Exploring the Creation of Organisation Strategy when Commercialising a New Technology

<p>This thesis takes a mixed methodology approach to exploring the creation of organisational strategy from the perspectives of both the classical strategy frameworks and Sarasvathy's theory of effectuation. The experience of working within the Masters of Advanced Technology Enterprise (MATE) is portrayed through using an ethnographic approach in conjunction with critical reflection to build ‘thick descriptions’. Following this descriptive phase, analysis is conducted through both classical strategic management frameworks and Sarasvathy’s theory of effectuation. The multifaceted approach was chosen enable a deep understanding of the variety of strategic directions, reasoning’s that were undertaken throughout the year.</p>

Exploring the Creation of Organisation Strategy when Commercialising a New Technology

<p>This thesis takes a mixed methodology approach to exploring the creation of organisational strategy from the perspectives of both the classical strategy frameworks and Sarasvathy's theory of effectuation. The experience of working within the Masters of Advanced Technology Enterprise (MATE) is portrayed through using an ethnographic approach in conjunction with critical reflection to build ‘thick descriptions’. Following this descriptive phase, analysis is conducted through both classical strategic management frameworks and Sarasvathy’s theory of effectuation. The multifaceted approach was chosen enable a deep understanding of the variety of strategic directions, reasoning’s that were undertaken throughout the year.</p>

Quantum Advantages of Communication Complexity from Bell Nonlocality

Communication games are crucial tools for investigating the limitations of physical theories. The communication complexity (CC) problem is a typical example, for which several distributed parties attempt to jointly calculate a given function with limited classical communications. In this work, we present a method to construct CC problems from Bell tests in a graph-theoretic way. Starting from an experimental compatibility graph and the corresponding Bell test function, a target function that encodes the information of each edge can be constructed; then, using this target function, we can construct a CC function, and by pre-sharing entangled states, its success probability exceeds that of the arbitrary classical strategy. The non-signaling protocol based on the Popescu–Rohrlich box is also discussed, and the success probability in this case reaches one.

Squeezing metrology: a unified framework

Quantum metrology theory has up to now focused on the resolution gains obtainable thanks to the entanglement among N probes. Typically, a quadratic gain in resolution is achievable, going from the 1/N of the central limit theorem to the 1/N of the Heisenberg bound. Here we focus instead on quantum squeezing and provide a unified framework for metrology with squeezing, showing that, similarly, one can generally attain a quadratic gain when comparing the resolution achievable by a squeezed probe to the best N-probe classical strategy achievable with the same energy. Namely, here we give a quantification of the Heisenberg squeezing bound for arbitrary estimation strategies that employ squeezing. Our theory recovers known results (e.g. in quantum optics and spin squeezing), but it uses the general theory of squeezing and holds for arbitrary quantum systems.

222AI-based strategy enables faster Holter ECG analysis with equivalent clinical accuracy compared to a classical strategy

BACKGROUND Analysis of Holter recordings can be challenging and time-consuming, therefore requiring significant clinical resources in order to achieve a high-quality diagnosis. Such resources depend largely on the qualifications of the person conducting the analysis and the duration of the recordings. A novel Holter analysis platform has been developed, based on deep neural networks trained with a dataset of one million ECGs, to allow fast and reliable Holter recording analysis. PURPOSE This study sought to compare the performance of an artificial intelligence (AI)-based Holter analysis platform using deep learning tools with a classical one used on a daily basis in hospitals (the reference). The main endpoints evaluated were duration to complete the analysis by the physician operating it as well as diagnostic accuracy of each strategy, when platforms are used by electrophysiologists (EPs). METHODS For this prospective evaluation, a total of 159 Holter recordings (24-hour) were selected from a large Holter dataset from 1 hospital, with a relatively high prevalence of electrical rhythm and conduction disorders. Recordings were analysed by four EPs using independently both the AI-based and classical analysis platforms. All four EPs had no previous experience with the AI-based platform, except for an introductory 6-hour training session. Three EPs had multiple years of experience with the traditional platform, while one EP had limited experience. For each recording, in addition to the analysis duration, diagnostic accuracy was evaluated through the analysis of the presence or absence of predefined cardiac arrhythmias and conduction disorders (prevalence): pauses (25.2%), ventricular tachycardia (VT, 30.2%), atrial fibrillation (AF, 26.4%), high grade atrioventricular block (AVB, 10.1%) and burden of premature ventricular complex larger than 10% (PVC, 23.9%). Definite diagnostics were established by an expert EP after a careful examination of all available analysis reports. RESULTS Time required for the AI-based analysis was on average 42% shorter compared to the traditional platform (6.65 min vs 11.5 min, p &lt; 0.0001). Regarding accuracy to detect electrical disorders, there was no statistically significant differences between AI-based and classical platforms (AF: 98.7% vs 96.9%, Pause: 99.4% vs 100%, PVC: 98.7% vs 98.7%, VT: 92.5% vs 96.2%, AVB: 98.7% vs 94.3%). CONCLUSION: These preliminary findings suggest that an AI-based strategy to analyse Holter recordings may be highly accurate in detecting cardiac electrical abnormalities, with significant time savings compared to a classical strategy, even for users with no previous experience with the novel AI-based platform. An AI-based Holter analysis platform may contribute to a broader and more resource-efficient adoption of Holter monitoring. Abstract Figure. analysis duration using each strategy

Diversity-oriented synthesis of 17-spirosteroids

A diversity-oriented synthesis (DOS) approach has been used to functionalize 17-ethynyl-17-hydroxysteroids through a one-pot procedure involving a ring-closing enyne metathesis (RCEYM) and a Diels–Alder reaction on the resulting diene, under microwave irradiations. Taking advantage of the propargyl alcohol moiety present on commercially available steroids, this classical strategy was applied to mestranol and lynestrenol, giving a collection of new complex 17-spirosteroids.