Iowa Influenza Surveillance Network: Weekly Activity Report, June, 2016

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report, July, 2016

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report, August, 2016

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report, September, 2016

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Differences in grain growth of calcite: a field-based modeling approach

Normal grain growth of calcite was investigated by combining grain size analysis of calcite across the contact aureole of the Adamello pluton, and grain growth modeling based on a thermal model of the surroundings of the pluton. In an unbiased model system, i.e., location dependent variations in temperature-time path, 2/3 and 1/3 of grain growth occurs during pro- and retrograde metamorphism at all locations, respectively. In contrast to this idealized situation, in the field example three groups can be distinguished, which are characterized by variations in their grain size versus temperature relationships: Group I occurs at low temperatures and the grain size remains constant because nano-scale second phase particles of organic origin inhibit grain growth in the calcite aggregates under these conditions. In the presence of an aqueous fluid, these second phases decay at a temperature of about 350 °C enabling the onset of grain growth in calcite. In the following growth period, fluid-enhanced group II and slower group III growth occurs. For group II a continuous and intense grain size increase with T is typical while the grain growth decreases with T for group III. None of the observed trends correlate with experimentally based grain growth kinetics, probably due to differences between nature and experiment which have not yet been investigated (e.g., porosity, second phases). Therefore, grain growth modeling was used to iteratively improve the correlation between measured and modeled grain sizes by optimizing activation energy (Q), pre-exponential factor (k0) and grain size exponent (n). For n=2, Q of 350 kJ/mol, k0 of 1.7×1021 μmns−1 and Q of 35 kJ/mol, k0 of 2.5×10-5 μmns−1 were obtained for group II and III, respectively. With respect to future work, field-data based grain growth modeling might be a promising tool for investigating the influences of secondary effects like porosity and second phases on grain growth in nature, and to unravel differences between nature and experiment.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

An Overview of Racial Disproportionality in Juvenile Arrests and Offenses in South Carolina

This report attempts to examine a very narrow, yet vital, segment of the criminal justice process, racial disproportionality among juvenile arrest and offense rates. The purpose of this report was to demonstrate the utility of South Carolina's incident based crime data, the South Carolina Incident Based Reporting System, as an analytical tool to address matters of policy relevance.

Estimating interactive coefficients for analysing interactive failures

Engineering assets are often complex systems. In a complex system, components often have failure interactions which lead to interactive failures. A system with interactive failures may lead to an increased failure probability. Hence, one may have to take the interactive failures into account when designing and maintaining complex engineering systems. To address this issue, Sun et al have developed an analytical model for the interactive failures. In this model, the degree of interaction between two components is represented by interactive coefficients. To use this model for failure analysis, the related interactive coefficients must be estimated. However, methods for estimating the interactive coefficients have not been reported. To fill this gap, this paper presents five methods to estimate the interactive coefficients including probabilistic method; failure data based analysis method; laboratory experimental method; failure interaction mechanism based method; and expert estimation method. Examples are given to demonstrate the applications of the proposed methods. Comparisons among these methods are also presented.

Identifying child sexual abuse within school contexts : policy problems and solutions, and a landmark case

As a strategy to identify child sexual abuse, most Australian States and Territories have enacted legislation requiring teachers to report suspected cases. Some Australian State and non-State educational authorities have also created policy-based obligations to report suspected child sexual abuse. Significantly, these can be wider than non-existent or limited legislative duties, and therefore are a crucial element of the effort to identify sexual abuse. Yet, no research has explored the existence and nature of these policy-based duties. The first purpose of this paper is to report the results of a three-State study into policy-based reporting duties in State and non-State schools in Australia. In an extraordinary coincidence, while conducting the study, a case of failure to comply with reporting policy occurred with tragic consequences. This led to a rare example in Australia (and one of only a few worldwide) of a professional being prosecuted for failure to comply with a legislative duty. It also led to disciplinary proceedings against school staff. The second purpose of this paper is to describe this case and connect it with findings from our policy analysis.

Determination of a set of surrogate parameters to assess urban stormwater quality

This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

Behavioral drivers of EIS failure

We argue that the sustained successful operation of an ES is determined by, and is dependent on, multiple organizational stakeholders. The single greatest organizational barrier to EIS success and achieving widespread organizational benefits can be attributed to the way in which different subcultures treat data critical to EIS operation. Building on Lee & Strong’s (2004) data roles we incorporate Schien’s (1996) cultural framework along with DeLone and McLean’s (2003) dimensions of IS success, unpacking the underlying drivers of behaviors as they relate to EIS data. Further, we explain the origins of data based conflict resulting in poor EIS data utilization.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical VC dimension, empirical VC entropy, and margin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

The molar effect on citizenship and nomad immigration: Reading, readingthe world and self

This presentation explores molarization and overcoding of social machines and relationality within an assemblage consisting of empirical data of immigrant families in Australia. Immigration is key to sustainable development of Western societies like Australia and Canada. Newly arrived immigrants enter a country and are literally taken over by the Ministry of Immigration regarding housing, health, education and accessing job possibilities. If the immigrants do not know the official language(s) of the country, they enroll in language classes for new immigrants. Language classes do more than simply teach language. Language is presented in local contexts (celebrating the national day, what to do to get a job) and in control societies, language classes foreground values of a nation state in order for immigrants to integrate. In the current project, policy documents from Australia reveal that while immigration is the domain of government, the subject/immigrant is nevertheless at the core of policy. While support is provided, it is the subject/immigrant transcendent view that prevails. The onus remains on the immigrant to “succeed”. My perspective lies within transcendental empiricism and deploys Deleuzian ontology, how one might live in order to examine how segmetary lines of power (pouvoir) reflected in policy documents and operationalized in language classes rupture into lines of flight of nomad immigrants. The theoretical framework is Multiple Literacies Theory (MLT); reading is intensive and immanent. The participants are one Korean and one Sudanese family and their children who have recently immigrated to Australia. Observations in classrooms were obtained and followed by interviews based on the observations. Families also borrowed small video cameras and they filmed places, people and things relevant to them in terms of becoming citizen and immigrating to and living in a different country. Interviews followed. Rhizoanalysis informs the process of reading data. Rhizoanalysis is a research event and performed with an assemblage (MLT, data/vignettes, researcher, etc.). It is a way to work with transgressive data. Based on the concept of the rhizome, a bloc of data has no beginning, no ending. A researcher enters in the middle and exists somewhere in the middle, an intermezzo suggesting that the challenges to molar immigration lie in experimenting and creating molecular processes of becoming citizen.

Proactive management of collision risks in port waters using navigational traffic conflicts

Navigational collisions are one of the major safety concerns in many seaports. To address this safety concern, a comprehensive and structured method of collision risk management is necessary. Traditionally management of port water collision risks has been relied on historical collision data. However, this collision-data-based approach is hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of samples for a sound statistical analysis, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these shortcomings is the navigational traffic conflict technique that uses traffic conflicts as an alternative to the collision data. This paper proposes a collision risk management method by utilizing the principles of this technique. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which, consequently, has great potential for managing collision risks in a fast, reliable and efficient manner.

Students’ approaches to learning a new mathematical model

In this article, we report on the findings of an exploratory study into the experience of undergraduate students as they learn new mathematical models. Qualitative and quanti- tative data based around the students’ approaches to learning new mathematical models were collected. The data revealed that students actively adopt three approaches to under- standing a new mathematical model: gathering information for the task of understanding the model, practising with and using the model, and finding interrelationships between elements of the model. We found that the students appreciate mathematical models that have a real world application and that this can be used to engage students in higher level learning approaches.