48670 research outputs found
Sort by
How Leaders Develop Collaborative Leadership for Effectiveness
No full textLeader emergence research indicates that organizations select leaders based on individualistic traits such as confidence, intelligence, and dominance. However, once in the role, leadership effectiveness research states that leaders are evaluated based on their ability to build strong relationships and to accomplish goals through other people. Increasingly, they must collaborate with people who may not report directly to them. Unfortunately, the qualities used to identify emerging leaders such as, confidence, intelligence, and dominance, are not necessarily the skills and qualities needed to build strong relationships and manage multiple collaborations. Few research studies have looked at how leaders collaborate or how they learn the skills necessary to collaborate effectively. This research study used qualitative interviews with board members, CEOs, C-Suite leaders, and mid-level managers who currently work in for-profit companies in the United States. Interviews sought to learn the leaders\u27 observations and experiences regarding how they collaborate and how they learned their collaboration skills. This research study found that all participants had key collaborations as a part of their role and that 91% of participants felt those collaborations were an essential or important part of their job. Despite how important this aspect of leadership is, the most common ways that participants learned how to collaborate came from trial and error or childhood experiences. The skills associated with effective collaboration include maintaining focus on a goal, understanding other’s motives, listening, building trust through honest conversations, humbly being willing to learn, and encouraging diversity of thought. Leaders can recruit others by understanding their motives and aligning those motivations to a mutually beneficial goal. Further research is needed to develop training for leaders in gaining collaborative skills
Investigations of Pincer Iridium Complexes for Glycerol Deoxygenation and for Alkane Dehydrogenation
No full textGreen chemistry is being paid increased attention with the growing awareness of the environmental impact of the chemical industry. Catalysis is important in the development of green processes as it reduces the waste that is generated and lowers the energy required. Abundant feedstocks such as natural gas or biomass can be catalytically converted to value-added chemicals. Catalysts are employed in a wide range of applications, and innovations in green catalysis are crucial to achieve sustainability. To reduce the dependency on the unsustainable petroleum feedstock, biodiesel has been recognized as an effective, sustainable alternative. During biodiesel production, by-product glycerol is generated in a large amount. Catalyst development for the deoxygenation of low-cost glycerol to value-added 1,3-propanediol is discussed in Chapter 2. Alkane dehydrogenation to olefin is energy-intensive due to the endothermic nature of the reaction. A selective, energy-efficient catalyst is essential for sustainability. Immobilization of a homogeneous catalysts on heterogeneous supports can provide active, selective catalysts with robustness and recyclability. The immobilization enables the implementation of gas-phase continuous-flow reaction design. In the flow system, the by-product H2 can be effectively removed to achieve higher TON. Chapter 3 demonstrates catalytic dehydrogenation and hydrogenation reactions by an immobilized (POCOP)Ir complex on silica. Since homogeneous (Phebox)Ir and (CCC)Ir complexes have been demonstrated to activate C-H bonds, immobilization of those complexes on silica were attempted. The synthesis of Phebox and CCC ligands with functional groups to allow immobilization to silica are outlined in Chapter 4
Like a Snake in Difficult Mountains: A Historical and Archaeological Analysis of the Character and Origin of the Iron Age Kingdom of Muṣaṣir
No full textSmall polities of marginal borderland regions in the Near East were often pushed and pulled by their far larger neighbors’ political and economic spheres, forced to adapt to their social and environmental situation to thrive and maintain independence. The kingdom of Muṣaṣir, the home to the chief Urartian deity, Ḫaldi, lay in one of these frontier zones in the rugged mountains of northeast Iraq. Despite the significance of the kingdom’s temple for the Urartian kings’ religious ideology, the steep peaks and narrow flatlands of Muṣaṣir’s environs were ill-suited to substantial occupation. In order to locate Muṣaṣir and better understand the settlement behaviors of ancient occupation in the Sidekan subdistrict of Erbil, Iraq, the Rowanduz Archaeological Program (RAP) commenced a series of excavations and a survey in 2013. Excavation of the rural homestead of Gund-i Topzawa provided a dataset to investigate the reasons for settlement in this marginal environment. Synchronizing archaeological data to the Middle Iron Age (1050–550 BCE) Neo-Assyrian campaign texts and illustrations led to broader research questions exploring the factors driving the region’s chronologically limited sedentary occupation and the impact coopting a religious system has on the local polity and its appropriators. This study publishes the ceramic typology, stratigraphic, and architectural findings from the excavations of Gund-i Topzawa and Sidekan Bank, as well as the collected pottery and occupation qualities of surveyed sites in the Sidekan subdistrict (2014–2016). The pottery sequence, structural characteristics, and settlement patterns added to the understanding of the chronological sequence of the northern Zagros Mountains and further confirmed the locational specificity of Muṣaṣir with the Ḫaldi temple’s likely location at Mudjesir. Modeling the Iron Age populace’s ecological adaptations to environmental, social, and political stimuli indicate the interaction of cultural and technology factors first spurred Sidekan’s sedentary occupation in the Late Bronze Age, and the later cooption of Ḫaldi by the Urartian kings led to the area’s subsequent stagnation and contraction as the god’s appropriators declined
