Search Results (6)

The global space economy, valued at approximately USD 400–630 billion (depending on definitional scope), is projected to expand rapidly, crossing USD 1 trillion as early as 2032 and reaching up to about USD 1.8 trillion by 2035. This growth has been driven by a surge (a roughly twelvefold increase) in satellite launches over the past decade, transforming Earth’s orbits into an increasingly congested domain plagued by space debris. The proliferation of space junk poses an escalating threat to orbital sustainability, yet effective governance mechanisms remain limited. This paper examines why conventional solutions for managing common-pool resources (command-and-control regulation, Pigouvian taxes, private property rights, allocation of tradable permits, and horizontal governance regimes) are not fully effective or are difficult to implement in addressing the orbital debris problem. Using a system dynamics perspective, the study qualitatively maps hypothesized feedback mechanisms shaping orbital expansion and space debris accumulation. It suggests that, under the assumed causal structure, reinforcing growth loops associated with geopolitical rivalry and commercial cost reductions linked to the New Space paradigm currently dominate over delayed balancing effects arising from the finite nature of orbital space, whose regenerative capacity is progressively degraded. There exists a threshold of exploitation beyond which orbital space effectively behaves as a non-renewable resource. The analysis suggests that, without binding international coordination, meaningful intervention may require the occurrence of a catalyzing crisis—e.g., a localized cascade of orbital object collisions that could transform stakeholder perceptions and enables active debris removal deployment. Full article

Background: Patients with arrhythmias, particularly paroxysmal supraventricular tachycardia (PSVT), face an increased risk of cardiac complications. Currently, non-parenteral medications for rapid PSVT cessation are lacking. Etripamil, a novel intranasal, short-acting calcium channel blocker, offers a rapid onset and the potential for unsupervised PSVT management. However, data on its use in arrhythmia management remain limited. Aims: We aimed to assess the efficacy and safety of 70 mg of etripamil compared with placebo in the treatment of PSVT. Methods: We systematically searched PubMed, Embase, Web of Science, Scopus, and the Cochrane Library for randomized controlled trials (RCTs) from inception to April 2025. We calculated pooled risk ratios (RRs) with 95% confidence intervals (CIs) using random or common effects models, depending on the heterogeneity. Results: Four RCTs including 540 patients were analyzed. Etripamil demonstrated higher conversion rates to the sinus rhythm at 15 min (RR 1.84 [95% CI: 1.32–2.48]), 30 min (RR 1.80 [95% CI: 1.38–2.35]), and 60 min (RR 1.24 [95% CI: 1.04–1.48]). PSVT recurrence rates were similar between groups (RR 0.52 [95% CI: 0.20–1.34]). Adverse events (AEs) and severe AEs were comparable between etripamil and the placebo. Etripamil was associated with higher rates of nasal discomfort, nasal congestion, rhinorrhea, and epistaxis but not with increased bradyarrhythmia, atrial fibrillation, or non-sustained ventricular tachycardia. Conclusions: Etripamil appears to be a promising treatment for cardiac arrhythmias. Larger long-term RCTs are needed to confirm its safety and efficacy in clinical practice. Full article

Automatic modulation classification is an important component in many modern aeronautical communication systems to achieve efficient spectrum usage in congested wireless environments and other communications systems applications. In recent years, numerous convolutional deep learning architectures have been proposed for automatically classifying the modulation used on observed signal bursts. However, a comprehensive analysis of these differing architectures and the importance of each design element has not been carried out. Thus, it is unclear what trade-offs the differing designs of these convolutional neural networks might have. In this research, we investigate numerous architectures for automatic modulation classification and perform a comprehensive ablation study to investigate the impacts of varying hyperparameters and design elements on automatic modulation classification accuracy. We show that a new state-of-the-art accuracy can be achieved using a subset of the studied design elements, particularly as applied to modulation classification over intercepted bursts of varying time duration. In particular, we show that a combination of dilated convolutions, statistics pooling, and squeeze-and-excitation units results in the strongest performing classifier achieving 98.9% peak accuracy and 63.7% overall accuracy on the RadioML 2018.01A dataset. We further investigate this best performer according to various other criteria, including short signal bursts of varying length, common misclassifications, and performance across differing modulation categories and modes. Full article

A multi-cluster cloud radio access network (C-RAN) is considered in this paper where the remote radio heads (RRHs) form different clusters. A cluster includes RRHs that have the same radio resource unit capacity. In addition, all RRHs are separated from the common pool of computational resource units named baseband units. Each RRH accommodates calls whose arrival process can be random, quasi-random, or even bursty. The latter is modeled according to the compound Poisson process where calls arrive in the C-RAN in the form of batches whose size (in calls) is generally distributed. An arriving call requires a radio and a computational resource unit so as to be accepted in the C-RAN. If at least one of these units is not available, the call is blocked. To analyze the proposed multi-cluster C-RAN we model it as a loss system, show that the steady-state probabilities have a product form solution and propose an algorithm for the computation of congestion probabilities. The accuracy of the proposed algorithm is verified via simulation. Full article

This study extends recent research on informal property rights at surf breaks by exploring the process through which nature, by establishing conditions conducive (or not) to the presence of sharks, shapes the baseline level of exploitation by surfers of the common-pool resource represented by surf breaks. Since 1980, there have been nine fatal shark attacks off the coast of California, and in all nine cases the great white shark was the offending species. Given this inherent danger, the presence of large sharks mitigates, at least to some degree, the tendency toward the ‘tragedy of the commons’ in the case of surf breaks. Using data on surf break congestion, surf break quality, shark activity, and other key variables from 144 surf breaks in California, empirical results from OLS and ordered probit models presented in this study indicate that surf breaks in California that are associated with the highest levels of shark activity tend to be less congested, perhaps by as much as 28%, than their counterparts that are visited less often by sharks. Full article

In most developing coastal countries, the artisanal fisheries sector is managed as a common pool resource. As a result, such fisheries are overcapitalized and overfished. In Ghana, in addition to anthropogenic factors, there is evidence of rising coastal temperature and its variance, which could impact the environmental carrying capacity of the fish stock. This study investigates the effect of climate variation on biophysical parameters and yields. Our results indicate that the rising temperature is decreasing the carrying capacity. As a result, an optimum tax on harvest must reflect climate variability, as well as the congestion externality. Full article