Self-propagating high temperature synthesis and dynamic compaction of titanium diboride/titanium carbide composites

Self-propagating High-temperature Synthesis (SHS) of titanium and boron carbide (B 4 C) combined with explosively driven Dynamic Compaction (DC) was employed for the fabrication of composite TiB 2 /TiC compacts. A 2 3 factorially designed experiment set was used to examine the effects of the TiB 2 /TiC ratio, delay time and C/M ratio on the consolidation and properties of the compacts. The delay time is the time between completion of the SHS reaction and compaction. The C/M ratio, the ratio of the explosive mass to that of the flyer plate, influences the pressure applied to the samples during compaction. Composites with molar TiB 2 /TiC ratios of 2:1 or 1:2 were prepared using Ti and B 4 C or Ti, C and B 4 C, respectively, as reactants. The SHS/DC of Ti and B 4 C resulted in high quality, near fully dense TiB 2 /TiC composite compacts. Under best conditions, the densities were greater than 98% of the theoretical maximum. While the microhardness and densities of the compacts with TiB 2 /TiC ratio of 2:1 were comparable to those of monolithic TiB 2 and TiC, compacts with TiB 2 /TiC ratios of 1:2 were poorly consolidated and contained extensive cracks. Given the high energy and time efficiency, high product quality and inexpensive reactants, the SHS/DC of Ti and B 4 C represents an attractive technique for the economical fabrication of TiB 2 /TiC composites.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44760/1/10853_2004_Article_263157.pd

An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis.

Thousands of epigenomic data sets have been generated in the past decade, but it is difficult for researchers to effectively use all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for validated systematic integration of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By using IDEAS as our integrative and discriminative epigenome annotation system, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of more than 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website to aid research in genomics and hematopoiesis.National Institute of Diabetes and Digestive and Kidney Diseases (grant number R24DK106766-01A1), the National Human Genome Research Institute (grant number U54HG006998

Using Management Objectives to Specify Management Information Systems - A Contribution to MIS Success

Data warehouse projects, today, are in an ambivalent situation. On the one hand, data warehouses are critical for a company’s success and various methodological and technological tools are sophisticatedly developed to implement them. On the other hand, a significant amount of data warehouse projects fails due to non-technical reasons such as insufficient management support or in-corporative employees. But management support and user participation can be increased dramatically with specification methods that are understandable to these user groups. This paper aims at overcoming possible non-technical failure reasons by introducing a user-adequate specification approach within the field of management information systems.\u

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature

E-retailing ethics in Egypt and its effect on customer repurchase intention

The theoretical understanding of online shopping behaviour has received much attention. Less focus has been given to the formation of the ethical issues that result from online shopper interactions with e-retailers. The vast majority of earlier research on this area is conceptual in nature and limited in scope by focusing on consumers’ privacy issues. Therefore, the purpose of this paper is to propose a theoretical model explaining what factors contribute to online retailing ethics and its effect on customer repurchase intention. The data were analysed using variance-based structural equation modelling, employing partial least squares regression. Findings indicate that the five factors of the online retailing ethics (security, privacy, non- deception, fulfilment/reliability, and corporate social responsibility) are strongly predictive of online consumers’ repurchase intention. The results offer important implications for e-retailers and are likely to stimulate further research in the area of e-ethics from the consumers’ perspective

Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations:A Configurational Perspective

Big data analytics (BDA) is beneficial for organizations, yet implementing BDA to leverage profitability is fundamental challenge confronting practitioners. Although prior research has explored the impact that BDA has on business growth, there is a lack of research that explains the full complexity of BDA implementations. Examination of how and under what conditions BDA achieves organizational performance from a holistic perspective is absent from the existing literature. Extending the theoretical perspective from the traditional views (e.g. resource-based theory) to configuration theory, the authors have developed a conceptual model of BDA success that aims to investigate how BDA capabilities interact with complementary organizational resources and organizational capabilities in multiple configuration solutions leading to higher quality of care in healthcare organizations. To test this model, the authors use fuzzy-set qualitative comparative analysis to analyse multi-source data acquired from a survey and databases maintained by the Centres for Medicare & Medicaid Services. The findings suggest that BDA, when given alone, is not sufficient in achieving the outcome, but is a synergy effect in which BDA capabilities and analytical personnel's skills together with organizational resources and capabilities as supportive role can improve average excess readmission rates and patient satisfaction in healthcare organizations

Structural and mechanical properties of TiB 2 and TiC prepared by self-propagating high-temperature synthesis/dynamic compaction

Titanium-diboride and titanium-carbide compacts with diameters of 100 mm and thicknesses of 25 mm were fabricated by self-propagating high-temperature synthesis/dynamic compaction (SHS/DC) of the elemental powders. Under the best conditions, the densities were greater than 99% and 96.8% of the theoretical densities for TiB 2 and TiC, respectively. The microhardness, compressive strength, and elastic modulus of the TiB 2 prepared by the SHS/DC method were comparable to reported values for hot-pressed TiB 2 . While the microhardness and elastic modulus of the TiC compacts were comparable to those for hotpressed TiC, the compressive strength was lower due to extensive cracks in the compacts. The TiB 2 prepared using a low-purity boron powder (1–5% carbon impurity) compacted to higher densities and had less cracking than that prepared using a high-purity boron powder (0.2% carbon). This result could have an impact on the cost of producing TiB 2 /TiC structural components by the SHS/DC process.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44732/1/10853_2005_Article_BF01162518.pd

The impact of big data analytics on firms’ high value business performance

Big Data Analytics (BDA) is an emerging phenomenon with the reported potential to transform how firms manage and enhance high value businesses performance. The purpose of our study is to investigate the impact of BDA on operations management in the manufacturing sector, which is an acknowledged infrequently researched context. Using an interpretive qualitative approach, this empirical study leverages a comparative case study of three manufacturing companies with varying levels of BDA usage (experimental, moderate and heavy). The information technology (IT) business value literature and a resource based view informed the development of our research propositions and the conceptual framework that illuminated the relationships between BDA capability and organizational readiness and design. Our findings indicate that BDA capability (in terms of data sourcing, access, integration, and delivery, analytical capabilities, and people’s expertise) along with organizational readiness and design factors (such as BDA strategy, top management support, financial resources, and employee engagement) facilitated better utilization of BDA in manufacturing decision making, and thus enhanced high value business performance. Our results also highlight important managerial implications related to the impact of BDA on empowerment of employees, and how BDA can be integrated into organizations to augment rather than replace management capabilities. Our research will be of benefit to academics and practitioners in further aiding our understanding of BDA utilization in transforming operations and production management. It adds to the body of limited empirically based knowledge by highlighting the real business value resulting from applying BDA in manufacturing firms and thus encouraging beneficial economic societal changes