Prominent Competitor Research Articles

Adaptive location and scale estimation with kernel-weighted averages

A wide variety of location and scale estimators have been developed for light-tailed distributions. Despite indisputable importance in business, finance, cybersecurity, etc., statistical estimation and inference in the presence of heavy tails have received less attention in the literature. We adopt the Kernel-Weighted Average (KWA) approach to location and scale estimation and present a set of extensive comparisons with five prominent competitors. Unlike nonparametric kernel density estimation, the optimally tuned bandwidth for KWA estimators does not necessarily converge to zero as sample size grows. We also perform a large-scale Monte Carlo simulation to search for the optimal bandwidth that minimizes the mean squared error (MSE) of KWA location and scale estimators with simulated samples from Student’s t-distribution with degrees of freedom (df) 1 , 2 , … , 30 . We further develop an adaptive technique to estimate the df that best match the observed samples using Cramér-von Mises test of goodness-of-fit. Unlike many existing methodologies, our approach is data-driven and exhibits excellent statistical performance. To illustrate this, we apply it to three real-world financial datasets containing daily closing prices of AMC Entertainment (AMC), GameStop (GME) and Meta Platforms (META) stocks to calibrate a geometric random walk model with Student’s t log-increments.

A new Topp-Leone Kumaraswamy Marshall-Olkin generated family of distributions with applications

We aim in this paper to propose a novel class of distributions that was created by merging the Topp-Leone distribution and the Generated families of Kumaraswamy and Marshall-Olkin. Its cumulative distribution function characterizes it and includes rational and polynomial functions. In particular, the following desirable properties of the new family are presented: Shannon entropy, order statistics, the quantile power series, and several associated measures and functions. Then, using a specific family member identified before, we create a parametric statistical model with the basic distribution being the inverse exponential distribution. Finally, a thorough investigation has been made to implement this new distribution with three data sets: the glass fibers data set, the glass Alumina data set and the hailing times data set. In comparison to six prominent competitors, the new model performs favorably on all statistical tests and criteria that were examined.

Synthesis and Optimization of Cs2B'B″X6 Double Perovskite for Efficient and Sustainable Solar Cells.

Hybrid perovskite materials with high light absorption coefficients, long diffusion lengths, and high mobility have attracted much attention, but their commercial development has been seriously hindered by two major problems: instability and lead toxicity. This has led to lead-free halide double perovskite becoming a prominent competitor in the photovoltaic field. For lead-free double perovskites, Pb2+ can be heterovalent, substituted by non-toxic metal cations as a double perovskite structure, which promotes the flexibility of the composition. However, the four component elements and low solubility in the solvent result in synthesis difficulties and phase impurity problems. And material phase purity and film quality are closely related to the number of defects, which can limit the photoelectric performance of solar cells. Therefore, based on this point, we summarize the synthesis methods of Cs2B'B″X6 double perovskite crystals and thin films. Moreover, in the application of solar cells, the existing research mainly focuses on the formation process of thin films, band gap adjustment, and surface engineering to improve the quality of films and optimize the performance of devices. Finally, we propose that Cs2B'B″X6 lead-free perovskites offer a promising pathway toward developing highly efficient and stable perovskite solar cells.

Optimal Portfolio Using Factor Graphical Lasso

Abstract Graphical models are a powerful tool to estimate a high-dimensional inverse covariance (precision) matrix, which has been applied for a portfolio allocation problem. The assumption made by these models is a sparsity of the precision matrix. However, when stock returns are driven by common factors, such assumption does not hold. We address this limitation and develop a framework, Factor Graphical Lasso (FGL), which integrates graphical models with the factor structure in the context of portfolio allocation by decomposing a precision matrix into low-rank and sparse components. Our theoretical results and simulations show that FGL consistently estimates the portfolio weights and risk exposure and also that FGL is robust to heavy-tailed distributions which makes our method suitable for financial applications. FGL-based portfolios are shown to exhibit superior performance over several prominent competitors including equal-weighted and index portfolios in the empirical application for the S&P500 constituents.

