University Patent Licensing for the Research and Development of Pharmaceuticals in Developing Countries

Waiting for permission from publisher - University Patent Licensing for the Research and Development of Pharmaceuticals in Developing Countries” I.P.Q. No.3 [2009] 311-344.University Patent Licensing for the Research and Development of Pharmaceuticals in Developing Countries” I.P.Q. No.3 [2009] 311-344.University Patent Licensing for the Research and Development of Pharmaceuticals in Developing Countries” I.P.Q. No.3 [2009] 311-344.University Patent Licensing for the Research and Development of Pharmaceuticals in Developing Countries” I.P.Q. No.3 [2009] 311-344.University Patent Licensing for the Research and Development of Pharmaceuticals in Developing Countries” I.P.Q. No.3 [2009] 311-344

The Comparative Advantages of Geographical Indications and Community Trademarks for the Marketing of Agricultural Products in the European Union

UNDER EMBARGO - until 2012The aim of this article is to compare the registrability of geographical names under the GI and CTM Regulations, in light of their respective capacities to accommodate the landholdings, yields and marketing plans of diverse agricultural undertakings

Topological mechanics of origami and kirigami

Origami and kirigami have emerged as potential tools for the design of mechanical metamaterials whose properties such as curvature, Poisson ratio, and existence of metastable states can be tuned using purely geometric criteria. A major obstacle to exploiting this property is the scarcity of tools to identify and program the flexibility of fold patterns. We exploit a recent connection between spring networks and quantum topological states to design origami with localized folding motions at boundaries and study them both experimentally and theoretically. These folding motions exist due to an underlying topological invariant rather than a local imbalance between constraints and degrees of freedom. We give a simple example of a quasi-1D folding pattern that realizes such topological states. We also demonstrate how to generalize these topological design principles to two dimensions. A striking consequence is that a domain wall between two topologically distinct, mechanically rigid structures is deformable even when constraints locally match the degrees of freedom.Comment: 5 pages, 3 figures + ~5 pages S

Evaluation of Supermarket Energy Use and Emissions with Various Technology Options

In this paper, an operational supermarket in the UK has been selected to be modelled by the previously developed supermarket energy simulation software ‘SuperSIM’. Detailed information of the supermarket and model development procedures are explained. The model was previously validated through comparisons with site measurements of space air temperature and humidity and energy consumptions. It is therefore used to simulate, quantify and evaluate supermarket energy performance at various technology options in terms of heat recovery from refrigerant discharge, high efficiency condensers and evaporators and store locations etc

Can spoofing countermeasure and speaker verification systems be jointly optimised?

Spoofing countermeasure (CM) and automatic speaker verification (ASV) sub-systems can be used in tandem with a backend classifier as a solution to the spoofing aware speaker verification (SASV) task. The two sub-systems are typically trained independently to solve different tasks. While our previous work demonstrated the potential of joint optimisation, it also showed a tendency to over-fit to speakers and a lack of sub-system complementarity. Using only a modest quantity of auxiliary data collected from new speakers, we show that joint optimisation degrades the performance of separate CM and ASV sub-systems, but that it nonetheless improves complementarity, thereby delivering superior SASV performance. Using standard SASV evaluation data and protocols, joint optimisation reduces the equal error rate by 27\% relative to performance obtained using fixed, independently-optimised sub-systems under like-for-like training conditions.Comment: Accepted to ICASSP 2023. Code will be available soo

Machine Learning for Quantum-Enhanced Gravitational-Wave Observatories

Machine learning has become an effective tool for processing the extensive data sets produced by large physics experiments. Gravitational-wave detectors are now listening to the universe with quantum-enhanced sensitivity, accomplished with the injection of squeezed vacuum states. Squeezed state preparation and injection is operationally complicated, as well as highly sensitive to environmental fluctuations and variations in the interferometer state. Achieving and maintaining optimal squeezing levels is a challenging problem and will require development of new techniques to reach the lofty targets set by design goals for future observing runs and next-generation detectors. We use machine learning techniques to predict the squeezing level during the third observing run of the Laser Interferometer Gravitational-Wave Observatory (LIGO) based on auxiliary data streams, and offer interpretations of our models to identify and quantify salient sources of squeezing degradation. The development of these techniques lays the groundwork for future efforts to optimize squeezed state injection in gravitational-wave detectors, with the goal of enabling closed-loop control of the squeezer subsystem by an agent based on machine learning

On the potential of jointly-optimised solutions to spoofing attack detection and automatic speaker verification

The spoofing-aware speaker verification (SASV) challenge was designed to promote the study of jointly-optimised solutions to accomplish the traditionally separately-optimised tasks of spoofing detection and speaker verification. Jointly-optimised systems have the potential to operate in synergy as a better performing solution to the single task of reliable speaker verification. However, none of the 23 submissions to SASV 2022 are jointly optimised. We have hence sought to determine why separately-optimised sub-systems perform best or why joint optimisation was not successful. Experiments reported in this paper show that joint optimisation is successful in improving robustness to spoofing but that it degrades speaker verification performance. The findings suggest that spoofing detection and speaker verification sub-systems should be optimised jointly in a manner which reflects the differences in how information provided by each sub-system is complementary to that provided by the other. Progress will also likely depend upon the collection of data from a larger number of speakers.Comment: Accepted to IberSPEECH 2022 Conferenc

Malafide: a novel adversarial convolutive noise attack against deepfake and spoofing detection systems

We present Malafide, a universal adversarial attack against automatic speaker verification (ASV) spoofing countermeasures (CMs). By introducing convolutional noise using an optimised linear time-invariant filter, Malafide attacks can be used to compromise CM reliability while preserving other speech attributes such as quality and the speaker's voice. In contrast to other adversarial attacks proposed recently, Malafide filters are optimised independently of the input utterance and duration, are tuned instead to the underlying spoofing attack, and require the optimisation of only a small number of filter coefficients. Even so, they degrade CM performance estimates by an order of magnitude, even in black-box settings, and can also be configured to overcome integrated CM and ASV subsystems. Integrated solutions that use self-supervised learning CMs, however, are more robust, under both black-box and white-box settings.Comment: Accepted at INTERSPEECH 202

Work and heat probability distributions in out-of-equilibrium systems

We review and discuss the equations governing the distribution of work done on a system which is driven out of equilibrium by external manipulation, as well as those governing the entropy flow to a reservoir in a nonequilibrium system. We take advantage of these equations to investigate the path phase transition in a manipulated mean-field Ising model and the large-deviation function for the heat flow in the asymmetric exclusion process with periodically varying transition probabilities.Comment: Contribution to Proceedings of "Work, Dissipation, and Fluctuations in Nonequilibrium Physics", Brussels, 200