Developing Whole Leaders for the Whole World

How do we holistically develop leaders with the capacity and character to tackle the most pressing moral challenges in our modern world? While it may be easier to focus on one thing such as strengths, experiences, or mentors, the reality is that developing a leader’s capacity to lead well includes many interrelated components. Based on our experience and research, the six components of the Holistic Leadership Development Model (HLDM) are presented, along with strategies for creating rich conversations that connect the components in a meaningful way for leaders. The six areas are (1) experiences and learning; (2) strategic networking; (3) developing others; (4) integrated fulfillment; (5) leading under pressure; and (6) calling and purpose. While we are not suggesting that these are the only areas to consider when developing leaders, focusing on these six creates conversations and development plans for leaders that they perceive as capturing the reality of the challenges they face in developing their leadership capacity. Guides for evaluating one’s own leadership development and for having rich development conversations are included

Characterization and Dynamics of Substituted Ruthenacyclobutanes Relevant to the Olefin Cross-Metathesis Reaction

The reaction of the phosphonium alkylidene [(H_(2)IMes)RuCl2═CHP(Cy)_3)]^(+) BF_(4)^− with propene, 1-butene, and 1-hexene at −45 °C affords various substituted, metathesis-active ruthenacycles. These metallacycles were found to equilibrate over extended reaction times in response to decreases in ethylene concentrations, which favored increased populations of α-monosubstituted and α,α′-disubstituted (both cis and trans) ruthenacycles. On an NMR time scale, rapid chemical exchange was found to preferentially occur between the β-hydrogens of the cis and trans stereoisomers prior to olefin exchange. Exchange on an NMR time scale was also observed between the α- and β-methylene groups of the monosubstituted ruthenacycle (H_(2)IMes)Cl_(2)Ru(CHRCH_(2)CH_(2)) (R = CH_3, CH_(2)CH_3, (CH_2)_)_(3)CH_3). EXSY NMR experiments at −87 °C were used to determine the activation energies for both of these exchange processes. In addition, new methods have been developed for the direct preparation of metathesis-active ruthenacyclobutanes via the protonolysis of dichloro(1,3-bis(2,4,6-trimethylphenyl)-2-imidazolidinylidene)(benzylidene) bis(pyridine)ruthenium(II) and its 3-bromopyridine analogue. Using either trifluoroacetic acid or silica-bound toluenesulfonic acid as the proton source, the ethylene-derived ruthenacyclobutane (H_(2)IMes)Cl_(2)Ru(CH_(2)CH_(2)CH_(2)) was observed in up to 98% yield via NMR at −40 °C. On the basis of these studies, mechanisms accounting for the positional and stereochemical exchange within ruthenacyclobutanes are proposed, as well as the implications of these dynamics toward olefin metathesis catalyst and reaction design are described

Ruthenium Metallacycles Derived from 14-Electron Complexes. New Insights into Olefin Metathesis Intermediates

Ruthenium(IV) metallacycles derived from both ethylene and propene are reported. The propene-derived metallacycles represent the first observed examples of substituted ruthenacyclobutanes and offer new insight into the preferred stereochemical orientation about metathesis intermediates. In addition, a metallacycle possessing an unsymmetrical N-heterocyclic carbene (NHC) ligand was prepared and investigated to ascertain the dynamics of the NHC relative to the metallacycle ring. Metallacycles investigated were found to possess exchange cross-peaks between the α- and β-positions in the 2D NMR, indicating a dynamic structure. The implications of these results to the mechanism of ruthenium-catalyzed olefin metathesis are discussed

Discovery of the high-field polar RX J1724.0+4114

We report the discovery of a new AM Herculis binary (polar) as the optical counterpart of the soft X-ray source RX J1724.0+4114 detected during the ROSAT all-sky survey. The magnetic nature of this V~17 mag object is confirmed by low-resolution spectroscopy showing strong Balmer and HeII emission lines superimposed on a blue continuum which is deeply modulated by cyclotron humps. The inferred magnetic field strength is 50+/-4 MG (or possibly even ~70 MG). Photometric observations spanning ~3 years reveal a period of 119.9 min, right below the period gap. The morphology of the optical and X-ray light curves which do not show eclipses by the secondary star, suggests a self-eclipsing geometry. We derive a lower limit of d~250 pc.Comment: 6 pages, LATEX with mn.sty, incl 4 Figs., to appear in MNRAS; [email protected]

Möglichkeiten des Einsatzes von Zika-Virus-Kapsid-Antikörpern und Zika-Virus-Kapsid als diagnostische Marker für den Nachweis einer Zika-Virus-Infektion beim Menschen

