Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO

Das intelligente Tutorensystem LARGO für die Rechtswissenschaften soll Jurastudenten helfen, Argumentationsstrategien zu lernen. Im verwendeten Ansatz werden Gerichtsprotokolle als Lernmaterialien verwendet: Studenten annotieren diese und erstellen graphische Repräsentationen des Argumentationsverlaufs. Das System kann dabei zur Reflexion über die von Anwälten vorgebrachten Argumente anregen und Lernende auf mögliche Schwächen in ihrer Analyse des Disputs hinweisen. Zur Erkennung von Schwächen verwendet das System Graphgrammatiken und kollaborative Filtermechanismen. Dieser Artikel stellt dar, wie in LARGO auf Basis der Bestimmung eines „Benutzungskontextes“ die Rückmeldungen im System benutzungsadaptiv gestaltet werden. Weiterhin diskutieren wir auf Basis der Ergebnisse einer kontrollierten Studie mit dem System, welche mit Jurastudierenden an der University of Pittsburgh stattfand, in wie weit der automatisch bestimmte Benutzungskontext zur Vorhersage von Lernerfolgen bei Studenten verwendbar ist.

Konzeption eines proaktiven Risikomanagements in Logistiknetzwerken

Logistiknetzwerke von Unternehmen wachsen sehr schnell und werden immer komplexer. Unternehmen wissen oft nicht, von welchen anderen Unternehmen sie abhängig sind und welche geschäftskritischen Risiken sich daraus für sie ergeben. Aus diesem Grund wird in diesem Artikel ein Konzept eines proaktiven Ri-sikomanagements in Logistiknetzwerken vorgestellt. Das Konzept basiert auf der Big Data Technologie und verwendet zur Identifikation von Risiken und zum Aufbau eines Logistiknetzwerkes neben internen Unternehmensdaten auch externe Daten, z. B. Social Media Plattformen oder andere Datenportale. Diese Daten werden ausgewertet und mit Risiken behaftete Beziehungen werden dem Bediener grafisch angezeigt. Zusätzlich dazu kann das System dem Benutzer mögliche Alternativen zur Vermeidung dieser Risiken aufzeigen und somit zur Entscheidungsunterstützung genutzt werden.

Selection and hydroponic growth of bread wheat cultivars for bioregenerative life support systems

As part of the ESA-funded MELiSSA program, the suitability, the growth and the development of four bread wheat cultivars were investigated in hydroponic culture with the aim to incorporate such a cultivation system in an Environmental Control and Life Support System (ECLSS). Wheat plants can fulfill three major functions in space: (a) fixation of CO2 and production of O2, (b) production of grains for human nutrition and (c) production of cleaned water after condensation of the water vapor released from the plants by transpiration. Four spring wheat cultivars (Aletsch, Fiorina, Greina and CH Rubli) were grown hydroponically and compared with respect to growth and grain maturation properties. The height of the plants, the culture duration from germination to harvest, the quantity of water used, the number of fertile and non-fertile tillers as well as the quantity and quality of the grains harvested were considered. Mature grains could be harvested after around 160 days depending on the varieties. It became evident that the nutrient supply is crucial in this context and strongly affects leaf senescence and grain maturation. After a first experiment, the culture conditions were improved for the second experiment (stepwise decrease of EC after flowering, pH adjusted twice a week, less plants per m2) leading to a more favorable harvest (higher grain yield and harvest index). Considerably less green tillers without mature grains were present at harvest time in experiment 2 than in experiment 1. The harvest index for dry matter (including roots) ranged from 0.13 to 0.35 in experiment 1 and from 0.23 to 0.41 in experiment 2 with modified culture conditions. The thousand-grain weight for the four varieties ranged from 30.4 to 36.7 g in experiment 1 and from 33.2 to 39.1 g in experiment 2, while market samples were in the range of 39.4–46.9 g. Calcium levels in grains of the hydroponically grown wheat were similar to those from field-grown wheat, while potassium, magnesium, phosphorus, iron, zinc, copper, manganese and nickel levels tended to be higher in the grains of experimental plants. It remains a challenge for future experiments to further adapt the nutrient supply in order to improve senescence of vegetative plant parts, harvest index and the composition of bread wheat grains.

