ReaderBench goes Online: A Comprehension-Centered Framework for Educational Purposes

In this paper we introduce the online version of our ReaderBench framework, which includes multi-lingual comprehension-centered web services designed to address a wide range of individual and collaborative learning scenarios, as follows. First, students can be engaged in reading a course material, then eliciting their understanding of it; the reading strategies component provides an in-depth perspective of comprehension processes. Second, students can write an essay or a summary; the automated essay grading component provides them access to more than 200 textual complexity indices covering lexical, syntax, semantics and discourse structure measurements. Third, students can start discussing in a chat or a forum; the Computer Supported Collaborative Learning (CSCL) component provides indepth conversation analysis in terms of evaluating each member’s involvement in the CSCL environments. Eventually, the sentiment analysis, as well as the semantic models and topic mining components enable a clearer perspective in terms of learner’s points of view and of underlying interests.

No second chance: junior neonatal nurses' experiences of caring for babies at the end-of-life and their families

Death of an infant is acutely stressful for parents and professionals. Little is known about junior nurses' experiences providing end-of-life care in Neonatal units (NNU). This study aimed to better understand junior nurses' experiences providing end-of-life care in NNU. Neonatal nurses (n = 12) with less than 3 years experience participated in a focus group. Nominal Group Technique (NGT) was used to build consensus around the challenges faced, alongside suggested developments in improving future care provision. Primary analysis involved successive rounds of ranking and decision-making whilst secondary analysis involved thematic analysis. All issues, whether environmental, professional or social appeared driven by an awareness on the part of nurses, that there was no ‘second chance’ which created a huge pressure to ‘get if right’ for the infants and families. Regarding future care 2 areas of improvement identified were ‘Education and Training’ and Support. This paper unpacks these findings making recommendations for practice.

No second chance: the experiences of junior neonatal nurses in providing end-of-life care for babies and families in the NNU

Background

An infant’s death is acutely stressful for parents and professionals. Little is known about junior nurses’ experiences providing end-of-life care in Neonatal Units (NNU).

Objectives

To better understand junior nurses’ experiences providing end-of-life care in NNU, the study explored the challenges and opportunities inherent in their practice relating to providing such care to babies and their families.

Methods

Neonatal nurses (n=12) with less than 3 years’ experience who were undergoing a neonatal education programme participated. Two focus groups were convened each with 6 nurses. The Ethics Committee at the relevant University approved the study. Nominal Group Technique (NGT) was used in the focus groups to build consensus around the challenges faced by junior nurses, alongside suggested developments in improving future care provision. Primary analysis involved successive rounds of ranking and decision making whilst secondary analysis involved thematic analysis.

Results

The study identified the pressures these nurses felt in having only one chance to ‘get it right’ for the infants and their families. They perceived the need for further ‘education and training’ highlighting that improved education provision would include both additional courses and internal training sessions. Greater ‘support’ from mentors themselves more experienced in this aspect of care within the NNU was identified as important in addressing issues around confidence building and skill development.

Conclusions

The results highlight junior nurses’ need for specific education and mentorship around end-of-life care for babies. This presentation will outline the implications for practice, education and further research.

On Queueinginventory Models – product form solution; reservation, Cancellation and common life time

Queueing theory is the mathematical study of ‘queue’ or ‘waiting lines’ where an item from inventory is provided to the customer on completion of service. A typical queueing system consists of a queue and a server. Customers arrive in the system from outside and join the queue in a certain way. The server picks up customers and serves them according to certain service discipline. Customers leave the system immediately after their service is completed. For queueing systems, queue length, waiting time and busy period are of primary interest to applications. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, mean queue length, traffic intensity, the expected number waiting or receiving service, mean busy period, distribution of queue length, and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served.

A Framework for Realistic 3D Tele-Immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite different from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experience of talking in person. Several causes for these differences have been identified and we propose inspiring and innovative solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational experience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic experiences to a multitude of users that for them will feel much more similar to having face to face meetings than the experience offered by conventional teleconferencing systems.