The Upstream Sources of Bias: Investigating Theory, Design, and Methods Shaping Adaptive Learning Systems
No full textAdaptive systems in education need to ensure population validity to meet the needs of all students for an equitable outcome. Recent research highlights how these systems encode societal biases leading to discriminatory behaviors towards specific student subpopulations. However, the focus has mostly been on investigating bias in predictive modeling, particularly its downstream stages like model development and evaluation. My dissertation work hypothesizes that the upstream sources (i.e., theory, design, training data collection method) in the development of adaptive systems also contribute to the bias in these systems, highlighting the need for a nuanced approach to conducting fairness research. By empirically analyzing student data previously collected from various virtual learning environments, I investigate demographic disparities in three cases representative of the aspects that shape technological advancements in education: 1) non-conformance of data to a widely-accepted theoretical model of emotion, 2) differing implications of technology design on student outcomes, and 3) varying effectiveness of methodological improvements in annotated data collection. In doing so, I challenge implicit assumptions of generalizability in theory, design, and methods and provide an evidence-based commentary on future research and design practices in adaptive and artificially intelligent educational systems surrounding how we consider diversity in our investigations
Essays on College Investment and Income Inequality
No full textThis dissertation consists of two chapters studying the importance of household income for shaping student outcomes in the market for higher education in the United States. The first chapter uses the High School Longitudinal Study of 2009 to document that conditional on student ability, high-income students are more likely to enroll in college and are more likely to attend a highly selective college conditional on enrolling. These gaps are mostly explained by differences in application rates and in enrollment rates conditional on being admitted, rather than differences in admission rates. While students generally prefer to attend the most selective college they are accepted to, low-income students are less likely to attend their preferred college due to costs. These findings suggest that financial aid provided by colleges is generally insufficient in closing enrollment gaps, and that the observed application gaps may be rational: low-income students will choose not to apply if doing so is costly and they do not expect to receive sufficient aid if admitted. Motivated by the empirical findings of the first chapter, the second chapter builds and estimates an equilibrium model of the U.S. college market featuring tuition discrimination and a decentralized admissions system. Students who differ in their financial resources and innate ability apply to a subset of colleges and are uncertain about their prospective admissions and financial aid. Colleges observe a noisy signal of student ability and compete by choosing admissions standards and tuition schedules. According to the estimated model, differences in application rates between high- and low-income students, conditional on ability, are due to student expectations over admissions and financial aid, which are consistent with college policies in equilibrium. Low-income students receive generous financial aid at selective colleges because only the highest-ability among them apply, making their signals highly informative. If signals became less informative (e.g., colleges stopped using the SAT), all high-ability students would be worse off and only high-income, low-ability students would modestly benefit. Finally, the model suggests that increasing federal need-based financial aid greatly benefits low-income, high-ability students by alleviating credit constraints
Probing the Dark Universe from Galactic to Cosmological Scales
No full textAstronomical observations strongly suggest that the universe is mostly dark. Its two dominant components, dark energy and dark matter, remain among the most mysterious concepts in cosmology today. The effects of these two substances are imprinted in the remaining few percent of the universe that consists of normal (baryonic) matter. Dark energy is responsible for the accelerating expansion of the universe and the existence of dark matter is deduced from the orbital properties of stars in galaxies. This thesis probes the observable effects of both these phenomena. The first part is about Baryon Acoustic Oscillations (BAO) by which we can measure the expansion rate of the universe and constrain dark energy. The second part focuses on ways to probe the nature of dark matter by studying the dynamics of galaxies and the orbital properties of their stars. The third and final part of this thesis discusses Optimal Transport (OT) theory, which unites the BAO and the Galactic Dynamics parts. The results of this thesis would develop novel ways to place stronger constraints on cosmology and dark energy; while also revealing the distribution of dark matter in galaxies, thus constraining dark matter\u27s properties
Biglycan Regulation of Regional Tendon Development Via the Pericellular Matrix
