Universal inversion formulas for recovering a function from spherical means

The problem of reconstruction a function from spherical means is at the heart of several modern imaging modalities and other applications. In this paper we derive universal back-projection type reconstruction formulas for recovering a function in arbitrary dimension from averages over spheres centered on the boundary an arbitrarily shaped smooth convex domain. Provided that the unknown function is supported inside that domain, the derived formulas recover the unknown function up to an explicitly computed smoothing integral operator. For elliptical domains the integral operator is shown to vanish and hence we establish exact inversion formulas for recovering a function from spherical means centered on the boundary of elliptical domains in arbitrary dimension.Comment: [20 pages, 2 figures] Compared to the previous versions I corrected some typo

Reductions in global biodiversity loss predicted from conservation spending

Halting global biodiversity loss is central to both the Convention on Biological Diversity (CBD) and United Nations Sustainable Development Goals (SDGs)1,2, but success to date has been very limited3–5. A critical determinant of overall strategic success (or failure) is the financing committed to biodiversity6–9; however, financing decisions are still hindered by considerable uncertainty over what any investment is likely to achieve6–9.. For greater effectiveness, we need an evidence-based model (EBM)10–12 showing how conservation spending quantitatively reduces the rate of loss. Here, we empirically quantify how i$14.4 billion of conservation investment reduced biodiversity loss across 109 signatory countries between 1996 and 2008, by an average 29% per country. We also show that biodiversity change in signatory countries can be predicted with high accuracy, using a dual model that combines the positive impact of conservation investment with the negative impact of economic, agricultural and population growth (i.e. human development pressures)13–18. Decision-makers can use this dual model to forecast the improvement that any proposed biodiversity budget would achieve under various scenarios of human development pressure, comparing those forecasts to any chosen policy target (including the CBD and SDGs). Importantly, we further find that spending impacts shrink as human development pressures grow, implying that funding may need to increase over time. The model therefore offers a flexible tool for balancing the SDGs of human development and biodiversity, by predicting the dynamic changes needed in conservation finance as human development proceeds

Simulation of Yield and Environmental Impacts of Wheat after Rice in Bangladesh and Australia

CERES-wheat and SWAGMAN Destiny models, respectively, were used to estimate the optimum time of sowing, and trade-off between yield and net recharge of the watertable, for wheat grown after rice in northern Bangladesh and southern NSW, Australia. Simulated wheat yields in Bangladesh, for sowings from Sept to Jan, with two supplemental irrigations, ranged from 0.4 to 4.6 t/ha. November-sown crops yielded more than the earlier- or later-sown crops due to reduced water and heat stress during grain filling. In Australia, simulated yields of non-irrigated wheat were always greater for April than June sowings due to less water deficit at the end of the season. With an initial shallow (0.5 m), fresh (1 dS/m) watertable, simulated yields usually exceeded 3 t/ha, and declined as watertable salinity increased. Nonirrigated wheat almost always lowered the watertable. Frequent irrigation increased simulated yields to 5-6 t/ha, regardless of initial conditions and sowing date, but this was at the cost of decreased discharge or increased recharge leading to rising watertables

Addressing the nitrogen problem in sugarcane production to reduce pollution of the Great Barrier Reef

The N pollution footprint of sugarcane cropping is large due to inefficiencies caused by mismatched N supply and crop N demand over sugarcane’s long N accumulation phase. The Great Barrier Reef lagoon receives excessive N loads that contribute to the rapidly declining reef health. Exceeding international average nitrous oxide emission rates several fold, sugarcane soils contribute significantly to Australia’s agricultural emissions. Nitrogen pollution reduction schemes over recent decades have mostly targeted reducing N fertiliser rates in line with expected yields and improving soil quality. Overall, these measures have not resulted in the desired N pollution reduction and further innovation is needed to address this problem. We present research that aims to aid agronomic innovation with (i) next-generation fertilisers that are based on repurposed nutrient-rich wastes and sorbent materials to better match N supply and crop demand and to improve soil function and carbon levels, (ii) understanding of soil N cycling and microbial processes, (iii) legume companion cropping as a source of biologically fixed N, and (iv) genetic improvement of sugarcane that more effectively captures and uses N. We conclude that evidence-based innovation has to support crop growers across climate and soil gradients in the 400,000 hectares of catchments of the Great Barrier Reef. This should include investment into new technologies to support ecologically-sound agriculture and a circular economy without waste and pollution

