Target Acceleration Estimation from Radar Position Data using Neural Network

This work is a preliminary investigation on target manoeuvre estimation in real-time from the available measurements of noisy position data from tracking radar using an artificial neural network (ANN). Recently, simulation study of target manoeuvre estimation in real-time from the same position alone measurement using extended Kalman filter has been carried out in a simulated environment using measurements at 100 ms interval. The results reveal that the estimated acceleration consists of substantial error and lag, which is a stumbling block for guidance accuracy in real-time. So, the target acceleration has been estimated using the ANN with less error and lag than the same using Kalman estimator

Target Acceleration Estimation from Radar Position Data using Neural Network

This work is a preliminary investigation on target manoeuvre estimation in real-time from the available measurements of noisy position data from tracking radar using an artificial neural network (ANN). Recently, simulation study of target manoeuvre estimation in real-time from the same position alone measurement using extended Kalman filter has been carried out in a simulated environment using measurements at 100 ms interval. The results reveal that the estimated acceleration consists of substantial error and lag, which is a stumbling block for guidance accuracy in real-time. So, the target acceleration has been estimated using the ANN with less error and lag than the same using Kalman estimator

Generalized quantum Fokker-Planck, diffusion and Smoluchowski equations with true probability distribution functions

Traditionally, the quantum Brownian motion is described by Fokker-Planck or diffusion equations in terms of quasi-probability distribution functions, e.g., Wigner functions. These often become singular or negative in the full quantum regime. In this paper a simple approach to non-Markovian theory of quantum Brownian motion using {\it true probability distribution functions} is presented. Based on an initial coherent state representation of the bath oscillators and an equilibrium canonical distribution of the quantum mechanical mean values of their co-ordinates and momenta we derive a generalized quantum Langevin equation in $c$-numbers and show that the latter is amenable to a theoretical analysis in terms of the classical theory of non-Markovian dynamics. The corresponding Fokker-Planck, diffusion and the Smoluchowski equations are the {\it exact} quantum analogues of their classical counterparts. The present work is {\it independent} of path integral techniques. The theory as developed here is a natural extension of its classical version and is valid for arbitrary temperature and friction (Smoluchowski equation being considered in the overdamped limit).Comment: RevTex, 16 pages, 7 figures, To appear in Physical Review E (minor revision

Timing of Radiotherapy (RT) after Radical Prostatectomy (RP): Long-term outcomes in the RADICALS-RT trial [NCT00541047]

Background The optimal timing of radiotherapy (RT) after radical prostatectomy for prostate cancer has been uncertain. RADICALS-RT compared efficacy and safety of adjuvant RT versus an observation policy with salvage RT for PSA failure. Methods RADICALS-RT was a randomised controlled trial enrolling patients with ≥1 risk factor (pT3/4, Gleason 7-10, positive margins, pre-op PSA≥10ng/ml) for recurrence after radical prostatectomy. Patients were randomised 1:1 to adjuvant RT (“Adjuvant-RT”) or an observation policy with salvage RT for PSA failure (“Salvage-RT”) defined as PSA≥0.1ng/ml or 3 consecutive rises. Stratification factors were Gleason score, margin status, planned RT schedule (52.5Gy/20 fractions or 66Gy/33 fractions) and treatment centre. The primary outcome measure was freedom-from-distant metastasis, designed with 80% power to detect an improvement from 90% with Salvage-RT (control) to 95% at 10yr with Adjuvant-RT. Secondary outcome measures were bPFS, freedom-from-non-protocol hormone therapy, safety and patient-reported outcomes. Standard survival analysis methods were used; HR<1 favours Adjuvant-RT. Findings Between Oct-2007 and Dec-2016, 1396 participants from UK, Denmark, Canada and Ireland were randomised: 699 Salvage-RT, 697 Adjuvant-RT. Allocated groups were balanced with median age 65yr. 93% (649/697) Adjuvant-RT reported RT within 6m after randomisation; 39% (270/699) Salvage-RT reported RT during follow-up. Median follow-up was 7.8 years. With 80 distant metastasis events, 10yr FFDM was 93% for Adjuvant-RT and 90% for Salvage-RT: HR=0.68 (95%CI 0·43–1·07, p=0·095). Of 109 deaths, 17 were due to prostate cancer. Overall survival was not improved (HR=0.980, 95%CI 0.667–1.440, p=0.917). Adjuvant-RT reported worse urinary and faecal incontinence one year after randomisation (p=0.001); faecal incontinence remained significant after ten years (p=0.017). Interpretation Long-term results from RADICALS-RT confirm adjuvant RT after radical prostatectomy increases the risk of urinary and bowel morbidity, but does not meaningfully improve disease control. An observation policy with salvage RT for PSA failure should be the current standard after radical prostatectomy

