Management of Patients Presenting with Acute Subdural Hematoma due to Ruptured Intracranial Aneurysm

Acute subdural hematoma is a rare presentation of ruptured aneurysms. The rarity of the disease makes it difficult to establish reliable clinical guidelines. Many patients present comatose and differential diagnosis is complicated due to aneurysm rupture results in or mimics traumatic brain injury. Fast decision-making is required to treat this life-threatening condition. Determining initial diagnostic studies, as well as making treatment decisions, can be complicated by rapid deterioration of the patient, and the mixture of symptoms due to the subarachnoid hemorrhage or mass effect of the hematoma. This paper reviews initial clinical and radiological findings, diagnostic approaches, treatment modalities, and outcome of patients presenting with aneurysmal subarachnoid hemorrhage complicated by acute subdural hematoma. Clinical strategies used by several authors over the past 20 years are discussed and summarized in a proposed treatment flowchart.

Simulating the impact of four control strategies on the population dynamics of Neospora caninum infection in Swiss dairy cattle

A dynamic deterministic simulation model was developed to assess the impact of different putative control strategies on the seroprevalence of Neospora caninum in female Swiss dairy cattle. The model structure comprised compartments of "susceptible" and "infected" animals (SI-model) and the cattle population was divided into 12 age classes. A reference model (Model 1) was developed to simulate the current (status quo) situation (present seroprevalence in Switzerland 12%), taking into account available demographic and seroprevalence data of Switzerland. Model 1 was modified to represent four putative control strategies: testing and culling of seropositive animals (Model 2), discontinued breeding with offspring from seropositive cows (Model 3), chemotherapeutic treatment of calves from seropositive cows (Model 4), and vaccination of susceptible and infected animals (Model 5). Models 2-4 considered different sub-scenarios with regard to the frequency of diagnostic testing. Multivariable Monte Carlo sensitivity analysis was used to assess the impact of uncertainty in input parameters. A policy of annual testing and culling of all seropositive cattle in the population reduced the seroprevalence effectively and rapidly from 12% to <1% in the first year of simulation. The control strategies with discontinued breeding with offspring from all seropositive cows, chemotherapy of calves and vaccination of all cattle reduced the prevalence more slowly than culling but were still very effective (reduction of prevalence below 2% within 11, 23 and 3 years of simulation, respectively). However, sensitivity analyses revealed that the effectiveness of these strategies depended strongly on the quality of the input parameters used, such as the horizontal and vertical transmission factors, the sensitivity of the diagnostic test and the efficacy of medication and vaccination. Finally, all models confirmed that it was not possible to completely eradicate N. caninum as long as the horizontal transmission process was not interrupted.

Osteoporosis case finding in the general practice: phalangeal radiographic absorptiometry with and without risk factors for osteoporosis to select postmenopausal women eligible for lumbar spine and hip densitometry

Mass screening for osteoporosis using DXA measurements at the spine and hip is presently not recommended by health authorities. Instead, risk factor questionnaires and peripheral bone measurements may facilitate the selection of women eligible for axial bone densitometry. The aim of this study was to validate a case finding strategy for postmenopausal women who would benefit most from subsequent DXA measurement by using phalangeal radiographic absorptiometry (RA) alone or in combination with risk factors in a general practice setting. The sensitivity and specificity of this strategy in detecting osteoporosis (T-score < or =2.5 SD at the spine and/or the hip) were compared with those of the current reimbursement criteria for DXA measurements in Switzerland. Four hundred and twenty-three postmenopausal women with one or more risk factors for osteoporosis were recruited by 90 primary care physicians who also performed the phalangeal RA measurements. All women underwent subsequent DXA measurement of the spine and the hip at the Osteoporosis Policlinic of the University Hospital of Berne. They were allocated to one of two groups depending on whether they matched with the Swiss reimbursement conditions for DXA measurement or not. Logistic regression models were used to predict the likelihood of osteoporosis versus "no osteoporosis" and to derive ROC curves for the various strategies. Differences in the areas under the ROC curves (AUC) were tested for significance. In women lacking reimbursement criteria, RA achieved a significantly larger AUC (0.81; 95% CI 0.72-0.89) than the risk factors associated with patients' age, height and weight (0.71; 95% C.I. 0.62-0.80). Furthermore, in this study, RA provided a better sensitivity and specificity in identifying women with underlying osteoporosis than the currently accepted criteria for reimbursement of DXA measurement. In the Swiss environment, RA is a valid case finding tool for patients with risk factors for osteoporosis, especially for those who do not qualify for DXA reimbursement.