China’s Digital Yuan: Motivations of the Chinese Government and Potential Global Effects

ABSTRACT This article highlights the key motivations behind China’s plan to launch the digital yuan and reviews the potential impacts on China and abroad. The article analyzes the digital yuan’s benefits to consumers, such as a reliable low-risk, low cost, and high-efficiency payment solution and the potential to promote financial inclusion. It compares the digital yuan with its most prominent competitors. Also discussed is how the digital yuan is expected to provide the Chinese Communist Party with a new powerful tool to monitor and control its economy and people. The article provides a critical evaluation of the potential of the digital yuan’s internationalization. This article also provides a perspective on the digital yuan to set global standards for the development of national digital currencies.

Container Technologies for ARM Architecture: A Comprehensive Survey of the State-of-the-Art

Container technology is becoming increasingly popular as an alternative to traditional virtual machines because it provides a faster, lighter, and more portable runtime environment for the applications. A container bundles the application and its binary code, libraries, and configuration files together while sharing the host operating system image. Accordingly, containers efficiently share resources and operate small micro-services, software programs, and even more extensive applications with less overhead than virtual machines. There are many container technologies available with Docker being the most popular and many technologies support multiple architectures, including the ARM architecture. Due to its energy efficiency and high-performance, which are crucial parameters in containerization, ARM architecture is becoming prevalent in container technologies. In this paper, we explore various container technologies that support ARM architecture and investigate the pros and cons of each technology. Moreover, we provide a comparative analysis of both container orchestrators and container runtimes that are most prominent competitors of Docker. We also consider security of container technologies with particular focus on the image scanning tools that supports ARM architecture. Our survey reveals that ARM technology is gaining popularity in containerization and almost all recent technologies support ARM architecture.

Testing normality in any dimension by Fourier methods in a multivariate Stein equation

We study a novel class of affine‐invariant and consistent tests for multivariate normality. The tests are based on a characterization of the standard d‐variate normal distribution by way of the unique solution of an initial value problem connected to a partial differential equation, which is motivated by a multivariate Stein equation. The test criterion is a suitably weighted L2‐statistic. We derive the limit distribution of the test statistic under the null hypothesis as well as under contiguous and fixed alternatives to normality. A consistent estimator of the limiting variance under fixed alternatives, as well as an asymptotic confidence interval of the distance of an underlying alternative with respect to the multivariate normal law, is derived. In simulation studies, we show that the tests are strong in comparison with prominent competitors and that the empirical coverage rate of the asymptotic confidence interval converges to the nominal level. We present a real data example and also outline topics for further research.

The Microalga Chlorella vulgaris as a Natural Bioenergetic System for Effective CO2 Mitigation—New Perspectives against Global Warming

In the present contribution, the differentiation in the molecular structure and function of the photosynthetic apparatus of the unicellular green alga Chlorella vulgaris was studied at several light intensities (0–400 μmol m−2 s−1) and various CO2 concentrations (0.04–60% CO2), in completely autotrophic conditions. Asymmetries that occur by different light intensities and CO2 concentrations induce metabolic and functional changes. Using chlorophyll fluorescence induction techniques (OJIP test), we showed that Chlorella vulgaris tolerates extremely high CO2 levels and converts them photosynthetically into valuable products, including O2 and biomass rich in carbohydrates and lipids. Interestingly, the microalga Chlorella vulgaris under extremely high CO2 concentrations induces a new metabolic state intensifying its photosynthetic activity. This leads to a new functional symmetry. The results highlight a potent CO2 bio-fixation mechanism of Chlorella vulgaris that captures up to 288 L CO2 L PCV−1 day−1 under optimal conditions, therefore, this microalga can be used for direct biological CO2-reducing strategies and other green biotechnological applications. All of the above suggest that Chlorella vulgaris is one of the most prominent competitors for a closed algae-powered bioreactor that is able to consume huge amounts of CO2. Thus, it is a sustainable and natural bioenergetic system with perspectives in dealing with major environmental issues such as global warming. In addition, Chlorella vulgaris cultures could also be used as bioregeneration systems in extraterrestrial missions for continuous atmospheric recycling of the human settlements, paving the way for astrobiological applications.

Sequential search and firm prominence

We explore the role of prominence in equilibrium pricing in markets where search is sequential and random. Our model key feature is that more prominent firms are more likely to be sampled first. In contrast to ordered-search models, we find that more prominent firms inherit larger but less elastic demands, and as such have incentives to post larger prices. However, they might post lower prices but still charge higher markups than less prominent competitors only if they are also sufficiently more efficient. Our results suggest that when search is sequential, the role of prominence depends on whether it modifies the order or just the chances with which firms are sampled.

