Girls as Thriving Leaders: Cultivating a Community of True Belonging in an All-Girls School

In an all-girls school, what conditions are required to authentically cultivate a community of true belonging? This inquiry explores what girls need in schools today to support each other now and as women. This Organization Improvement Plan is developed for an all-girls Canadian independent school. Challenges in maintaining true belonging stem from the systemic, patriarchal structure of education. This gap creates a culture of scarcity and competition, which leads to intragender microaggression. To implement change in this organization as an informal leader and teacher, I use a participatory-based approach that aligns with the feminist-transformative theoretical lens. The ethic of community and ethic of critique frameworks ensure that this inquiry goes beyond the narrative of the neoliberal definition of girlhood. To address this challenge, a skillset of competence, mindset of confidence, and heartset of connectedness must be present and continually developed as indicators of true belonging in all-girls schools today. I developed a conceptual model for leading, teaching, and learning to guide a multi-layered leadership practice in our learning community in order for true belonging to be possible. As a leader, my actions align with transformative, inclusive, and connective leadership styles. The chosen solution addresses true belonging by offering an interdisciplinary program that aligns with the conceptual model. This solution uses an iterative, cyclical framework for organizational development, with an emphasis on appreciative inquiry for positive change. The plans for implementation, monitoring and evaluation, and communication ensure active participation, opportunity for voice and choice, and reflection through generative dialogue

The Need for Due Diligence and Financial Statement Analysis – The Bank of America-Merrill Lynch Case

Mr. Ken Lewis, Chief Executive of Bank of America (BOA), was harshly questioned regarding BOA’s acquisition of Merrill Lynch. This was driven by an earnings release on January 16, 2009 indicating Bank of America had massive losses for the 4th quarter of 2008 due to the Merrill Lynch acquisition. Bank of America’s stock fell to $7.18, its lowest level in 17 years following the release of the earnings announcement. Complicating the matter was that the market capitalization of Bank of America, including Merrill Lynch, was just$45 billion, and Bank of American had offered $50 billion to acquire Merrill. These events led both insiders and outsiders to question the acquisition. What due diligence should have been completed and were there were relevant accounting policies and valuation issues of concern? In this case, students are placed in a decision-making role to provide a financial analysis considering different options and assessing the benefits and detriments of the acquisition. It provides students an opportunity to apply acquisition principles in a real-life setting

Transaction Complexity and the Movement to Fair Value Accounting

Our global economy has pushed the complexity of business transactions to a new level, as companies now employ sophisticated contracts and financial instruments. However, it is unclear whether accounting standards are able to effectively capture transaction complexity, which has been growing at a rapid pace. In this study, we examine three questions related to transaction complexity: (1) Do accounting standards reflect differences in the complexity of the transactions being recorded? (2) Does the use of mark-to-market (i.e., fair value) accounting reduce the complexity of standards by relying on market valuations to capture transaction complexity? (3) Does the reliance on fair value measurements reduce audit costs for transactions with significant complexity? Our findings suggest that complex transactions result in complex accounting guidance, making the standards difficult to read and understand. However, the use of fair value accounting might be a solution to the challenges arising from transaction complexity. Our study informs regulatory bodies, investors, creditors, and public companies that are increasingly concerned about the state of financial reporting standards, which arguably have become very costly to implement yet less effective in communicating the economic substance of complex transactions

Option compensation and optimism bias in management earnings forecasts

We examine the link between the managers' option compensation and the optimism bias in management earnings forecasts. More particularly, we are interested in investigating the extent of self-serving optimism in the earnings forecasts made by managers with a high amount of option compensation. We hypothesize that managements' optimism (optimism bias in their earnings forecasts) increases with an increase in their stock option compensation. We provide evidence that managers issue optimistic forecasts since their compensation is a function of the stock price, and optimistic earnings forecasts usually result in a higher share price

An investigation to infer social welfare implications from the market reactions to SFAS no. 52

Includes bibliographical references (p. 14-15)

A pedestrian path-planning model in accordance with obstacle's danger with reinforcement learning

Most microscopic pedestrian navigation models use the concept of "forces" applied to the pedestrian agents to replicate the navigation environment. While the approach could provide believable results in regular situations, it does not always resemble natural pedestrian navigation behaviour in many typical settings. In our research, we proposed a novel approach using reinforcement learning for simulation of pedestrian agent path planning and collision avoidance problem. The primary focus of this approach is using human perception of the environment and danger awareness of interferences. The implementation of our model has shown that the path planned by the agent shares many similarities with a human pedestrian in several aspects such as following common walking conventions and human behaviours

A Remote Health Coaching, Text-Based Walking Program in Ethnic Minority Primary Care Patients With Overweight and Obesity: Feasibility and Acceptability Pilot Study

