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This Kids Count factbook examines statewide and county trends in the well-being of Georgia's children. The statistical portrait is based on indicators in five domains: family and community, economic well-being, health, education, and safety and security. The 21 indicators of well-being are: (1) child population; (2) public school enrollment; (3) families starting at risk of poverty; (4) children in poverty; (5) median household income; (6) students receiving free or reduced school lunch; (7) children in families receiving TANF; (8) children in families receiving food stamps; (9) low birth weight babies; (10) infant mortality; (11) prenatal care; (12) births to teens; (13) repeat births to teens; (14) Iowa Test of Basic Skills scores; (15) high school completions; (16) high school graduates eligible for HOPE scholarships; (17) babies born to mothers with less than 12 years of education; (18) child deaths; (19) teen deaths by accident, homicide, and suicide; (20) child abuse and neglect; and (21) juvenile arrests. The report's findings indicate that progress was made toward improving: poverty rates among children, infant mortality rates, rate of births to teens, math scores on the Iowa Tests, high school completions, rates of child deaths and teen deaths, and incidents of child abuse and neglect. The report's findings also indicate change for the worse in the areas of: families starting at risk of poverty, students eligible to receive free or reduced school lunches, low birthweight babies, some Iowa Test reading scores, and juvenile arrests. The factbook ends with a special report concerning economic development and child well-being. (SD)

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson’s disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug–gene interactions. We performed automated ML on multimodal data from the Parkinson’s progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson’s Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Increased demand for livestock products is exacerbating conflict with predators in many parts of the world, fuelling an increase in predation management practices in many grazing systems. In Australia, exclusion fences are being erected across broad areas to facilitate the sustained eradication of dingoes, an apex predator, prompting concern for possible cascading effects on extant wildlife populations. We experimentally assessed population trends of mammals, reptiles and ground-dwelling birds inside and outside of two large, fenced areas over a five-year period subsequent to the erection of the fences and the removal of dingoes. Wildlife population abundances inside the fences were always higher or the same as outside the fences, and all wildlife species exhibited similar population trends within each treatment over time. The only exception to this was kangaroo populations, which fluctuated widely inside fenced areas but remained relatively low and stable outside fenced areas. Kangaroos exhibited negative relationships with dingoes, although unmeasured variables limited our ability to quantify specific causes for kangaroo population trends. Vegetation trends were virtually identical between treatments, indicating that wildlife population trends are closely linked to vegetation conditions and not predator abundances. These applied, experimental results demonstrate that top-predator removal does not routinely cause trophic cascades (including mesopredator releases) in Australian rangeland ecosystems. We therefore encourage exploration of opportunities for targeted threatened species recovery in predator-free areas on land used for livestock production.

We aim to enhance the stability of finite element models of dynamic structural contact with multiphase granular soils which are described by advanced soil plasticity models that can simulate monotonic and cyclic behaviour of multiphase soils. Often, numerical oscillations cannot be avoided in these contact models and can cause advanced soil models to significantly overshoot stress, leading to unrealistic discontinuities in the stress paths. This situation can challenge the stability of the stress integration scheme and the global finite element solver and lead to the early termination of the analysis. We specifically address the issue of stress overshooting by presenting novel solutions and the corresponding stress integration schemes for a representative soil model for unsaturated granular soils. Also, several examples are provided to evaluate the integration scheme and show the advantages and limitations of the proposed overshooting solutions in solving a contact-impact problem involving unsaturated granular soils.

Several models exist for predicting dilution from large rooftop exhausts, but their validity has not been assessed for horizontally directed through-wall exhausts such as those that often exist in new multi-family residential construction. Separation distances derived from rules of thumb or simplified versions of these models are prescribed in ventilation standards, but their appropriateness has not been assessed and they are sometimes difficult to achieve in practice. In order to provide more justifiable separation distances, we conducted a series of wind tunnel experiments and computational fluid dynamics (CFD) simulations measuring dilution of a horizontally-directed exhaust from a test building. We then compared these measurements to existing models and assessed the models’ validity for this situation. Lastly, we gathered dilution criteria for several contaminants of interest and used wind tunnel and CFD results along with published emission rates to specify a separation distance that is likely to result in acceptable air quality at neighboring intakes. Results show that mitigation of chronic health concerns from cooking, and smoking in dwelling units, as well as odor concerns from bathrooms, can likely be achieved with separation distances of 5 feet or less. To prevent irritation from smoking in neighboring units, a separation distance of 10 feet is recommended. We did not find that furnace exhaust can be diluted sufficiently with separation distances that are feasible on multi-family buildings.

