Development and application of operational techniques for the inventory and monitoring of resources and uses for the Texas coastal zone

The author has identified the following significant results. Four LANDSAT scenes were analyzed for the Harbor Island area test sites to produce land cover and land use maps using both image interpretation and computer-assisted techniques. When evaluated against aerial photography, the mean accuracy for three scenes was 84% for the image interpretation product and 62% for the computer-assisted classification maps. Analysis of the fourth scene was not completed using the image interpretation technique, because of poor quality, false color composite, but was available from the computer technique. Preliminary results indicate that these LANDSAT products can be applied to a variety of planning and management activities in the Texas coastal zone

A study of detecting child pornography on smart phone

© Springer International Publishing AG 2018. Child Pornography is an increasingly visible rising cybercrime in the world today. Over the past decade, with rapid growth in smart phone usage, readily available free Cloud Computing storage, and various mobile communication apps, child pornographers have found a convenient and reliable mobile platform for instantly sharing pictures or videos of children being sexually abused. Within this new paradigm, law enforcement officers are finding that detecting, gathering, and processing evidence for the prosecution of child pornographers is becoming increasingly challenging. Deep learning is a machine learning method that models high-level abstractions in data and extracts hierarchical representations of data by using a deep graph with multiple processing layers. This paper presents a conceptual model of deep learning approach for detecting child pornography within the new paradigm by using log analysis, file name analysis and cell site analysis which investigate text logs of events that have happened in the smart phone at the scene of the crime using physical and logical acquisition to assists law enforcement officers in gathering and processing child pornography evidence for prosecution. In addition, this paper shows an illustrative example of logical and physical acquisition on smart phones using forensics tools

Institutional context: What elements shape how community occupational therapists think about their clients’ care?

Abstract : Clinical reasoning (CR) is the cognitive process that therapists use to plan, direct, perform and reflect on client care. Linked to intervention efficiency and quality, CR is a core competency that occurs within an institutional context (legal, regulatory, administrative and organisational elements). Because this context can shape how community therapists think about their clients’ care, its involvement in their CR could have a major impact on the interventions delivered. However, little is known about this involvement. Our study thus aimed to describe the elements of the institutional context involved in community therapists’ CR. From March 2012 to June 2014, we conducted an institutional ethnography (IE) inquiry in three Health and Social Services Centres in Québec (Canada). We observed participants and conducted semi-structured interviews with 10 occupational therapists. We also interviewed 12 secondary key informants (colleagues and managers) and collected administrative documents (n = 50). We analysed data using the IE process. Of the 13 elements of the institutional context identified, we found that four are almost constantly involved in participants’ CR. These four elements, that is, institutional procedures, organisation's basket of services, occupational therapists’ mandate and wait times for their services, restrictively shape CR. Specifically, occupational therapists restrict their representation of the client's situation and exploration of potential solutions to what is possible within the bounds of these four elements. In light of such restrictions on the way they think about their clients’ care, therapists should pay close attention to the elements of their own institutional context and how they are involved in their CR. Because of its potentially important impact on the future of professions (e.g. further restrictions on professionals’ role, reduced contribution to population health and well-being), this involvement of the institutional context in CR concerns all professionals, be they clinicians, educators, researchers or regulatory college officers

Simulating aerosol microphysics with the ECHAM/MADE GCM ? Part I: Model description and comparison with observations

International audienceThe aerosol dynamics module MADE has been coupled to the general circulation model ECHAM4 to simulate the chemical composition, number concentration, and size distribution of the global submicrometer aerosol. The present publication describes the new model system ECHAM4/MADE and presents model results in comparison with observations. The new model is able to simulate the full life cycle of particulate matter and various gaseous precursors including emissions of primary particles and trace gases, advection, convection, diffusion, coagulation, condensation, nucleation of sulfuric acid vapor, aerosol chemistry, cloud processing, and size-dependent dry and wet deposition. Aerosol components considered are sulfate (SO4), ammonium (NH4), nitrate (NO3), black carbon (BC), particulate organic matter (POM), sea salt, mineral dust, and aerosol liquid water. The model is numerically efficient enough to allow long term simulations, which is an essential requirement for application in general circulation models. In order to evaluate the results obtained with this new model system, calculated mass concentrations, particle number concentrations, and size distributions are compared to observations. The intercomparison shows, that ECHAM4/MADE is able to reproduce the major features of the geographical patterns, seasonal cycle, and vertical distributions of the basic aerosol parameters. In particular, the model performs well under polluted continental conditions in the northern hemispheric lower and middle troposphere. However, in comparatively clean remote areas, e.g. in the upper troposphere or in the southern hemispheric marine boundary layer, the current model version tends to underestimate particle number concentrations

Helicity sensitive terahertz radiation detection by dual-grating-gate high electron mobility transistors