Development of a cytology-based multivariate analytical risk index for oral cancer

Objectives The diagnosis and management of oral cavity cancers are often complicated by the uncertainty of which patients will undergo malignant transformation, obligating close surveillance over time. However, serial biopsies are undesirable, highly invasive, and subject to inherent issues with poor inter-pathologist agreement and unpredictability as a surrogate for malignant transformation and clinical outcomes. The goal of this study was to develop and evaluate a Multivariate Analytical Risk Index for Oral Cancer (MARIO) with potential to provide non-invasive, sensitive, and quantitative risk assessments for monitoring lesion progression. Materials and methods A series of predictive models were developed and validated using previously recorded single-cell data from oral cytology samples resulting in a “continuous risk score”. Model development consisted of: (1) training base classification models for each diagnostic class pair, (2) pairwise coupling to obtain diagnostic class probabilities, and (3) a weighted aggregation resulting in a continuous MARIO. Results and conclusions Diagnostic accuracy based on optimized cut-points for the test dataset ranged from 76.0% for Benign, to 82.4% for Dysplastic, 89.6% for Malignant, and 97.6% for Normal controls for an overall MARIO accuracy of 72.8%. Furthermore, a strong positive relationship with diagnostic severity was demonstrated (Pearson’s coefficient = 0.805 for test dataset) as well as the ability of the MARIO to respond to subtle changes in cell composition. The development of a continuous MARIO for PMOL is presented, resulting in a sensitive, accurate, and non-invasive method with potential for enabling monitoring disease progression, recurrence, and the need for therapeutic intervention of these lesions

Impacts of environmental and socio-economic factors on emergence and epidemic potential of Ebola in Africa

Abstract: Recent outbreaks of animal-borne emerging infectious diseases have likely been precipitated by a complex interplay of changing ecological, epidemiological and socio-economic factors. Here, we develop modelling methods that capture elements of each of these factors, to predict the risk of Ebola virus disease (EVD) across time and space. Our modelling results match previously-observed outbreak patterns with high accuracy, and suggest further outbreaks could occur across most of West and Central Africa. Trends in the underlying drivers of EVD risk suggest a 1.75 to 3.2-fold increase in the endemic rate of animal-human viral spill-overs in Africa by 2070, given current modes of healthcare intervention. Future global change scenarios with higher human population growth and lower rates of socio-economic development yield a 1.63-fold higher likelihood of epidemics occurring as a result of spill-over events. Our modelling framework can be used to target interventions designed to reduce epidemic risk for many zoonotic diseases

Data Mining and Knowledge Reuse for the Initial Systems Design and Manufacturing: Aero-engine Service Risk Drivers

Service providers of civil aero engines are typically confronted with a high cost of maintenance, replacement and refurbishment of the service damaged components. In such context, service experience becomes a key issue for determining the service risk drivers for operational disruptions and maintenance burden. This paper presents an industrial case study to produce new knowledge on the relationships between degradation and component design to manufacture. The study applied semantic data mining as a methodology for an efficient and the consistent data capture, representation, and analysis. The paper aims at identifying the service risk drivers based on service experience and event data. The analysis shows that the 3 top mechanisms accounting for 32% of the mechanism references have a strong Pareto effect. The paper concludes with missing information links and future research directions

Watch and Learn: Seeing Is Better than Doing when Acquiring Consecutive Motor Tasks

During motor adaptation learning, consecutive physical practice of two different tasks compromises the retention of the first. However, there is evidence that observational practice, while still effectively aiding acquisition, will not lead to interference and hence prove to be a better practice method. Observers and Actors practised in a clockwise (Task A) followed by a counterclockwise (Task B) visually rotated environment, and retention was immediately assessed. An Observe-all and Act-all group were compared to two groups who both physically practised Task A, but then only observed (ObsB) or did not see or practice Task B (NoB). The two observer groups and the NoB control group better retained Task A than Actors, although importantly only the observer groups learnt Task B. RT data and explicit awareness of the rotation suggested that the observers had acquired their respective tasks in a more strategic manner than Actor and Control groups. We conclude that observational practice benefits learning of multiple tasks more than physical practice due to the lack of updating of implicit, internal models for aiming in the former

What we talk about when we talk about "global mindset": managerial cognition in multinational corporations

Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as “global mindset” that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research