Im Rahmen dieser Arbeit wurde untersucht, ob humane Antikörper gegen ZIKV-Kapsid und ZIKV-Kapsid selbst geeignete Biomarker für den Nachweis einer ZIKV-Infektion sind. Sie kann damit als erste Phase einer Studie zur Entwicklung neuer ZIKV-Diagnostika angesehen werden. Der Aufbau, das klinische Erscheinungsbild, die Epidemiologie und der Nachweis von ZIKV, bzw. einer ZIKV-Infektion, wurden erörtert. Die Möglichkeiten und Limitationen aktueller ZIKV-Diagnostika wurden beschrieben, insbesondere hinsichtlich der Spezifität. Durch Analyse des Genoms von ZIKV und anderen Flaviviren wurde gezeigt, dass die Aminoäuresequenzidentität zwischen den einzelnen Flaviviren für flavivirales Kapsid geringer ist als für andere Bestandteile und potenzielle Antigene von Flaviviren. Relevant ist insbesondere die Abgrenzung zu DENV, da eine akute oder abgelaufene DENV-Infektion eine häufige Ursache von Kreuzreaktivität beim Nachweis einer ZIKV-Infektion darstellt. Mittels webserverbasierten In-silico-Analysen konnten immunogene Regionen innerhalb des ZIKV-Kapsid-Proteins kartiert und mit den immunogenen Regionen, welche für ZIKV-Kapsid anderer Flaviviren In-silico oder experimentell ermittelt wurden, verglichen werden. Auf Basis dieser Analysen war die Erwartung, dass bei einer ZIKV-Infektion humane Antikörper gegen ZIKV-Kapsid gebildet werden, welche sich in ihren Paratopen von Antikörpern, die gegen Kapsid-Proteine anderer Flaviviren gebildet werden, unterscheiden. Der Umfang der humanen Antikörperantwort auf ZIKV-Kapsid wurde in dieser Arbeit anschließend untersucht. Dazu wurde das Antigen ZIKV-Kapsid eines ZIKV-Stamms aus der afrikanischen Linie (hier: Stamm MR766) rekombinant hergestellt. Rekombinantes ZIKV-Kapsid eines Stammes der asiatischen Linie (hier: Stamm Z1106033) wurde erworben. In 11 humanen Seren und einem Pool-Serum (WHO-Referenzserum) wurde versucht Anti-ZIKV-Kapsid-Antikörper mittels ELISAs und Western Blots nachzuweisen. Es fanden sich keine bis schwache Hinweise auf das Vorhandensein von Anti-ZIKV-Kapsid-Antikörpern in diesen Seren. Im direkten Vergleich mit 10 Seren von ZIKV-negativen Blutspendern zeigten sich für die Seren des ZIKV-Serumpanels keine höheren ELISA-Extinktionswerte. Dies galt sowohl für den Einsatz von ZIKV-Kapsid des Stammes der afrikanischen Linie als auch beim Einsatz von ZIKV-Kapsid des Stammes der asiatischen Linie. Im Sinn der Ermittlung der Paralleltestreliabilität fand sich für Anti-ZIKV-Kapsid-IgG in einer Regressionsanalyse ein schwacher linearer Zusammenhang zu Messwerten eines gut validierten Referenztests, dem ZIKV-NS1-ELISA der Firma Euroimmun. Dies ist ein schwacher Hinweis auf die postinfektiöse Bildung von humanen Anti-ZIKV-Kapsid-Antikörpern. Obwohl der lineare Zusammenhang signifikant war, ist die Aussagekraft dieses Ergebnisses eingeschränkt. Es fanden sich Hinweise auf unspezifische, im Rahmen dieser Arbeit nicht vollständig identifizierte, Einflüsse auf die Testergebnisse der eigenen Anti-ZIKV-Kapsid-Antikörper-ELISAs. Es ist vorstellbar, dass der gefundene lineare Zusammenhang zum Referenztest teilweise durch diese unspezifischen Einflüsse, im Sinn von Kovariablen, verursacht wird. Die im Rahmen dieser Arbeit entwickelten Anti-ZIKV-Kapsid-Antikörper-ELISAs zeigten Hinweise für falsch-positive Messergebnisse bei der Testung von fünf DENV-positiven Seren. Mit Hilfe von Western Blots, welche verglichen mit ELISAs als spezifischer gelten, konnten in Seren des ZIKV-Serumpanels keine ZIKV-Kapsid-spezifischen Antikörper nachgewiesen werden. Auch Antikörper aus Seren von ZIKV-negativen Blutspendern und IgG-Antikörper aus gereinigten IgG-Antikörper-Lösungen verursachten positive und somit unspezifische Testergebnisse (Banden). Eine mögliche Erklärung dafür liegt in der hohen Hydrophobizität von ZIKV-Kapsid, was für die Anlagerung nichtspezifischer humaner Antikörper sorgen könnte. Es ist möglich diese Arbeit in zwei Teile zu unterteilen, wobei sich der erste Teil vor allem dem Nachweis von humanen Antikörpern gegen ZIKV-Kapsid widmet und der Nachweis von ZIKV-Kapsid in Serum von Infizierten den zweiten Teil darstellt. Für den Nachweis des Antigens wurden polyklonale und monoklonale Antikörper eingesetzt. Durch Immunisierung von Mäusen mit ZIKV-Kapsid und anschließendem Einsatz der Hybridomtechnik konnten durch Dr. Sven Reiche (Friedrich-Löffler-Institut) und Prof. Christian Jassoy vier monoklonale Antikörper gegen ZIKV-Kapsid gewonnen werden. Diese Antikörper wurden in dieser Arbeit weiter charakterisiert. Sie zeigten sich als geeignet und spezifisch beim Nachweis von ZIKV-infizierten Vero-Zellen durch Immunfluoreszenzfärbungen. Durch Kompetitionstests hatte sich zuvor bereits gezeigt, dass alle Antikörper an dasselbe, oder mindestens nahe beieinander liegende Epitope binden. Da sie sich somit bei Einsatz in einem Sandwich-ELISA zum Nachweis von ZIKV-Kapsid als Antigen verdrängen würden, wurden zwei polyklonale Anti-ZIKV-Kapsid-Antikörper erworben. Ein Sandwich-ELISA, der polyklonale Anti-ZIKV-Kapsid-Antikörper als Fängerantikörper und monoklonale Anti-ZIKV-Kapsid-Antikörper als Detektionsantikörper nutzt, konnte erfolgreich zum Nachweis von ZIKV-Kapsid in verschiedenen Lösungen, u. a. nativem ZIKV-Kapsid in Zellkulturüberstand, eingesetzt werden. Der so aufgebaute Antigen-ELISA erreichte, abhängig von der Kombination an Antikörper und Antigen, eine untere Nachweisgrenze zwischen 2 bis 345 ng/ml. Um zum Nachweis von ZIKV-Kapsid in humanem Serum eines ZIKV-infizierten Patienten eingesetzt werden zu können, müsste seine Sensitivität um etwa zwei bis drei Logstufen steigen. Möglichkeiten dazu wurden diskutiert.:1 Inhaltsverzeichnis 2 2 Abkürzungsverzeichnis 7 3 Einführung 10 4 Aufgabenstellung 47 5 Materialien und Methoden 49 6 Ergebnisse 97 7 Diskussion 131 8 Zusammenfassung 156 9 Literaturverzeichnis 158 10 Abbildungs- und Tabellenverzeichnis 182 11 Anlagen 18

