Redesigning the European Court of Human Rights: Embeddedness as a Deep Structural Principle of the European Human Rights Regime

The European Court of Human Rights (ECHR) is the crown jewel of the world’s most advanced international system for protecting civil and political liberties. In recent years, however, the ECHR has become a victim of its own success. The Court now faces a docket crisis of massive proportions, the consequence of the growing number of states subject to its jurisdiction, its favourable public reputation, its expansive interpretations of individual liberties, a distrust of domestic judiciaries in some countries, and entrenched human rights problems in others. In response to this growing backlog of individual complaints, the Council of Europe has, over the last five years, considered numerous proposals to restructure the European human rights regime and redesign the European Convention on Human Rights (ECHR). This article argues that these proposals should be understood not as ministerial changes in supranational judicial procedure, nor as resolving a debate over whether the ECHR should strive for individual or constitutional justice, but rather as raising more fundamental questions concerning the Court’s future identity. In particular, the article argues for recognition of ‘ embeddedness ’ in national legal systems as a deep structural principle of the ECHR, a principle that functions as a necessary counterpoint to the subsidiary doctrine that has animated the Convention since its founding. Embeddedness does not substitute ECHR rulings for the decisions of national parliaments or domestic courts. Rather, it requires the Council of Europe and the Court to bolster the mechanisms for governments to remedy human rights violations at home, obviating the need for individuals to seek supranational relief and restoring countries to a position in which the ECHR’s deference to national decision-makers is appropriate

Backscattering UWB/UHF hybrid solutions for multi-reader multi-tag passive RFID systems

Ultra-wideband (UWB) technology is foreseen as a promising solution to overcome the limits of ultra-high frequency (UHF) techniques toward the development of green radio frequency identification (RFID) systems with low energy consumption and localization capabilities. While UWB techniques have been already employed for active tags, passive tags solutions are more appealing also due to their lower cost. With the fundamental requirement of maintaining backward compatibility in the RFID domain, we propose a hybrid UWB/UHF architecture to improve passive tag identification both in single-reader and multi-reader scenarios. We then develop two hybrid algorithms: the first one exploits the UWB signal to improve ISO/IEC 18000-6C UHF standard, while the other one exploits UWB to enhance a compressive sensing (CS) technique for tag identification in the multi-reader, multi-tag scenario. Both solutions are able to improve success rate and reading speed in the tag identification process and reduce the energy consumption. The multi-reader version of the proposed approaches is based on a cooperative scheme in order to manage reader-tag collisions and reader-reader collisions besides the typical tag-tag collisions. Furthermore, timing synchronization non-idealities are analyzed for the proposed solutions and simulation results reveal the effectiveness of the developed schemes

Impact of Correlated Failures in 5G Dual Connectivity Architectures for URLLC Applications

Achieving end-to-end ultra-reliability and resiliency in mission critical communications is a major challenge for future wireless networks. Dual connectivity has been proposed by 3GPP as one of the viable solutions to fulfill the reliability requirements. However, the potential correlation in failures occurring over different wireless links is commonly neglected in current network design approaches. In this paper, we investigate the impact of realistic correlation among different wireless links on end-to-end reliability for two selected architectures from 3GPP. In ultra-reliable use-cases, we show that even small values of correlation can increase the end-to-end error rate by orders of magnitude. This may suggest alternative feasible architecture designs and paves the way towards serving ultra-reliable communications in 5G networks.Comment: Accepted in 2019 IEEE Globecom Workshops (GC Wkshps

