Environmental technologies, intellectual property and climate change (2013) edited by Abbe Brown

Abbe Brown from the University of Aberdeen, Scotland, is one of the leading international researchers on intellectual property and climate change. She is an intellectual dynamo. Her work brings together a mastery of intellectual property, with a strong interest in innovation theory and practice, and an engagement with public policy issues surrounding human rights, competition policy, and access to knowledge. Abbe Brown has shown a particular aptitude for tackling big ideas and wicked global problems, with intelligence, gusto, insight, and formidable wisdom.

The solar capital: Canberra, clean tech, and climate change

There has been an increasing focus upon the role of cities and local government in respect of action upon climate change...

Norway's sovereign wealth fund, ethical investment, and climate change

This year, there has been great debate over whether Norway’s Sovereign Wealth Fund should invest in renewable energy; divest from fossil fuels; and engage in ethical investment...

Geopiracy: Patent law, climate change, and geoengineering

Patent law is a regime of intellectual property, which provides exclusive rights regarding scientific inventions, which are novel, inventive, and useful. There has been much debate over the limits of patentable subject matter relating to emerging technologies. The Supreme Court of the US has sought to rein in the expansive interpretation of patentability by lower courts in a series of cases dealing with medical information (Prometheus), finance (Bilski), and gene patents (Myriad). This has led to a reinvigoration of the debate over the boundaries of patentable subject matter. There has been controversy about the rise in patenting of geoengineering - particularly by firms such as Intellectual Ventures.

A proposal for a clean technology directive: European patent law and climate change

This article charts the conflicted, dissonant policies of the European Union towards intellectual property and climate change. It contends that there is a mismatch between the empirical work of the European Patent Office and the quietist policy options contemplated by the European Union. This article contends that the European Union needs to develop a Clean Technology Directive to allow for a differentiated approach to patent law and clean technologies - especially given the past complicity of the European Union in global warming and climate change. It highlights essential elements in a comprehensive policy package for the reform of patent law - considering patentable subject matter; patent incentives; and patent exceptions.

Intellectual property and biofuels: The energy crisis, food security, and climate change

In light of larger public policy debates over intellectual property and climate change, this article considers patent practice, law, and policy in respect of biofuels. This debate has significant implications for public policy discussions in respect of energy independence, food security, and climate change. The first section of the paper provides a network analysis of patents in respect of biofuels across the three generations. It provides empirical research in respect of patent subject matter, ownership, and strategy in respect of biofuels. The second section provides a case study of significant patent litigation over biofuels. There is an examination of the biofuels patent litigation between the Danish company Novozymes, and Danisco and DuPont. The third section examines flexibilities in respect of patent law and clean technologies in the context of the case study of biofuels. In particular, it explores the debate over substantive doctrinal matters in respect of biofuels – such as patentable subject matter, technology transfer, patent pools, compulsory licensing, and disclosure requirements. The conclusion explores the relevance of the debate over patent law and biofuels to the larger public policy discussions over energy independence, food security, and climate change.

The culture wars of climate change

Of late, there has been a growth in cultural expression about climate change – with the rise of climate fiction (‘cli-fi’); art and photography responding to changes in nature; musical anthems about climate change; plays and dramas about climate change; and environmental documentaries, and climate cinema. Drawing comparisons to past controversies over cultural funding, this paper considers the cultural wars over climate change. This article considers a number of cultural fields. Margaret Atwood made an important creative and critical contribution to the debate over climate change. The work examines Ian McEwan's novel, Solar, a tragi-comedy about authorship, invention, intellectual property, and climate science. After writing a history of Merchants of Doubt, Naomi Oreskes and Erik Conway have experimented with fiction – as well as history. This article focuses upon artistic works about climate change. It analyses James Balog’s work with the Extreme Ice Survey, which involved photography of glaciers under retreat in a warming world. The work was turned into a documentary called Chasing Ice. It also considers the artistic project of 350.org 'to transform the human rights and environmental issues connected to climate change into powerful art that gets people to stop, think and act.' The paper examines musical storytelling in respect of climate change. The paper explores dramatic works about climate change including Steve Waters' The Contingency Plan, Stephen Emmott's Ten Billion, and Andrew Bovell's When the Rain Stops Falling and Hannie Rayson’s Extinction. The paper also examines the role of documentary film-making. It also considers the cinematographic film, Beasts of the Southern Wild. Such a survey will enable a consideration of the larger question of whether creative art about climate change matters; and whether it is deserving of public funding.

Change visualisation: Analysing the resource and timing differences between two event logs

With organisations facing significant challenges to remain competitive, Business Process Improvement (BPI) initiatives are often conducted to improve the efficiency and effectiveness of their business processes, focussing on time, cost, and quality improvements. Event logs which contain a detailed record of business operations over a certain time period, recorded by an organisation's information systems, are the first step towards initiating evidence-based BPI activities. Given an (original) event log as a starting point, an approach to explore better ways to execute a business process was developed, resulting in an improved (perturbed) event log. Identifying the differences between the original event log and the perturbed event log can provide valuable insights, helping organisations to improve their processes. However, there is a lack of automated techniques to detect the differences between two event logs. Therefore, this research aims to develop visualisation techniques to provide targeted analysis of resource reallocation and activity rescheduling. The differences between two event logs are first identified. The changes between the two event logs are conceptualised and realised with a number of visualisations. With the proposed visualisations, analysts will then be able to identify the changes related to resource and time, resulting in a more efficient business process. Ultimately, analysts can make use of this comparative information to initiate evidence-based BPI activities.

Genetics of white matter development: A DTI study of 705 twins and their siblings aged 12 to 29

White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12-29; 290. M/415. F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 80% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity.

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.

Sex differences in the human connectome: 4-Tesla high angular resolution diffusion imaging (HARDI) tractography in 234 young adult twins

Cortical connectivity is associated with cognitive and behavioral traits that are thought to vary between sexes. Using high-angular resolution diffusion imaging at 4 Tesla, we scanned 234 young adult twins and siblings (mean age: 23.4 2.0 SD years) with 94 diffusion-encoding directions. We applied a novel Hough transform method to extract fiber tracts throughout the entire brain, based on fields of constant solid angle orientation distribution functions (ODFs). Cortical surfaces were generated from each subject's 3D T1-weighted structural MRI scan, and tracts were aligned to the anatomy. Network analysis revealed the proportions of fibers interconnecting 5 key subregions of the frontal cortex, including connections between hemispheres. We found significant sex differences (147 women/87 men) in the proportions of fibers connecting contralateral superior frontal cortices. Interhemispheric connectivity was greater in women, in line with long-standing theories of hemispheric specialization. These findings may be relevant for ongoing studies of the human connectome.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 ± 1.9 years) and 14 matched controls (age: 71.4 ± 0.9 years), each scanned twice (2.1 ± 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Corrigendum to "Mapping hippocampal and ventricular change in Alzheimer disease" [NeuroImage 22 (2004) 1754-1766] (DOI:10.1016/j.neuroimage.2004.03.040)

We recently noticed an error in the demographic data in this article. The validity of the findings and the conclusions of the paper is not affected. However, there is an error in the reported sample size and in the means and standard deviations of the subjects’ ages and MMSE scores. We would like to correct this error, which came to light when we were re-analyzing the data for a meta-analysis. The error occurred because an older version of a spreadsheet was incorrectly used when reporting the sample composition. Instead of examining 12 Alzheimer's disease patients and 14 healthy elderly controls, we in fact examined 17 Alzheimer’s disease patients and 14 healthy elderly controls. All maps and morphometric data reported in the paper are correct, except that the sample size was in fact slightly higher than that originally reported, and the maps computed in the paper were based on the larger sample (which included five more subjects in the Alzheimer’s disease group). All of the maps and figures in the paper are correct, and the conclusions of the paper are unchanged. We apologize for this error, which falls under the sole responsibility of the first author. The corrected demographic information appears below.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood- and adult-onset schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages.