Specialist nursing training in Poland: Applications for neuroscience nursing

Background: Nurses have a pivotal role in providing, facilitating, advocating and promoting the best possible care and outcome for the client. To ensure decisions and actions are based on current standards of practice, nurses must be accountable for participation in ongoing education in their area of practice. Aim: To present a description of the current state of Polish nursing education and specialized model for neurological and neurosurgical nursing that can be utilized for both undergraduate and postgraduate continuing education in Poland. Data sources: The model of postgraduate training introduced in Poland in 2000 was taken into consideration in developing the framework for neuroscience nursing postgraduate continuing education presented here. The framework for neurological continuing education is also based on a review of the literature and is consistent with Poland’s legally binding professional nursing regulations (normative and implementing regulations). Conclusion: The model demonstrates the need for the content of pre- and post-undergraduate degree education in neurological nursing to be graduated, based on the frameworks for undergraduate education (acquiring the knowledge and basic skills for performing the work of nurses) and postgraduate education (acquiring knowledge and specialist skills necessary for providing advanced nursing care including medical acts on patients with nervous system diseases). Implications for nursing: New and advanced skills gained in specialization training can be applied to complex functions, roles and professional tasks undertaken by nurses in relation to care of patients with neurological dysfunctions.

Synthesis, characterization and applications of graphene oxide-polymer nanocomposites

Graphene has emerged as one of the most exciting materials of the 21st century due to its unique properties which have demonstrated great potential for applications in energy storage, flexible electronics and multifunctional composites. This thesis has established a new technique for investigating the structure-property relationship of graphene-polymer nanocomposites at micro and nanoscales. The outcomes can help gain a fundamental understanding of the toughening mechanism in these novel nanocomposites and benefit the development of broad graphene based materials and devices.

Labeling white matter tracts in hardi by fusing multiple tract atlases with applications to genetics

Accurate identification of white matter structures and segmentation of fibers into tracts is important in neuroimaging and has many potential applications. Even so, it is not trivial because whole brain tractography generates hundreds of thousands of streamlines that include many false positive fibers. We developed and tested an automatic tract labeling algorithm to segment anatomically meaningful tracts from diffusion weighted images. Our multi-atlas method incorporates information from multiple hand-labeled fiber tract atlases. In validations, we showed that the method outperformed the standard ROI-based labeling using a deformable, parcellated atlas. Finally, we show a high-throughput application of the method to genetic population studies. We use the sub-voxel diffusion information from fibers in the clustered tracts based on 105-gradient HARDI scans of 86 young normal twins. The whole workflow shows promise for larger population studies in the future.

The rapid manufacture of uniform composite multicellular-biomaterial micropellets, their assembly into macroscopic organized tissues, and potential applications in cartilage tissue engineering

We and others have published on the rapid manufacture of micropellet tissues, typically formed from 100-500 cells each. The micropellet geometry enhances cellular biological properties, and in many cases the micropellets can subsequently be utilized as building blocks to assemble complex macrotissues. Generally, micropellets are formed from cells alone, however when replicating matrix-rich tissues such as cartilage it would be ideal if matrix or biomaterials supplements could be incorporated directly into the micropellet during the manufacturing process. Herein we describe a method to efficiently incorporate donor cartilage matrix into tissue engineered cartilage micropellets. We lyophilized bovine cartilage matrix, and then shattered it into microscopic pieces having average dimensions < 10 μm diameter; we termed this microscopic donor matrix "cartilage dust (CD)". Using a microwell platform, we show that ~0.83 μg CD can be rapidly and efficiently incorporated into single multicellular aggregates formed from 180 bone marrow mesenchymal stem/stromal cells (MSC) each. The microwell platform enabled the rapid manufacture of thousands of replica composite micropellets, with each micropellet having a material/CD core and a cellular surface. This micropellet organization enabled the rapid bulking up of the micropellet core matrix content, and left an adhesive cellular outer surface. This morphological organization enabled the ready assembly of the composite micropellets into macroscopic tissues. Generically, this is a versatile method that enables the rapid and uniform integration of biomaterials into multicellular micropellets that can then be used as tissue building blocks. In this study, the addition of CD resulted in an approximate 8-fold volume increase in the micropellets, with the donor matrix functioning to contribute to an increase in total cartilage matrix content. Composite micropellets were readily assembled into macroscopic cartilage tissues; the incorporation of CD enhanced tissue size and matrix content, but did not enhance chondrogenic gene expression.

