Iowa Highway Program, Finances and Progress, 1954

(a) Iowa has a total of 101,451 miles of rural roads, both primary and secondary. (b) On January 1, l954, a total of 77,024 miles of these rural roads were surfaced - mostly with gravel and crushed stone. This is 5,53l miles greater than on January l, 1952. (c) Additional roads are being surfaced at the rate of 2766 miles per year. (d) Iowa's highway program provides for a surfaced road to every reasonably located rural home and a paved or other type of dustless surface on all primary roads. (e) Iowa's highway funds come 25.4 per cent from property taxes and special taxes......................................$29,708,546.67 63.7 per cent from road use taxes.......... 74,581,080.30 10.6 per cent from Federal Aid (1952 Act).. 12,424,000.00 0.3 per cent from miscellaneous receipts.. 287,922.86 ---- ------------- 100.0 $117,001,549.83 (f) Annual income under present laws, available for highway construction, is approximately, For primary roads $29,420,000.00 For secondary roads $44,328,000.00 In 19_3, $7,299,000 of secondary road construction funds was transferred to the maintenance fund. (g) Iowa's highway improvements are being paid for as built. No new bonds are being issued.

2017-2021 Iowa Transportation Improvement Program

This document describes planned investments in Iowa’s multimodal transportation system including aviation, transit, railroads, trails, and highways. This five-year program documents $3.5 billion of highway and bridge construction projects on the primary road system using federal and state funding. Of that funding, a little over $500 million is available due to the passage of Senate File 257 in February 2015. As required by Senate File 257, this program includes a list of the critical highway and bridge projects funded with the additional revenue. Since last year’s program, a new federal surface transportation authorization bill was passed and signed into law. This authorization bill is titled Fixing America’s Surface Transportation (FAST) Act. The FAST Act, for the first time in many years, provides federal funding certainty over most of the time covered by this Program. In addition, it provided additional federal funding for highway and bridge projects.

Citizen science and natural resource governance: program design for vernal pool policy innovation

Effective natural resource policy depends on knowing what is needed to sustain a resource and building the capacity to identify, develop, and implement flexible policies. This retrospective case study applies resilience concepts to a 16-year citizen science program and vernal pool regulatory development process in Maine, USA. We describe how citizen science improved adaptive capacities for innovative and effective policies to regulate vernal pools. We identified two core program elements that allowed people to act within narrow windows of opportunity for policy transformation, including (1) the simultaneous generation of useful, credible scientific knowledge and construction of networks among diverse institutions, and (2) the formation of diverse leadership that promoted individual and collective abilities to identify problems and propose policy solutions. If citizen science program leaders want to promote social-ecological systems resilience and natural resource policies as outcomes, we recommend they create a system for internal project evaluation, publish scientific studies using citizen science data, pursue resources for program sustainability, and plan for leadership diversity and informal networks to foster adaptive governance.

EXAMINING THE IMPACT OF TEACHER PRACTICE ON STUDENT LEARNING IN INTERACTIVE RADIO INSTRUCTION (IRI) CLASSROOMS: LESSONS FROM NEW DELHI AND RAJASTHAN (INDIA)

This quantitative study examines the impact of teacher practices on student achievement in classrooms where the English is Fun Interactive Radio Instruction (IRI) programs were being used. A contemporary IRI design using a dual-audience approach, the English is Fun IRI programs delivered daily English language instruction to students in grades 1 and 2 in Delhi and Rajasthan through 120 30-minute programs via broadcast radio (the first audience) while modeling pedagogical techniques and behaviors for their teachers (the second audience). Few studies have examined how the dual-audience approach influences student learning. Using existing data from 32 teachers and 696 students, this study utilizes a multivariate multilevel model to examine the role of the primary expectations for teachers (e.g., setting up the IRI classroom, following instructions from the radio characters and ensuring students are participating) and the role of secondary expectations for teachers (e.g., modeling pedagogies and facilitating learning beyond the instructions) in promoting students’ learning in English listening skills, knowledge of vocabulary and use of sentences. The study finds that teacher practice on both sets of expectations mattered, but that practice in the secondary expectations mattered more. As expected, students made the smallest gains in the most difficult linguistic task (sentence use). The extent to which teachers satisfied the primary and secondary expectations was associated with gains in all three skills – confirming the relationship between students’ English proficiency and teacher practice in a dual-audience program. When it came to gains in students’ scores in sentence use, a teacher whose focus was greater on primary expectations had a negative effect on student performance in both states. In all, teacher practice clearly mattered but not in the same way for all three skills. An optimal scenario for teacher practice is presented in which gains in all three skills are maximized. These findings have important implications for the way the classroom teacher is cast in IRI programs that utilize a dual-audience approach and in the way IRI programs are contracted insofar as the role of the teacher in instruction is minimized and access is limited to instructional support from the IRI lessons alone.