Investigating the effect of construction management strategies on project greenhouse gas emissions using interactive simulation

The challenges posed by global climate change are motivating the investigation of strategies that can reduce the life cycle greenhouse gas (GHG) emissions of products and processes. While new construction materials and technologies have received significant attention, there has been limited emphasis on understanding how construction processes can be best managed to reduce GHG emissions. Unexpected disruptive events tend to adversely impact construction costs and delay project completion. They also tend to increase project GHG emissions. The objective of this paper is to investigate ways in which project GHG emissions can be reduced by appropriate management of disruptive events. First, an empirical analysis of construction data from a specific highway construction project is used to illustrate the impact of unexpected schedule delays in increasing project GHG emissions. Next, a simulation based methodology is described to assess the effectiveness of alternative project management strategies in reducing GHG emissions. The contribution of this paper is that it explicitly considers projects emissions, in addition to cost and project duration, in developing project management strategies. Practical application of the method discussed in this paper will help construction firms reduce their project emissions through strategic project management, and without significant investment in new technology. In effect, this paper lays the foundation for best practices in construction management that will optimize project cost and duration, while minimizing GHG emissions.

Investigation of the effect of using data collection technology on students' attitudes to science instruction

The purpose of this project was to investigate the effect of using of data collection technology on student attitudes towards science instruction. The study was conducted over the course of two years at Madison High School in Adrian, Michigan, primarily in college preparatory physics classes, but also in one college preparatory chemistry class and one environmental science class. A preliminary study was conducted at a Lenawee County Intermediate Schools student summer environmental science day camp. The data collection technology used was a combination of Texas Instruments TI-84 Silver Plus graphing calculators and Vernier LabPro data collection sleds with various probeware attachments, including motion sensors, pH probes and accelerometers. Students were given written procedures for most laboratory activities and were provided with data tables and analysis questions to answer about the activities. The first year of the study included a pretest and posttest measuring student attitudes towards the class they were enrolled in. Pre-test and post-test data were analyzed to determine effect size, which was found to be very small (Coe, 2002). The second year of the study focused only on a physics class and used Keller’s ARCS model for measuring student motivation based on the four aspects of motivation: Attention, Relevance, Confidence and Satisfaction (Keller, 2010). According to this model, it was found that there were two distinct groups in the class, one of which was motivated to learn and the other that was not. The data suggest that the use of data collection technology in science classes should be started early in a student’s career, possibly in early middle school or late elementary. This would build familiarity with the equipment and allow for greater exploration by the student as they progress through high school and into upper level science courses.

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

Assessing Decision Making Strategies In Construction Management By Using A Schedule-Based Simulation Framework

During the project, managers encounter numerous contingencies and are faced with the challenging task of making decisions that will effectively keep the project on track. This task is very challenging because construction projects are non-prototypical and the processes are irreversible. Therefore, it is critical to apply a methodological approach to develop a few alternative management decision strategies during the planning phase, which can be deployed to manage alternative scenarios resulting from expected and unexpected disruptions in the as-planned schedule. Such a methodology should have the following features but are missing in the existing research: (1) looking at the effects of local decisions on the global project outcomes, (2) studying how a schedule responds to decisions and disruptive events because the risk in a schedule is a function of the decisions made, (3) establishing a method to assess and improve the management decision strategies, and (4) developing project specific decision strategies because each construction project is unique and the lessons from a particular project cannot be easily applied to projects that have different contexts. The objective of this dissertation is to develop a schedule-based simulation framework to design, assess, and improve sequences of decisions for the execution stage. The contribution of this research is the introduction of applying decision strategies to manage a project and the establishment of iterative methodology to continuously assess and improve decision strategies and schedules. The project managers or schedulers can implement the methodology to develop and identify schedules accompanied by suitable decision strategies to manage a project at the planning stage. The developed methodology also lays the foundation for an algorithm towards continuously automatically generating satisfactory schedule and strategies through the construction life of a project. Different from studying isolated daily decisions, the proposed framework introduces the notion of {em decision strategies} to manage construction process. A decision strategy is a sequence of interdependent decisions determined by resource allocation policies such as labor, material, equipment, and space policies. The schedule-based simulation framework consists of two parts, experiment design and result assessment. The core of the experiment design is the establishment of an iterative method to test and improve decision strategies and schedules, which is based on the introduction of decision strategies and the development of a schedule-based simulation testbed. The simulation testbed used is Interactive Construction Decision Making Aid (ICDMA). ICDMA has an emulator to duplicate the construction process that has been previously developed and a random event generator that allows the decision-maker to respond to disruptions in the emulation. It is used to study how the schedule responds to these disruptions and the corresponding decisions made over the duration of the project while accounting for cascading impacts and dependencies between activities. The dissertation is organized into two parts. The first part presents the existing research, identifies the departure points of this work, and develops a schedule-based simulation framework to design, assess, and improve decision strategies. In the second part, the proposed schedule-based simulation framework is applied to investigate specific research problems.

