Implementing a new mathematics curriculum in England: district Research Lesson Study as a driver for student learning, teacher learning and professional dialogue.

Against a backdrop of a transformation in teacher professional development and learning and state school organisation in England this century, this chapter describes a project which harnessed six cycles of Research Lesson Study at school and district level over two years to tailor the implementation of a new statutory curriculum in England to address the professional development needs of teachers and classroom learning needs of London students. It also reports the findings of research carried out during the project into how these teachers learned and developed this new curricular expertise and practice- knowledge through lesson study dialogues that supported student learning. It concludes by proposing future directions for teacher professional learning research and practice

Parameters in panoramic radiography for differentiation of radiolucent lesions

OBJECTIVE: The aims of this study were to establish parameters in panoramic radiography for interpretation of unilocular radiolucent lesions, and to compare the accuracy of diagnoses given by examiners before and after using these parameters. MATERIAL AND METHODS: In Part I, 12 specialists analyzed 24 images and the diagnostic criteria used by each examiner to make correct diagnoses were used to build a list of basic radiographic parameters for each pathology (ameloblastoma, keratocystic odontogenic tumor, dentigerous cyst, and idiopathic bone cavity). In Part II, this list was used by 6 undergraduate students (Un), 8 recently graduated dentists (D), 3 oral pathologists, 3 stomatologists, 3 oral radiologists, and 3 oral surgeons to diagnose the corresponding pathologies in the other set of 24 panoramic radiographs (T2). The same analysis occurred without using this list (T1). The method of generalized estimating equations (GEE) was used in order to estimate the probability of making a correct diagnosis depending on the specialty of the examiner, type of lesion, and moment of the evaluation, T1 or T2 (before or after they had access to the list of parameters, respectively). RESULTS: Higher values were obtained for the probability (GEE) of making a correct diagnosis on T2; the group Un presented the highest improvement (14.6 %); no differences between the probabilities were observed either between Un and D, or among the different groups of specialists. CONCLUSIONS: The use of panoramic radiographic parameters did allow improving the diagnostic accuracy for all groups of examiners

Development and Validation of a Nurse Station Ergonomics Assessment Tool

Background: Nurse stations are one of the primary units for supporting effective functioning of any hospital. They are important working environments that demand adherence to known ergonomic principles for the well-being of both staff and patients. The aim of this study was to develop a psychometrically tested tool for the assessment of the ergonomic conditions of nurse workstations in hospitals. Methods: Ten hospitals, with a total of 133 nurse stations participated in this mixed-methods research. The domains and items of the tool were developed based on a literature review, an experts’ panel, and interviews with nurses. Results: The final nurse station ergonomic assessment (NSEA) tool has good psychometric properties. Validity was assessed by face validity and content validity. Reliability was evaluated using inter-rater agreement and test-retest reliability analyses with a four-week interval between assessments. The NSEA is comprised of 64 items across eight domains: layout and location (7 items), workspace (11 items), security-safety (5 items), environmental conditions (8 items), counter (8 items), chair (13 items), desk (9 items), and monitor (3 items). Conclusions: The NSEA adds to the literature a tool for managers to ensure they comply with legal requirements and support best practice for those working on hospital wards. The NSEA can be used to identify challenges for healthcare professionals who use nurse stations and support the execution of targeted interventions to improve human-environment interaction

SMART: A process-oriented methodology for resilient smart cities

Cities are engines of economic prosperity and social development. Rapid urbanization and the impacts of climate change have resulted in increased vulnerabilities in cities. On the other hand, the increasing proliferation of connected devices and distributed monitoring of the environment around us has opened up an opportunity to transform the way we create and manage cities. Contextual evidence of performance, outcome and efficiency can now be readily collected at a higher resolution to aid multi-disciplinary and multi-objective decision-making, enabling optimal evolution of cities against the backdrop of constrained resources and intensified vulnerabilities. This paper first argues that distributed and ubiquitous monitoring is at the heart of smart cities. Insights can be inferred from the gathered data with potential for evidence-based decisions at the required spatial and temporal scales. The paper then discusses the development of a comprehensive but concise frameworks called DICES (data, insights, citizen, evidence and standards) for conceptualizing smart cities. The dimensions of DICES are then translated into a process oriented methodology called SMART (specify, monitor, analyze, resolve and transform) by formalizing key aspects of the smart city process. Generality and scalability of DICES and SMART are demonstrated through the development of REPRO, a risk- and evidence-based platform for resilient and optimal design of buildings and infrastructure in a smart city

Phi-array: a novel method for fitness visualization and decision making in evolutionary design optimization

There is a growing interest in integrating model based evolutionary optimization in engineering design decision making for effective search of the solution space. Most applications of evolutionary optimization are concerned with the search for optimal solutions satisfying pre-defined constraints while minimizing or maximizing desired goals. A few have explored post-optimization decision making using concepts such as Pareto optimality, but mostly in multi-objective problems. Sub-optimal solutions are usually discarded and do not contribute to decision making after optimization runs. However, the discarded ‘inferior’ solutions and their fitness contain useful information about underlying sensitivities of the system and can play an important role in creative decision making. The need for understanding the underlying system behavior is more pronounced in cases where variations in the genotype space can cause non-deterministic changes in either the fitness or phenotype space and where fitness evaluations are computationally expensive. The optimized design of an artificial lighting environment of a senior living room is used as a test case to demonstrate the need for and application of fitness visualization in genotype and phenotype spaces for effective decision making. Sub-optimal solutions are retained during optimization and visualized along with the optimum solution in a fitness array visualization system called phi-array, developed as part of this research. The optimization environment is based on genetic algorithm (GA) in which a compute-intensive raytracing rendering engine, RADIANCE, is used to evaluate the fitness of prospective design solutions. Apart from describing the development of the optimization system and demonstrating the utility of phi-array in effective decision making, this article explores optimization parameters and their effectiveness for artificial lighting design problems and the nature of their rugged fitness and constraint landscapes

Digital analysis of trabecular pattern in jaws of patients with sickle cell anemia

Objectives: To characterize how the morphological features of the cancellous bone of the maxilla and mandible differ in patients with sickle cell anemia compared with normal subjects. Methods: Periapical radiographs of 18 young African American patients with sickle cell anemia and 18 control African Americans were digitized at 600 d.p.i. A customized computer program measured 24 morphological features of the trabecular and marrow architecture in the anterior maxilla and mandible. The mean values for each of the features were determined for the sickle cell and control groups and compared by anatomical site. Results: Patients with sickle cell anemia have a significant increase in area of the marrow (53% compared with 47% in controls) and a less complex trabecular structure as evidenced by fewer skeletal branch points per square cm (451 compared with 584 in controls in the anterior maxilla and, 553 compared with 678 in controls in the anterior mandible). All values are significantly different (P\u3c0.001). Conclusions: The data support the hypothesis that an automated image-interpretation program can distinguish patients with sickle cell anemia from normal individuals

Optimisation of a daylight-window: Hospital patient room as a test case

Optimisation of a daylight-window: hospital patient room as a test cas