On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation

This paper considers the distribution of the mutual information of frequency-selective spatially-uncorrelated Rayleigh fading MIMO channels. Results are presented for OFDM-based spatial multiplexing. New exact closed-form expressions are derived for the variance of the mutual information. In contrast to previous results, our new expressions apply for systems with both arbitrary numbers of antennas and arbitrary-length channels. Simplified expressions are also presented for high and low SNR regimes. The analytical variance results are used to provide accurate analytical approximations for the distribution of the mutual information and the outage capacity.Comment: 18 pages, 10 figures, accepted for publication in IEEE Transactions on Information Theor

Ultraviolet writing of channel waveguides in proton-exchanged LiNbO₃

We report on a direct ultraviolet (UV) writing method for the fabrication of channel waveguides at 1.55 µm in LiNbO3 through UV irradiation of surface and buried planar waveguides made by annealed proton exchange and reverse proton exchange. A systematic study of the guidance properties as a function of the UV writing conditions is presented

Electromagnetic navigation in total knee arthroplasty—a single center, randomized, single-blind study comparing the results with conventional techniques

We report on the results of a randomized study (n = 200) to compare total knee arthroplasty performed using conventional instrumentation or electromagnetic computer assisted surgical technique. 92% of navigated and 85% of conventional knees were implanted within ± 3° from neutral mechanical alignment; there was no statistically significant difference between these proportions. There was also no difference in femoral or tibial rotation assessed by CT scan. At 1 year follow up there was no statistical difference between the two groups in American Knee Society Score, Oxford Knee Scores, patient satisfaction, quality of life, hospital length of stay, complication rates or other adverse events. Tourniquet time in the navigated group was longer. Proving value for navigation in total knee arthroplasty surgery remains a challenge

Machine learning to refine decision making within a syndromic surveillance service

Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms. Methods: A record of the risk assessment process was obtained from Public Health England for all 67505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final ‘Decision’ outcome made by an epidemiologist of ‘Alert’, ‘Monitor’ or ‘No-action’. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of ‘No-action’ outcomes. Results: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of ‘Alert’ outcomes. If the ‘Alert’ and ‘Monitor’ actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system. Conclusions: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process

Strength in diversity: enhancing learning in vocationally-orientated, master's level courses

Postgraduate education in geography, especially at the Master’s level, is undergoing significant changes in the developed world. There is an expansion of vocationally-oriented degree programmes, increasing recruitment of international students, integration of work place skills, and the engagement of non-traditional postgraduate students as departments respond to policies for a more ‘inclusive’ higher education. This paper sets the context by outlining some programmatic changes in selected countries (Australia, the UK, and the USA). We briefly reflect on how postgraduate ‘bars’ or ‘levels’ are defined and explore in detail what ‘diversity’ or ‘heterogeneity’ means in these new postgraduate settings. The paper then explores some examples of practice drawn from our own experiences, whilst recognising that relevance will vary in other contexts. Finally we consider how diversity can be harnessed as a strength that has potential to enhance taught elements of contemporary postgraduate education in and beyond the discipline

Scenario planning for the Edinburgh city region

This paper examines the application of scenario planning techniques to the detailed and daunting challenge of city re-positioning when policy makers are faced with a heavy history and a complex future context. It reviews a process of scenario planning undertaken in the Edinburgh city region, exploring the scenario process and its contribution to strategies and policies for city repositioning. Strongly rooted in the recent literature on urban and regional economic development, the text outlines how key individuals and organisations involved in the process participated in far-reaching analyses of the possible future worlds in which the Edinburgh city region might find itself

(9R,9aS,12aR,13S)-9,13-Diphenyl-9,9a,12a,13-tetrahydro-9,13-methanotriphenyleno[2,3-c]furan-10,12,14-trione

X-ray crystallography was used to characterise the title compound for the first time, and the 1H NMR, 13C NMR and IR spectroscopic data from earlier reports were also updated.Publisher PDFPeer reviewe

Responsible participation and housing: restoring democratic theory to the scene

Tensions between individual liberty and collective social justice characterise many advanced liberal societies. These tensions are reflected in the challenges posed for representative democracy both by participatory democratic practices and by the current emphasis on (so-called) responsible participation. Based on the example of ‘community’ housing associations in Scotland, this paper explores these tensions. It is argued that the critique of responsibility may have been over-stated – that, in particular, ‘community’ housing associations offer the basis for relatively more inclusive and effective processes of decision-making than council housing, which relies on the traditional processes and institutions of representative local government for its legitimacy