iLeadership: the leadership style of Steve Jobs

In a technology-driven society, the global hunger for innovative products has put increased pressure on organizations to think differently. The pressure from shareholders on management to drive innovation and deliver financial results has forced leaders to adapt and look for new solutions to meet this demand. The solutions for which organizations are searching may reside in a new form of leadership required to achieve this expectation of performance. The purpose of this dissertation was to discover what leadership characteristics are required to achieve a high-performance technology organization. The primary goal was to review and decode archival scholarly and contemporary literature to understand the key elements of effective leadership in modern leadership theory. After establishing a general understanding of leadership, the next goal was to learn the main characteristics that comprise transformational leadership. The next focus was to review a variety of secondary sources to provide insight into the leadership of Steve Jobs: a leader with a proven track record for driving profitable technology innovation. This dissertation then looked to discover the main components of Jobs\u27 leadership style. After an extensive leadership theory review to create a baseline of understanding of effective leader concepts, the study examined the leadership style of a dynamic and influential leader in history, Steve Jobs. This study then explored the significance of a new leadership model for other technology based organizations to develop their leaders to stimulate profitable growth and innovation

Dolly B. Davis Hoover: Pioneer Black Librarian

On November 26, 2000, friends and colleagues gathered at Saint Stephens Episcopal Church to honor the memory of Dolly B. Davis Hoover, the first African American faculty member at Indiana State University. The newspaper accounts of this occasion make note of her contribution to diversification and her role as a librarian at the university. As Charles Chillington eulogized “she opened ways that were not opened to most of us here.” These accounts, however, only offer a mere palimpsest of her remarkable career, a career which should be acknowledged in annals of Black Librarianship. The accomplishments of Dolly B. Davis Hoover are remarkable given the context of the time when she embarked upon the career of professional librarian in 1945

Place: The Cunningham Memorial Library of Indiana State University

When one thinks of a library, often the first image that comes to mind is a brick or stone building. However, one should also remember that a library is a gathering place. Within its walls are carefully gathered or collected resources, whether electronic, print, or sound. Beyond such artifacts, the library is moreover a gathering place for people, be it library faculty and staff, or the patrons which they serve. It is a place for people to work, investigate, socialize, or repose. Indiana State University’s Cunningham Memorial Library (CML) embodies both these concepts. Yes, it is a physical structure, but even more so it is a gathering place. What follows is an exposition of the library’s rich history, its buildings, its collections, and the means through which it gathers people into its fold – library faculty, staff, and patron alike

Algebra in Computational Complexity

At its core, much of Computational Complexity is concerned with combinatorial objects and structures. But it has often proven true that the best way to prove things about these combinatorial objects is by establishing a connection to a more well-behaved algebraic setting. Indeed, many of the deepest and most powerful results in Computational Complexity rely on algebraic proof techniques. The Razborov-Smolensky polynomial-approximation method for proving constant-depth circuit lower bounds, the PCP characterization of NP, and the Agrawal-Kayal-Saxena polynomial-time primality test are some of the most prominent examples. The algebraic theme continues in some of the most exciting recent progress in computational complexity. There have been significant recent advances in algebraic circuit lower bounds, and the so-called "chasm at depth 4" suggests that the restricted models now being considered are not so far from ones that would lead to a general result. There have been similar successes concerning the related problems of polynomial identity testing and circuit reconstruction in the algebraic model, and these are tied to central questions regarding the power of randomness in computation. Representation theory has emerged as an important tool in three separate lines of work: the "Geometric Complexity Theory" approach to P vs. NP and circuit lower bounds, the effort to resolve the complexity of matrix multiplication, and a framework for constructing locally testable codes. Coding theory has seen several algebraic innovations in recent years, including multiplicity codes, and new lower bounds. This seminar brought together researchers who are using a diverse array of algebraic methods in a variety of settings. It plays an important role in educating a diverse community about the latest new techniques, spurring further progress

Algebraic and Combinatorial Methods in Computational Complexity

Computational Complexity is concerned with the resources that are required for algorithms to detect properties of combinatorial objects and structures. It has often proven true that the best way to argue about these combinatorial objects is by establishing a connection (perhaps approximate) to a more well-behaved algebraic setting. Indeed, many of the deepest and most powerful results in Computational Complexity rely on algebraic proof techniques. The Razborov-Smolensky polynomial-approximation method for proving constant-depth circuit lower bounds, the PCP characterization of NP, and the Agrawal-Kayal-Saxena polynomial-time primality test are some of the most prominent examples. The algebraic theme continues in some of the most exciting recent progress in computational complexity. There have been significant recent advances in algebraic circuit lower bounds, and the so-called chasm at depth 4 suggests that the restricted models now being considered are not so far from ones that would lead to a general result. There have been similar successes concerning the related problems of polynomial identity testing and circuit reconstruction in the algebraic model (and these are tied to central questions regarding the power of randomness in computation). Another surprising connection is that the algebraic techniques invented to show lower bounds now prove useful to develop efficient algorithms. For example, Williams showed how to use the polynomial method to obtain faster all-pair-shortest-path algorithms. This emphases once again the central role of algebra in computer science. The seminar aims to capitalize on recent progress and bring together researchers who are using a diverse array of algebraic methods in a variety of settings. Researchers in these areas are relying on ever more sophisticated and specialized mathematics and this seminar can play an important role in educating a diverse community about the latest new techniques, spurring further progress