BACKGROUND: Over half of US adults have at least one chronic disease, including obesity. Although physical activity is an important component of chronic disease self-management, few reach the recommended physical activity goals. Individuals who identify as racial and ethnic minorities are disproportionally affected by chronic diseases and physical inactivity. Interventions using consumer-based wearable devices have shown promise for increasing physical activity among patients with chronic diseases; however, populations with the most to gain, such as minorities, have been poorly represented to date. OBJECTIVE: This study aims to assess the feasibility, acceptability, and preliminary outcomes of an 8-week text-based coaching and Fitbit program aimed at increasing the number of steps in a predominantly overweight ethnic minority population. METHODS: Overweight patients (BMI \u3e 25 kg/m(2)) were recruited from an internal medicine clinic located in an inner-city academic medical center. Fitbit devices were provided. Using 2-way SMS text messaging, health coaches (HCs) guided patients to establish weekly step goals that were specific, measurable, attainable, realistic, and time-bound. SMS text messaging and Fitbit activities were managed using a custom-designed app. Program feasibility was assessed via the recruitment rate, retention rate (the proportion of eligible participants completing the 8-week program), and patient engagement (based on the number of weekly text message goals set with the HC across the 8-week period). Acceptability was assessed using a qualitative, summative evaluation. Exploratory statistical analysis included evaluating the average weekly steps in week 1 compared with week 8 using a paired t test (2-tailed) and modeling daily steps over time using a linear mixed model. RESULTS: Of the 33 patients initially screened; 30 (91%) patients were enrolled in the study. At baseline, the average BMI was 39.3 (SD 9.3) kg/m(2), with 70% (23/33) of participants presenting as obese. A total of 30% (9/30) of participants self-rated their health as either fair or poor, and 73% (22/30) of participants set up \u3e /=6 weekly goals across the 8-week program. In total, 93% (28/30) of participants completed a qualitative summative evaluation, and 10 themes emerged from the evaluation: patient motivation, convenient SMS text messaging experience, social support, supportive accountability, technology support, self-determined goals, achievable goals, feedback from Fitbit, challenges, and habit formation. There was no significant group change in the average weekly steps for week 1 compared with week 8 (mean difference 7.26, SD 6209.3; P=.99). However, 17% (5/30) of participants showed a significant increase in their daily steps. CONCLUSIONS: Overall, the results demonstrate the feasibility and acceptability of a remotely delivered walking study that included an HC; SMS text messaging; a wearable device (Fitbit); and specific, measurable, attainable, realistic, and time-bound goals within an ethnic minority patient population. Results support further development and testing in larger samples to explore efficacy

Probabilistic movement modeling for intention inference in human-robot interaction.

Intention inference can be an essential step toward efficient humanrobot interaction. For this purpose, we propose the Intention-Driven Dynamics Model (IDDM) to probabilistically model the generative process of movements that are directed by the intention. The IDDM allows to infer the intention from observed movements using Bayes ’ theorem. The IDDM simultaneously finds a latent state representation of noisy and highdimensional observations, and models the intention-driven dynamics in the latent states. As most robotics applications are subject to real-time constraints, we develop an efficient online algorithm that allows for real-time intention inference. Two human-robot interaction scenarios, i.e., target prediction for robot table tennis and action recognition for interactive humanoid robots, are used to evaluate the performance of our inference algorithm. In both intention inference tasks, the proposed algorithm achieves substantial improvements over support vector machines and Gaussian processes.

Levosimendan increases brain tissue oxygen levels after cardiopulmonary resuscitation independent of cardiac function and cerebral perfusion

Prompt reperfusion is important to rescue ischemic tissue; however, the process itself presents a key pathomechanism that contributes to a poor outcome following cardiac arrest. Experimental data have suggested the use of levosimendan to limit ischemia–reperfusion injury by improving cerebral microcirculation. However, recent studies have questioned this effect. The present study aimed to investigate the influence on hemodynamic parameters, cerebral perfusion and oxygenation following cardiac arrest by ventricular fibrillation in juvenile male pigs. Following the return of spontaneous circulation (ROSC), animals were randomly assigned to levosimendan (12 µg/kg, followed by 0.3 µg/kg/min) or vehicle treatment for 6 h. Levosimendan-treated animals showed significantly higher brain PbtO(2) levels. This effect was not accompanied by changes in cardiac output, preload and afterload, arterial blood pressure, or cerebral microcirculation indicating a local effect. Cerebral oxygenation is key to minimizing damage, and thus, current concepts are aimed at improving impaired cardiac output or cerebral perfusion. In the present study, we showed that NIRS does not reliably detect low PbtO(2) levels and that levosimendan increases brain oxygen content. Thus, levosimendan may present a promising therapeutic approach to rescue brain tissue at risk following cardiac arrest or ischemic events such as stroke or traumatic brain injury