Search Results (6)

In the context of ongoing climate change, extreme weather events are becoming increasingly frequent and unpredictable, posing significant challenges for traditional probability-based methods. This study presents an innovative uncertainty-based Box–Cox regression framework to assess the impacts of climate change factors, specifically temperature and precipitation, on the volatility of extreme weather events in the Chengdu-Chongqing region. To address data imprecision, we establish a new estimation theorem for the Extended Least Squares Estimator (ELSE), proving its existence, uniqueness, unbiasedness, and variance consistency under uncertainty theory. The Mann–Kendall trend test is applied to detect event frequency trends, and a coupling coordination degree model is employed to evaluate the dynamic relationship between climate resources and economic development. The results show that (1) temperature has a more significant impact on the volatility of extreme weather events than precipitation; (2) the thermal resource–economy coupling degree has remained above 0.45 since 2015, indicating a strengthening relationship but suboptimal coordination; and (3) since 2014, the water resource–economy coupling degree has consistently exceeded 0.5, reaching optimal levels and highlighting the growing importance of water resources in regional development. Based on these findings, we recommend enhancing extreme weather monitoring systems, improving infrastructure resilience, optimizing climate-related resource management, and fostering regional cooperation. This study provides a rigorous theoretical and empirical basis for integrating uncertainty modeling into climate–economy analysis. Future work should further explore alternative modeling strategies and validate conclusions using extended datasets. Full article

This paper investigates the stability of predator–prey models within multi-patch environments, with a particular focus on the influence of cross-dispersion across patches. We apply Kirchhoff’s matrix tree theorem and Liapunov’s method to derive criteria related to the cross-dispersion topology, thus solving the challenge of determining global asymptotic stability conditions. The method incorporates realistic ecological interactions and spatial heterogeneity, offering a framework for stability analysis. Our findings demonstrate that an appropriate level of cross-dispersion can effectively mitigate oscillations and foster convergence toward equilibrium. Two numerical examples validate these theoretical results and demonstrate the feasibility and effectiveness of the model across multiple patches. Full article

Quantum computing allows the implementation of powerful algorithms with enormous computing capabilities and promises a secure quantum Internet. Despite the advantages brought by quantum communication, certain communication paradigms are impossible or cannot be completely implemented due to the no-cloning theorem. Qubit retransmission for reliable communications and point-to-multipoint quantum communication (QP2MP) are among them. In this paper, we investigate whether a Universal Quantum Copying Machine (UQCM) generating imperfect copies of qubits can help. Specifically, we propose the Quantum Automatic Repeat Request (QARQ) protocol, which is based on its classical variant, as well as to perform QP2MP communication using imperfect clones. Note that the availability of these protocols might foster the development of new distributed quantum computing applications. As current quantum devices are noisy and they decohere qubits, we analyze these two protocols under the presence of various sources of noise. Three major quantum technologies are studied for these protocols: direct transmission (DT), teleportation (TP), and telecloning (TC). The Nitrogen-Vacancy (NV) center platform is used to create simulation models. Results show that TC outperforms TP and DT in terms of fidelity in both QARQ and QP2MP, although it is the most complex one in terms of quantum cost. A numerical study shows that the QARQ protocol significantly improves qubit recovery and that creating more clones does not always improve qubit recovery. Full article

Inspired by the development in modern data science, a shift is increasingly visible in the foundation of statistical inference, away from a real space, where random variables reside, toward a nonmetrized and nonordinal alphabet, where more general random elements reside. While statistical inferences based on random variables are theoretically well supported in the rich literature of probability and statistics, inferences on alphabets, mostly by way of various entropies and their estimation, are less systematically supported in theory. Without the familiar notions of neighborhood, real or complex moments, tails, et cetera, associated with random variables, probability and statistics based on random elements on alphabets need more attention to foster a sound framework for rigorous development of entropy-based statistical exercises. In this article, several basic elements of entropic statistics are introduced and discussed, including notions of general entropies, entropic sample spaces, entropic distributions, entropic statistics, entropic multinomial distributions, entropic moments, and entropic basis, among other entropic objects. In particular, an entropic-moment-generating function is defined and it is shown to uniquely characterize the underlying distribution in entropic perspective, and, hence, all entropies. An entropic version of the Glivenko–Cantelli convergence theorem is also established. Full article

A newborn girl had, from two weeks on, small bruises on varying body locations, but not on her chest. Her Armenian grandmother easily bruised, too. Her mother was diagnosed with hypermobility-type Ehlers-Danlos-Syndrome (hEDS), an autosomal dominant connective tissue disorder, with a 50% inheritance probability. Referral to a University Medical Center located “Dutch Expertise Center for Child Abuse” resulted (prior to consultation) in physical abuse suspicion. Protocol-based skeletal X-rays showed three healed, asymptomatic rib fractures. A protocol-based Bayesian likelihood ratio guesstimation gave 10–100, erroneously used to suggest a 10–100 times likelier non-accidental-than-accidental cause. Foster care placement followed, even in a secret home, where she also bruised, suggesting hEDS inheritance. Correct non-accidental/accidental Bayes’ probability of symptoms is (likelihood ratio) × (physical abuse incidence). From the literature, we derived an infant abuse incidence between about ≈0.0009 and ≈0.0026 and a likelihood ratio of <5 for bruises. For rib fractures, we used a zero likelihood ratio, arguing their cause was birth trauma from the extra delivery pressure on the chest, combined with fragile bones as the daughter of an hEDS-mother. We thus derived a negligible abuse/accidental probability between <5 × 0.0009 <0.005 and <5 × 0.0026 <0.013. The small abuse incidence implies that correctly using Bayes’ theorem will also miss true infant physical abuse cases. Curiously, because likelihood ratios assess how more often symptoms develop if abuse did occur versus non-abuse, Bayes’ theorem then implies a 100% infant abuse incidence (unwittingly) used by LECK. In conclusion, probabilities should never replace differential diagnostic procedures, the accepted medical method of care. Well-known from literature, supported by the present case, is that (child abuse pediatrics) physicians, child protection workers, and judges were unlikely to understand Bayesian statistics. Its use without statistics consultation should therefore not have occurred. Thus, Bayesian statistics, and certainly (misused) likelihood ratios, should never be applied in cases of physical child abuse suspicion. Finally, parental innocence follows from clarifying what could have caused the girl’s bruises (inherited hEDS), and rib fractures (birth trauma from fragile bones). Full article

Negative inertia is an unusual and counter-intuitive property of matter, extensively investigated in some of the most exotic branches of physics and engineering at both macroscopic and microscopic levels. Such an exotic property promises a wide range of applications, from Alcubierre drive to acoustic wave manipulation. Here, a novel approach to the realization of negative inertia and the concept of negative-inertia converters are introduced for both translational and rotational motion. The proposed devices, capable of exhibiting negative mass and negative moment of inertia, base their operational principle on actuating the loading inertia, concealed within the housing of the device, synchronously with the displacement of the housing itself. Negative-inertia converters share many similarities with negative-impedance converters, including their proneness to instability. Thus, an equivalent circuit model of the proposed devices is developed and simulated in lossless and lossy environments. Friction, unavoidable in every practical system, is found to be the main cause of instability. The derived closed-form stability condition suggests that the effective inertia of a system containing a negative-inertia converter must remain positive to ensure the stability. Despite this limitation, negative-inertia converters may become the key elements in applications requiring reduction of an object’s inertia. Full article