Tools for better SLM knowledge management and informed decision-making in addressing land degradation at different scales: the WOCAT–LADA–DESIRE methodology

Desertification research conventionally focuses on the problem – that is, degradation – while neglecting the appraisal of successful conservation practices. Based on the premise that Sustainable Land Management (SLM) experiences are not sufficiently or comprehensively documented, evaluated, and shared, the World Overview of Conservation Approaches and Technologies (WOCAT) initiative (www.wocat.net), in collaboration with FAO’s Land Degradation Assessment in Drylands (LADA) project (www.fao.org/nr/lada/) and the EU’s DESIRE project (http://www.desire-project.eu/), has developed standardised tools and methods for compiling and evaluating the biophysical and socio-economic knowledge available about SLM. The tools allow SLM specialists to share their knowledge and assess the impact of SLM at the local, national, and global levels. As a whole, the WOCAT–LADA–DESIRE methodology comprises tools for documenting, self-evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing and decision support in the field, at the planning level, and in scaling up identified good practices. SLM depends on flexibility and responsiveness to changing complex ecological and socioeconomic causes of land degradation. The WOCAT tools are designed to reflect and capture this capacity of SLM. In order to take account of new challenges and meet emerging needs of WOCAT users, the tools are constantly further developed and adapted. Recent enhancements include tools for improved data analysis (impact and cost/benefit), cross-scale mapping, climate change adaptation and disaster risk management, and easier reporting on SLM best practices to UNCCD and other national and international partners. Moreover, WOCAT has begun to give land users a voice by backing conventional documentation with video clips straight from the field. To promote the scaling up of SLM, WOCAT works with key institutions and partners at the local and national level, for example advisory services and implementation projects. Keywords: Sustainable Land Management (SLM), knowledge management, decision-making, WOCAT–LADA–DESIRE methodology.

Assessing and mapping LD and SLM to directly support the planning and scaling up of SLM interventions to combat desertification

Global investment in Sustainable Land Management (SLM) has been substantial, but knowledge gaps remain. Overviews of where land degradation (LD) is taking place and how land users are addressing the problem using SLM are still lacking for most individual countries and regions. Relevant maps focus more on LD than SLM, and they have been compiled using different methods. This makes it impossible to compare the benefits of SLM interventions and prevents informed decision-making on how best to invest in land. To fill this knowledge gap, a standardised mapping method has been collaboratively developed by the World Overview of Conservation Approaches and Technologies (WOCAT), FAO’s Land Degradation Assessment in Drylands (LADA) project, and the EU’s Mitigating Desertification and Remediating Degraded Land (DESIRE) project. The method generates information on the distribution and characteristics of LD and SLM activities and can be applied at the village, national, or regional level. It is based on participatory expert assessment, documents, and surveys. These data sources are spatially displayed across a land-use systems base map. By enabling mapping of the DPSIR framework (Driving Forces-Pressures-State-Impacts-Responses) for degradation and conservation, the method provides key information for decision-making. It may also be used to monitor LD and conservation following project implementation. This contribution explains the mapping method, highlighting findings made at different levels (national and local) in South Africa and the Mediterranean region. Keywords: Mapping, Decision Support, Land Degradation, Sustainable Land Management, Ecosystem Services, Participatory Expert Assessment

Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records.

BACKGROUND: We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria. METHODS: We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content. RESULTS: All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified. CONCLUSION: If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.

Development, implementation, and evaluation of a structured reporting web tool for abdominal aortic aneurysms

BACKGROUND The majority of radiological reports are lacking a standard structure. Even within a specialized area of radiology, each report has its individual structure with regards to details and order, often containing too much of non-relevant information the referring physician is not interested in. For gathering relevant clinical key parameters in an efficient way or to support long-term therapy monitoring, structured reporting might be advantageous. OBJECTIVE Despite of new technologies in medical information systems, medical reporting is still not dynamic. To improve the quality of communication in radiology reports, a new structured reporting system was developed for abdominal aortic aneurysms (AAA), intended to enhance professional communication by providing the pertinent clinical information in a predefined standard. METHODS Actual state analysis was performed within the departments of radiology and vascular surgery by developing a Technology Acceptance Model. The SWOT (strengths, weaknesses, opportunities, and threats) analysis focused on optimization of the radiology reporting of patients with AAA. Definition of clinical parameters was achieved by interviewing experienced clinicians in radiology and vascular surgery. For evaluation, a focus group (4 radiologists) looked at the reports of 16 patients. The usability and reliability of the method was validated in a real-world test environment in the field of radiology. RESULTS A Web-based application for radiological "structured reporting" (SR) was successfully standardized for AAA. Its organization comprises three main categories: characteristics of pathology and adjacent anatomy, measurements, and additional findings. Using different graphical widgets (eg, drop-down menus) in each category facilitate predefined data entries. Measurement parameters shown in a diagram can be defined for clinical monitoring and be adducted for quick adjudications. Figures for optional use to guide and standardize the reporting are embedded. Analysis of variance shows decreased average time required with SR to obtain a radiological report compared to free-text reporting (P=.0001). Questionnaire responses confirm a high acceptance rate by the user. CONCLUSIONS The new SR system may support efficient radiological reporting for initial diagnosis and follow-up for AAA. Perceived advantages of our SR platform are ease of use, which may lead to more accurate decision support. The new system is open to communicate not only with clinical partners but also with Radiology Information and Hospital Information Systems.