TECHNOLOGICAL ADVANCEMENT IN REMOTE SENSING AND INNOVATIVE APPLICATION TO VOLCANOLOGY

The integration of remote monitoring techniques at different scales is of crucial importance for monitoring of volcanoes and assessment of the associated hazard. In this optic, technological advancement and collaboration between research groups also play a key role. Vhub is a community cyberinfrastructure platform designed for collaboration in volcanology research. Within the Vhub framework, this dissertation focuses on two research themes, both representing novel applications of remotely sensed data in volcanology: advancement in the acquisition of topographic data via active techniques and application of passive multi-spectral satellite data to monitoring of vegetated volcanoes. Measuring surface deformation is a critical issue in analogue modelling of Earth science phenomena. I present a novel application of the Microsoft Kinect sensor to measurement of vertical and horizontal displacements in analogue models. Specifically, I quantified vertical displacement in a scaled analogue model of Nisyros volcano, Greece, simulating magmatic deflation and inflation and related surface deformation, and included the horizontal component to reconstruct 3D models of pit crater formation. The detection of active faults around volcanoes is of importance for seismic and volcanic hazard assessment, but not a simple task to be achieved using analogue models. I present new evidence of neotectonic deformation along a north-south trending fault from the Mt Shasta debris avalanche deposit (DAD), northern California. The fault was identified on an airborne LiDAR campaign of part of the region interested by the DAD and then confirmed in the field. High resolution LiDAR can be utilized also for geomorphological assessment of DADs, and I describe a size-distance analysis to document geomorphological aspects of hummock in the Shasta DAD. Relating the remote observations of volcanic passive degassing to conditions and impacts on the ground provides an increased understanding of volcanic degassing and how satellite-based monitoring can be used to inform hazard management strategies in nearreal time. Combining a variety of satellite-based spectral time series I aim to perform the first space-based assessment of the impacts of sulfur dioxide emissions from Turrialba volcano, Costa Rica, on vegetation in the surrounding environment, and establish whether vegetation indices could be used more broadly to detect volcanic unrest.

Using a Prediction and Option Generation Paradigm to Understand Decision Making

In many complex and dynamic domains, the ability to generate and then select the appropriate course of action is based on the decision maker's "reading" of the situation--in other words, their ability to assess the situation and predict how it will evolve over the next few seconds. Current theories regarding option generation during the situation assessment and response phases of decision making offer contrasting views on the cognitive mechanisms that support superior performance. The Recognition-Primed Decision-making model (RPD; Klein, 1989) and Take-The-First heuristic (TTF; Johnson & Raab, 2003) suggest that superior decisions are made by generating few options, and then selecting the first option as the final one. Long-Term Working Memory theory (LTWM; Ericsson & Kintsch, 1995), on the other hand, posits that skilled decision makers construct rich, detailed situation models, and that as a result, skilled performers should have the ability to generate more of the available task-relevant options. The main goal of this dissertation was to use these theories about option generation as a way to further the understanding of how police officers anticipate a perpetrator's actions, and make decisions about how to respond, during dynamic law enforcement situations. An additional goal was to gather information that can be used, in the future, to design training based on the anticipation skills, decision strategies, and processes of experienced officers. Two studies were conducted to achieve these goals. Study 1 identified video-based law enforcement scenarios that could be used to discriminate between experienced and less-experienced police officers, in terms of their ability to anticipate the outcome. The discriminating scenarios were used as the stimuli in Study 2; 23 experienced and 26 less-experienced police officers observed temporally-occluded versions of the scenarios, and then completed assessment and response option-generation tasks. The results provided mixed support for the nature of option generation in these situations. Consistent with RPD and TTF, participants typically selected the first-generated option as their final one, and did so during both the assessment and response phases of decision making. Consistent with LTWM theory, participants--regardless of experience level--generated more task-relevant assessment options than task-irrelevant options. However, an expected interaction between experience level and option-relevance was not observed. Collectively, the two studies provide a deeper understanding of how police officers make decisions in dynamic situations. The methods developed and employed in the studies can be used to investigate anticipation and decision making in other critical domains (e.g., nursing, military). The results are discussed in relation to how they can inform future studies of option-generation performance, and how they could be applied to develop training for law enforcement officers.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