Hydrodynamic simulation of the effects of stable in-channel large wood on the flood hydrographs of a low mountain range creek, Ore Mountains, Germany

Large wood (LW) can alter the hydromorphological and hydraulic characteristics of rivers and streams and may act positively on a river's ecology by i.e. leading to increased habitat availability. On the contrary, floating as well as stable LW is a potential threat for anthropogenic goods and infrastructure during flood events. Concerning the contradiction of potential risks and positive ecological impacts, addressing the physical effects of stable large wood is highly important. Hydrodynamic models offer the possibility of investigating the hydraulic effects of anchored large wood. However, the work and time involved varies between approaches that incorporate large wood in hydrodynamic models. In this study, a two-dimensional hydraulic model is set up for a mountain creek to simulate the hydraulic effects of stable LW and to compare multiple methods of accounting for LW-induced roughness. LW is implemented by changing in-channel roughness coefficients and by adding topographic elements to the model; this is carried out in order to determine which method most accurately simulates observed hydrographs and to provide guidance for future hydrodynamic modelling of stable large wood with two-dimensional models. The study area comprises a 282 m long reach of the Ullersdorfer Teichbächel, a creek in the Ore Mountains (south-eastern Germany). Discharge time series from field experiments allow for a validation of the model outputs with field observations with and without stable LW. We iterate in-channel roughness coefficients to best fit the mean simulated and observed flood hydrographs with and without LW at the downstream reach outlet. As an alternative approach for modelling LW-induced effects, we use simplified discrete topographic elements representing individual LW elements in the channel. In general, the simulations reveal a high goodness of fit between the observed flood hydrographs and the model results without and with stable in-channel LW. The best fit of the simulation and mean observed hydrograph with in-channel LW can be obtained when increasing in-channel roughness coefficients throughout the reach instead of an increase at LW positions only. The best fit in terms of the hydrograph's general shape can be achieved by integrating discrete elements into the calculation mesh. The results illustrate that the mean observed hydrograph can be satisfactorily modelled using an adjustment of roughness coefficients. In conclusion, a time-consuming and work-intensive mesh manipulation is suitable for analysing the more detailed effects of stable LW on a small spatio-temporal scale where high precision is required. In contrast, the reach-wise adjustment of in-channel roughness coefficients seems to provide similarly accurate results on the reach scale and, thus, could be helpful for practical applications of model-based impact assessments of stable LW on flood hydrographs of small streams and rivers