In the cybersecurity setting, defenders are often at the mercy of their detection technologies and subject to the information and experiences that individual analysts have. In order to give defenders an advantage, it is important to understand an attacker's motivation and their likely next best action. As a first step in modeling this behavior, we introduce a security game framework that simulates interplay between attackers and defenders in a noisy environment, focusing on the factors that drive decision making for attackers and defenders in the variants of the game with full knowledge and observability, knowledge of the parameters but no observability of the state (``partial knowledge''), and zero knowledge or observability (``zero knowledge''). We demonstrate the importance of making the right assumptions about attackers, given significant differences in outcomes. Furthermore, there is a measurable trade-off between false-positives and true-positives in terms of attacker outcomes, suggesting that a more false-positive prone environment may be acceptable under conditions where true-positives are also higher., Comment: Accepted at AAAI-23 Workshop on Artificial Intelligence and Cybersecurity (AICS)

We propose two unconditionally stable, linear ensemble algorithms with pre-computable shared coefficient matrices across different realizations for the magnetohydrodynamics equations. The viscous terms are treated by a standard perturbative discretization. The nonlinear terms are discretized fully explicitly within the framework of the generalized positive auxiliary variable approach (GPAV). Artificial viscosity stabilization that modifies the kinetic energy is introduced to improve accuracy of the GPAV ensemble methods. Numerical results are presented to demonstrate the accuracy and robustness of the ensemble algorithms., Comment: 24 pages, 30 figures

Scott Sloan (1954–2019) was a leader of academic engineering in Australia and beyond, as evidenced by his numerous professional accolades and important research achievements, which have had significant impact on his chosen profession of geotechnical engineering. Educated in Australia and the United Kingdom, he returned to Australia in 1984 and developed a large and active research group at the University of Newcastle, and tackled a wide range of important problems in civil and mining engineering. These include the development of computational methods to predict the mechanical behaviour of soil and rock masses, and his pioneering methods to predict the collapse states of structures made of, on, and in, earth materials, allowing engineers to design cheaper and safer civil infrastructure around the globe. Sloan established long-standing international collaborations and was awarded many honours for his research achievements. He was also a keen and skilful fisherman and a more than competent blues guitar player., Postprint (published version)

Land clearing generates coarse woody debris (CWD), much of which ultimately becomes atmospheric CO2. Schemes for greenhouse gas accounting must consider the contribution from land clearing, but the timing of the contribution will have large uncertainty, due to a paucity of knowledge about the rate of CWD disappearance. To better understand above-ground CWD disappearance following a land clearing event—through the actions of microorganisms, invertebrates, wildfire, or deliberate burning—we combined statistical modelling with an archive of semi-quantitative observations (units of CWD %), made within Queensland, Australia.

This work explores the evaluation of a machine learning anomaly detector using custom-made parameterizable malware in an Internet of Things (IoT) Ecosystem. It is assumed that the malware has infected, and resides on, the Linux router that serves other devices on the network, as depicted in Figure 1. This IoT Ecosystem was developed as a testbed to evaluate the efficacy of a behavior-based anomaly detector. The malware consists of three types of custom-made malware: ransomware, cryptominer, and keylogger, which all have exfiltration capabilities to the network. The parameterization of the malware gives the malware samples multiple degrees of freedom, specifically relating to the rate and size of data exfiltration. The anomaly detector uses feature sets crafted from system calls and network traffic, and uses a Support Vector Machine (SVM) for behavioral-based anomaly detection. The custom-made malware is used to evaluate the situations where the SVM is effective, as well as the situations where it is not effective., Comment: To appear in Proceedings of the 17th International Conference on Ubiquitous Security (UbiSec 2021)

After the successful landing of the Mars Science Laboratory rover, both NASA and ESA initiated a selection process for potential landing sites for the Mars2020 and ExoMars missions, respectively. Two ellipses located in the Mawrth Vallis region were proposed and evaluated during a series of meetings (3 for Mars2020 mission and 5 for ExoMars). We describe here the regional context of the two proposed ellipses as well as the framework of the objectives of these two missions. Key science targets of the ellipses and their astrobiological interests are reported. This work confirms the proposed ellipses contain multiple past Martian wet environments of subaerial, subsurface and/or subaqueous character, in which to probe the past climate of Mars, build a broad picture of possible past habitable environments, evaluate their exobiological potentials and search for biosignatures in well-preserved rocks. A mission scenario covering several key investigations during the nominal mission of each rover is also presented, as well as descriptions of how the site fulfills the science requirements and expectations of in situ martian exploration. These serve as a basis for potential future exploration of the Mawrth Vallis region with new missions and describe opportunities for human exploration of Mars in terms of resources and science discoveries.

