Unreinforced masonry structures : nonlinear analysis and evaluation of some rehab schemes

Unreinforced masonry (URM) structures have been a common type of construction in the past and are still used in regions of low seismicity. Retrofitting of these structures is necessary because of two reasons: Firstly, observed damage after earthquakes reveals that URM construction is one of the most hazardous constructions even in the region of low seismicity; secondly, reclassification of seismic zones would require retrofitting of existing structures to comply with new guidelines for earthquake design. Retrofitting measures require that the response of original and new structural systems as well as their interaction be considered. It is therefore important to correctly understand and predict the response of URM structures before implementing any strengthening scheme. Special techniques for analysis of URM structures are necessary because mortar joints act as planes of weakness. In this thesis a new approach for analytical modeling of URM structures is presented with a special emphasis on nonlinear behavior of mortar joints. This approach is included in a general purpose finite element software so that various options of the software can be effectively utilized for linear and nonlinear analysis of different structural systems under static and dynamic loading conditions. The analytical scheme is verified at element as well as structure level by comparison with available experimental and analytical results. Two rehabilitation schemes commonly used to strengthen existing URM structures are analyzed and their effectiveness in increasing strength and stiffness is discussed. Finally, nonlinear dynamic analysis is performed to study the effect of ground motion on URM walls and rehabilitation schemes

The Association of Cognitive Function with Autonomic-Cardiovascular Reactivity to and Recovery From Stress

The contribution of stress in the development of chronic and terminal disease has garnered significant interest in contemporary research. The current study aims to look at how performance in domains of cognitive function may affect autonomic-cardiovascular reactivity and recovery to psychologically stressful tasks as such reactions, over time, may contribute to the development of cardiovascular disease. The current study analyzed data from 209 healthy middle-age adults. This included four neuropsychological tests utilized here to represent abilities in four different cognitive domains: response inhibition, mental flexibility, verbal memory, and nonverbal memory. The participants were also introduced to three psychologically stressful tasks while blood pressure, heart rate, and spectral components of heart rate variability measurements were taken during the tasks and the post-task recovery period. Results showed no significant relationship between blood pressure reactivity or recovery and cognitive function. No significant relationship was found between heart rate variability reactivity and cognitive function. Results showed no significant relationship between blood pressure reactivity or recovery and cognitive function. No significant relationship was found between heart rate variability reactivity and cognitive function. However, superior performance in response inhibition was significantly positively associated with both LF-HRV (p = .04) and HF-HRV (p = .02) in the immediate recovery phase and HF-HRV (p = .02) in the delayed recovery phase. Such findings suggest that greater response inhibition abilities may contribute to greater vagally induced recovery from stressful tasks. Such a response can be considered healthy and likely acts as a protective factor against the development of cardiovascular disease

Microbiological profile of diabetic foot ulcers and its antibiotic susceptibility pattern in a teaching hospital, Gujarat

Background: Diabetic foot lesions are a major medical, social and economic problem and are the leading cause of hospitalization for patients with diabetes worldwide. Infection sometimes leads to amputation of the infected foot if not treated promptly. The present study was conducted to isolate and identify the bacterial pathogens associated with diabetic foot ulcer and to find out its antibiotic susceptibility pattern to reduce the risk of complications.Methods: Total 100 pus samples were collected from patients having diabetic foot ulcer, during July to October 2012. Samples were processed as per standard guidelines.Results: Out of 100 pus samples, 73 (73%) yielded growth of organisms making total of 92 isolates. Out of 92 bacterial isolates, 72 were gram negative and 20 were gram positive. Pseudomonas aeruginosa 25 (27%) was most common isolate causing diabetic foot infections followed by 20 (22%) Klebsiella sp., 17 (19%) E. coli, 15 (17%) S. aureus, 6 (7%) Proteus sp. and 4(3%) Enterococci, 2 (2%) Acinetobacter sp. and 2(2%) CONS and 1(1%) Providencia. Out of 72 GNB, 50 (69.4%) were extended spectrum β lactamase (ESBL) producer. Most gram negative isolates were resistant to levofloxacin, gentamicin, ampicillin-sulbactam and gatifloxacin. All GNB were sensitive to imipenem. Out of 15 S. aureus, 9 (60%) were Methicillin Resistant Staphylococcus aureus (MRSA) and were sensitive to vancomycin and linezolid.Conclusions: Pseudomonas sp. was the most common cause of infections.  Most isolates were multi drug resistance