Flexible learning design in curriculum delivery promotes student engagement and develops metacognitive learners: An integrated review

Historically, university students have been the passive recipients of face-to-face instructor designed and led classes (Hudson, 2014; Myers et al., 2011). Technological advancement, however, has provided an opportunity for greater flexibility around educational structure; students are starting to expectmore fromtertiary education providers, specifically around the delivery and provision of education (Myers et al., 2011). For universities to meet the ever-changing needs of the student they need to consider the integration of flexible learning designs into their curricula. The consequent willingness of the faculty to rethink the design and delivery of curricula has seen a recent shift in the design and delivery of education. As universities strive to promote student engagement, active learning, and communities of enquiry, they are moving progressively towards flexible learning models, virtual interaction and student centric curricula (Heise and Himes, 2010; Hsu and Hsieh, 2011). The challenge this shift creates is how to best engage students throughout their studies in order to produce graduates with the skills necessary for societal and professional sustainability (Castle and McGuire, 2010). Despite a wealth of literature addressing this topic, there is a paucity of substantive, conclusive outcomes as to the efficacy of its full implementation and potential for producing capable learners. This integrative review therefore aims to inform curriculum delivery that is flexible, student centric and scaffolds learning. It also aims to identify whether this approach assists in the development of metacognitive learners.

A service-oriented architecture for text analytics enabled business applications

Experiences showed that developing business applications that base on text analysis normally requires a lot of time and expertise in the field of computer linguistics. Several approaches of integrating text analysis systems with business applications have been proposed, but so far there has been no coordinated approach which would enable building scalable and flexible applications of text analysis in enterprise scenarios. In this paper, a service-oriented architecture for text processing applications in the business domain is introduced. It comprises various groups of processing components and knowledge resources. The architecture, created as a result of our experiences with building natural language processing applications in business scenarios, allows for the reuse of text analysis and other components, and facilitates the development of business applications. We verify our approach by showing how the proposed architecture can be applied to create a text analytics enabled business application that addresses a concrete business scenario. © 2010 IEEE.

Hydraulic conductivity increases in a sodic clay soil in response to gypsum applications impacts of bulk density and cation exchange

Amelioration of sodic soils is commonly achieved by applying gypsum, which increases soil hydraulic conductivity by altering soil chemistry. The magnitude of hydraulic conductivity increases expected in response to gypsum applications depends on soil properties including clay content, clay mineralogy, and bulk density. The soil analyzed in this study was a kaolinite rich sodic clay soil from an irrigated area of the Lower Burdekin coastal floodplain in tropical North Queensland, Australia. The impact of gypsum amelioration was investigated by continuously leaching soil columns with a saturated gypsum solution, until the hydraulic conductivity and leachate chemistry stabilized. Extended leaching enabled the full impacts of electrolyte effects and cation exchange to be determined. For the columns packed to 1.4 g/cm3, exchangeable sodium concentrations were reduced from 5.0 ± 0.5 mEq/100 g to 0.41 ± 0.06 mEq/100 g, exchangeable magnesium concentrations were reduced from 13.9 ± 0.3 mEq/100 g to 4.3 ± 2.12 mEq/100 g, and hydraulic conductivity increased to 0.15 ± 0.04 cm/d. For the columns packed to 1.3 g/cm3, exchangeable sodium concentrations were reduced from 5.0 ± 0.5 mEq/100 g to 0.51 ± 0.03 mEq/100 g, exchangeable magnesium concentrations were reduced from 13.9 ± 0.3 mEq/100 g to 0.55 ± 0.36 mEq/100 g, and hydraulic conductivity increased to 0.96 ± 0.53 cm/d. The results of this study highlight that both sodium and magnesium need to be taken into account when determining the suitability of water quality for irrigation of sodic soils and that soil bulk density plays a major role in controlling the extent of reclamation that can be achieved using gypsum applications.

Integrated scheduling for ambulances and ambulance crews

This project developed three mathematical models for scheduling ambulances and ambulance crews and proceeded to solve each model for test scenarios based on real data. Results from these models can serve as decision aids for dispatching or relocating ambulances; and for strategic decisions on the ambulance crews needed each shift. This thesis used Flexible Flow Shop Scheduling techniques to formulate strategic, dynamic and real time models. Metaheuristic solutions techniques were applied for a case study with realistic data. These models are suitable for ambulance planners and dispatchers.