This paper is the first paper of a series that will present the derivation of the modal mineralogy of Mars (M3 project) at a global scale from the near-infrared dataset acquired by the imaging spectrometer OMEGA (Observatoire pour la Min\'eralogie, l'Eau, les Glaces et l'Activit\'e) on board ESA/Mars Express. The objective is to create and provide a global 3-D image-cube of Mars at 32px/{\deg} covering most of Mars surface. This product has several advantages. First, it can be used to instantaneously extract atmospheric- and aerosol-corrected near-infrared (NIR) spectra from any location on Mars. Second, several new data maps can be built as discussed here. That includes new global mineral distributions, quantitative mineral abundance distributions and maps of Martian surface chemistry (wt % oxide) detailed in a companion paper (Riu et al., submitted). Here we present the method to derive the global hyperspectral cube from several hundred millions of spectra. Global maps of some mafic minerals are then shown, and compared to previous works.

© 2020 IEEE. There has been a considerable amount of recent work on high-speed micro-aerial vehicle flight in unknown and unstructured environments. Generally these approaches either use active sensing or fly slowly enough to ensure a safe braking distance with the relatively short sensing range of passive sensors. The former generally requires carrying large and heavy LIDARs and the latter only allows flight far away from the dynamic limits of the vehicle. One of the significant challenges for high-speed flight is the computational demand of trajectory planning at sufficiently high rates and length scales required in outdoor environments. We tackle both problems in this work by leveraging semantic information derived from an RGB camera on-board the vehicle. We first describe how to use semantic information to increase the effective range of perception on certain environment classes. Second, we present a sparse representation of the environment that is sufficiently lightweight for long distance path planning. We show how our approach outperforms more traditional metric planners which seek the shortest path, demonstrate the semantic planner's capabilities in a set of simulated and excessive real-world autonomous quadrotor flights in an urban environment., Army Research Laboratory (Contract W911NF-17-2-0181)

© 2019 IEEE. Autonomous navigation through unknown environments is a challenging task that entails real-time localization, perception, planning, and control. UAVs with this capability have begun to emerge in the literature with advances in lightweight sensing and computing. Although the planning methodologies vary from platform to platform, many algorithms adopt a hierarchical planning architecture where a slow, low-fidelity global planner guides a fast, high-fidelity local planner. However, in unknown environments, this approach can lead to erratic or unstable behavior due to the interaction between the global planner, whose solution is changing constantly, and the local planner; a consequence of not capturing higher-order dynamics in the global plan. This work proposes a planning framework in which multi-fidelity models are used to reduce the discrepancy between the local and global planner. Our approach uses high-, medium-, and low-fidelity models to compose a path that captures higher-order dynamics while remaining computationally tractable. In addition, we address the interaction between a fast planner and a slower mapper by considering the sensor data not yet fused into the map during the collision check. This novel mapping and planning framework for agile flights is validated in simulation and hardware experiments, showing replanning times of 5-40 ms in cluttered environments.

© 2018 IEEE. We would like robots to be able to safely navigate at high speed, efficiently use local 3D information, and robustly plan motions that consider pose uncertainty of measurements in a local map structure. This is hard to do with previously existing mapping approaches, like occupancy grids, that are focused on incrementally fusing 3D data into a common world frame. In particular, both their fragile sensitivity to state estimation errors and computational cost can be limiting. We develop an alternative framework, NanoMap, which alleviates the need for global map fusion and enables a motion planner to efficiently query pose-uncertainty-aware local 3D geometric information. The key idea of NanoMap is to store a history of noisy relative pose transforms and search over a corresponding set of depth sensor measurements for the minimum-uncertainty view of a queried point in space. This approach affords a variety of capabilities not offered by traditional mapping techniques: (a) the pose uncertainty associated with 3D data can be incorporated in motion planning, (b) poses can be updated (i.e., from loop closures) with minimal computational effort, and (c) 3D data can be fused lazily for the purpose of planning. We provide an open-source implementation of NanoMap, and analyze its capabilities and computational efficiency in simulation experiments. Finally, we demonstrate in hardware its effectiveness for fast 3D obstacle avoidance onboard a quadrotor flying up to 10 m/s.