System Identification for Model Predictive Control of Building Region Temperature

Model predictive control (MPC) is a promising technology for energy cost optimization of buildings because it provides a natural framework for optimally controlling such systems by computing control actions that minimize the energy cost while meeting constraints. In our previous work, we developed a cascaded MPC framework capable of minimizing the energy cost of building zone temperature control applications. The outer loop MPC computes power set-points to minimize the energy cost while ensuring that the zone temperature is maintained within its comfort constraints. The inner loop MPC receives the power set-points from the outer loop MPC and manipulates the zone temperature set-point to ensure that the zone power consumption tracks the power set-points computed by the outer layer MPC. Since both MPCs require a predictive model, a modeling framework and system identification (SI) methodology must be developed that is capable of accurately predicting the energy usage and zone temperature for a diverse range of building zones. In this work, two grey-box models for the outer and inner loop MPCs are developed and parameterized. The model parameters are fit to input-output data for a particular zone application so that the resulting model accurately predicts the behavior of the zone. State and disturbance estimation, which is required by the MPCs, is performed via a Kalman filter with a steady-state Kalman gain. The model parameters and Kalman gains of each grey-box model are updated in a sequential fashion. The significant disturbances affecting the zone temperature (e.g., outside temperature and occupancy) may typically be considered as a slowly varying disturbance (with respect to the control time-scale). To prevent steady-state offset in the identified model caused by the slowly time-varying disturbance, a high-pass filter is applied to the input-output data to filter out the effect of the disturbance. The model parameters are subsequently computed from the filtered input-output data without the Kalman filter applied. The Kalman gain is also adjusted as the model parameters are updated to ensure stability of the resulting observer and for optimal estimation. After the model parameters are computed, the steady-state Kalman gain matrix is parameterized and the parameters are updated using the prediction error method with the unfiltered input-output data and the updated model parameters. The Kalman gain update methodology is advantageous because it avoids the need to estimate the noise statistics. Stability of the observer is verified after the parameters are updated. If the updated parameters result in an unstable observer, the update is rejected and the previous parameters are retained. Additionally, since a standard quadratic cost function that penalizes the squared prediction error is sensitive to data outliers in the prediction error method, a piecewise defined cost function is employed to reduce its sensitivity to outliers and to improve the robustness of the SI methodology. The cost function penalizes the squared prediction error when the error is within certain thresholds. When the error is outside the thresholds, the cost function evaluates to a constant. The SI algorithm is applied to a building zone to assess the approach

Autonomous Optimization and Control for Central Plants with Energy Storage

A model predictive control (MPC) framework is used to determine how to optimize the distribution of energy resources across a central energy facility including chillers, water heaters, and thermal energy storage; present the results to an operator; and execute the plan. The objective of this MPC framework is to minimize cost in real-time in response to both real-time energy prices and demand charges as well as allow the operator to appropriately interact with the system. Operators must be given the correct intersection points in order to build trust before they are willing to turn the tool over and put it into fully autonomous mode. Once in autonomous mode, operators need to be able to intervene and impute their knowledge of the facilities they are serving into the system without disengaging optimization. For example, an operator may be working on a central energy facility that serves a college campus on Friday night before a home football game. The optimization system is predicting the electrical load, but does not have knowledge of the football game. Rather than try to include every possible factor into the prediction of the loads, a daunting task, the optimization system empowers the operator to make human-in-the-loop decisions in these rare scenarios without exiting autonomous (auto) mode. Without this empowerment, the operator either takes the system out of auto mode or allows the system to make poor decisions. Both scenarios will result in an optimization system that has low “on time†and thus saves little money. A cascaded, model predictive control framework lends itself well to allowing an operator to intervene. The system presented is a four tiered approach to central plant optimization. The first tier is the prediction of the energy loads of the campus; i.e., the inputs to the optimization system. The predictions are made for a week in advance, giving the operator ample time to react to predictions they do not agree with and override the predictions if they feel it necessary. The predictions are inputs to the subplant-level optimization. The subplant-level optimization determines the optimal distribution of energy across major equipment classes (subplants and storage) for the prediction horizon and sends the current distribution to the equipment level optimization. The operators are able to use the subplant-level optimization for “advisory†only and enter their own load distribution into the equipment level optimization. This could be done if they feel that they need to be conservative with the charge of the tank. Finally, the equipment level optimization determines the devices to turn on and their setpoints in each subplant and sends those setpoints to the building automation system. These decisions can be overridden, but should be extremely rare as the system takes device availability, accumulated runtime, etc. as inputs. Building an optimization system that empowers the operator ensures that the campus owner realizes the full potential of his investment. Optimal plant control has shown over 10% savings, for large plants this can translate to savings of more than US $1 million per year

Model Predictive Control for Central Plant Optimization with Thermal Energy Storage

An optimization framework is used in order to determine how to distribute both hot and cold water loads across a central energy plant including heat pump chillers, conventional chillers, water heaters, and hot and cold water (thermal energy) storage. The objective of the optimization framework is to minimize cost in response to both real-time energy prices and demand charges. The linear programming framework used allows for the optimal solution to be found in real-time. Real-time optimization lead to two separate applications: A planning tool and a real-time optimization tool. In the planning tool the optimization is performed repeatedly with a sliding horizon accepting a subset of the optimized distribution trajectory horizon as each subsequent optimization problem is solved. This is the same strategy as model predictive control except that in the design and planning tool the optimization is working on a given set of loads, weather (e.g. TMY data), and real-time pricing data and does not need to predict these values. By choosing the varying lengths of the horizon (2 to 10 days) and size of the accepted subset (1 to 24 hours), the design and planning tool can be used to find the design year’s optimal distribution trajectory in less than 5 minutes for interactive plant design, or the design and planning tool can perform a high fidelity run in a few hours. The fast solution times also allow for the optimization framework to be used in real-time to optimize the load distribution of an operational central plant using a desktop computer or microcontroller in an onsite Enterprise controller. In the real-time optimization tool Model Predictive Control is used; estimation, prediction, and optimization are performed to find the optimal distribution of loads for duration of the horizon in the presence of disturbances. The first distribution trajectory in the horizon is then applied to the central energy plant and the estimation, prediction, and optimization is repeated in 15 minutes using new plant telemetry and forecasts. Prediction is performed using a deterministic plus stochastic model where the deterministic portion of the model is a simplified system representing the load of all buildings connected to the central energy plant and the stochastic model is used to respond to disturbances in the load. The deterministic system uses forecasted weather, time of day, and day type in order to determine a predicted load. The estimator uses past data to determine the current state of the stochastic model; the current state is then projected forward and added to the deterministic system’s projection. In simulation, the system has demonstrated more than 10% savings over other schedule based control trajectories even when the subplants are assumed to be running optimally in both cases (i.e., optimal chiller staging, etc.). For large plants this can mean savings of more than US $1 million per year

Microbiological Factors Influencing the Outcome of Nosocomial Bloodstream Infections: A 6-Year Validated, Population-Based Model

All patients (n = 1,745) with nosocomial bloodstream infection identified between 1986 and 1991 at a single 900-bed tertiary care hospital were studied to identify microbiological factors independently associated with mortality due to the infection. Patients were identified by prospective, case-based surveillance and positive blood cultures. Mortality rates were examined for secular trends. Prognostic factors were determined with use of univariate and multivariate analyses, and both derivation and validation sets were used. A total of 1,745 patients developed nosocomial bloodstream infection. The 28-day crude mortality was 22%, and crude in-hospital mortality was 35%. Factors independently (all P < .05) associated with increased 28-day mortality rates were older age, longer length of hospital stay before bloodstream infection, and a diagnosis of cancer or disease of the digestive system. After adjustment for major confounders, Candida species were the only organisms independently influencing the outcome of nosocomial bloodstream infection (odds ratio [OR] for mortality = 1.84; 95% confidence interval [CI], 1.22-2.76; P = .0035). The two additional microbiological factors independently associated with increased mortality were pneumonia as a source of secondary infection (OR = 2.74; 95% CI, 1.87-4.00; P < .0001) and polymicrobial infection (OR = 1.68; 95% CI, 1.22-2.32; P = .0014). Our data suggest that microbiological factors independently affect the outcome of nosocomial bloodstream infectio