Heuristics and Biases in the Intuitive Projection of Retail Sales

Retail merchandise buyers are shown to exhibit a nonregressive bias when making sales projections. A quantitative model based on the principle of statistical regression is found to outperform the judgmental sales predictions of experienced buyers. Implications for the appropriate roles of intuitive and model-based decision making in retail merchandise buying are discussed

Reconfiguring an Irrigation Landscape to Improve Provision of Ecosystem Services

Over-allocation of fresh water resources to consumptive uses, coupled with recurring drought and the prospect of climate change, is compromising the stocks of natural capital in the world’s basins and reducing their ability to provide ecosystem services. To combat this, governments world wide are making significant investment in efforts to improve sharing of water between consumptive uses and the environment, with many investments centred on modernisation of inefficient irrigation delivery systems, and the purchase of water by government for environmental flows. In this study, spatial targeting was applied within a cost-benefit framework to reconfigure agricultural land use in an irrigation district to achieve a 20% reduction in agricultural water use to increase environmental flows and improve the provision of other ecosystem services. We demonstrate using spatial planning and optimisation models that a targeted land use reconfiguration policy approach could potentially increase the net present value of ecosystem services by up to AUS$463.7m. This provides a threshold level of investment that would be justified on the basis of benefits that the investment produces. The increase in ecosystem services include recovering 61 GL of water for environmental flows, the sequestration of 10.6m tonnes of CO2-e/yr, a 13 EC (?S/cm) reduction in river salinity, and an overall 24$68.7m in economic returns to agriculture which may be only marginally offset by the increased value of ecosystem services resulting from the return of 61 GL of water to the environment.landscape planning, geographic information systems, cost-benefit analysis, irrigation, climate change, water management, spatial targeting, environmental valuation

Poisson-event-based analysis of cell proliferation.

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture

Honeycomb Structures for High Shear Flexure

The present invention provides an improved shear band for use in non-pneumatic tires, pneumatic tires, and other technologies. The improved shear band is uniquely constructed of honeycomb shaped units that can replace the elastomeric continuum materials such as natural or synthetic rubber or polyurethane that are typically used. In particular, honeycomb structures made of high modulus materials such as metals or polycarbonates are used that provide the desired shear strains and shear modulus when subjected to stress. When used in tire construction, improvements in rolling resistance can be obtained because of less mass being deformed and reduced hysteresis provided by these materials. The resulting mass of the shear band is greatly reduced if using low density materials. Higher density materials can be used (such as metals) without increasing mass while utilizing their characteristic low energy loss

Luminescence Properties of Thin Film Ta2 Zn3 O8 and Mn Doped Ta2 Zn3 O8

Blue luminescence from TaZZn30g and green luminescence from Mn doped TaZZn30g has been observed under low voltage cathodoluminescent excitation, In this article , the luminescence mechanisms of TaZZn30g and Mn doped TaZZn30 g are discussed in detail. The results suggest that the intrinsic blue luminescence of TaZZn30g results from a metal-to-ligand transition, whereas the green luminescence of Mn doped TaZZn30g results from the Mn 4T 1-6A I transition. The suppression of the blue intrinsic luminescence in Mn doped TaZZn30g suggests that efficient energy transfer from the host material to the Mn occurs. This energy transfer phenomenon is also discussed by comparing the photoluminescence excitation spectra of both thin film materials. Finally, the relative efficiency versus voltage and current density is demonstrated and discussed pertaining to field emission device operation

Optimization of switching losses and capacitor voltage ripple using model predictive control of a cascaded H-bridge multi-level StatCom

This paper further develops a Model Predictive Control (MPC) scheme which is able to exploit the large number of redundant switching states available in a multi-level H-bridge StatCom (H-StatCom). The new sections of the scheme provide optimised methods to trade off the harmonic performance with converter switching losses and capacitor voltage ripple. Varying the pulse placement within the modulation scheme and modifying the heuristic model of the voltage balancing characteristics allows the MPC scheme to achieve superior performance to that of the industry standard phase shifted carrier modulation technique. The effects of capacitor voltage ripple on the lifetime of the capacitors is also investigated. It is shown that the MPC scheme can reduce capacitor voltage ripple and increase capacitor lifetime. Simulation and experimental results are presented that confirm the correct operation of the control and modulation strategies

Image-Based Cell Profiling Enables Quantitative Tissue Microscopy in Gastroenterology.