An Investigation of the Impact of an Aspiring Principals Preparation Program on Principal Leadership Effectiveness

School districts need to “build the bench” to ensure that their schools will have effective principals when vacancies arise (Johnson-Taylor & Martin, 2007). Assistant principals represent a potential pool of new school leaders who are prepared to move confidently into the principalship (Oliver, 2005). Although a critical leader in schools, the assistant principal position is underutilized and under-researched (Oleszewski, Shoho, & Barnett, 2012). This lack of focus on assistant principals is concerning because they are part of the school leadership team and often advance to the position of school principal. The purpose of this study was to examine the impact of Bay City Public Schools’ (a pseudonym) Aspiring Principals Preparation Program (AP3; also a pseudonym) on assistant principals’ learning-centered leadership behaviors, as assessed by the Vanderbilt Assessment of Leadership in Education (Val-Ed) survey. The study compared the Val-Ed scores of assistant principals who had participated in one of three cohorts of AP3 training to the scores of assistant principals who did not participate. The results indicated that participation in the AP3 had no significant impact on respondents’ learning-centered leadership behaviors, as assessed on the VAL-ED instrument. This study may be useful as the district seeks to validate the effectiveness of AP3 and identify potential refinements and program modifications.

Fold and Unfold for Program Semantics

In this paper we explain how recursion operators can be used to structure and reason about program semantics within a functional language. In particular, we show how the recursion operator fold can be used to structure denotational semantics, how the dual recursion operator unfold can be used to structure operational semantics, and how algebraic properties of these operators can be used to reason about program semantics. The techniques are explained with the aid of two main examples, the first concerning arithmetic expressions, and the second concerning Milner's concurrent language CCS. The aim of the paper is to give functional programmers new insights into recursion operators, program semantics, and the relationships between them.

A Relational Derivation of a Functional Program

This article is an introduction to the use of relational calculi in deriving programs. Using the relational caluclus Ruby, we derive a functional program that adds one bit to a binary number to give a new binary number. The resulting program is unsurprising, being the standard $quot;column of half-adders$quot;, but the derivation illustrates a number of points about working with relations rather than with functions.

Five-year review of an international clinical research-training program

The exponential increase in clinical research has profoundly changed medical sciences. Evidence that has accumulated in the past three decades from clinical trials has led to the proposal that clinical care should not be based solely on clinical expertise and patient values, and should integrate robust data from systematic research. As a consequence, clinical research has become more complex and methods have become more rigorous, and evidence is usually not easily translated into clinical practice. Therefore, the instruction of clinical research methods for scientists and clinicians must adapt to this new reality. To address this challenge, a global distance-learning clinical research-training program was developed, based on collaborative learning, the pedagogical goal of which was to develop critical thinking skills in clinical research. We describe and analyze the challenges and possible solutions of this course after 5 years of experience (2008-2012) with this program. Through evaluation by students and faculty, we identified and reviewed the following challenges of our program: 1) student engagement and motivation, 2) impact of heterogeneous audience on learning, 3) learning in large groups, 4) enhancing group learning, 5) enhancing social presence, 6) dropouts, 7) quality control, and 8) course management. We discuss these issues and potential alternatives with regard to our research and background.