In cybersecurity, attackers range from brash, unsophisticated script kiddies and cybercriminals to stealthy, patient advanced persistent threats. When modeling these attackers, we can observe that they demonstrate different risk-seeking and risk-averse behaviors. This work explores how an attacker's risk seeking or risk averse behavior affects their operations against detection-optimizing defenders in an Internet of Things ecosystem. Using an evaluation framework which uses real, parametrizable malware, we develop a game that is played by a defender against attackers with a suite of malware that is parameterized to be more aggressive and more stealthy. These results are evaluated under a framework of exponential utility according to their willingness to accept risk. We find that against a defender who must choose a single strategy up front, risk-seeking attackers gain more actual utility than risk-averse attackers, particularly in cases where the defender is better equipped than the two attackers anticipate. Additionally, we empirically confirm that high-risk, high-reward scenarios are more beneficial to risk-seeking attackers like cybercriminals, while low-risk, low-reward scenarios are more beneficial to risk-averse attackers like advanced persistent threats., Comment: To appear in Proceedings of the Conference on Decision and Game Theory for Security 2021

GenoML is a Python package automating machine learning workflows for genomics (genetics and multi-omics) with an open science philosophy. Genomics data require significant domain expertise to clean, pre-process, harmonize and perform quality control of the data. Furthermore, tuning, validation, and interpretation involve taking into account the biology and possibly the limitations of the underlying data collection, protocols, and technology. GenoML's mission is to bring machine learning for genomics and clinical data to non-experts by developing an easy-to-use tool that automates the full development, evaluation, and deployment process. Emphasis is put on open science to make workflows easily accessible, replicable, and transferable within the scientific community. Source code and documentation is available at https://genoml.com.

Discusses how schools might benefit by enlisting older adults as participants in a rejuvenation of public education. Argues that many retirees are looking for avenues of usefulness and activity. Suggests ways schools might utilize older adults. (HB)

PURPOSE: We aimed to evaluate the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) as a potential means of improving on the SCID's diagnostic efficacy.METHODS: 76 first-admission patients were assigned DSM-IV consensus diagnoses by two experienced psychiatrists using all available information, then dichotomized into non-affective psychosis and other mental illness groups. The patients were also given the SCID and the MMPI-2. The diagnostic performance of the MMPI-2 was compared to that of the SCID to assess both diagnostic accuracy and incremental validity.RESULTS: MMPI-2 scales 8 (Schizophrenia) and BIZ (Bizarre Mentations) correctly identified 58% and 56% respectively of non-affective psychotic patients. The Goldberg Index had an overall correct classification rate of 70%, but only identified 49% of the psychosis group. The SCID had a correct classification rate of 66% but correctly identified only 25% of the non-affective psychosis patients. Three MMPI-2 scales combined with the SCID resulted in an overall correct classification rate of 73%, and identification of 66% of the non-affective psychosis patients.CONCLUSION: The results suggest that the MMPI-2 may identify early psychosis at least as well as the SCID. Furthermore, using a combination of the MMPI-2 and the SCID shows incremental validity over using the SCID alone.

Chin Ting Chan, coordinator, Julius Bucsis, technical director, Carter Rice, assistant technical director. ; With guest artists Popebama.; Includes programs for 5 individual concerts.; Includes lists of BSU College of Fine Arts administrators, School of Music administrators, and School of Music faculty members., Series LXXIII, Number 138., This archival material has been provided for educational purposes. Ball State University Libraries recognizes that some historic items may include offensive content. Our statement regarding objectionable content is available at: https://dmr.bsu.edu/digital/about

Composers : Chin Ting Chan, Carter John Rice, Christopher Monty, Stephen Weigel, Michael Pounds, Chad Powers, Julius Bucsis, Robert Willey. ; Chin Ting Chan, coordinator, Julius Bucsis and Theron Dalton, co-technical directors, Rachel D. Hemm, lighting designer. ; Includes a list of upcoming School of Music events (for April 2019)., Series LXXIII, Number 192., This archival material has been provided for educational purposes. Ball State University Libraries recognizes that some historic items may include offensive content. Our statement regarding objectionable content is available at: https://dmr.bsu.edu/digital/about

