Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Regional variation in tolvaptan prescribing across England: national data and retrospective evaluation from an expert centre

Background Tolvaptan, a vasopressin V2 receptor antagonist, was approved in 2015 by the UK National Institute for Health and Care Excellence for use in patients with autosomal dominant polycystic kidney disease (ADPKD) and rapid disease progression. Simultaneous guidance was issued by the UK Kidney Association (UKKA) to facilitate national implementation. Methods Data on tolvaptan prescribing in England was obtained through the National Health Service (NHS) Digital, a national survey of all 77 adult kidney units, and the implementation of UKKA guidance was evaluated at an expert PKD centre. Results A regional variation of up to 4-fold for tolvaptan prescribing in England was found. Despite most kidney units following UKKA guidance, centre-based estimates of eligible or treated patient numbers were highly variable. Retrospective evaluation at an expert PKD centre revealed that in a cohort demonstrating rapid estimated glomerular filtration rate (eGFR) decline, 14% would not be eligible for tolvaptan by Mayo imaging classification and more than half (57%) would not be eligible by Predicting Renal Outcome in Polycystic Kidney Disease score. The 3-year discontinuation rate was higher than expected (56%), the majority (70%) due to aquaretic symptoms. In patients taking tolvaptan for at least 2 years, 81% showed a reduction in the rate of eGFR decline compared with baseline, with earlier disease associated with positive treatment response. Conclusion Real-world data have revealed a much higher regional variation in tolvaptan prescribing for ADPKD in England than expected. We propose further investigation into the factors responsible for this variation

Biallelic inheritance of hypomorphic PKD1 variants is highly prevalent in very early onset polycystic kidney disease

Purpose To investigate the prevalence of biallelic PKD1 and PKD2 variants underlying very early onset (VEO) polycystic kidney disease (PKD) in a large international pediatric cohort referred for clinical indications over a 10-year period (2010–2020). Methods All samples were tested by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA) of PKD1 and PKD2 genes and/or a next-generation sequencing panel of 15 additional cystic genes including PKHD1 and HNF1B. Two patients underwent exome or genome sequencing. Results Likely causative PKD1 or PKD2 variants were detected in 30 infants with PKD-VEO, 16 of whom presented in utero. Twenty-one of 30 (70%) had two variants with biallelic in trans inheritance confirmed in 16/21, 1 infant had biallelic PKD2 variants, and 2 infants had digenic PKD1/PKD2 variants. There was no known family history of ADPKD in 13 families (43%) and a de novo pathogenic variant was confirmed in 6 families (23%). Conclusion We report a high prevalence of hypomorphic PKD1 variants and likely biallelic disease in infants presenting with PKD-VEO with major implications for reproductive counseling. The diagnostic interpretation and reporting of these variants however remains challenging using current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) and Association of Clinical Genetic Science (ACGS) variant classification guidelines in PKD-VEO and other diseases affected by similar variants with incomplete penetrance

Distributed compressive video sensing: A review of the state-of-the-art architectures

Low complexity video coding that provides efficient compression with reasonable reconstruction quality has been a desired requirement for resource-constrained video sensors in distributed vision-based sensing applications. In this paper, we present a review of the state-of-the-art codec architectures based on distributed compressive video sensing (DCVS), which is a relatively new video coding paradigm that integrates the techniques of distributed video coding (DVC) and compressive sensing (CS). The review includes a comparative discussion of several well-known DCVS architectures in literature with a focus on their functional aspects, and suggests a number of possible enhancements to the design of these architectures

A review of the state-of-the-art distributed compressive video sensing architectures

Low complexity video coding that provides efficient compression with reasonable reconstruction quality has been a desired requirement for resource-constrained video sensors in distributed vision-based sensing applications. In this paper, we present a review of the state-of-the-art codec architectures based on distributed compressive video sensing (DCVS), which is a relatively new video coding paradigm that integrates the techniques of distributed video coding (DVC) and compressive sensing (CS). The review includes a comparative discussion of several well-known DCVS architectures in literature with a focus on their functional aspects, and suggests a number of possible enhancements to the design of these architectures

RSS ranging based Wi-Fi localization for unknown path loss exponent

Localization of mobile phones is important to location-based mobile services, but achieving good location estimation of mobile phones is difficult especially in environment whose path loss exponent is unknown. In this paper, we present a Wi-Fi localization solution specifically designed for dense WLANs with unknown path loss exponent. In order to leverage between the computational cost and localization accuracy, our solution establishes a neighbor selection scheme based on the Voronoi diagram to identify a subset of Access Points (APs) to participate in localization. It considers the identified subset of APs and a mobile phone to be located as a mass-spring system. Provided with information of known coordinates of APs, the solution estimates the path loss exponent of the physical environment, infers inter-distances between APs and the mobile phone from Wi-Fi signals received, and implements spring relaxation algorithm to approximate the geographical location of the mobile phone, where this location estimation is fed back to refine the estimated exponent iteratively. Extensive simulation results confirm that our solution is able to provide location estimation with an attractive average accuracy of below 2 m in a typical Wi-Fi setup

Hybrid RF mapping and ranging based localization for wireless sensor networks

In this paper, we propose a hybrid approach to the wireless sensor network (WSN) localization problem. The proposed approach harnesses the strengths of two techniques: RF mapping and cooperative ranging, to overcome the potential weaknesses in one another. The idea is to first allow every node to obtain an initial estimate of its own position in a neighbor-independent way using a coarse-grained RF map acquired with minimal efforts. Then each node iteratively refines its own position through distance ranging to each of its neighbors, irregardless of their positions with respect to itself. Through simulation performance experiments, we show the potential of this hybrid approach as a practical localization system for WSN that can achieve reasonable localization accuracy without significant deployment efforts

Combining genotype with height-adjusted kidney length predicts rapid progression of ADPKD

Introduction Our main objective was to identify baseline prognostic factors predictive of rapid disease progression in a large unselected clinical autosomal dominant polycystic kidney disease (ADPKD) cohort. Methods A cross-sectional analysis was performed in 618 consecutive ADPKD patients assessed and followed-up for over a decade. A total of 123 patients (19.9%) had reached kidney failure by the study date. Data were available for the following: baseline eGFR (n = 501), genotype (n = 549), baseline ultrasound mean kidney length (MKL, n = 424) and height-adjusted baseline MKL (HtMKL, n = 377). Rapid disease progression was defined as an annualized eGFR decline (∆eGFR) of >2.5 mL/min/year by linear regression over 5 years (n = 158). Patients were further divided into slow, rapid and very rapid ∆eGFR classes for analysis. Genotyped patients were classified into several categories: PKD1 (T, truncating; or NT, non-truncating), PKD2, other genes (non-PKD1 or -PKD2), no mutation detected or variants of uncertain significance. Results A PKD1-T genotype had the strongest influence on the probability of reduced baseline kidney function by age. A multivariate logistic regression model identified PKD1-T genotype and HtMKL (>9.5 cm/m) as independent predictors for rapid disease progression. The combination of both factors increased the positive predictive value for rapid disease progression over age 40 years and of reaching kidney failure by age 60 years to 100%. Exploratory analysis in a subgroup with available total kidney volumes showed higher positive predictive value (100% vs 80%) and negative predictive value (42% vs 33%) in predicting rapid disease progression compared with the Mayo Imaging Classification (1C–E). Conclusion Real-world longitudinal data confirm the importance of genotype and kidney length as independent variables determining ∆eGFR. Individuals with the highest risk of rapid disease progression can be positively selected for treatment based on this combination