A methodology for appraising and selecting strategies to mitigate desertification based on stakeholder participation and global best practices

The main aim of the methodology presented in this paper is to provide a framework for a participatory process for the appraisal and selection of options to mitigate desertification and land degradation. This methodology is being developed within the EU project DESIRE (www.desire-project.eu/) in collaboration with WOCAT (www.wocat.org). It is used to select promising conservation strategies for test-implementation in each of the 16 degradation and desertification hotspot sites in the Mediterranean and around the world. The methodology consists of three main parts: In a first step, prevention and mitigation strategies already applied at the respective DESIRE study site are identified and listed during a workshop with representatives of different stakeholders groups (land users, policy makers, researchers). The participatory and process-oriented approach initiates a mutual learning process among the different stakeholders by sharing knowledge and jointly reflecting on current problems and solutions related to land degradation and desertification. In the second step these identified, locally applied solutions (technologies and approaches) are assessed with the help of the WOCAT methodology. Comprehensive questionnaires and a database system have been developed to document and evaluate all relevant aspects of technical measures as well as implementation approaches by teams of researchers and specialists, together with land users. This research process ensures systematic assessing and piecing together of local information, together with specific details about the environmental and socio-economic setting. The third part consists of another stakeholder workshop where promising strategies for sustainable land management in the given context are selected, based on the best practices database of WOCAT, including the evaluated locally applied strategies at the DESIRE sites. These promising strategies will be assessed with the help of a selection and decision support tool and adapted for test-implementation at the study site.

Roadmap for implementing the Chronic Care Model for weight management: Healthcare Institution's Response to Obesity (HIRO)

Background. Excess weight and obesity are at epidemic proportions in the United States and place individuals at increased risk for a variety of chronic conditions. Rates of diabetes, high blood pressure, coronary artery disease, stroke, cancer, and arthritis are all influenced by the presence of obesity. Small reductions in excess weight can produce significant positive clinical outcomes. Healthcare organizations have a vital role to play in the identification and management of obesity. Currently, healthcare providers do not adequately diagnose and manage excess weight in patients. Lack of skill, time, and knowledge are commonly cited as reasons for non-adherence to recommended standards of care. The Chronic Care Model offers an approach to healthcare organizations for chronic disease management. The model consists of six elements that work together to empower both providers and patients to have more productive interactions: the community, the health system itself, self-management support, delivery system design, decision support, and clinical information systems. The model and its elements may offer a framework through which healthcare organizations can adapt to support, educate, and empower providers and patients in the management of excess weight and obesity. Successful management of excess weight will reduce morbidity and mortality of many chronic conditions. Purpose. The purpose of this review is to synthesize existing research on the effectiveness of the Chronic Care Model and its elements as they relate to weight management and behaviors associated with maintaining a healthy weight. Methods: A narrative review of the literature between November 1998 and November 2008 was conducted. The review focused on clinical trials, systematic reviews, and reports related to the chronic care model or its elements and weight management, physical activity, nutrition, or diabetes. Fifty-nine articles are included in the review. Results. This review highlights the use of the Chronic Care Model and its elements that can result in improved quality of care and clinical outcomes related to weight management, physical activity, nutrition, and diabetes. Conclusions. Healthcare organizations can use the Chronic Care Model framework to implement changes within their systems to successfully address overweight and obesity in their patient populations. Specific recommendations for operationalizing the Chronic Care Model elements for weight management are presented.^