Big Data Mining and Semantic Technologies: Challenges and Opportunities

Big data a term coined due to the explosion in the quantity and diversity of high frequency digital data which is having a potential for valuable insights has drawn the most attention in the area of research and development. Converting big data to actionable insights requires depth understanding of big data, its characteristics, challenges and current technological trends. A rise of big data is changing the existing data storage, management, processing and analytical mechanisms and leads to the new architecture/ecosystems to handle big data applications. This paper covers finding of our research study about big data characteristic, various types of analysis associated with it and basic big data types. First, we are presenting the big data study from data mining and analysis perspective and discuss the challenges and next, we present the result of research study on meaningful use of big data in the context of semantic technologies. Moreover, we discuss various case studies related to social media analysis and recent development trends to identify potential research directions for big data with semantic technologies. DOI: 10.17762/ijritcc2321-8169.150711

Importance of the Internet in University Curriculums: A Case Study at Sam Houston State University

The advances in technology today have made the use of the Internet important in almost every discipline. Educators, business people, scientists and those in the criminal justice field all rely on the Internet to help them perform their jobs to the fullest. The Internet is immense and has many uses that can assist student in each discipline. Knowledge of the Internet and the full extent of its capabilities are important to anyone entering the workforce in today’s technologically advanced environment. In order to keep their graduates competitive in this environment, it is important that universities offer courses which not only cover the basics of Internet use but also show how the Internet can help them advance and excel no matter which field they enter. The current lack of a course for all students which covers in-depth internet use opposed to the number of fields that utilize the Internet, and the extent to which they use it, exposes the need for a course to better prepare students for the changing environment they will enter after graduation

The critical role of surfactants towards CdS nanoparticles: synthesis, stability, optical and PL emission properties

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Cadmium sulfide (CdS) nanoparticles (NPs), prepared by a convenient chemical precipitation method, have been characterized using techniques such as TEM, XRD, zeta potential, absorption and photoluminescence (PL) emission spectroscopy to establish the structure directing role of different cationic and anionic surfactants and their impact on the nanoparticles stabilization. In the synthesis of the CdS NPs, cadmium acetate and sodium sulfide, employed as starting reagents, were dissolved in aqueous solutions of different surfactants to study the effect of their structures on the nucleation, growth, optical and PL emission properties of the NPs. By varying the surfactant species, the CdS NPs have significantly different optical and PL emission properties despite being produced under similar reaction conditions. Depending on the surfactant structure, the growing CdS NPs were stabilized by the surfactants to different extents. For example, in the surfactant with the longest chain length (e.g. cetyltrimethylammonium bromide; CTAB), the CdS NPs were most stable, whereas using a surfactant with a smaller chain length i.e. DTAB, the NPs were unstable for even 1 h. On the other hand, anionic surfactants of even smaller chain lengths were able to stabilize the CdS NPs for quite long times. The generalized study of growth of spherical CdS NPs involves monitoring the kinetics during the progress of the reaction. Additionally, an interesting prominent effect of surfactant structure on the PL emission properties of the NPs has been established under identical reaction conditions

Using the Delphi Technique to Determine the Effectiveness of Internet Advertisements

Over the past few years, there has been tremendous growth in the use of the Internet for promoting goods and services. This new technology is enabling companies to reach new markets all over the world. Locating target markets and advertising on the Internet takes a different approach. This paper examines several popular Internet advertising techniques used by marketers to attract the attention of the target market to particular sites. It uses the Delphi technique to determine that banner ads are still the most effective overall

Global Geo-Demographic Data and GIS for E-Business

The results of a comprehensive survey of the availability and characteristics of digital geo-demographic data in 40 countries around the world are presented. Geographic information systems (GIS) often used in conjunction with the Internet are being used by technologically savvy companies to perform marketing studies and provide location specific data such as maps to clients and customers. However, the national level Availability and characteristics of the required digital geo-spatial data vary considerably from nation to nation. Every country’s data differs in terms of existence, cost, accuracy, precision, format, content, and availability over the Internet. Some countries (such as Switzerland and the United Kingdom) have current data on every hectare and house along with demographics for every group of 100 residents available for interactive web-based mapping and analysis. Other nations have such data in only non-digital forms and then only internally. Most nations are intermediate in terms of the use of characteristics and availability of geospatial data relevant for E-business. Presented here are the results, especially those pertaining to E-business, of an e-mail survey of the national census and national mapping authorities of 40 selected countries. These the G7, Russia, China (PRC, Taiwan and Hong Kong), India, Australia, many European countries, along with 4 other Asian, 4 Latin American, 2 Middle Eastern and 2 African nations. Also presented is statistical analysis of the responses and information from follow-up questions