Spin-state crossover and hyperfine interactions of ferric iron in MgSiO3_3 perovskite

Using density functional theory plus Hubbard $U$ calculations, we show that the ground state of (Mg,Fe)(Si,Fe)O$_3$ perovskite, a major mineral phase in the Earth's lower mantle, has high-spin ferric iron ($S=5/2$) at both the dodecahedral (A) and octahedral (B) site. As the pressure increases, the B-site iron undergoes a spin-state crossover to the low-spin state ($S=1/2$), while the A-site iron remains in the high-spin state. Our calculation shows that the B-site spin-state crossover in the pressure range of 40-70 GPa is accompanied by a noticeable volume reduction and an increase in quadrupole splitting, consistent with recent X-ray diffraction and M\"ossbauer spectroscopy measurements. The volume reduction leads to a significant softening in the bulk modulus, which suggests a possible source of seismic velocity anomalies in the lower mantle.Comment: 11 pages, 4 figures, 1 tabl

Optimal Tests of Treatment Effects for the Overall Population and Two Subpopulations in Randomized Trials, using Sparse Linear Programming

We propose new, optimal methods for analyzing randomized trials, when it is suspected that treatment effects may differ in two predefined subpopulations. Such sub-populations could be defined by a biomarker or risk factor measured at baseline. The goal is to simultaneously learn which subpopulations benefit from an experimental treatment, while providing strong control of the familywise Type I error rate. We formalize this as a multiple testing problem and show it is computationally infeasible to solve using existing techniques. Our solution involves a novel approach, in which we first transform the original multiple testing problem into a large, sparse linear program. We then solve this problem using advanced optimization techniques. This general method can solve a variety of multiple testing problems and decision theory problems related to optimal trial design, for which no solution was previously available. In particular, we construct new multiple testing procedures that satisfy minimax and Bayes optimality criteria. For a given optimality criterion, our new approach yields the optimal tradeoff? between power to detect an effect in the overall population versus power to detect effects in subpopulations. We demonstrate our approach in examples motivated by two randomized trials of new treatments for HIV

Communicating Climate Change In Internet Discussion Fora: Processes and Implications

Communicating climate change issues in the Internet era requires new strategies that incorporate online communication. The rapid growth of new media and widespread use of the internet has marked everyday lifestyles in modern society. Information on a wide range of social issues, including climate change, is disseminated and debated through online discussions in internet fora. In this research, communication on internet fora and other potential forms of online social interaction are explored, to identify ways to enhance climate change communication on the Internet. The thesis raises three research questions to explore the communication context of internet fora discussion, namely: what are characteristics of the communication process on internet fora? Who is involved in the communication process? What influences do these online communication activities have on users’ everyday activities? The research applies a mixed-methods approach of analysing the usage of Internet fora and the contents of fora communication activities to explore these questions. This includes qualitative reviews of topic-thread discussions to reveal users’ roles in discussions, as well as surveys of fora users. It is argued that with increasing levels of interaction among communicators (people who post or reply to articles in order to express or respond ideas) on internet fora, these communicators are mobilised to join the online discussion process, competing for opinion leadership. The online discussions further contribute to the formation of opinions on climate change, as climate change and related issues are discussed The thesis thereby aims to contribute to the development of effective approaches for opinion formation and climate change communication online, and to encourage individuals to discuss changing behaviour patterns and public engagement of greenhouse gas reduction actions

Structural, spin, and metal-insulator transitions of (Mg,Fe)O at ultrahigh pressure

Fe-bearing MgO [(Mg$_{1-x}$Fe$_x$)O] is considered a major constituent of terrestrial exoplanets. Crystallizing in the B1 structure in the Earth's lower mantle, (Mg$_{1-x}$Fe$_x$)O undergoes a high-spin (HS, $S=2$) to low-spin (LS, $S=0$) transition at $\sim$45 GPa, accompanied by anomalous changes of this mineral's physical properties, while the intermediate-spin (IS, $S=1$) state has not been observed. In this work, we investigate (Mg$_{1-x}$Fe$_x$)O ($x \leq 0.25$) up to $1.8$ TPa via first-principles calculations. Our calculations indicate that (Mg$_{1-x}$Fe$_x$)O undergoes a simultaneous structural and spin transition at $\sim$0.6 TPa, from the B1 phase LS state to the B2 phase IS state, with Fe's total electron spin ($S$) re-emerging from $0$ to $1$ at ultrahigh pressure. Upon further compression, an IS--LS transition occurs in the B2 phase. Depending on the Fe concentration ($x$), metal--insulator transition and rhombohedral distortions can also occur in the B2 phase. These results suggest that Fe and spin transition may affect planetary interiors over a vast pressure range