Relating one's social support network to one's mid term grade

Much has been written about the relation of social support to health outcomes. Support networks were found to be predictive of health status. Not so clear was the manner in which social support helped the individual to avoid health complications. Whereas some aspects of the support network were protective, others were burdensome. Duties to one's network could serve as a stressor and duties outside one's network might stress the support system itself. Exposure to one's network was associated with certain health risks while disruption in one's social support network was associated with other health risks.^ Many factors contributed to the impact of a social support network upon the individual member: the characteristics of the individual, the individual's role or position within the network, qualities of the network and duties or indebtedness of the individual to the network. This investigation considered the possibility that performance could serve as a stressor in a fashion similar to an exposure to a health hazard.^ Because the literature includes many examples of studies in which the subjects were college students, academic progress is a performance common to most subjects. A profile of the support networks of successful students was contrasted with those of less successful students in this correlational study.^ What was uncovered in this investigation was a very complex web of interrelated constructs. Most aspects of the social support network did not significantly predict academic performance. Only a limited number of characteristics were associated with academic success: the frequency of support, student age, the existence of a 'mentor' within one' s network, and the extent to which one received a predominant source of support. Other factors had a tendency to be negatively correlated with midterm grade, suggesting those factors may impede academic performance.^ Medical status did not predict grades, but was correlated with many aspects of the network. Disruptions in particular parts of one's network were correlated with particular health categories. In fact, disruption in social support was more predictive of academic outcomes than medical complications. Whereas the individual's values were related to the contributing factors, only the individual's satisfaction with certain aspects of the support network were predictive of higher midterm grades in a psychology class. Dissatisfaction was associated with lower grades, suggesting a disruptive effect within the network. Associations among the features of support networks which predicted academic progress were considered. ^

Errors in the administration of medication in inpatient hospitals: A systematic review of the research literature on commercial computerized physician order entry systems

Errors in the administration of medication represent a significant loss of medical resources and pose life altering or life threatening risks to patients. This paper considered the question, what impact do Computerized Physician Order Entry (CPOE) systems have on medication errors in the hospital inpatient environment? Previous reviews have examined evidence of the impact of CPOE on medication errors, but have come to ambiguous conclusions as to the impact of CPOE and decision support systems (DSS). Forty-three papers were identified. Thirty-one demonstrated a significant reduction in prescribing error rates for all or some drug types; decreases in minor errors were most often reported. Several studies reported increases in the rate of duplicate orders and failures to remove contraindicated drugs, often attributed to inappropriate design or to an inability to operate the system properly. The evidence on the effectiveness of CPOE to reduce errors in medication administration is compelling though it is limited by modest study sample sizes and designs. ^

Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study

The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

Continuous multi-criteria methods for crop and soil conservation planning on La Colacha (Río Cuarto, Province of Cordoba, Argentina)

Agro-areas of Arroyos Menores (La Colacha) west and south of Rand south of R?o Cuarto (Prov. of Cordoba, Argentina) basins are very fertile but have high soil loses. Extreme rain events, inundations and other severe erosions forming gullies demand urgently actions in this area to avoid soil degradation and erosion supporting good levels of agro production. The authors first improved hydrologic data on La Colacha, evaluated the systems of soil uses and actions that could be recommended considering the relevant aspects of the study area and applied decision support systems (DSS) with mathematic tools for planning of defences and uses of soils in these areas. These were conducted here using multi-criteria models, in multi-criteria decision making (MCDM); first of discrete MCDM to chose among global types of use of soils, and then of continuous MCDM to evaluate and optimize combined actions, including repartition of soil use and the necessary levels of works for soil conservation and for hydraulic management to conserve against erosion these basins. Relatively global solutions for La Colacha area have been defined and were optimised by Linear Programming in Goal Programming forms that are presented as Weighted or Lexicographic Goal Programming and as Compromise Programming. The decision methods used are described, indicating algorithms used, and examples for some representative scenarios on La Colacha area are given.

AUTOFLY-Aid: Flight Deck Automation Support with Dynamic 4D Trajectory Management for Responsive and Adaptive Airborne Collision Avoidance

AUTOFLY-Aid Project aims to develop and demonstrate novel automation support algorithms and tools to the flight crew for flight critical collision avoidance using “dynamic 4D trajectory management”. The automation support system is envisioned to improve the primary shortcomings of TCAS, and to aid the pilot through add-on avionics/head-up displays and reality augmentation devices in dynamically evolving collision avoidance scenarios. The main theoretical innovative and novel concepts to be developed by AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck’s perspective, as seen/measured/informed by the aircraft flying in SESAR 2020, b) design and development of a dynamic trajectory planning algorithm that can generate at real-time (on the order of seconds) flyable (i.e. dynamically and performance-wise feasible) alternative trajectories across the evolving stochastic composite airspace picture (which includes new conflicts, blunder risks, terrain and weather limitations) and c) development and testing of the Collision Avoidance Automation Support System on a Boeing 737 NG FNPT II Flight Simulator with synthetic vision and reality augmentation while providing the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures.