Inefficiencies in markets for intellectual property rights: experiences of academic and public research institutions

The formal use of such intellectual property rights (IPR) as patents and registered copyright by universities has increased steadily in the last two decades. Mainstream arguments, embedded in economic theory and policy, advocating the use of IPR to protect academic research results are based on the view that IPR marketplaces work well and allow universities to reap significant benefits. However, there is a lack of evidence-based research to justify or critically evaluate these claims. Building upon an original survey of 46 universities and public research organizations in the United Kingdom, this study analyses the quality of the institutions underpinning the markets for patents and copyright, investigating potential inefficiencies that could lead to underperformance of the IPR system. These include ‘IPR market failures’ with respect to search processes and transparency; price negotiation processes; uncertainties in the perception of the economic value of IRP and the relationship with R&D cost. Further sources of underperformance may include ‘institutional failures’ with respect to enforcement and regulation. Particular attention is paid to the role of governance forms (e.g. alternative types of licensing agreements) through which IPR exchanges take place. We find that a high share of universities report market failures in IPR transactions and that the choice of IPR governance forms matter for the obstacles that are encountered. Given the importance of widely disseminating university research outcomes to foster innovation and economic development, the presence of inefficiencies in IPR markets suggests that such objectives could best be achieved by encouraging open distribution of knowledge, rather than privatization of academic knowledge

White Matter Diffusion Alterations in Normal Women at Risk of Alzheimer\u27s Disease

Increased white matter mean diffusivity and decreased fractional anisotropy (FA) has been observed in subjects diagnosed with mild cognitive impairment (MCI) and Alzheimer\u27s disease (AD). We sought to determine whether similar alterations of white matter occur in normal individuals at risk of AD. Diffusion tensor images were acquired in 42 cognitively normal right-handed women with both a family history of dementia and at least one apolipoprotein E4 allele. These were compared with images from 23 normal women without either AD risk factor. Group analyses were performed using tract-based spatial statistics. Reduced FA was observed in the fronto-occipital and inferior temporal fasciculi (particularly posteriorly), the splenium of the corpus callosum, subcallosal white matter and the cingulum bundle. These findings demonstrate that specific white matter pathways are altered in normal women at increased risk of AD years before the expected onset of cognitive symptoms

Dopaminergic Modulation of Medial Prefrontal Cortex Deactivation in Parkinson Depression

Parkinson\u27s disease (PD) is associated with emotional abnormalities. Dopaminergic medications ameliorate Parkinsonian motor symptoms, but less is known regarding the impact of dopaminergic agents on affective processing, particularly in depressed PD (dPD) patients. The aim of this study was to examine the effects of dopaminergic pharmacotherapy on brain activation to emotional stimuli in depressed versus nondepressed Parkinson disease (ndPD) patients. Participants included 18 ndPD patients (11 men, 7 women) and 10 dPD patients (7 men, 3 women). Patients viewed photographs of emotional faces during functional MRI. Scans were performed while the patient was taking anti-Parkinson medication and the day after medication had been temporarily discontinued. Results indicate that dopaminergic medications have opposite effects in the prefrontal cortex depending upon depression status. DPD patients show greater deactivation in the ventromedial prefrontal cortex (VMPFC) on dopaminergic medications than off, while ndPD patients show greater deactivation in this region off drugs. The VMPFC is in the default-mode network (DMN). DMN activity is negatively correlated with activity in brain systems used for external visual attention. Thus dopaminergic medications may promote increased attention to external visual stimuli among dPD patients but impede normal suppression of DMN activity during external stimulation among ndPD patients

Demersal fish biomass declines with temperature across productive shelf seas

Aim: Theory predicts fish community biomass to decline with increasing temperature due to higher metabolic losses resulting in less efficient energy transfer in warm-water food webs. However, whether these metabolic predictions explain observed macroecological patterns in fish community biomass is virtually unknown. Here, we test these predictions by examining the variation in demersal fish biomass across productive shelf regions. Location: Twenty one continental shelf regions in the North Atlantic and Northeast Pacific. Time Period: 1980-2015. Methods: We compiled high-resolution bottom trawl survey data of fish biomass containing 166,000 unique tows and corrected biomass for differences in sampling area and trawl gear catchability. We examined whether relationships between net primary production and demersal fish community biomass are mediated by temperature, food-web structure and the level of fishing exploitation, as well as the choice of spatial scale of the analysis. Subsequently, we examined if temperature explains regional changes in fish biomass over time under recent warming. Results: We find that biomass per km2 varies 40-fold across regions and is highest in cold waters and areas with low fishing exploitation. We find no evidence that temperature change has impacted biomass within marine regions over the time period considered. The biomass variation is best explained by an elementary trophodynamic model that accounts for temperature-dependent trophic efficiency. Main Conclusions: Our study supports the hypothesis that temperature is a main driver of large-scale cross-regional variation in fish community biomass. The cross-regional pattern suggests that long-term impacts of warming will be negative on biomass. These results provide an empirical basis for predicting future changes in fish community biomass and its associated services for human wellbeing that is food provisioning, under global climate change

On a formula of Gammelgaard for Berezin-Toeplitz quantization

We give a proof of a slightly refined version of Gammelgaard's graph theoretic formula for Berezin-Toeplitz quantization on (pseudo-)Kaehler manifolds. Our proof has the merit of giving an alternative approach to Karabegov-Schlichenmaier's identification theorem. We also identify the dual Karabegov-Bordemann-Waldmann star product.Comment: 18 page

Dissociation of Automatic and Strategic Lexical-semantics: Functional Magnetic Resonance Imaging Evidence for Differing Roles of Multiple Frontotemporal Regions

Behavioral research has demonstrated three major components of the lexical-semantic processing system: automatic activation of semantic representations, strategic retrieval of semantic representations, and inhibition of competitors. However, these component processes are inherently conflated in explicit lexical-semantic decision tasks typically used in functional magnetic resonance imaging (fMRI) research. Here, we combine the logic of behavioral priming studies and the neurophysiological phenomenon of fMRI priming to dissociate the neural bases of automatic and strategic lexical-semantic processes across a series of three studies. A single lexical decision task was used in all studies, with stimulus onset asynchrony or linguistic relationship between prime and target being manipulated. Study 1 demonstrated automatic semantic priming in the left mid-fusiform gyrus (mid-FFG) and strategic semantic priming in five regions: left middle temporal gyrus (MTG), bilateral anterior cingulate, anterior left inferior prefrontal cortex (aLIPC), and posterior LIPC (pLIPC). These priming effects were explored in more detail in two subsequent studies. Study 2 replicated the automatic priming effect in mid-FFG and demonstrated that automatic priming in this region is preferential for the semantic domain. Study 3 demonstrated a neural dissociation in regions contributing to the strategic semantic priming effect. Strategic semantic facilitation was observed in the aLIPC and MTG, whereas strategic semantic inhibition was observed in the pLIPC and anterior cingulate. These studies provide reproducible evidence for a neural dissociation between three well established components of the lexical-semantic processing system

Dopaminergic Modulation of Memory and Affective Processing in Parkinson Depression

Depression is common in Parkinson\u27s disease and is associated with cognitive impairment. Dopaminergic medications are effective in treating the motor symptoms of Parkinson\u27s disease; however, little is known regarding the effects of dopaminergic pharmacotherapy on cognitive function in depressed Parkinson patients. This study examines the neuropsychological effects of dopaminergic pharmacotherapy in Parkinsonian depression. We compared cognitive function in depressed and non-depressed Parkinson patients at two time-points: following overnight withdrawal and after the usual morning regimen of dopaminergic medications. A total of 28 non-demented, right-handed patients with mild to moderate idiopathic Parkinson\u27s disease participated. Ten of these patients were depressed according to DSM IV criteria. Results revealed a statistically significant interaction between depression and medication status on three measures of verbal memory and a facial affect naming task. In all cases, depressed Parkinson\u27s patients performed significantly more poorly while on dopaminergic medication than while off. The opposite pattern emerged for the non-depressed Parkinson\u27s group. The administration of dopaminergic medication to depressed Parkinson patients may carry unintended risks

Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces

We present a new deep multi-state Dynamic Recurrent Neural Network (DRNN) architecture for Brain Machine Interface (BMI) applications. Our DRNN is used to predict Cartesian representation of a computer cursor movement kinematics from open-loop neural data recorded from the posterior parietal cortex (PPC) of a human subject in a BMI system. We design the algorithm to achieve a reasonable trade-off between performance and robustness, and we constrain memory usage in favor of future hardware implementation. We feed the predictions of the network back to the input to improve prediction performance and robustness. We apply a scheduled sampling approach to the model in order to solve a statistical distribution mismatch between the ground truth and predictions. Additionally, we configure a small DRNN to operate with a short history of input, reducing the required buffering of input data and number of memory accesses. This configuration lowers the expected power consumption in a neural network accelerator. Operating on wavelet-based neural features, we show that the average performance of DRNN surpasses other state-of-the-art methods in the literature on both single- and multi-day data recorded over 43 days. Results show that multi-state DRNN has the potential to model the nonlinear relationships between the neural data and kinematics for robust BMIs