Implementing A Balanced Scorecard In A Not-For-Profit Organization

This paper examines the use of the Balanced Scorecard in a not-for-profit organization (Cattaraugus County ReHabilitation Center).  The ReHabilitation Center has begun using the Balanced Scorecard paradigm in its strategic planning process.  In this paper an overview is presented of the basic concepts of the Balanced Scorecard including the financial perspective, customer perspective, internal process perspective, and learning and growth perspective.  The history and services of the ReHabilitation Center are then summarized.  The application of the Balanced Scorecard approach to the ReHabilitation Center is discussed in detail.  Implications in using the Balanced Scorecard are discussed.  Finally, conclusions regarding the use of the Balanced Scorecard in a not-for-profit organization are presented

Implementing A Balanced Scorecard In A Not-For-Profit Organization

This paper examines the use of the Balanced Scorecard in a not-for-profit organization (Cattaraugus County ReHabilitation Center).  The ReHabilitation Center has begun using the Balanced Scorecard paradigm in its strategic planning process.  In this paper an overview is presented of the basic concepts of the Balanced Scorecard including the financial perspective, customer perspective, internal process perspective, and learning and growth perspective.  The history and services of the ReHabilitation Center are then summarized.  The application of the Balanced Scorecard approach to the ReHabilitation Center is discussed in detail.  Implications in using the Balanced Scorecard are discussed.  Finally, conclusions regarding the use of the Balanced Scorecard in a not-for-profit organization are presented

Crack Resistant Concrete Material for Transportation Construction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84828/1/Li_TRB2004.pd

Simple Determination of Affinity Constants of Antibodies by Competitive Immunoassays

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (Kd), can be considered as one of the most important characteristics for any antibody–antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise and effort that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC50 approaches the Kd value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to Kd. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.This research received no external funding.Peer Reviewe

Shotcreting with ECC

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84822/1/Li_Fischer_Lepech_Shotcreting.pd

Far Infrared and Submillimeter Emission from Galactic and Extragalactic Photo-Dissociation Regions

Photodissociation Region (PDR) models are computed over a wide range of physical conditions, from those appropriate to giant molecular clouds illuminated by the interstellar radiation field to the conditions experienced by circumstellar disks very close to hot massive stars. These models use the most up-to-date values of atomic and molecular data, the most current chemical rate coefficients, and the newest grain photoelectric heating rates which include treatments of small grains and large molecules. In addition, we examine the effects of metallicity and cloud extinction on the predicted line intensities. Results are presented for PDR models with densities over the range n=10^1-10^7 cm^-3 and for incident far-ultraviolet radiation fields over the range G_0=10^-0.5-10^6.5, for metallicities Z=1 and 0.1 times the local Galactic value, and for a range of PDR cloud sizes. We present line strength and/or line ratio plots for a variety of useful PDR diagnostics: [C II] 158 micron, [O I] 63 and 145 micron, [C I] 370 and 609 micron, CO J=1-0, J=2-1, J=3-2, J=6-5 and J=15-14, as well as the strength of the far-infrared continuum. These plots will be useful for the interpretation of Galactic and extragalactic far infrared and submillimeter spectra observable with ISO, SOFIA, SWAS, FIRST and other orbital and suborbital platforms. As examples, we apply our results to ISO and ground based observations of M82, NGC 278, and the Large Magellenic Cloud.Comment: 54 pages, 20 figures, accepted for publication in The Astrophysical Journa

VPRTempo: A Fast Temporally Encoded Spiking Neural Network for Visual Place Recognition

Spiking Neural Networks (SNNs) are at the forefront of neuromorphic computing thanks to their potential energy-efficiency, low latencies, and capacity for continual learning. While these capabilities are well suited for robotics tasks, SNNs have seen limited adaptation in this field thus far. This work introduces a SNN for Visual Place Recognition (VPR) that is both trainable within minutes and queryable in milliseconds, making it well suited for deployment on compute-constrained robotic systems. Our proposed system, VPRTempo, overcomes slow training and inference times using an abstracted SNN that trades biological realism for efficiency. VPRTempo employs a temporal code that determines the timing of a single spike based on a pixel's intensity, as opposed to prior SNNs relying on rate coding that determined the number of spikes; improving spike efficiency by over 100%. VPRTempo is trained using Spike-Timing Dependent Plasticity and a supervised delta learning rule enforcing that each output spiking neuron responds to just a single place. We evaluate our system on the Nordland and Oxford RobotCar benchmark localization datasets, which include up to 27k places. We found that VPRTempo's accuracy is comparable to prior SNNs and the popular NetVLAD place recognition algorithm, while being several orders of magnitude faster and suitable for real-time deployment -- with inference speeds over 50 Hz on CPU. VPRTempo could be integrated as a loop closure component for online SLAM on resource-constrained systems such as space and underwater robots.Comment: 8 pages, 3 figures, accepted to the IEEE International Conference on Robotics and Automation (ICRA) 202

Mean-field expansion in Bose-Einstein condensates with finite-range interactions

We present a formal derivation of the mean-field expansion for dilute Bose-Einstein condensates with two-particle interaction potentials which are weak and finite-range, but otherwise arbitrary. The expansion allows for a controlled investigation of the impact of microscopic interaction details (e.g., the scaling behavior) on the mean-field approach and the induced higher-order corrections beyond the s-wave scattering approximation.Comment: 6 pages of RevTex4; extended discussion, added reference

Preparing Medical Students to Be Physician Leaders: A Leadership Training Program for Students Designed and Led by Students

Introduction: Leadership is an area of education and training that is critical to the development of medical providers as health care professionals, yet few medical school curricula offer formal training in this area. Methods: We designed and implemented a course to develop and enhance the leadership and teamwork skills of first-year medical students to better prepare them for medical practice. Following a systematic literature review to identify leadership core competencies, the Leadership in Medicine Optional Enrichment Elective (OEE) was developed in accordance with the University of Massachusetts Medical School’s course guidelines. The elective included six interactive sessions to advance skills in the areas of recognizing and utilizing effective leadership styles, communication within the health care team, giving and receiving feedback, delegating responsibilities, and direction setting. We designed a robust, evidence-based, scholarly evaluation plan for the OEE that was integral to ongoing quality improvement of the course. Results: Outcomes were assessed in alignment with the Kirkpatrick method of standardized evaluation. A total of 26 participants completed the course. At completion, participants demonstrated learning and advancement of skills in all five leadership domains. Furthermore, participants found meaning in the course and planned to utilize their skills in future medical practice. Discussion: The development, implementation, and evaluation of this program can serve as a model for future course development, and the program can be adapted and implemented by other institutions in an effort to address the learning gap regarding leadership education