Faith on the Home Front: Aspects of Church Life and Popular Religion in Birmingham, 1939-1945

The nature of religion on the domestic front in Britain during the Second World War has, hitherto, been relatively unexplored. This study focuses on Birmingham and describes wartime popular religion, primarily as recounted in oral testimony. The difference the War made to people’s faith, and the consolation wrought by prayer and a religious outlook are explored, as are the religious language and concepts utilised by the wartime popular media of cinema and wireless. Clerical rhetoric about the War and concerns to spiritualise the war effort are dealt with by an analysis of locally published sources, especially parish magazines and other religious ephemera, which set the War on the spiritual as much as the military plane. A final section of the study is devoted to measuring the extent of the influence of the churches in the creation of a vision for post-war Britain and Birmingham.

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

Do you want some cash-back?: assessing the demand for a no-claim rebate life-insurance product

Diseña e implementa un experimento de campo en el Perú rural, con el fin de examinar la sensibilidad de la demanda de los productos de microseguros de vida con la introducción de las devoluciones, que son reembolsos parciales de la prima del seguro cuando no se produce alguna eventualidad en el asegurado. Se encontró que las devoluciones crean mayores niveles de confianza entre el asegurador y el asegurado, lo que promete aumentar la demanda de seguros. Los resultados sugieren que las devoluciones pueden ser productos de innovación atractivos en los países en desarrollo.

Uma abordagem evolucionária para o planejamento online de rotas para múltiplos robôs móveis em ambiente multiagente

O problema de planejamento de rotas de robôs móveis consiste em determinar a melhor rota para um robô, em um ambiente estático e/ou dinâmico, que seja capaz de deslocá-lo de um ponto inicial até e um ponto final, também em conhecido como estado objetivo. O presente trabalho emprega o uso de uma abordagem baseada em Algoritmos Genéticos para o planejamento de rotas de múltiplos robôs em um ambiente complexo composto por obstáculos fixos e obstáculos moveis. Através da implementação do modelo no software do NetLogo, uma ferramenta utilizada em simulações de aplicações multiagentes, possibilitou-se a modelagem de robôs e obstáculos presentes no ambiente como agentes interativos, viabilizando assim o desenvolvimento de processos de detecção e desvio de obstáculos. A abordagem empregada busca pela melhor rota para robôs e apresenta um modelo composto pelos operadores básicos de reprodução e mutação, acrescido de um novo operador duplo de refinamento capaz de aperfeiçoar as melhores soluções encontradas através da eliminação de movimentos inúteis. Além disso, o calculo da rota de cada robô adota um método de geração de subtrechos, ou seja, não calcula apenas uma unica rota que conecta os pontos inicial e final do cenário, mas sim várias pequenas subrotas que conectadas formam um caminho único capaz de levar o robô ao estado objetivo. Neste trabalho foram desenvolvidos dois cenários, para avaliação da sua escalabilidade: o primeiro consiste em um cenário simples composto apenas por um robô, um obstáculo movel e alguns obstáculos fixos; já o segundo, apresenta um cenário mais robusto, mais amplo, composto por múltiplos robôs e diversos obstáculos fixos e moveis. Ao final, testes de desempenho comparativos foram efetuados entre a abordagem baseada em Algoritmos Genéticos e o Algoritmo A*. Como critério de comparação foi utilizado o tamanho das rotas obtidas nas vinte simulações executadas em cada abordagem. A analise dos resultados foi especificada através do Teste t de Student.

Strangers in a strange land: do life history traits differ for alien and native colonisers of novel environments?

Do alien invasive species exhibit life history characteristics that are similar to those of native species that have become pests in their continent of origin? We compared eucalypt specialists that have become pests in Australian plantations (natives) to those that have established overseas (aliens) using 13 life history traits and found that although traits that support rapid population build-up were shared, overall, aliens and native colonisers differed significantly. Distance from source (New Zealand vs. other) had no significant effect, but species that established more than 50 years ago exhibited different life history traits from those that established within the last 50 years, possibly because of more effective quarantine. Native and alien eucalypt insect invaders differed predominantly in traits that facilitate long-distance movement (pathway traits), compared to traits that facilitate establishment and spread. Aliens had longer adult flight seasons, were smaller and more closely host-associated (cryptic eggs and larvae), had lower incidence of diapause (i.e. were more seasonally plastic) and more generations per year than natives. Thus, studies of species invasive within their country of origin can shed light on alien invasions.