Context: Feral pigs (Sus scrofa) are highly fecund, and populations can increase rapidly under favourable conditions. Population size can also fluctuate widely, driven largely by changes in juvenile mortality in response to food availability, but these relationships have only been explored on a limited number of sites and over short periods.Aims: The present study aimed to investigate and quantify the numerical response of feral pig populations to changes in their food supply in north-eastern Australia.Methods: Pig population densities were determined from aerial surveys conducted over a 21-year period on 10 regional blocks (~2000–6000 km2) throughout the Queensland rangelands. Densities were used to calculate annual exponential rates of increase (r), which were then corrected for anthropogenic mortality (baiting and commercial harvesting). Six proxy measures of annual food supply, including rainfall, pasture biomass and pasture growth (using the AussieGRASS model), were calculated for each survey block, and assessed as predictors of corrected r. The rates of increase predicted from the first half of the data series were then applied to initial population densities to estimate successive pig densities during the second period in each bioregion.Key results: The most parsimonious model of the numerical response had parameters common to three bioregions, with rainfall in the 12 months between surveys being the best predictor variable. Modelled densities for each bioregion were a good fit to actual, observed densities. Relationships between r and each measure of food supply at the individual block level were inconsistent.Conclusions: Using rainfall as a measure of food supply, the numerical response relationship provides a method for predicting the dynamics of feral pig populations at the bioregional scale. Predicting population dynamics at any one site using this relationship is less precise, suggesting that differences in landscape composition affect utilisation of re

Operating a high degree of freedom mobile manipulator, such as a humanoid, in a field scenario requires constant situational awareness, capable perception modules, and effective mechanisms for interactive motion planning and control. A well-designed operator interface presents the operator with enough context to quickly carry out a mission and the flexibility to handle unforeseen operating scenarios robustly. By contrast, an unintuitive user interface can increase the risk of catastrophic operator error by overwhelming the user with unnecessary information. With these principles in mind, we present the philosophy and design decisions behind Director—the open-source user interface developed by Team MIT to pilot the Atlas robot in the DARPA Robotics Challenge (DRC). At the heart of Director is an integrated task execution system that specifies sequences of actions needed to achieve a substantive task, such as drilling a wall or climbing a staircase. These task sequences, developed a priori, make online queries to automated perception and planning algorithms with outputs that can be reviewed by the operator and executed by our whole-body controller. Our use of Director at the DRC resulted in efficient high-level task operation while being fully competitive with approaches focusing on teleoperation by highly trained operators. We discuss the primary interface elements that comprise Director, and we provide an analysis of its successful use at the DRC., United States. Defense Advanced Research Projects Agency. (Air Force Research Laboratory (award FA8750-12-1-0321)), United States. Office of Naval Research (Award N00014-12-1-0071)

Seasonal flows on warm slopes, or recurring slope lineae ("RSL"), have been presented as strong evidence for currently flowing water on Mars. This assumption was supported by a correlation between activity and warm temperatures, and by the spectral identification of hydrated salts. Here we first demonstrate that salts spectral identification is not robust, and that flow activity occurs on a wider range of seasons and slope orientations than previously thought, ruling out liquid water as a probable contributor. We then show that morphology, location and timing of flow activity is fully consistent with the removal and deposition of bright dust above darker underlying surfaces occurring notably in relation with seasonal dust storm activity. Mars recurring slope lineae are thus consistent with dust movements typical of present-day dry planet Mars.

Autonomous navigation through unknown environments is a challenging task that entails real-time localization, perception, planning, and control. UAVs with this capability have begun to emerge in the literature with advances in lightweight sensing and computing. Although the planning methodologies vary from platform to platform, many algorithms adopt a hierarchical planning architecture where a slow, low-fidelity global planner guides a fast, high-fidelity local planner. However, in unknown environments, this approach can lead to erratic or unstable behavior due to the interaction between the global planner, whose solution is changing constantly, and the local planner; a consequence of not capturing higher-order dynamics in the global plan. This work proposes a planning framework in which multi-fidelity models are used to reduce the discrepancy between the local and global planner. Our approach uses high-, medium-, and low-fidelity models to compose a path that captures higher-order dynamics while remaining computationally tractable. In addition, we address the interaction between a fast planner and a slower mapper by considering the sensor data not yet fused into the map during the collision check. This novel mapping and planning framework for agile flights is validated in simulation and hardware experiments, showing replanning times of 5-40 ms in cluttered environments., Comment: ICRA 2019