Immunofluorescence microscopy is an essential tool for tissue-based research, yet data reporting is almost always qualitative. Quantification of images, at the per-cell level, enables "flow cytometry-type" analyses with intact locational data but achieving this is complex. Gastrointestinal tissue, for example, is highly diverse: from mixed-cell epithelial layers through to discrete lymphoid patches. Moreover, different species (e.g., rat, mouse, and humans) and tissue preparations (paraffin/frozen) are all commonly studied. Here, using field-relevant examples, we develop open, user-friendly methodology that can encompass these variables to provide quantitative tissue microscopy for the field. Antibody-independent cell labeling approaches, compatible across preparation types and species, were optimized. Per-cell data were extracted from routine confocal micrographs, with semantic machine learning employed to tackle densely packed lymphoid tissues. Data analysis was achieved by flow cytometry-type analyses alongside visualization and statistical definition of cell locations, interactions and established microenvironments. First, quantification of Escherichia coli passage into human small bowel tissue, following Ussing chamber incubations exemplified objective quantification of rare events in the context of lumen-tissue crosstalk. Second, in rat jejenum, precise histological context revealed distinct populations of intraepithelial lymphocytes between and directly below enterocytes enabling quantification in context of total epithelial cell numbers. Finally, mouse mononuclear phagocyte-T cell interactions, cell expression and significant spatial cell congregations were mapped to shed light on cell-cell communication in lymphoid Peyer's patch. Accessible, quantitative tissue microscopy provides a new window-of-insight to diverse questions in gastroenterology. It can also help combat some of the data reproducibility crisis associated with antibody technologies and over-reliance on qualitative microscopy. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC. on behalf of International Society for Advancement of Cytometry.UK Medical Research Council (grant number MR/R005699/1) UK Engineering and Physical Sciences Research Council (grant EP/H008683/1) UK Biotechnology and Biological Sciences Research Council (grant number BB/P026818/1

Image-Based Cell Profiling Enables Quantitative Tissue Microscopy in Gastroenterology.

Immunofluorescence microscopy is an essential tool for tissue-based research, yet data reporting is almost always qualitative. Quantification of images, at the per-cell level, enables "flow cytometry-type" analyses with intact locational data but achieving this is complex. Gastrointestinal tissue, for example, is highly diverse: from mixed-cell epithelial layers through to discrete lymphoid patches. Moreover, different species (e.g., rat, mouse, and humans) and tissue preparations (paraffin/frozen) are all commonly studied. Here, using field-relevant examples, we develop open, user-friendly methodology that can encompass these variables to provide quantitative tissue microscopy for the field. Antibody-independent cell labeling approaches, compatible across preparation types and species, were optimized. Per-cell data were extracted from routine confocal micrographs, with semantic machine learning employed to tackle densely packed lymphoid tissues. Data analysis was achieved by flow cytometry-type analyses alongside visualization and statistical definition of cell locations, interactions and established microenvironments. First, quantification of Escherichia coli passage into human small bowel tissue, following Ussing chamber incubations exemplified objective quantification of rare events in the context of lumen-tissue crosstalk. Second, in rat jejenum, precise histological context revealed distinct populations of intraepithelial lymphocytes between and directly below enterocytes enabling quantification in context of total epithelial cell numbers. Finally, mouse mononuclear phagocyte-T cell interactions, cell expression and significant spatial cell congregations were mapped to shed light on cell-cell communication in lymphoid Peyer's patch. Accessible, quantitative tissue microscopy provides a new window-of-insight to diverse questions in gastroenterology. It can also help combat some of the data reproducibility crisis associated with antibody technologies and over-reliance on qualitative microscopy. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC. on behalf of International Society for Advancement of Cytometry.UK Medical Research Council (grant number MR/R005699/1) UK Engineering and Physical Sciences Research Council (grant EP/H008683/1) UK Biotechnology and Biological Sciences Research Council (grant number BB/P026818/1

Adjacent Slice Prostate Cancer Prediction to Inform MALDI Imaging Biomarker Analysis

Prostate cancer is the second most common type of cancer among men in US [1]. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. Proteomic biomarkers can improve upon these methods. MALDI molecular spectra imaging is used to visualize protein/peptide concentrations across biopsy samples to search for biomarker candidates. Unfortunately, traditional processing methods require histopathological examination on one slice of a biopsy sample while the adjacent slice is subjected to the tissue destroying desorption and ionization processes of MALDI. The highest confidence tumor regions gained from the histopathological analysis are then mapped to the MALDI spectra data to estimate the regions for biomarker identification from the MALDI imaging. This paper describes a process to provide a significantly better estimate of the cancer tumor to be mapped onto the MALDI imaging spectra coordinates using the high confidence region to predict the true area of the tumor on the adjacent MALDI imaged slice