[Primary ciliary dyskinesia (Pcd) in Austria]

INTRODUCTION: Primary ciliary dyskinesia (PCD) is a rare hereditary recessive disease with symptoms of recurrent pneumonia, chronic bronchitis, bronchiectasis, and chronic sinusitis. Chronic rhinitis is often the presenting symptom in newborns and infants. Approximately half of the patients show visceral mirror image arrangements (situs inversus). In this study, we aimed 1) to determine the number of paediatric PCD patients in Austria, 2) to show the diagnostic and therapeutic modalities used in the clinical centres and 3) to describe symptoms of children with PCD. PATIENTS, MATERIAL AND METHODS: For the first two aims, we analysed data from a questionnaire survey of the European Respiratory Society (ERS) task force on Primary Ciliary Dyskinesia in children. All paediatric respiratory units in Austria received a questionnaire. Symptoms of PCD patients from Vienna Children's University Hospital (aim 3) were extracted from case histories. RESULTS: In 13 Austrian clinics 48 patients with PCD (36 aged from 0-19 years) were identified. The prevalence of reported cases (aged 0-19 yrs) in Austria was 1:48000. Median age at diagnosis was 4.8 years (IQR 0.3-8.2), lower in children with situs inversus compared to those without (3.1 vs. 8.1 yrs, p = 0.067). In 2005-2006, the saccharine test was still the most commonly used screening test for PCD in Austria (45%). Confirmation of the diagnosis was usually by electron microscopy (73%). All clinics treated exacerbations immediately with antibiotics, 73% prescribed airway clearance therapy routinely to all patients. Other therapies and diagnostic tests were applied very inconsistently across Austrian hospitals. All PCD patients from Vienna (n = 13) had increased upper and lower respiratory secretions, most had recurring airway infections (n = 12), bronchiectasis (n = 7) and bronchitis (n = 7). CONCLUSION: Diagnosis and therapy of PCD in Austria are inhomogeneous. Prospective studies are needed to learn more about the course of the disease and to evaluate benefits and harms of different treatment strategies.

Strategies for Optimizing Value of Finished Cattle in Value-Based Marketing Grids

Performance and carcass data from 624 steers in three experiments were used to evaluate potential strategies that might be used with incoming feeders to remove animals that produce low value carcasses when cattle are sold in a valuebased grid. Removing 10% of the carcasses with the lowest net value from each group increased the overall average net value of the remaining carcasses $17.50 to $21.09. Carcass weight was found to be the most significant factor determining net value of the carcass. Gain of the steers during the first 3 to 5 weeks of the feeding period was significantly related to average final gain and carcass value, but accounted for a small portion of the overall variation in gain or carcass value. Use of initial gain was successful in identifying ten of the sixty-four carcasses with least net value in a value-based grid. Adding frame score and measurement of initial thickness of backfat along with initial gain did not significantly improve identification of the low-value carcasses. Sorting the steers as feeders based on frame score and initial thickness of backfat resulted in differences in performance and carcass measurements. The low-value carcasses tended to be concentrated in the smaller-framed steers.

Distinct coping strategies differentially predict urge levels and lapses in a smoking cessation attempt

This study analysed mechanisms through which stress-coping and temptation-coping strategies were associated with lapses. Furthermore, we explored whether distinct coping strategies differentially predicted reduced lapse risk, lower urge levels, or a weaker association between urge levels and lapses during the first week of an unassisted smoking cessation attempt. Participants were recruited via the internet and mass media in Switzerland. Ecological momentary assessment (EMA) with mobile devices was used to assess urge levels and lapses. Online questionnaires were used to measure smoking behaviours and coping variables at baseline, as well as smoking behaviour at the three-month follow-up. The sample consisted of 243 individuals, aged 20 to 40, who reported 4199 observations. Findings of multilevel regression analyses show that coping was mainly associated with a reduced lapse risk and not with lower urge levels or a weaker association between urge levels and lapses. 'Calming down' and 'commitment to change' predicted a lower lapse risk and also a weaker relation between urge levels and lapses. 'Stimulus control' predicted a lower lapse risk and lower urge levels. Conversely, 'task-orientation' and 'risk assessment' were related to higher lapse risk and 'risk assessment' also to higher urge levels. Disengagement coping i.e. 'eating or shopping', 'distraction', and 'mobilising social support' did not affect lapse risk. Promising coping strategies during the initial stage of smoking cessation attempt are targeted directly at reducing the lapse risk and are characterised by engagement with the stressor or one's reactions towards the stressor and a focus on positive consequences instead of health risks.