Desert-Adjusted Utilitarianism, People, and Animals

Recent decades have witnessed a surge in philosophical attention to the moral standing of non-human animals. Kantians, Neo-Kantians, utilitarians, and radical animal rights theorists have staked their claims in the literature. Here Fred Feldman’s desert-adjusted utilitarianism is introduced into the fray. After canvassing the prominent competitors in the dialectic, a conception of an overall moral ranking (relative to a moral choice scenario) consonant with desert-adjusted utilitarianism is developed. Then the conception’s implications regarding the particular locations of individual people and animals in such rankings across various scenarios is explored. Ultimately, it is argued that when it comes to evaluating whether or not some benefit (or burden) morally ought to be bestowed upon some specific person or animal, this new conception of an overall moral ranking is sensitive to a wider range of morally relevant phenomena than its more prominent competitors.

A new test of multivariate normality by a double estimation in a characterizing PDE

This paper deals with testing for nondegenerate normality of a d-variate random vector X based on a random sample X_1,ldots ,X_n of X. The rationale of the test is that the characteristic function psi (t) = exp (-Vert tVert ^2/2) of the standard normal distribution in {mathbb {R}}^d is the only solution of the partial differential equation varDelta f(t) = (Vert tVert ^2-d)f(t), t in {mathbb {R}}^d, subject to the condition f(0) = 1, where varDelta denotes the Laplace operator. In contrast to a recent approach that bases a test for multivariate normality on the difference varDelta psi _n(t)-(Vert tVert ^2-d)psi (t), where psi _n(t) is the empirical characteristic function of suitably scaled residuals of X_1,ldots ,X_n, we consider a weighted L^2-statistic that employs varDelta psi _n(t) -(Vert tVert ^2-d)psi _n(t). We derive asymptotic properties of the test under the null hypothesis and alternatives. The test is affine invariant and consistent against general alternatives, and it exhibits high power when compared with prominent competitors. The main difference between the procedures are theoretically driven by different covariance kernels of the Gaussian limiting processes, which has considerable effect on robustness with respect to the choice of the tuning parameter in the weight function.

Production of referring expressions by children with ASD: Effects of referent accessibility and working memory capacity

ABSTRACT This study examines the discourse basis for referent accessibility and its relation to the choice of referring expressions by children with Autism Spectrum Disorder (ASD) and typically developing children. The aim is to delineate how the linguistic and extra-linguistic context affects referent accessibility to the speaker. The study also examines the degree to which accessibility effects are modulated by cognitive factors such as working memory capacity. In the study, the contrast levels between the referent and a competitor (one contrast/two contrasts) and the syntactic prominence of the referent (subject/object position in the preceding question) were manipulated in an elicited production task. The results provide evidence that the referring expressions of children with ASD correlate with the discourse status of referents to a similar extent as in typically developing controls. All children were more likely to refer with lexical NPs to referents that contrasted on two levels with a highly prominent competitor, compared to referents that contrasted on one level. They were also more likely to produce pronouns for referents previously mentioned in the subject than the object position. The effect of both discourse factors was modulated by the age and working memory capacity of the children with and without ASD. Accordingly, the study suggests that children with ASD do not generally differ from children with typical development in their referential choices when the discourse status of a referent allows them to model the referent’s accessibility from their own discourse perspective in a way that is modulated by working memory capacity.

Search and Price Dispersion in Oligopolies

We explore the role of prominence in equilibrium pricing in markets where search is sequential and random. Our model key feature is that more prominent firms are more likely to be sampled first. In contrast to ordered-search models, we find that more prominent firms inherit larger but less elastic demands, and as such have incentives to post larger prices. However, they might post lower prices than less prominent competitors only if they are also sufficiently more efficient. Our results suggest that when search is sequential, the role of prominence depends on whether it modifies the order or just the chances with which firms are sampled.

Disruptor-in-chief?

AbstractOne prominent competitor to press influence on the public in digital spaces is the President of the United States. This presidential influence is largely unaccounted for, however, in contemporary agenda-setting models. This study examines the network agenda-building and setting capabilities of President Trump around tax reform and North Korea to determine whether and how presidential use of Twitter facilitates agenda building and disrupts the traditional press/public agenda-setting process. Offered in this research are contributions to network agenda setting by placing this theoretical perspective in conversation with research on how the press and public “echo” the language of the president under particular circumstances. Our results illustrate the president can disrupt press-public agenda formation in some circumstances, but popular accounts of the all-disrupting influence President Trump has on political life should be approached cautiously.