Algebraic Methods in Computational Complexity

Computational Complexity is concerned with the resources that are required for algorithms to detect properties of combinatorial objects and structures. It has often proven true that the best way to argue about these combinatorial objects is by establishing a connection (perhaps approximate) to a more well-behaved algebraic setting. Indeed, many of the deepest and most powerful results in Computational Complexity rely on algebraic proof techniques. The Razborov-Smolensky polynomial-approximation method for proving constant-depth circuit lower bounds, the PCP characterization of NP, and the Agrawal-Kayal-Saxena polynomial-time primality test are some of the most prominent examples. In some of the most exciting recent progress in Computational Complexity the algebraic theme still plays a central role. There have been significant recent advances in algebraic circuit lower bounds, and the so-called chasm at depth 4 suggests that the restricted models now being considered are not so far from ones that would lead to a general result. There have been similar successes concerning the related problems of polynomial identity testing and circuit reconstruction in the algebraic model (and these are tied to central questions regarding the power of randomness in computation). Also the areas of derandomization and coding theory have experimented important advances. The seminar aimed to capitalize on recent progress and bring together researchers who are using a diverse array of algebraic methods in a variety of settings. Researchers in these areas are relying on ever more sophisticated and specialized mathematics and the goal of the seminar was to play an important role in educating a diverse community about the latest new techniques

Sentinel lymph node biopsy for breast cancer using methylene blue dye manifests a short learning curve among experienced surgeons: a prospective tabular cumulative sum (CUSUM) analysis

<p>Abstract</p> <p>Background</p> <p>The benefits of sentinel lymph node biopsy (SLNB) for breast cancer patients with histologically negative axillary nodes, in whom axillary lymph node dissection (ALND) is thereby avoided, are now established. Low false negative rate, certainly with blue dye technique, mostly reflects the established high inherent accuracy of SLNB and low axillary nodal metastatic load (subject to patient selection). SLN identification rate is influenced by volume, injection site and choice of mapping agent, axillary nodal metastatic load, SLN location and skill at axillary dissection. Being more subject to technical failure, SLN identification seems to be a more reasonable variable for learning curve assessment than false negative rate.</p> <p>Methylene blue is as good an SLN mapping agent as Isosulfan blue and is much cheaper. Addition of radio-colloid mapping to blue dye does not achieve a sufficiently higher identification rate to justify the cost. Methylene blue is therefore the agent of choice for SLN mapping in developing countries.</p> <p>The American Society of Breast Surgeons recommends that, for competence, surgeons should perform 20 SLNB but admits that the learning curve with a standardized technique may be "much shorter". One appropriate remedy for this dilemma is to plot individual learning curves.</p> <p>Methods</p> <p>Using methylene blue dye, experienced breast surgeons performed SLNB in selected patients with breast cancer (primary tumor < 5 cm and clinically negative ipsilateral axilla). Intraoperative assessment and completion ALND were performed for standardization on the first 13 of 24 cases. SLN identification was plotted for each surgeon on a tabular cumulative sum (CUSUM) chart with sequential probability ratio test (SPRT) limits based on a target identification rate of 85%.</p> <p>Results</p> <p>The CUSUM plot crossed the SPRT limit line after 8 consecutive, positively identified SLN, signaling achievement of an acceptable level of competence.</p> <p>Conclusion</p> <p>Tabular CUSUM charting, based on a justified choice of parameters, indicates that the learning curve for SLNB using methylene blue dye is completed after 8 consecutive, positively identified SLN. CUSUM charting may be used to plot individual learning curves for trainee surgeons by applying a proxy parameter for failure in the presence of a mentor (such as failed SLN identification within 15 minutes).</p

Paper-Based Electrochemical Sensors Using Paper as a Scaffold to Create Porous Carbon Nanotube Electrodes.

Paper-based sensors and assays have evolved rapidly due to the conversion of paper-based microfluidics, functional paper coatings, and new electrical and optical readout techniques. Nanomaterials have gained substantial attraction as key components in paper-based sensors, as they can be coated or printed relatively easily on paper to locally control the device functionality. Here, we report a new combination of methods to fabricate carbon nanotube-based (CNT) electrodes for paper-based electrochemical sensors using a combination of laser cutting, drop-casting, and origami. We applied this process to a range of filter papers with different porosities and used their differences in three-dimensional cellulose networks to study the influence of the cellulose scaffold on the final CNT network and the resulting electrochemical detection of glucose. We found that an optimal porosity exists, which balances the benefits of surface enhancement and electrical connectivity within the cellulose scaffold of the paper-based device and demonstrates a cost-effective process for the fabrication of device arrays