Social Meets Molecular: Combining Phylogenetic and Latent Class Analyses to Understand HIV-1 Transmission in Switzerland

Switzerland has a complex human immunodeficiency virus (HIV) epidemic involving several populations. We examined transmission of HIV type 1 (HIV-1) in a national cohort study. Latent class analysis was used to identify socioeconomic and behavioral groups among 6,027 patients enrolled in the Swiss HIV Cohort Study between 2000 and 2011. Phylogenetic analysis of sequence data, available for 4,013 patients, was used to identify transmission clusters. Concordance between sociobehavioral groups and transmission clusters was assessed in correlation and multiple correspondence analyses. A total of 2,696 patients were infected with subtype B, 203 with subtype C, 196 with subtype A, and 733 with recombinant subtypes (mainly CRF02_AG and CRF01_AE). Latent class analysis identified 8 patient groups. Most transmission clusters of subtype B were shared between groups of gay men (groups 1-3) or between the heterosexual groups "heterosexual people of lower socioeconomic position" (group 4) and "injection drug users" (group 8). Clusters linking homosexual and heterosexual groups were associated with "older heterosexual and gay people on welfare" (group 5). "Migrant women in heterosexual partnerships" (group 6) and "heterosexual migrants on welfare" (group 7) shared non-B clusters with groups 4 and 5. Combining approaches from social and molecular epidemiology can provide insights into HIV-1 transmission and inform the design of prevention strategies.

Loss to follow-up of HIV-infected women after delivery: The Swiss HIV Cohort Study and the Swiss Mother and Child HIV Cohort Study.

INTRODUCTION HIV-infected pregnant women are very likely to engage in HIV medical care to prevent transmission of HIV to their newborn. After delivery, however, childcare and competing commitments might lead to disengagement from HIV care. The aim of this study was to quantify loss to follow-up (LTFU) from HIV care after delivery and to identify risk factors for LTFU. METHODS We used data on 719 pregnancies within the Swiss HIV Cohort Study from 1996 to 2012 and with information on follow-up visits available. Two LTFU events were defined: no clinical visit for >180 days and no visit for >360 days in the year after delivery. Logistic regression analysis was used to identify risk factors for a LTFU event after delivery. RESULTS Median maternal age at delivery was 32 years (IQR 28-36), 357 (49%) women were black, 280 (39%) white, 56 (8%) Asian and 4% other ethnicities. One hundred and seven (15%) women reported any history of IDU. The majority (524, 73%) of women received their HIV diagnosis before pregnancy, most of those (413, 79%) had lived with diagnosed HIV longer than three years and two-thirds (342, 65%) were already on antiretroviral therapy (ART) at time of conception. Of the 181 women diagnosed during pregnancy by a screening test, 80 (44%) were diagnosed in the first trimester, 67 (37%) in the second and 34 (19%) in the third trimester. Of 357 (69%) women who had been seen in HIV medical care during three months before conception, 93% achieved an undetectable HIV viral load (VL) at delivery. Of 62 (12%) women with the last medical visit more than six months before conception, only 72% achieved an undetectable VL (p=0.001). Overall, 247 (34%) women were LTFU over 180 days in the year after delivery and 86 (12%) women were LTFU over 360 days with 43 (50%) of those women returning. Being LTFU for 180 days was significantly associated with history of intravenous drug use (aOR 1.73, 95% CI 1.09-2.77, p=0.021) and not achieving an undetectable VL at delivery (aOR 1.79, 95% CI 1.03-3.11, p=0.040) after adjusting for maternal age, ethnicity, time of HIV diagnosis and being on ART at conception. CONCLUSIONS Women with a history of IDU and women with a detectable VL at delivery were more likely to be LTFU after delivery. This is of concern regarding their own health, as well as risk for sexual partners and subsequent pregnancies. Further strategies should be developed to enhance retention in medical care beyond pregnancy.