Catalytic Motifs in Bio-Inspired Materials As New Generation Electrocatalysts

Bio-inspired and bioorganic materials gain outmost of interest due to a wide application area. In the past years, hydrogen-bonded organic semiconductors relying on indigoid pigment family are applied in various device geometries e.g. organic solar cells, organic field effect transistors but also as thin film electrodes in catalysis [1,2]. Currently, the integration of the bio-inspired materials in sustainable catalysis is powerful. Especially, organic functionalities present in the chemical structure of this new material class provide these compounds outstanding properties in terms of using these functional themes as catalytic active centers to substitute state-of-the-art metallic catalysts. Herein, we report on the suitability of a bio-originated polymer – Polydopamine (PDA) - as an effective electrocatalyst [3]. Polydopamine is a major pigment of the eumelanin family. Due to its hydrogen-bonded sequences in the conjugated structure, stabilized over hydroxyl, amine and carbonyl groups, PDA is a prominent competitor for the new generation of sustainable catalysis. We engineered a new synthetic pathway for the polydopamine electrode prepraration [4]. We apply the chemical vapor deposition technique in the presence of the monomer dopaminhydrochlorid together with sulfuric acid as an oxidant in order to form polydopamine films directly on 3D, sponge-like carbon felt electrodes, creating an increased catalytically active surface area. Electrochemical investigations exhibit the interaction and interplay of the functionalities in catalytic processes resulting in high yields and current densities and thus reducing energy losses. [1] Glowacki E. D.; Irimia-Vladu M.; Kaltenbrunner M.; Gasiorowski J.; White M. S.; Monkowius U.; G. Romanazzi G.; Suranna G. P.; Mastrorilli P.; Sekitani T.; Bauer S.; Someya T.; Torsi L.; Sariciftci N. S.; Adv. Mater., 2013, 25, 1563–1569. [2] Glowacki E. D.; Romanazzi G.; Yumusak C.; Coskun, H.; Monkowius U.; Voss G.; Burian M.; Lechner R. T.; Demitri N.; Redhammer G. J.; Sünger N.; Suranna G. P.; Sariciftci N. S.; Adv. Funct. Mater.; 2014, DOI: 10.1002/adfm.201402539. [3] Coskun, H.; Aljabour, A.; De Luna, P.; Farka, D.; Greunz, T.; Stifter, D.; Kus, M.; Zheng, X.; Liu, M.; Hassel, A. W.; Schöfberger, W.; Sargent, E. H.; Sariciftci, N. S.; Stadler, P.; Sci. Adv. 2017, 3 (8), e1700686 DOI: 10.1126/sciadv.1700686. [4] Coskun, H.; Aljabour, A.; Uiberlacker, L.; Strobel, M.; Hild, S.; Cobet, C.; Farka, D.; Stadler, P.; Sariciftci, N. S.; 2018, 645 (August 2017), 320–325 DOI: 10.1016/j.tsf.2017.10.063.

Improbable Denver

Improbable Denver

An improved binary randomized response model using six decks of cards

ABSTRACTThis article purposes the estimation of population proportion of a sensitive attribute through randomized response technique. An efficient estimator is suggested using six decks of cards to randomise the response. Many existing models can now be viewed as the special case of the proposed model. The superiority of the proposed procedure is established through numerical calculation of percentage relative efficiency with prominent competitors. The proposed procedure is also studied under stratified random sampling protocol. In addition, it is shown that, the proposed stratified estimator, performs better in term of efficiency than its only existing two deck stratified competitor.