A global research priority agenda to advance public health responses to fatty liver disease

Background & aims An estimated 38% of adults worldwide have non-alcoholic fatty liver disease (NAFLD). From individual impacts to widespread public health and economic consequences, the implications of this disease are profound. This study aimed to develop an aligned, prioritised fatty liver disease research agenda for the global health community. Methods Nine co-chairs drafted initial research priorities, subsequently reviewed by 40 core authors and debated during a three-day in-person meeting. Following a Delphi methodology, over two rounds, a large panel (R1 n = 344, R2 n = 288) reviewed the priorities, via Qualtrics XM, indicating agreement using a four-point Likert-scale and providing written feedback. The core group revised the draft priorities between rounds. In R2, panellists also ranked the priorities within six domains: epidemiology, models of care, treatment and care, education and awareness, patient and community perspectives, and leadership and public health policy. Results The consensus-built fatty liver disease research agenda encompasses 28 priorities. The mean percentage of ‘agree’ responses increased from 78.3 in R1 to 81.1 in R2. Five priorities received unanimous combined agreement (‘agree’ + ‘somewhat agree’); the remaining 23 priorities had >90% combined agreement. While all but one of the priorities exhibited at least a super-majority of agreement (>66.7% ‘agree’), 13 priorities had 90% combined agreement. Conclusions Adopting this multidisciplinary consensus-built research priorities agenda can deliver a step-change in addressing fatty liver disease, mitigating against its individual and societal harms and proactively altering its natural history through prevention, identification, treatment, and care. This agenda should catalyse the global health community’s efforts to advance and accelerate responses to this widespread and fast-growing public health threat. Impact and implications An estimated 38% of adults and 13% of children and adolescents worldwide have fatty liver disease, making it the most prevalent liver disease in history. Despite substantial scientific progress in the past three decades, the burden continues to grow, with an urgent need to advance understanding of how to prevent, manage, and treat the disease. Through a global consensus process, a multidisciplinary group agreed on 28 research priorities covering a broad range of themes, from disease burden, treatment, and health system responses to awareness and policy. The findings have relevance for clinical and non-clinical researchers as well as funders working on fatty liver disease and non-communicable diseases more broadly, setting out a prioritised, ranked research agenda for turning the tide on this fast-growing public health threat

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Major histocompatibility complex class I expression can be used as a diagnostic tool to differentiate idiopathic inflammatory myopathies from dystrophies

Aim: Utility of major histocompatibility complex (MHC) Class I antigen immunostaining was studied to differentiate idiopathic inflammatory myopathies from dystrophies. Materials and Methods: Forty muscle biopsies including seven dermatomyositis (DM), six polymyositis (PM), two sporadic inclusion body myositis (sIBM), 20 dystrophies (one Duchenne, three Becker′s, four alpha, one gamma sarcoglycanopathy, nine limb girdle, one myotonic and one fascioscapulohumeral muscular dystrophy) and five controls were stained with antibody for MHC Class I antigen (Novocastra clone W6/32 HL 1:100 dilution). Results: Polymyositis and sIBM showed MHC class I antigen positivity along sarcolemma of single and small groups of muscle fibers. The regenerating fibers in the perifascicular area in DM showed intense cytoplasmic positivity of MHC class I antigen. Muscle fibers in all dystrophies except regenerating fibers and control normal muscle were negative for MHC. Capillaries and lymphocytes were positive controls. There were no false positives in the study. Conclusion: MHC Class I immunostaining can be used as a complementary diagnostic tool for the diagnosis of idiopathic inflammatory myopathies

Not Available

Not AvailableMotivation: Simple sequence repeats (SSRs) are abundant across genomes. However, the significance of SSRs in organellar genomes of rice has not been completely understood. The availability of organellar genome sequences allows us to understand the organization of SSRs in their genic and intergenic regions. Results: We have analyzed SSRs in mitochondrial and chloroplast genomes of rice. We identified 2528 SSRs in the mitochondrial genome and average 870 SSRs in the chloroplast genomes. About 8.7% of the mitochondrial and 27.5% of the chloroplast SSRs were observed in the genic region. Dinucleotides were the most abundant repeats in genic and intergenic regions of the mitochondrial genome while mononucleotides were predominant in the chloroplast genomes. The rps and nad gene clusters of mitochondria had the maximum repeats, while the rpo and ndh gene clusters of chloroplast had the maximum repeats. We identified SSRs in both organellar genomes and validated in different cultivars and species.Not Availabl