The Threat to Interest-Free Home Financing: The Problem of State Governments\u27 Prohibition of Islamic-Compliant Financing Agreements

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A case study in the use of mentorships in academic instructional coach development.

Academic instructional coaches have long been used to support teacher development and student learning. As a recent position in the education field, there is little information regarding the development of staff in this role. This study sought to better understand how academic instructional coaches are mentored and developed within challenging school contexts. The theoretical framework for this research is guided by the social constructivism epistemology. In alignment with this framework, a collective case study was utilized to better understand the relationship between the principal and the academic instructional coach. Exploring this relationship emphasized how principals support academic instructional coach growth. Findings highlight the importance of academic instructional coach and principal relationships in forming clear opportunities to have honest dialogue and foster feelings of support. The research shows there is an overall lack of systems to support coaches and develop necessary relationships although coaches desire and seek out these opportunities. The Accelerated Improvement School context presented numerous challenges for principals and coaches. However, this particular context does offer some benefits including an atmosphere of collegiality, team support, and friendship that propagated relationships

Finding Australia’s social enterprise sector: final report

Executive Summary Social enterprises are organisations that: Are led by an economic, social, cultural, or environmental mission consistent with a public or community benefit; Trade to fulfil their mission; Derive a substantial portion of their income from trade; and Reinvest the majority of their profit/surplus in the fulfilment of their mission. This document reports on the research findings of the Finding Australia’s Social Enterprise Sector (FASES) project. FASES is a joint initiative of Social Traders and the Australian Centre for Philanthropy and Nonprofit Studies, Queensland University of Technology. It is a first attempt to identify the range and scope of social enterprises in Australia. The methodology utilised in this research included: a review of existing literature and methods of social enterprise mapping; establishment of a project website and preliminary discussion paper to stimulate public engagement with defining and identifying Australian social enterprises, which resulted in four online responses to the discussion paper and 157 nominations of social enterprises to be included in the research; a series of workshops and interviews with 34 key informants to assist in defining social enterprise for the purposes of the research; identification of the social enterprise population through a combination of web and media review, review of existing databases and feedback through the project website; development and administration of an online survey; and collation and analysis of secondary data. Five hundred and thirty-nine organisations commenced the online survey, of which 365 were valid social enterprises according to our definition. Based on pre-existing research data and information from our survey, we estimate that there are up to 20 000 Australian social enterprises. This estimate takes into account that some not for profit organisations have multiple business ventures, and that not all social enterprises are incorporated as not for profits. Our survey results suggest that the Australian social enterprise sector is mature, sustainable and internally diverse with regard to mission and organisational structure. Amongst the 365 survey respondents, 73% had been operational for at least five years, and 62% were at least 10 years old. Australian social enterprises seek to fulfil a diversity of missions and serve a wide variety of beneficiaries. As a whole, the dominant foci of our survey respondents were on creating opportunities for people to participate in their community, and on finding new solutions to social, environmental, cultural and economic problems. Australian social enterprises operate in every industry of our economy. Our survey data suggest that they trade predominantly in local and regional markets and focus on fulfilling their missions at local and regional goals. However, some social enterprises operate in international markets and seek to respond to missions of international scope

Refining reproductive parameters for modelling sustainability and extinction in hunted primate populations in the Amazon

Funding: Collections were made voluntarily by local people as part of a community conservation project. Some materials were paid for by YAVACUS, a Peruvian NGO.Primates are frequently hunted in Amazonia. Assessing the sustainability of hunting is essential to conservation planning. The most-used sustainability model, the 'Production Model', and more recent spatial models, rely on basic reproductive parameters for accuracy. These parameters are often crudely estimated. To date, parameters used for the Amazon's most-hunted primate, the woolly monkey (Lagothrix spp.), come from captive populations in the 1960s, when captive births were rare. Furthermore, woolly monkeys have since been split into five species. We provide reproductive parameters calculated by examining the reproductive organs of female Poeppig's woolly monkeys (Lagothrix poeppigii), collected by hunters as part of their normal subsistence activity. Production was 0.48-0.54 young per female per year, and an interbirth interval of 22.3 to 25.2 months, similar to parameters from captive populations. However, breeding was seasonal, which imposes limits on the maximum reproductive rate attainable. We recommend the use of spatial models over the Production Model, since they are less sensitive to error in estimated reproductive rates. Further refinements to reproductive parameters are needed for most primate taxa. Methods like ours verify the suitability of captive reproductive rates for sustainability analysis and population modelling for populations under differing conditions of hunting pressure and seasonality. Without such research, population modelling is based largely on guesswork.Publisher PDFPeer reviewe