Market-Dominant Small Jurisdictions in a Globalizing Financial World

Over recent decades small jurisdictions have become big players in cross-border corporate and financial services. To date, however, their nature, legal status, and market roles remain under-theorized. Lacking a coherent vocabulary to describe the functions that such jurisdictions perform -- and the peculiar strengths of those small jurisdictions actually achieving substantial success in the financial marketplace -- we find ourselves unable to evaluate their social and economic impacts in a nuanced and rigorous manner. Accordingly, this article proposes a new conceptual framework with the dual aim of refining the debate regarding the legitimacy and desirability of their activities, and reorienting that debate toward more productive inquiries. Part II canvasses extant conceptual frameworks used to describe and evaluate the roles of small jurisdictions in cross-border corporate and financial services. These include literatures exploring globalization and the impact of English legal origins, as well as literatures variously characterizing such jurisdictions as tax havens, offshore financial centers, micro-states, and global cities. Finding each paradigm incapable of accounting for the range of small jurisdictions that have achieved substantial success, Part III proposes a new concept that better captures their market roles and salient characteristics -- the market-dominant small (MDSJ). I first set out an ideal type, identifying the central, consequential features giving rise to their competitive strengths and fueling their substantial successes. Notably, MDSJs (1) are small in both population and land area; (2) are poorly endowed in natural resources, limiting their economic development options; (3) possess legislative autonomy (if not full sovereignty); (4) are culturally proximate to major economic powers, and favorably situated geographically vis-a-vis those powers, often performing critical bridging functions among them; (5) heavily invest in human capital, professional networks, and related institutional structures; (6) consciously balance close collaboration with and robust oversight of the financial professional community, at once conveying flexibility, stability, and credibility; (7) exhibit low levels of perceived public corruption; and (8) actively seek to minimize the political and diplomatic salience of cross-border corporate and financial services. The foregoing ideal type provides a benchmark against which to evaluate four jurisdictions that have achieved dominance in particular areas of cross-border corporate and financial services: Bermuda, well established among the world's preeminent insurance markets; Singapore, a rising power in wealth management; Switzerland, the long-standing leader in private banking; and Delaware, the predominant jurisdiction for the incorporation of U.S. publicly traded companies and a globally prominent competitor in the organization of various forms of business entities. Part IV concludes, suggesting that notwithstanding MDSJs' apparent vulnerability to exertions of economic and diplomatic pressure by major markets, the practical significance of MDSJs will likely continue to grow - as will the practical need for a more effective means of theorizing the roles they play in cross-border corporate and financial services, and the dynamics their ascendance reveals. Accordingly, we should not remain content with flawed conceptual frameworks and vocabularies that lack sufficient nuance and all too often facilitate glib -- and even hypocritical -- generalizations about their social and economic impacts.

A Max-Flow Design Approach for Improved Service Availability in Multi-Ring ERP Networks

Ethernet Ring Protection (ERP) has recently emerged to provide protection switching for Ethernet ring topologies with sub-50 ms failover capabilities. In addition to Ethernet's cost-effectiveness and simplicity, ERP's promise to also provide protection in mesh packet transport networks positions Ethernet as a prominent competitor to conventional SONET/SDH and the technology of choice for carrier networks. Higher service availability, however, in ERP mesh networks has been challenged by the issue of network partitioning and the contention for protection resources which may be caused by concurrent failures. In this paper, we show that in a mesh network designed to withstand only single failure situations, network services usually suffer from two outage categories subject to concurrent dual-link failures. We address the problem of minimal capacity network design to provide high service availability against concurrent dual-link failures. We cast this combinatorially complex design problem as an optimization one and show that higher service availability can be achieved by proper RPL (Ring Protection Link) placement and ring hierarchy selection. The objective is to maximize the network flow under any dual-link failure scenario. Our design achieves minimal capacity allocation that minimizes the number of service outages (up to 37%) therefore achieving higher service availability. Numerical evaluation and comparative study show that the joint desgin approach of the ILP model provisions 8% less capacity than the sequential two-step approach to achieve similar service availability.

Design of Resilient Ethernet Ring Protection (ERP) Mesh Networks With Improved Service Availability

Ethernet Ring Protection (ERP) has recently emerged to provide protection switching for Ethernet ring topologies with sub-50 ms failover capabilities. ERP's promise to provide protection in mesh packet transport networks positions Ethernet as a prominent competitor to conventional SONET/SDH and as the technology of choice for carrier networks. Higher service availability, however, in ERP has been challenged by the issue of network partitioning and contention for shared capacity caused by concurrent failures. In this paper, we show that in a network designed to withstand single-link failure, the service availability, in the presence of double link failures, depends on the designed ERP scheme, i.e., the RPL placement as well as the selection of ring hierarchy. Therefore, we present a study for characterizing service outages and propose a design method which strikes a balance between capacity requirement and service availability (i.e., the number of service outages resulting from concurrent failures). We observe that through effective design, remarkable reduction in service outages is obtained at a modest increase in capacity deployment.