Spiritual genealogy: early church influences on the life and work of John Wesley and their renewing impact on his successors today

https://place.asburyseminary.edu/ecommonsatsdissertations/1104/thumbnail.jp

Approximate resilience, monotonicity, and the complexity of agnostic learning

A function $f$ is $d$-resilient if all its Fourier coefficients of degree at most $d$ are zero, i.e., $f$ is uncorrelated with all low-degree parities. We study the notion of $\mathit{approximate}$ $\mathit{resilience}$ of Boolean functions, where we say that $f$ is $\alpha$-approximately $d$-resilient if $f$ is $\alpha$-close to a $[-1,1]$-valued $d$-resilient function in $\ell_1$ distance. We show that approximate resilience essentially characterizes the complexity of agnostic learning of a concept class $C$ over the uniform distribution. Roughly speaking, if all functions in a class $C$ are far from being $d$-resilient then $C$ can be learned agnostically in time $n^{O(d)}$ and conversely, if $C$ contains a function close to being $d$-resilient then agnostic learning of $C$ in the statistical query (SQ) framework of Kearns has complexity of at least $n^{\Omega(d)}$. This characterization is based on the duality between $\ell_1$ approximation by degree-$d$ polynomials and approximate $d$-resilience that we establish. In particular, it implies that $\ell_1$ approximation by low-degree polynomials, known to be sufficient for agnostic learning over product distributions, is in fact necessary. Focusing on monotone Boolean functions, we exhibit the existence of near-optimal $\alpha$-approximately $\widetilde{\Omega}(\alpha\sqrt{n})$-resilient monotone functions for all $\alpha>0$. Prior to our work, it was conceivable even that every monotone function is $\Omega(1)$-far from any $1$-resilient function. Furthermore, we construct simple, explicit monotone functions based on ${\sf Tribes}$ and ${\sf CycleRun}$ that are close to highly resilient functions. Our constructions are based on a fairly general resilience analysis and amplification. These structural results, together with the characterization, imply nearly optimal lower bounds for agnostic learning of monotone juntas

Carbohydrate Hydrolysis and Transport in the Extreme Thermoacidophile \u3ci\u3eSulfolobus solfataricus\u3c/i\u3e

Extremely thermoacidophilic microbes, such as Sulfolobus solfataricus, are strict chemoheterotrophs despite their geologic niche. To clarify their ecophysiology, the overlapping roles of endoglucanases and carbohydrate transporters were examined during growth on soluble cellodextrins as the sole carbon and energy source. Strain-specific differences in genome structure implied a unique role for one of three endogenous endoglucanases. Plasmid-based endoglucanase expression promoted the consumption of oligosaccharides, including cellohexaose (G6) through cellonanaose (G9). Protein transporters required for cellodextrin uptake were identified through mutagenesis and complementation of an ABC transporter cassette, including a putative oligosaccharide binding protein. In addition, ablation of the binding protein compromised growth on glucose and alpha-linked oligosaccharides while inactivation of a previously described glucose transporter had no apparent impact. These data demonstrate that S. solfataricus employs a redundant mechanism for soluble cellodextrin catabolism having both substrate uptake and extracytoplasmic hydrolytic components

Metal Resistance and Lithoautotrophy in the Extreme Thermoacidophile \u3ci\u3eMetallosphaera sedula\u3c/i\u3e

Archaea such as Metallosphaera sedula are thermophilic lithoautotrophs that occupy unusually acidic and metal-rich environments. These traits are thought to underlie their industrial importance for bioleaching of base and precious metals. In this study, a genetic approach was taken to investigate the specific relationship between metal resistance and lithoautotrophy during biotransformation of the primary copper ore, chalcopyrite (CuFeS2). In this study, a genetic system was developed for M. sedula to investigate parameters that limit bioleaching of chalcopyrite. The functional role of the M. sedula copRTA operon was demonstrated by cross-species complementation of a copper-sensitive Sulfolobus solfataricus copR mutant. Inactivation of the gene encoding the M. sedula copper efflux protein, copA, using targeted recombination compromised metal resistance and eliminated chalcopyrite bioleaching. In contrast, a spontaneous M. sedula mutant (CuR1) with elevated metal resistance transformed chalcopyrite at an accelerated rate without affecting chemoheterotrophic growth. Proteomic analysis of CuR1 identified pleiotropic changes, including altered abundance of transport proteins having AAA-ATPase motifs. Addition of the insoluble carbonate mineral witherite (BaCO3) further stimulated chalcopyrite lithotrophy, indicating that carbon was a limiting factor. Since both mineral types were actively colonized, enhanced metal leaching may arise from the cooperative exchange of energy and carbon between surface-adhered populations. Genetic approaches provide a new means of improving the efficiency of metal bioleaching by enhancing the mechanistic understanding of thermophilic lithoautotrophy

Methods and prospects for gravitational wave searches targeting ultralight vector boson clouds around known black holes

Ultralight bosons are predicted in many extensions to the Standard Model and are popular dark matter candidates. The black hole superradiance mechanism allows for these particles to be probed using only their gravitational interaction. In this scenario, an ultralight boson cloud may form spontaneously around a spinning black hole and extract a non-negligible fraction of the black hole's mass. These oscillating clouds produce quasi-monochromatic, long-duration gravitational waves that may be detectable by ground-based or space-based gravitational wave detectors. We discuss the capability of a new long-duration signal tracking method, based on a hidden Markov model, to detect gravitational wave signals generated by ultralight vector boson clouds, including cases where the signal frequency evolution timescale is much shorter than that of a typical continuous wave signal. We quantify the detection horizon distances for vector boson clouds with current- and next-generation ground-based detectors. We demonstrate that vector clouds hosted by black holes with mass $\gtrsim 60 M_{\odot}$ and spin $\gtrsim 0.6$ are within the reach of current-generation detectors up to a luminosity distance of $\sim 1$ Gpc. This search method enables one to target vector boson clouds around remnant black holes from compact binary mergers detected by gravitational-wave detectors. We discuss the impact of the sky localization of the merger events and demonstrate that a typical remnant black hole reasonably well-localized by the current generation detector network is accessible in a follow-up search.Comment: 21 pages, 12 figure

Was digitale Lehre zur „guten“ Lehre macht

Was macht gute digitale Lehre aus und welche Bedarfe stellen sich an ein digitales Bildungssetting im Hochschulkontext? Was leistet das bereits zur Verfügung gestellte Angebot und inwiefern lassen sich Handlungsfelder für die Zukunft der Hochschullehre ableiten? Am Zentrum für Qualitätsanalyse (ZQA) der TU Dresden wurden hierzu Studien unternommen, die Aufschluss darüber geben sollen, vor welchen Herausforderungen die Hochschulbildung steht und welche Chancen und Potentiale sich daraus ableiten lassen. Mittels eines regelmäßig erscheinenden Dossiers mit dem Titel „Potentiale und Herausforderungen digitaler Hochschulbildung“ sollen nun schrittweise die Ergebnisse hierzu aufgearbeitet werden. Das vorliegende erste Diskussionspapier versucht zunächst der Frage nachzugehen, was Studierende als besondere Herausforderungen eines rein digitalen Studiums wahrnehmen. Hierzu wurden 8.512 Studierende an der TU Dresden zu Beginn des Sommersemesters 2020 befragt