No full textTendons are a unique orthopaedic tissue that rely on a highly ordered tissue matrix for proper function. Tendon disease degrades this matrix order, causing deviations in resident cell behavior that result in decreased tissue function. Treatments for tendon disease remain ineffective due to a knowledge gap in the factors most vital for maintaining tendon health. Many matrix molecules help regulate tendon growth and maintenance, including biglycan and collagen VI. These molecules are attributed to the pericellular matrix, a critical matrix structure that preserves cellular health across multiple contexts. The role of the PCM, and how interactions between biglycan and collagen VI govern tendon health, however, remain unknown. This dissertation defined the coordinate roles of biglycan and collagen VI and determined that while both molecules are key for tendon health, collagen VI is a more robust regulator, and that biglycan and collagen VI do not play additive roles in tendon. This work sought to further refine biglycan’s regulatory mechanism in tendon by leveraging a unique model system of distinct tendon matrix environments—“wrap-around” tendons. In addition to the characteristic, aligned tendon matrix, wrap-around tendons contain a matrix that more closely mimics fibrocartilage. This work analyzed the effect of biglycan knockout across these distinct tissue contexts to determine the molecular mechanism by which biglycan regulates tendon function. In doing so, we mapped the postnatal development of regional tendon properties for the first time in mice. Results from this work demonstrate that while biglycan may regulated tendon function through the PCM, this mechanism is likely independent of collagen VI interactions. Instead, biglycan may regulate tendon properties by directly organizing the collagen matrix. Overall, this work provides unique insight into the role of biglycan across distinct tendon matrix environments and lays the foundation for future work that may identify the factors most essential for preserving tendon health. Such knowledge is critical for the prevention and treatment of tendon disease
Causal Inference Methods for Joint Censored Cost and Effectiveness Outcomes
No full textInformed healthcare policy decisions must be driven by consideration of an intervention\u27s effectiveness as well as its cost. Cost-effectiveness analyses provide a framework for decision making that balances these joint outcomes in some optimal way. However, because these studies often use data from observational sources, results may be biased due to unmeasured or time-varying confounding, informative cost censoring, and skewed or zero-inflated data. The goals of this dissertation are two-fold; we aim to (1) elucidate the conditions under which causal conclusions can be drawn from cost-effectiveness data, and (2) develop novel statistical methods for identifying cost-effective treatments while accounting for confounding and other data irregularities. We discuss three such developments: regression methodology for a novel probabilistic measure of cost-effectiveness, interpretable Q-learning based methods for identifying cost-effective treatment strategies, and a flexible and efficient influence function based estimator of average treatment cost that is robust to unmeasured confounding given a valid instrumental variable. We evaluate the operating characteristics of our proposed methods under several realistic data scenarios through simulation studies. We also illustrate usage by identifying cost-effective adjuvant treatments for early-stage endometrial cancer patients as well as assessing differences in costs between surgical and non-surgical interventions for gallstones and hemorrhaging using observational data
Some Investigations of Phase Transitions in Rod-Like Macro-Molecules and Fibrous Gels
No full textTwo problems pertaining to solid-solid phase transitions are presented here.First, we conduct Langevin dynamics calculations on a chain of masses and bistable springs in a viscous fluid, and extract a temperature dependent kinetic relation by observing that the dissipation at a phase boundary can be estimated by performing an energy balance. Using this kinetic relation we solve boundary value problems for a bistable bar immersed in a constant temperature bath and show that the resultant force-extension relation matches very well with the Langevin dynamics results. We estimate the force fluctuations at the pulled end of the bar due to thermal kicks from the bath by using a partition function. We also show rate dependence of hysteresis in cyclic loading of the bar arising from the stick-slip kinetics. we also extract equilibrium and non-equilibrium information from an over-damped Langevin system using fluctuation theorems.Second, we use a double-well stored energy function in a chemo-elastic model of gels to capture the existence of two phases of the network. We model cyclic compression/decompression experiments on fibrous gels and show that they exhibit propagating interfaces and hysteretic stress-strain curves that have been observed in experiments. We can capture features in the rate-dependent response of these fibrous gels without recourse to finite element calculations. We also use the model to study the rheological behavior of fibrous gels. We obtain the storage and loss modulus of fibrous gels by performing small amplitude oscillatory compression around various levels of deformation
Women\u27s Path to Tenure: Analysis of the Leaky Pipeline Phenomenon
Get PDFThis paper seeks to explain the leaky pipeline phenomenon at the University of Pennsylvania, characterized by the decreasing representation of women faculty at higher ranks of the professoriate. This study incorporates social role theory into its assessment of archival data on the composition of the faculty from 1999-2016. The paper finds no strong evidence of hiring discrimination; mixed evidence on the retention of women faculty, or that women are no less likely than men to leave the University; and little evidence of a positive trickle-down leadership effect, as universities who had never appointed a woman president had the greatest representation of women full professors in the years analyzed. The paper’s findings suggest that biased performance evaluations, unequal divisions of home responsibilities, and informal network exclusion of women faculty may contribute to the leaky pipeline, and highlight how historic gender roles continue to have salient consequences for women in the workforc