We would like robots to be able to safely navigate at high speed, efficiently use local 3D information, and robustly plan motions that consider pose uncertainty of measurements in a local map structure. This is hard to do with previously existing mapping approaches, like occupancy grids, that are focused on incrementally fusing 3D data into a common world frame. In particular, both their fragile sensitivity to state estimation errors and computational cost can be limiting. We develop an alternative framework, NanoMap, which alleviates the need for global map fusion and enables a motion planner to efficiently query pose-uncertainty-aware local 3D geometric information. The key idea of NanoMap is to store a history of noisy relative pose transforms and search over a corresponding set of depth sensor measurements for the minimum-uncertainty view of a queried point in space. This approach affords a variety of capabilities not offered by traditional mapping techniques: (a) the pose uncertainty associated with 3D data can be incorporated in motion planning, (b) poses can be updated (i.e., from loop closures) with minimal computational effort, and (c) 3D data can be fused lazily for the purpose of planning. We provide an open-source implementation of NanoMap, and analyze its capabilities and computational efficiency in simulation experiments. Finally, we demonstrate in hardware its effectiveness for fast 3D obstacle avoidance onboard a quadrotor flying up to 10 m/s., Comment: To Appear at ICRA 2018

Naturally occurring materials such as jute and coir have some favorable engineering characteristics and also degrade over time, so they have increasingly been used in engineering applications in recent years. The efficient way that naturally prefabricated vertical drains made from those materials help accelerate soil consolidation has been shown in previous studies, but they also tend to decompose rapidly in adverse environments, where cellulose-degrading bacteria cause a serious deterioration of their favorable drainage properties. This study presents a laboratory investigation into the biodegradation of prefabricated vertical jute drains in saturated soft soils, where the tensile strength of jute and coir fibers and the discharge capacity of drains decrease in response to different environments. Micro-observation also shows a transformation of the jute fibers and destruction of the drain structure due to biodegradation. DNA extraction and sequencing techniques to determine the microbial properties of these decayed fibers indicate that bacteria such as species of the genera Clostridium and Bacillus can cause rapid decomposition of cellulose-based material (i.e., jute), whereas other organic matter-consuming microbes such as sulfate-reducing bacteria do not directly contribute to the biodegradation of jute. In response, an analytical approach that incorporates various forms of drain discharge capacity over time is proposed to predict soil consolidation. The results indicate there is considerable deviation in dissipating the excess pore pressure when the drain degrades in different ways.

Both literature teachers who take the time to teach historical background and history teachers who take the time to incorporate literature into their classes will help students to discover that life is multidimensional. Some practical activities are required to correlate language arts with social studies. One such activity involves assigning students to write a dialogue between two historical figures whose lives they have researched, while another asks them to write a letter to an historical figure about life in the twentieth century. These assignments show students that writing is important in both literary and historical contexts. Students can also compare different biblical versions of the creation with twentieth century renditions, then write a revised and updated version of another biblical story. While dealing with historical subjects and creative literature, students will learn how to revise and update and how to handle such problems as setting and language changes. Assigning students to write a history book on a specific period and region will teach them to investigate, think, organize, and write. Other possible exercises include creating a graffiti wall on which students can write historical facts and quotes, and having them write advertisements for historical and cultural features. (HTH)

Although devised for the college level, this teaching guide could serve as a foundation for the development of courses in sports history or to supplement existing courses in the social studies curriculum at either the elementary, middle, or high school level. The guide is organized into three section: (1) preliminaries, consisting of two sample introductory lectures and a student profile questionnaire; (2) an outline of sports history which includes outlines for 19 lectures ranging from "Sports in the Ancient Near East" to "Sport Themes in the U.S.A.: 1925-1988"; and (3) suggested student activities, primarily consisting of suggested essay topics derived by looking at pictures of sports activities. A bibliography and book review preparation guide are included. (PPB)

Most constitutive models can only simulate cumulative deformation after a limited number of cycles. However, railroad ballast usually experiences a large number of train passages that cause history-dependent long-term deformation. Fractional calculus is an efficient tool for modelling this phenomenon and therefore is incorporated into a constitutive model for predicting the cumulative deformation. The proposed model is further validated by comparing the model predictions with a series of corresponding experimental results. It is observed that the proposed model can realistically simulate the cumulative deformation of ballast from the onset of loading up to a large number of load cycles.