The NumbersWithNames Program

We present the NumbersWithNames program which performs data-mining on the Encyclopedia of Integer Sequences to find interesting conjectures in number theory. The program forms conjectures by finding empirical relationships between a sequence chosen by the user and those in the Encyclopedia. Furthermore, it transforms the chosen sequence into another set of sequences about which conjectures can also be formed. Finally, the program prunes and sorts the conjectures so that themost plausible ones are presented first. We describe here the many improvements to the previous Prolog implementation which have enabled us to provide NumbersWithNames as an online program. We also present some new results from using NumbersWithNames, including details of an automated proof plan of a conjecture NumbersWithNames helped to discover.

Assessment of faculty training program for the use of e-learning platforms: analysis of current use

5th International Conference on Education and New Learning Technologies (Barcelona, Spain. 1-3 July, 2013)

A new age of fuel performance code criteria studied through advanced atomistic simulation techniques

A fundamental step in understanding the effects of irradiation on metallic uranium and uranium dioxide ceramic fuels, or any material, must start with the nature of radiation damage on the atomic level. The atomic damage displacement results in a multitude of defects that influence the fuel performance. Nuclear reactions are coupled, in that changing one variable will alter others through feedback. In the field of fuel performance modeling, these difficulties are addressed through the use of empirical models rather than models based on first principles. Empirical models can be used as a predictive code through the careful manipulation of input variables for the limited circumstances that are closely tied to the data used to create the model. While empirical models are efficient and give acceptable results, these results are only applicable within the range of the existing data. This narrow window prevents modeling changes in operating conditions that would invalidate the model as the new operating conditions would not be within the calibration data set. This work is part of a larger effort to correct for this modeling deficiency. Uranium dioxide and metallic uranium fuels are analyzed through a kinetic Monte Carlo code (kMC) as part of an overall effort to generate a stochastic and predictive fuel code. The kMC investigations include sensitivity analysis of point defect concentrations, thermal gradients implemented through a temperature variation mesh-grid, and migration energy values. In this work, fission damage is primarily represented through defects on the oxygen anion sublattice. Results were also compared between the various models. Past studies of kMC point defect migration have not adequately addressed non-standard migration events such as clustering and dissociation of vacancies. As such, the General Utility Lattice Program (GULP) code was utilized to generate new migration energies so that additional non-migration events could be included into kMC code in the future for more comprehensive studies. Defect energies were calculated to generate barrier heights for single vacancy migration, clustering and dissociation of two vacancies, and vacancy migration while under the influence of both an additional oxygen and uranium vacancy.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

“Deep-Arvor”: A new profiling float to extend the Argo observations down to 4000m depth.

The international Argo program, consisting of a global array of more than 3000 free-drifting profiling floats, has now been monitoring the upper 2000 meters of the ocean for several years. One of its main proposed evolutions is to be able to reach the deeper ocean in order to better observe and understand the key role of the deep ocean in the climate system. For this purpose, Ifremer has designed the new “Deep-Arvor” profiling float: it extends the current operational depth down to 4000 meters, and measures temperature and salinity for up to 150 cycles with CTD pumping continuously and 200 cycles in spot sampling mode. High resolution profiles (up to 2000 points) can be transmitted and data are delivered in near real time according to Argo requirements. Deep-Arvor can be deployed everywhere at sea without any pre-ballasting operation and its light weight (~ 26kg) makes its launching easy. Its design was done to target a cost effective solution. Predefined spots have been allocated to add an optional oxygen sensor and a connector for an extra sensor. Extensive laboratory tests were successful. The results of the first at sea experiments showed that the expected performances of the operational prototypes had been reached (i.e. to perform up to 150 cycles). Meanwhile, the industrialization phase was completed in order to manufacture the Deep-Arvor float for the pilot experiment in 2015. In this paper, we detail all the steps of the development work and present the results from the at sea experiments.

Transportation map of New Jersey.

Scale ca. 1:538,560; 1 in. represents approx. 8.5 miles.

Transportation map of New Jersey.

Scale ca. 1:538,560; 1 in. represents approx. 8.5 miles.