An Examination of Conductors’ Leadership Skills

Through my experiences as a member of various large orchestral ensembles, I have been intrigued by how diverse my musical experiences were with different conductors. Some of these experiences have been thoroughly inspiring; I felt compelled to achieve higher levels of performance and convinced that I was a crucial part of creating something much larger than the notes on the page. Other experiences have been less musically fulfilling for me; I became disinterested and bored and felt little affective connection with the music. Reflecting on these different personal responses, I realized that the conductors in these experiences, in part, influenced such reactions. I trusted and admired these conductors for their confidence, musicality, and ability to lead a large group of people. In essence, these musical leaders possessed various leadership skills that contributed to their success, effectiveness, and appeal as conductors in my eyes. First, the successful conductors in my past experiences all possessed excellent musicianship in offering meaningful and powerful interpretations of the music and demonstrating complete knowledge of the score and its background. Second, these effective conductors maintained a sense of energy and momentum throughout their rehearsals that allowed me to stay focused and interested in music-making. They also presented musical concepts and ideas in ways that increased my understanding of the music. Lastly, I realized that these conductors’ verbal comments provided me with specific feedback and understandable instructions on how to improve my performance. These conductors were futher able to depict their musical interpretations through conducting gestures, facial expressions, and physical demeanors. Therefore, I identified musicianship, organization, and instructional strategies—both verbal and nonverbal—as three significant leadership skills that has improved the quality of my orchestral experiences. Reflections on my own experiences as a member of orchestral ensembles fueled my interest in honing my work as a developing conductor through an exploration of these three leadership skills. I am fully aware that the successes of the conductors in my past experiences also were attributed to other leadership skills. However, in this project, I sought an opportunity, as a developing conductor, to examine and self-reflect on these three specific leadership skills in order to generate my own style as a musician and leader. The purpose of this project was to examine how conductors’ leadership skills—musicianship, organization, and instructional strategies—impact the musical development of my project’s orchestral ensemble. This project involved my conducting of a volunteer, collegiate orchestra that I recruited. I conducted this orchestra for five rehearsals and a concert performance at my graduate recital. A crucial part of this project included my personal reflections on my leadership skills and their effects on the musical development of the orchestra I rehearsed

Efficient Downlink Channel Reconstruction for FDD Multi-Antenna Systems

In this paper, we propose an efficient downlink channel reconstruction scheme for a frequency-division-duplex multi-antenna system by utilizing uplink channel state information combined with limited feedback. Based on the spatial reciprocity in a wireless channel, the downlink channel is reconstructed by using frequency-independent parameters. We first estimate the gains, delays, and angles during uplink sounding. The gains are then refined through downlink training and sent back to the base station (BS). With limited overhead, the refinement can substantially improve the accuracy of the downlink channel reconstruction. The BS can then reconstruct the downlink channel with the uplink-estimated delays and angles and the downlink-refined gains. We also introduce and extend the Newtonized orthogonal matching pursuit (NOMP) algorithm to detect the delays and gains in a multi-antenna multi-subcarrier condition. The results of our analysis show that the extended NOMP algorithm achieves high estimation accuracy. Simulations and over-the-air tests are performed to assess the performance of the efficient downlink channel reconstruction scheme. The results show that the reconstructed channel is close to the practical channel and that the accuracy is enhanced when the number of BS antennas increases, thereby highlighting that the promising application of the proposed scheme in large-scale antenna array systems

An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

While deep learning methods are increasingly being applied to tasks such as computer-aided diagnosis, these models are difficult to interpret, do not incorporate prior domain knowledge, and are often considered as a "black-box." The lack of model interpretability hinders them from being fully understood by target users such as radiologists. In this paper, we present a novel interpretable deep hierarchical semantic convolutional neural network (HSCNN) to predict whether a given pulmonary nodule observed on a computed tomography (CT) scan is malignant. Our network provides two levels of output: 1) low-level radiologist semantic features, and 2) a high-level malignancy prediction score. The low-level semantic outputs quantify the diagnostic features used by radiologists and serve to explain how the model interprets the images in an expert-driven manner. The information from these low-level tasks, along with the representations learned by the convolutional layers, are then combined and used to infer the high-level task of predicting nodule malignancy. This unified architecture is trained by optimizing a global loss function including both low- and high-level tasks, thereby learning all the parameters within a joint framework. Our experimental results using the Lung Image Database Consortium (LIDC) show that the proposed method not only produces interpretable lung cancer predictions but also achieves significantly better results compared to common 3D CNN approaches