Group Decision Diagrams (GDDs): A Data Structure for Mathematical Groups

Groups are an element of abstract algebra that are used in a number of different domains such as physics, chemistry, statistics and cryptography. Set operations like union, intersection and cartesian product on groups are fundamental to more complex algorithms and methods of analysis in the aforementioned fields. A concise representation of groups can help improve the speed and ease at which binary operations like taking union and intersection can be carried out on them. In abstract algebra, a group is an infinite or finite set of elements that satisfies the axioms of closure, associativity, inverse and identity. For the purpose of this project we will only consider finite abelian group. If the group operation is commutative over a group it is called an abelian group. According to the fundamental theorem of finitely-generated abelian groups, a finite abelian group has a unique decomposition that allows it to be expressed as the direct product of cyclic groups. Further, cyclic groups can be described using a single element that generates the group. The existence of a unique decomposition for finite abelian groups makes it ideal to use a decision tree for its representation. A decision tree is a data structure where each parent node represents a decision and each child node is one of the outcomes. Our decision tree for groups can have each node be the generator representing a cyclic group from its decomposition. This data structure is based on the prior work of Shin-ichi Minato on permutation decision diagrams, that is, binary decision tree for storing sets of permutations, and subsequent work we did last summer. The decision diagram for a set of permutations is a decision tree with each node representing elemental transpositions obtained using a decomposition algorithm where if a permutation has an accepting path through the diagram, it is a member of the set. This project models a similar data structure for storing groups which will allow set operations to be carried out with relative efficiency on them just like it did for large sets of permutations using Python. We also conducted time analysis on the operations and found that multiplying two groups together takes the most amount of time using our data structure, followed by the transpose function which swaps all two indexes of every permutation in the data structure. Overall we found that our data structure is considerably effective in taking intersections and unions of group. However, some work needs to be done for a more effective implementation of multip[ly and transpose operations

Meeting the Challenges of an Aging Population with Success

With 117,099 people over the age of 65, Franklin County has the second-highest number of seniors among all Ohio counties. Projection data from the Ohio Department of Development indicates that Franklin County's 65-and-over population will grow to 224,340 by the year 2040. Key findings from this report indicate that improved coordination between the complex web of federal, state, county, and municipal resources would have significant impact on seniors' health and quality of life. The report also includes an analysis of the most vulnerable seniors in Franklin County identified at the neighborhood level

Towards high-throughput 3D insect capture for species discovery and diagnostics

Digitisation of natural history collections not only preserves precious information about biological diversity, it also enables us to share, analyse, annotate and compare specimens to gain new insights. High-resolution, full-colour 3D capture of biological specimens yields color and geometry information complementary to other techniques (e.g., 2D capture, electron scanning and micro computed tomography). However 3D colour capture of small specimens is slow for reasons including specimen handling, the narrow depth of field of high magnification optics, and the large number of images required to resolve complex shapes of specimens. In this paper, we outline techniques to accelerate 3D image capture, including using a desktop robotic arm to automate the insect handling process; using a calibrated pan-tilt rig to avoid attaching calibration targets to specimens; using light field cameras to capture images at an extended depth of field in one shot; and using 3D Web and mixed reality tools to facilitate the annotation, distribution and visualisation of 3D digital models.Comment: 2 pages, 1 figure, for BigDig workshop at 2017 eScience conferenc

Effects of subtherapeutic concentrations of antimicrobials on gene acquisition events in Yersinia, Proteus, Shigella, and Salmonella recipient organisms in isolated ligated intestinal loops of swine

Objective—To assess antimicrobial resistance and transfer of virulence genes facilitated by subtherapeutic concentrations of antimicrobials in swine intestines. Animals—20 anesthetized pigs experimentally inoculated with donor and recipient bacteria. Procedures—4 recipient pathogenic bacteria (Salmonella enterica serotype Typhimurium, Yersinia enterocolitica, Shigella flexneri, or Proteus mirabilis) were incubated with donor bacteria in the presence of subinhibitory concentrations of 1 of 16 antimicrobials in isolated ligated intestinal loops in swine. Donor Escherichia coli contained transferrable antimicrobial resistance or virulence genes. After coincubations, intestinal contents were removed and assessed for pathogens that acquired new antimicrobial resistance or virulence genes following exposure to the subtherapeutic concentrations of antimicrobials. Results—3 antimicrobials (apramycin, lincomycin, and neomycin) enhanced transfer of an antimicrobial resistance plasmid from commensal E coli organisms to Yersinia and Proteus organisms, whereas 7 antimicrobials (florfenicol, hygromycin, penicillin G, roxarsone, sulfamethazine, tetracycline, and tylosin) exacerbated transfer of an integron (Salmonella genomic island 1) from Salmonella organisms to Yersinia organisms. Sulfamethazine induced the transfer of Salmonella pathogenicity island 1 from pathogenic to nonpathogenic Salmonella organisms. Six antimicrobials (bacitracin, carbadox, erythromycin, sulfathiazole, tiamulin, and virginiamycin) did not mediate any transfer events. Sulfamethazine was the only antimicrobial implicated in 2 types of transfer events. Conclusions and Clinical Relevance—10 of 16 antimicrobials at subinhibitory or subtherapeutic concentrations augmented specific antimicrobial resistance or transfer of virulence genes into pathogenic bacteria in isolated intestinal loops in swine. Use of subtherapeutic antimicrobials in animal feed may be associated with unwanted collateral effects

Insights from unifying modern approximations to infections on networks

Networks are increasingly central to modern science owing to their ability to conceptualize multiple interacting components of a complex system. As a specific example of this, understanding the implications of contact network structure for the transmission of infectious diseases remains a key issue in epidemiology. Three broad approaches to this problem exist: explicit simulation; derivation of exact results for special networks; and dynamical approximations. This paper focuses on the last of these approaches, and makes two main contributions. Firstly, formal mathematical links are demonstrated between several prima facie unrelated dynamical approximations. And secondly, these links are used to derive two novel dynamical models for network epidemiology, which are compared against explicit stochastic simulation. The success of these new models provides improved understanding about the interaction of network structure and transmission dynamics