The objective of this dissertation is to examine the orchestration methods of Johannes Brahms, apply these methods to an orchestral transcription of his Sonata for Violin and Piano No. 3 in D Minor, op. 108, and provide a conductor's analysis of the transcription. Chapter 1 gives a brief historical background, and discusses reasons for and methods of the project. Chapter 2 examines general aspects of Brahms's orchestrational style. Chapter 3 addresses the transcription process and its application to the Third Violin Sonata. Chapter 4 explores areas in which a thorough understanding of a work's compositional and orchestrational structure informs performance practice. Chapter 5 discusses differences in chamber and orchestral music observed during the project. The full score of the transcription is included at the end.

Annual scholarly and creative journal sponsored by the Ball State University Honors College.; Contents of this issue: Veggie Tanka -- Spirit -- Beach Tanka -- pins and needles -- explode-dissolve -- Shiny -- Doornails: a prose poem -- Bygone -- Jamaican Sunset -- A Story -- Michelangelo the Unicorn's Sidewalk Cafe -- Dear You, Every Piece of This Life Ride -- Rivers, Veins -- A Fool's Hope -- the blue dress -- Fifteen Seconds -- Floating Market -- Daniela -- Rousseau Confessions - Childhood -- Liquid and Luck -- Hybrid Allegory -- Delicious Salamanders -- Scheduled -- prophecy -- Confused Pastures -- Still Life -- H.O. Model, This archival material has been provided for educational purposes. Ball State University Libraries recognizes that some historic items may include offensive content. Our statement regarding objectionable content is available at: https://dmr.bsu.edu/digital/about

Jody Nagel, director.; Composers : Dan Smith, John Horgeshimer, Chad Powers, John Carter Rice, Adam Goldberg, Daniel Sitler.; Performers : Dan Smith, piano, Jennifer Woodrum, clarinet, Eric Heidbreder, bassoon, Eric Snoza, double bass.; Includes a list of upcoming BSU School of Music events (for March 2016-April 2016)., Series LXX, Number 175., This archival material has been provided for educational purposes. Ball State University Libraries recognizes that some historic items may include offensive content. Our statement regarding objectionable content is available at: https://dmr.bsu.edu/digital/about

Michael Pounds, coordinator.; Composers : Chin Ting Chan, Jaime Reis, Joo Won Park, Eli Fieldsteel, Julius Bucsis, Konstantinos Karathanasis, Carter John Rice.; Includes a list of upcoming BSU School of Music events (for September 2016)., Series LXXI, Number 7., This archival material has been provided for educational purposes. Ball State University Libraries recognizes that some historic items may include offensive content. Our statement regarding objectionable content is available at: https://dmr.bsu.edu/digital/about

Eli Fieldsteel, coordinator.; Composers : Stephen Weigel, Marcea McGuire, Eli Fieldsteel, Angie Chan Ramirez, Julius Bucsis, Mario Davidovsky, Lucas Baughman, Michael Pounds, Carter John Rice, Christoph Thompson.; Includes a list of upcoming BSU School of Music events (for February 2016)., Series LXX, Number 130., This archival material has been provided for educational purposes. Ball State University Libraries recognizes that some historic items may include offensive content. Our statement regarding objectionable content is available at: https://dmr.bsu.edu/digital/about

Natural prefabricated vertical drains (NPVDs) produced from biodegradable materials such as jute and coir have some distinct advantages over conventional polymeric prefabricated vertical drains (CPVDs). For instance, NPVDs are not only able to discharge excess pore pressure effectively but are also beneficial to the environment thanks to their biodegradability. However, due to the biodegradability of the natural fibres, NPVDs can sometimes deteriorate too quickly in an adverse environment such as in highly acidic clay, which hampers the dissipation of excess pore pressure. In this paper, an analytical solution for radial consolidation that considers the time-dependent decay of drain discharge capacity is therefore proposed. The solution is applied to an exponential form of reduction of the drain discharge capacity, and then verified with the experimental results obtained in previous studies. The effect of drain degradation on soil consolidation is simulated using a finite element method (ABAQUS) and these numerical results are then compared to those obtained from the analytical approach. In addition, a new and flexible method using a matching factor to convert the parameters from axisymmetric to plane strain models is introduced and applied to radial consolidation. The modelling outcomes indicate a significant retardation of excess pore pressure dissipation due to drain degradation and this suggests the need to exercise caution when using biodegradable NPVDs.