Sport across cultures: Applications of the human capital model in refugee communities

When working with the world’s most vulnerable populations there are questions surrounding the salience of physical activity promotion programs given the multitude of basic needs that must first be met. Indeed, physical activity may be a low priority for individuals seeking safety, reunification with loved ones, and food for their families, as a subsistence lifestyle makes excess weight gain, diabetes, and cardiovascular disease irrelevant. Yet, when working with people from a refugee background for whom these challenges all too frequently apply, opportunities for sport and activity have repeatedly surfaced as desirable and needed, yet are utterly deficient. If we conceptualize physical activity purely as a chronic disease prevention tool, its significance within under-resourced communities is most assuredly lost; however, if we harness the power of physical activity to serve as an agent of positive social change, then it instantly becomes more meaningful and necessary.

Formation of highly conductive composite coatings and their applications to broadband antennas and mechanical transducers

Tight networks of interwoven carbon nanotube bundles are formed in our highly conductive composite. The composite possesses propertiessuggesting a two-dimensional percolative network rather than other reported dispersions displaying three-dimensional networks. Binding nanotubes into large but tight bundles dramatically alters the morphology and electronic transport dynamics of the composite. This enables itto carry higher levels of charge in the macroscale leading to conductivities as high as 1600 S/cm. We now discuss in further detail, the electronic and physical properties of the nanotube composites through Raman spectroscopy and transmission electron microscopy analysis. When controlled and usedappropriately, the interesting properties of these composites reveal their potential for practical device applications. For instance, we used this composite to fabricate coatings, whic improve the properties of an electromagnetic antenna/amplifier transducer. The resulting transducer possesses a broadband range up to GHz frequencies. A strain gauge transducer was also fabricated using changes in conductivity to monitor structural deformations in the composite coatings.

Isolation and inheritance of microsatellite loci for the oily bittering (Acheilognathus koreensis): applications for analysis of genetic diversity of wild populations

The oily bittering Acheilognathus koreensis is a freshwater species that is endemic to Korea and is experiencing severe declines in natural populations as a result of habitat fragmentation and water pollution. For the conservation and restoration of this species, it is necessary to assess its genetic diversity at the population level. We developed 13 polymorphic microsatellite loci that were used to analyze the genetic diversity of two populations collected from the Kum River and the Tamjin River in Korea. All loci exhibited Mendelian inheritance patterns when examined in controlled crosses. Both populations revealed high levels of variability, with the number of alleles ranging from 3 to 20 and observed and expected heterozygosities ranging from 0.500 to 0.969 and from 0.529 to 0.938, respectively. None of the loci showed significant deviation from Hardy–Weinberg equilibrium, and one pair of loci showed significant linkage disequilibrium after Bonferroni correction. Pairwise F ST and genetic distance estimation showed significant differences between two populations. These results suggest that the microsatellites developed herein can be used to study the genetic diversity, population structure and conservation measure of A. koreensis.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

An integrated framework for theories of individual attitudes toward technology

Theories of individual attitudes toward IT include task technology fit (TTF), technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT), cognitive fit, expectation disconfirmation, and computer self-efficacy. Examination of these theories reveals three main concerns. First, the theories mostly ‘‘black box’’ (or omit) the IT artifact. Second, appropriate mid-range theory is not developed to contribute to disciplinary progress and to serve the needs of our practitioner community. Third, theories are overlapping but incommensurable. We propose a theoretical framework that harmonizes these attitudinal theories and shows how they can be specialized to include relevant IS phenomenon.

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

Mobile medical applications for melanoma risk assessment: False assurance or valuable tool?

With the smartphone revolution, consumer-focused mobile medical applications (apps) have flooded the market without restriction. We searched the market for commercially available apps on all mobile platforms that could provide automated risk analysis of the most serious skin cancer, melanoma. We tested 5 relevant apps against 15 images of previously excised skin lesions and compared the apps' risk grades to the known histopathologic diagnosis of the lesions. Two of the apps did not identify any of the melanomas. The remaining 3 apps obtained 80% sensitivity for melanoma risk identification; specificities for the 5 apps ranged from 20%-100%. Each app provided its own grading and recommendation scale and included a disclaimer recommending regular dermatologist evaluation regardless of the analysis outcome. The results indicate that autonomous lesion analysis is not yet ready for use as a triage tool. More concerning is the lack of restrictions and regulations for these applications.