Comparison of Archeological Survey Techniques at Camp Lawton, a Civil War Prison Stockade

In 2009, Dr. Sue Moore of Georgia Southern University was contacted by State Archeologist Dr. Dave Crass of the Georgia Department of Natural Resources Historic Preservation Division. He proposed an exploratory survey of the site of a Civil War Confederate prisoner of war camp known as Camp Lawton located on Magnolia Springs State Park and Bo Ginn National Fish Hatchery in Millen, Georgia. Camp Lawton was constructed, occupied, and abandoned over an approximately three month period in the fall of 1864. The survey served a twofold purpose. First, was to evaluate survey methods to determine the most efficient for use on this and similar sites. Second, was to determine the archeological integrity of the site

Rural smokers : a prevention opportunity

Background: Smoking is the largest single cause of preventable death and disease in Australia. This study describes smoking prevalence and the characteristics of rural smokers to guide general practitioners in targeting particular groups.Methods: Cross sectional surveys in the Greater Green Triangle region of southeast Australia using a random population sample (n=1563, participation rate 48.7%) aged 25&ndash;74 years. Smoking information was assessed by a self administered questionnaire.Results: Complete smoking data were available for 1494 participants. Overall age adjusted current smoking prevalence was 14.9% (95% CI: 13.1&ndash;16.7). In both genders, current smoking prevalence decreased with age. Those aged 25&ndash;44 years were more likely to want to stop smoking and to have attempted cessation, but less likely to have received cessation advice than older smokers.Discussion: This study provides baseline smoking data for rural health monitoring and identifies intervention opportunities. General practice is suited to implement interventions for smoking prevention and cessation at every patient encounter, particularly in younger individuals.<br /

Novel Batch Active Learning Approach and Its Application to Synthetic Aperture Radar Datasets

Active learning improves the performance of machine learning methods by judiciously selecting a limited number of unlabeled data points to query for labels, with the aim of maximally improving the underlying classifier's performance. Recent gains have been made using sequential active learning for synthetic aperture radar (SAR) data arXiv:2204.00005. In each iteration, sequential active learning selects a query set of size one while batch active learning selects a query set of multiple datapoints. While batch active learning methods exhibit greater efficiency, the challenge lies in maintaining model accuracy relative to sequential active learning methods. We developed a novel, two-part approach for batch active learning: Dijkstra's Annulus Core-Set (DAC) for core-set generation and LocalMax for batch sampling. The batch active learning process that combines DAC and LocalMax achieves nearly identical accuracy as sequential active learning but is more efficient, proportional to the batch size. As an application, a pipeline is built based on transfer learning feature embedding, graph learning, DAC, and LocalMax to classify the FUSAR-Ship and OpenSARShip datasets. Our pipeline outperforms the state-of-the-art CNN-based methods.Comment: 16 pages, 7 figures, Preprin

Mind Your Outcomes: The ∆QSD Paradigm for Quality-Centric Systems Development and Its Application to a Blockchain Case Study

This paper directly addresses a long-standing issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply, and reliably whether they can deliver their intended performance before expending significant time, effort, and money on detailed design and implementation. We describe ΔQSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The distinctive feature of outcome diagrams is that they capture the essential observational properties of the system, independent of the details of system structure and behaviour. The ΔQSD paradigm derives bounds on performance expressed as probability distributions encompassing all possible executions of the system. The ΔQSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way so that approximate results can be obtained quickly and subsequently refined. ΔQSD has been successfully used by a small team in Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings worth billions of US dollars. The paper outlines the ΔQSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain. ΔQSD has supported the development of an industry-leading proof-of-stake blockchain implementation that reliably and consistently delivers blocks of up to 80 kB every 20 s on average across a globally distributed network of collaborating block-producing nodes operating on the public internet.publishedVersio

Algebraic Reasoning About Timeliness

Designing distributed systems to have predictable performance under high load is difficult because of resource exhaustion, non-linearity, and stochastic behaviour. Timeliness, i.e., delivering results within defined time bounds, is a central aspect of predictable performance. In this paper, we focus on timeliness using the DELTA-Q Systems Development paradigm (DELTA-QSD, developed by PNSol), which computes timeliness by modelling systems observationally using so-called outcome expressions. An outcome expression is a compositional definition of a system's observed behaviour in terms of its basic operations. Given the behaviour of the basic operations, DELTA-QSD efficiently computes the stochastic behaviour of the whole system including its timeliness. This paper formally proves useful algebraic properties of outcome expressions w.r.t. timeliness. We prove the different algebraic structures the set of outcome expressions form with the different DELTA-QSD operators and demonstrate why those operators do not form richer structures. We prove or disprove the set of all possible distributivity results on outcome expressions. On our way for disproving 8 of those distributivity results, we develop a technique called properisation, which gives rise to the first body of maths for improper random variables. Finally, we also prove 14 equivalences that have been used in the past in the practice of DELTA-QSD. An immediate benefit is rewrite rules that can be used for design exploration under established timeliness equivalence. This work is part of an ongoing project to disseminate and build tool support for DELTA-QSD. The ability to rewrite outcome expressions is essential for efficient tool support.Comment: In Proceedings ICE 2023, arXiv:2308.0892

Neocortical long-term potentiation and experience-dependent synaptic plasticity require alpha-calcium/calmodulin-dependent protein kinase II autophosphorylation

Experience-dependent plasticity can be induced in the barrel cortex by removing all but one whisker, leading to potentiation of the neuronal response to the spared whisker. To determine whether this form of potentiation depends on synaptic plasticity, we studied long-term potentiation (LTP) and sensory-evoked potentials in the barrel cortex of -calcium/calmodulin-dependent protein kinase II (CaMKII)T286A mutant mice. We studied three different forms of LTP induction: theta-burst stimulation, spike pairing, and postsynaptic depolarization paired with low-frequency presynaptic stimulation. None of these protocols produced LTP in CaMKIIT286A mutant mice, although all three were successful in wild-type mice. To study synaptic plasticity in vivo, we measured sensory-evoked potentials in the barrel cortex and found that single-whisker experience selectively potentiated synaptic responses evoked by sensory stimulation of the spared whisker in wild types but not in CaMKIIT286A mice. These results demonstrate that CaMKII autophosphorylation is required for synaptic plasticity in the neocortex, whether induced by a variety of LTP induction paradigms or by manipulation of sensory experience, thereby strengthening the case that the two forms of plasticity are related

Ligand modulation of sidechain dynamics in a wild-type human GPCR

GPCRs regulate all aspects of human physiology, and biophysical studies have deepened our understanding of GPCR conformational regulation by different ligands. Yet there is no experimental evidence for how sidechain dynamics control allosteric transitions between GPCR conformations. To address this deficit, we generated samples of a wild-type GPCR (A2AR) that are deuterated apart from 1H/13C NMR probes at isoleucine d1 methyl groups, which facilitated 1H/13C methyl TROSY NMR measurements with opposing ligands. Our data indicate that low [Na+] is required to allow large agonist-induced structural changes in A2AR, and that patterns of sidechain dynamics substantially differ between agonist (NECA) and inverse agonist (ZM241385) bound receptors, with the inverse agonist suppressing fast ps-ns timescale motions at the G protein binding site. Our approach to GPCR NMR creates a framework for exploring how different regions of a receptor respond to different ligands or signaling proteins through modulation of fast ps-ns sidechain dynamics