_1357633X231177742 - Supplemental material for Patient and provider perspectives on the use of patient portals during pregnancy and the postpartum period
No full textSupplemental material, sj-docx-1-jtt-10.1177_1357633X231177742 for Patient and provider perspectives on the use of patient portals during pregnancy and the postpartum period by Sarah R MacEwan, Naleef Fareed, Pallavi Jonnalagadda, Holly Heffer, Abigail M Petrecca and
Ann Scheck McAlearney in Journal of Telemedicine and Telecare</p
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