We report on the observation of a radiation helicity sensitive photocurrent excited by terahertz (THz) radiation in dual-grating-gate (DGG) InAlAs/InGaAs/InAlAs/InP high electron mobility transistors (HEMT). For a circular polarization the current measured between source and drain contacts changes its sign with the inversion of the radiation helicity. For elliptically polarized radiation the total current is described by superposition of the Stokes parameters with different weights. Moreover, by variation of gate voltages applied to individual gratings the photocurrent can be defined either by the Stokes parameter defining the radiation helicity or those for linear polarization. We show that artificial non-centrosymmetric microperiodic structures with a two-dimensional electron system excited by THz radiation exhibit a dc photocurrent caused by the combined action of a spatially periodic in-plane potential and spatially modulated light. The results provide a proof of principle for the application of DGG HEMT for all-electric detection of the radiation's polarization state.Comment: 7 pages, 4 figure

Wiring up pre-characterized single-photon emitters by laser lithography

Future quantum optical chips will likely be hybrid in nature and include many single-photon emitters, waveguides, filters, as well as single-photon detectors. Here, we introduce a scalable optical localization-selection-lithography procedure for wiring up a large number of single-photon emitters via polymeric photonic wire bonds in three dimensions. First, we localize and characterize nitrogen vacancies in nanodiamonds inside a solid photoresist exhibiting low background fluorescence. Next, without intermediate steps and using the same optical instrument, we perform aligned three-dimensional laser lithography. As a proof of concept, we design, fabricate, and characterize three-dimensional functional waveguide elements on an optical chip. Each element consists of one single-photon emitter centered in a crossed-arc waveguide configuration, allowing for integrated optical excitation and efficient background suppression at the same time

Public health program capacity for sustainability: A new framework

Abstract Background Public health programs can only deliver benefits if they are able to sustain activities over time. There is a broad literature on program sustainability in public health, but it is fragmented and there is a lack of consensus on core constructs. The purpose of this paper is to present a new conceptual framework for program sustainability in public health. Methods This developmental study uses a comprehensive literature review, input from an expert panel, and the results of concept-mapping to identify the core domains of a conceptual framework for public health program capacity for sustainability. The concept-mapping process included three types of participants (scientists, funders, and practitioners) from several public health areas (e.g., tobacco control, heart disease and stroke, physical activity and nutrition, and injury prevention). Results The literature review identified 85 relevant studies focusing on program sustainability in public health. Most of the papers described empirical studies of prevention-oriented programs aimed at the community level. The concept-mapping process identified nine core domains that affect a program’s capacity for sustainability: Political Support, Funding Stability, Partnerships, Organizational Capacity, Program Evaluation, Program Adaptation, Communications, Public Health Impacts, and Strategic Planning. Concept-mapping participants further identified 93 items across these domains that have strong face validity—89% of the individual items composing the framework had specific support in the sustainability literature. Conclusions The sustainability framework presented here suggests that a number of selected factors may be related to a program’s ability to sustain its activities and benefits over time. These factors have been discussed in the literature, but this framework synthesizes and combines the factors and suggests how they may be interrelated with one another. The framework presents domains for public health decision makers to consider when developing and implementing prevention and intervention programs. The sustainability framework will be useful for public health decision makers, program managers, program evaluators, and dissemination and implementation researchers

Machine Learning Assisted Design of Experiments for Solid State Electrolyte Lithium Aluminum Titanium Phosphate

Lithium-ion batteries with solid electrolytes offer safety, higher energy density and higher long-term performance, which are promising alternatives to conventional liquid electrolyte batteries. Lithium aluminum titanium phosphate (LATP) is one potential solid electrolyte candidate due to its high Li-ion conductivity. To evaluate its performance, influences of the experimental factors on the materials design need to be investigated systematically. In this work, a materials design strategy based on machine learning (ML) is employed to design experimental conditions for the synthesis of LATP. In the variation of parameters, we focus on the tolerance against the possible deviations in the concentration of the precursors, as well as the influence of sintering temperature and holding time. Specifically, models built with different design selection strategies are compared based on the training data assembled from previous laboratory experiments. The best one is then chosen to design new experiment parameters, followed by measuring the corresponding properties of the newly synthesized samples. A previously unknown sample with ionic conductivity of 1.09 × 10$^{-3}$ S cm$^{-1}$ is discovered within several iterations. In order to further understand the mechanisms governing the high ionic conductivity of these samples, the resulting phase compositions and crystal structures are studied with X-ray diffraction, while the microstructures of sintered pellets are investigated by scanning electron microscopy. Our studies demonstrate the advantages of applying machine learning in designing experimental conditions by the synthesis of desired materials, which can effectively help researchers to reduce the number of required experiments