A Portfolio of Compositions with Commentary and Spectral Research

Prelude to a Composition by Research Thesis: Shall I compare thee to other research? Thou art less work and of less gen'ral use, or so say musicologists who perch on piles of books which vex them and confuse. But truth be told all this does have an aim, involving guiding listeners through a piece - even if you might call their ear “untrained' - and so my work, in part, consists of this: Spectrally analysing overtones and the bass clarinet's multiphonics; a pitch hierarchy using microtones decides a note's relation to the tonic. If asked what my research topic may be, I simply reply, 'my own harmony.

Analysis of Elliptic Curve Cryptography (ECC) for Energy Efficiency in Wireless Sensor Networks

Rapid growth of wireless sensor networks (WSN) in recent times has resulted in greater security requirements. One of the primary concerns in wireless sensor networks is energy efficiency and security mechanisms are no different.  Currently, security in wireless sensor networks is often implemented by symmetric key cryptography due to its low-power implementation. Public Key Cryptography (PKC), on the other hand, is advantageous as it requires less overhead information during transmission of packets that ultimately lessens overall size of the protocol. In addition, Public Key Cryptography provides better data confidentiality and authentication in wireless sensor networks. In this study, we focus on Public Key Cryptography for greater efficiency in key distribution, low protocol overhead and efficient hardware implementation on the sensor nodes. Considering the constraints of energy efficient wireless sensor networks, we analyze and compare some well known Public Key algorithms, their implementation in wireless sensor networks, and how these algorithms can benefit the fundamental security services. We also evaluate energy consumption parameters for encryption as well as data transmission and suggest energy efficient encryption mechanisms

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Association of British Clinical Diabetologists and Renal Association guidelines on the detection and management of diabetes post solid organ transplantation

Post‐transplant diabetes mellitus (PTDM) is common after solid organ transplantation (SOT) and associated with increased morbidity and mortality for allograft recipients. Despite the significant burden of disease, there is a paucity of literature with regards to detection, prevention and management. Evidence from the general population with diabetes may not be translatable to the unique context of SOT. In light of emerging clinical evidence and novel anti‐diabetic agents, there is an urgent need for updated guidance and recommendations in this high‐risk cohort. The Association of British Clinical Diabetologists (ABCD) and Renal Association (RA) Diabetic Kidney Disease Clinical Speciality Group has undertaken a systematic review and critical appraisal of the available evidence. Areas of focus are; (1) epidemiology, (2) pathogenesis, (3) detection, (4) management, (5) modification of immunosuppression, (6) prevention, and (7) PTDM in the non‐renal setting. Evidence‐graded recommendations are provided for the detection, management and prevention of PTDM, with suggested areas for future research and potential audit standards. The guidelines are endorsed by Diabetes UK, the British Transplantation Society and the Royal College of Physicians of London. The full guidelines are available freely online for the diabetes, renal and transplantation community using the link below. The aim of this review article is to introduce an abridged version of this new clinical guideline ( https://abcd.care/sites/abcd.care/files/site_uploads/Resources/Position‐Papers/ABCD‐RA%20PTDM%20v14.pdf)

Inequalities in the Management of Diabetic Kidney Disease in UK Primary Care: :A Cross‐Sectional Analysis of A Large Primary Care Database

Aims: To determine differences in the management of diabetic kidney disease (DKD) relevant to patient sex, ethnicity and socio-economic group in UK primary care. Methods: A cross-sectional analysis as of January 1, 2019 was undertaken using the IQVIA Medical Research Data dataset, to determine the proportion of people with DKD managed in accordance with national guidelines, stratified by demographics. Robust Poisson regression models were used to calculate adjusted risk ratios (aRR) adjusting for age, sex, ethnicity and social deprivation. Results: Of the 2.3 million participants, 161,278 had type 1 or 2 diabetes, of which 32,905 had DKD. Of people with DKD, 60% had albumin creatinine ratio (ACR) measured, 64% achieved blood pressure (BP, <140/90 mmHg) target, 58% achieved glycosylated haemoglobin (HbA1c, <58 mmol/mol) target, 68% prescribed renin–angiotensin–aldosterone system (RAAS) inhibitor in the previous year. Compared to men, women were less likely to have creatinine: aRR 0.99 (95% CI 0.98–0.99), ACR: aRR 0.94 (0.92–0.96), BP: aRR 0.98 (0.97–0.99), HbA 1c: aRR 0.99 (0.98–0.99) and serum cholesterol: aRR 0.97 (0.96–0.98) measured; achieve BP: aRR 0.95 (0.94–0.98) or total cholesterol (<5 mmol/L) targets: aRR 0.86 (0.84–0.87); or be prescribed RAAS inhibitors: aRR 0.92 (0.90–0.94) or statins: aRR 0.94 (0.92–0.95). Compared to the least deprived areas, people from the most deprived areas were less likely to have BP measurements: aRR 0.98 (0.96–0.99); achieve BP: aRR 0.91 (0.8–0.95) or HbA 1c: aRR 0.88 (0.85–0.92) targets, or be prescribed RAAS inhibitors: aRR 0.91 (0.87–0.95). Compared to people of white ethnicity; those of black ethnicity were less likely to be prescribed statins aRR 0.91 (0.85–0.97). Conclusions: There are unmet needs and inequalities in the management of DKD in the UK. Addressing these could reduce the increasing human and societal cost of managing DKD

PS4: a Next-Generation Dataset for Protein Single Sequence Secondary Structure Prediction

AbstractProtein secondary structure prediction is a subproblem of protein folding. A lightweight algorithm capable of accurately predicting secondary structure from only the protein residue sequence could provide a useful input for tertiary structure prediction, alleviating the reliance on MSA typically seen in today’s best-performing models. Unfortunately, existing datasets for secondary structure prediction are small, creating a bottleneck. We present PS4, a dataset of 18,731 non-redundant protein chains and their respective secondary structure labels. Each chain is identified, and the dataset is also non-redundant against other secondary structure datasets commonly seen in the literature. We perform ablation studies by training secondary structure prediction algorithms on the PS4 training set, and obtain state-of-the-art accuracy on the CB513 test set in zero shots.</jats:p