ASSESSING QUALITY IN HIGH-UNCERTAINTY MARKETS: ONLINE REVIEWS OF CREDENCE SERVICES

In economics of information theory, credence products are those whose quality is difficult or impossible for consumers to assess, even after they have consumed the product (Darby & Karni, 1973). This dissertation is focused on the content, consumer perception, and power of online reviews for credence services. Economics of information theory has long assumed, without empirical confirmation, that consumers will discount the credibility of claims about credence quality attributes. The same theories predict that because credence services are by definition obscure to the consumer, reviews of credence services are incapable of signaling quality. Our research aims to question these assumptions. In the first essay we examine how the content and structure of online reviews of credence services systematically differ from the content and structure of reviews of experience services and how consumers judge these differences. We have found that online reviews of credence services have either less important or less credible content than reviews of experience services and that consumers do discount the credibility of credence claims. However, while consumers rationally discount the credibility of simple credence claims in a review, more complex argument structure and the inclusion of evidence attenuate this effect. In the second essay we ask, “Can online reviews predict the worst doctors?” We examine the power of online reviews to detect low quality, as measured by state medical board sanctions. We find that online reviews are somewhat predictive of a doctor’s suitability to practice medicine; however, not all the data are useful. Numerical or star ratings provide the strongest quality signal; user-submitted text provides some signal but is subsumed almost completely by ratings. Of the ratings variables in our dataset, we find that punctuality, rather than knowledge, is the strongest predictor of medical board sanctions. These results challenge the definition of credence products, which is a long-standing construct in economics of information theory. Our results also have implications for online review users, review platforms, and for the use of predictive modeling in the context of information systems research.

Development of a long-life vacuum-packaged ready-to-eat meat product based on a traditional Portuguese seasoned meat

Carne do alguidar is a Portuguese traditional pork fried meat, usually manufactured for self-consumption purposes. This study developed a ready-to-eat (RTE) meat product, to meet today's consumers’ convenience, manufactured at the industrial scale evaluating its quality and shelf-life, assessing the effect of vacuum packaging and the use of an antioxidant (50 ppm BHT) to enhance oxidative stability. Physicochemical and microbiological parameters were assessed and a sensory analysis was performed. Interestingly, no significant differences were recorded between control (non-BHT) and antioxidant (BHT) samples. Microbiological counts remained at low levels throughout the storage period, ensuring the product’s required microbiological quality. At later storage stages, higher values of thiobarbituric acid reactive substances arose and off flavours and aromas were perceived. Still, overall appreciation was not affected until 12 months storage and a significant depreciation was perceived only after 15 months. Fibrousness and rising of off flavours were negatively correlated with overall appreciation.

Effect of Aging in the Perception of Health-Related Quality of Life in End-Stage Renal Disease Patients under Online-Hemodiafiltration

This work aimed to evaluate how aging could influence patients' perception of health quality of life (HRQOL), as well as, the effect of aging on dialysis adequacy and in hematological, iron status, inflammatory and nutritional markers. In this transversal study were enrolled 305 ESRD patients under online-hemodiafiltration (OL-HDF) (59.67% males; 64.9 ± 14.3 years old). Data about comorbidities, hematological data, iron status, dialysis adequacy, nutritional and inflammatory markers were collected from patient's records. Moreover, HRQOL score, by using the Kidney Disease Quality of Life-Short Form (KDQOL-SF), was assessed. Analyzing the results according to quartiles of age, significant differences were found for some parameters evaluated by the KDQOL-SF instrument, namely for work status, physical functioning and role-physical, which decreased with increasing age. We also found a higher proportion of diabetic patients, a decrease in creatinine, iron, albumin serum levels, transferrin saturation and nPCR, with increasing age. Moreover, significant negative correlations were found between age and mean cell hemoglobin concentration, iron, transferrin saturation, albumin, nPCR, work status, physical functioning and role-physical. In conclusion, our results showed that aging is associated with a decreased work status, physical functioning and role-physical, with a decreased dialysis adequacy, iron availability and nutritional status, and with an increased proportion of diabetic patients and of patients using central venous catheter, as the vascular access. The knowledge of these changes associated with aging, which have impact in the quality of life of the patients, could be useful in their management.