Deceived by the Fick principle: blood flow distribution in heart failure

Aims: The Fick principle states that oxygen uptake (V̇O2) is cardiac output (Qc)*arterial-venous O2 content difference [ΔC(a-v)O2]. Blood flow distribution is hidden in Fick principle and its relevance during exercise in heart failure (HF) is undefined.To highlight the role of blood flow distribution, we evaluated peak-exercise V̇O2, Qc and ΔC(a-v)O2, before and after HF therapeutic interventions. Methods: Symptoms-limited cardiopulmonary exercise tests with Qc measurement (inert-gas-rebreathing) was performed in 234 HF patients before and 6 months after successful exercise training, cardiac-resynchronization therapy or percutaneous-edge-to-edge mitral valve repair. Results: Considering all tests (n=468) a direct correlation between peakV̇O2 and peakQc (R2=0.47) and workload (R2=0.70) were observed. Patients were grouped according to treatment efficacy in group 1 (peakV̇O2 increase >10%, n=93), group 2 (peakV̇O2 change between 0 and 10%, n=60) and group 3 (reduction in peakV̇O2, n=81). Post-treatment peakV̇O2 changes poorly correlated with peakQc and peakΔC(a-v)O2 changes. Differently, post-procedures peakQc vs. peakΔC(a-v)O2 changes showed a close negative correlation (R2=0.46), becoming stronger grouping patients according to peakV̇O2 improvement (R2=0.64, 0.79 and 0.58 in group 1, 2 and 3, respectively). In 76% of patients peakQc and ΔC(a-v)O2 changes diverged regardless of treatment. Conclusion: The bulk of these data suggests that blood flow distribution plays a pivotal role on peakV̇O2 determination regardless of HF treatment strategies. Accordingly, for assessing HF treatment efficacy on exercise performance the sole peakV̇O2 may be deceptive and the combination of V̇O2, Qc and ΔC(a-v)O2, must be considered

Enhanced detection of patients with previous COVID-19: superiority of the double diffusion technique

BackgroundPersistent pulmonary dysfunction is common after COVID-19, yet traditional assessments using carbon monoxide diffusing capacity (DLCO) alone may miss alveolar-capillary impairment.ObjectiveTo determine whether combining nitric oxide (DLNO5s) and carbon monoxide (DLCO5s) diffusing capacities enhances detection of post-COVID-19 lung impairment and whether summed z-scores outperform individual measures in classifying affected individuals.Design and methodsWe conducted an individual participant data meta-analysis using hierarchical mixed-effects modelling. The dataset included 572 COVID-19 survivors and 72 matched controls from six European centres. Lung function metrics-including spirometry, total lung capacity, DLNO5s and DLCO5s-were standardised into z-scores. Logistic models were compared using Bayesian Information Criterion and Leave-One-Out Information Criterion. Classification accuracy was assessed with Matthews Correlation Coefficient (MCC) and net reclassification improvement (NRI). Principal Component Analysis examined score structures, and dyspnoea severity was correlated with z-scores. Assessments were conducted 32-575 days post-infection (median=130 days).ResultsThe number of days between SARS-CoV-2 diagnosis and testing did not affect any of the measured z-scores. Summed DLNO5s + DLCO5s z-scores consistently outperformed individual metrics. The combined model improved MCC by 0.06 (95% CI 0.01 to 0.11) and NRI by 37% (95% CI 13 to 62%) over DLCO5s alone. The top model summed DLNO5s + DLCO5s model explained 10% of fixed and 59% of random variance. DLCO5s alone failed to identify reduced membrane diffusion in approximately 16% of cases. Dyspnoea severity was significantly associated with all diffusion indices (p<0.001), though combined scores showed no stronger correlation than single predictors.ConclusionSummed DLNO5s + DLCO5s z-scores enhance classification of post-COVID-19 pulmonary impairment beyond DLCO5s alone. The NO-CO double diffusion approach offers improved diagnostic discrimination between previously infected individuals and controls and aligns with symptom severity. These findings support broader clinical integration of combined diffusion metrics in post-COVID assessment

Pulmonary diffusing capacity and dyspnoea following COVID-19: Insights from multicentre datasets

Pulmonary complications remain a significant challenge for COVID-19 survivors, necessitating advanced diagnostic approaches for long-term assessment. We present a curated, open-access dataset of pulmonary function measurements-including nitric oxide (DLNO) and carbon monoxide (DLCO) diffusing capacities-in 572 post-COVID-19 patients and 72 healthy controls (filtered from an original cohort of 726 survivors and 126 controls). Collected across eight international centres, the data include demographics, spirometry, lung volumes, and 5-6 s single-breath DLNO5s, DLCO5s, and alveolar volume (VA5s). Missing values for total lung capacity were imputed, and low-quality or system-specific (Hyp'Air Compact) measurements were excluded in the filtered dataset. A third subset (333 patients, 54 controls) links these measurements to dyspnoea severity (mMRC scale) for correlation and proportional odds analyses. This resource underpins predictive modeling of post-COVID pulmonary impairment via summed z-scores (DLNO + DLCO) and aims to accelerate validation of NO-CO diagnostics. The freely accessible datasets are provided in both SPSS (.sav) and .csv formats at the Mendeley Data Cloud-based repository and includes nominal, ordinal, and scalar data