Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times ...to maturity; the Capital Asset Pricing Model (CAPM) implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as
t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.
In modern society, traffic and transportation and the manufacturing industry and construction industries continuously release large amounts of dust and particles into the atmosphere, which can cause ...heavy air pollution, leading to health hazards. The haze disaster, a serious problem in developing countries such as China and India, has become one of the main issues of global environmental pollution in recent decades. Many air filtration technologies have been developed. Air filtration using electrospun fibers that intercept fine particles/volatile organic gases/bacterium is a relatively new, but highly promising, technique. Due to their interconnected nanoscale pore structures, highly specific surface areas, fine diameters, and porous structure as well as their ability to incorporate active chemistry on a nanoscale surface, electrospun fibers are becoming a promising versatile platform for air filtration. In this review, following a short introduction concerning the need for air filtration and filtration theory and mechanism, electrospun nanofibers membranes for air filtration have been highlighted, including the preparation (electrospinning process) and the parameters relevant to filtration efficacy. Additionally, various types (function) of the electrospun air filtration membranes have been classified in detail. Furthermore, their potential in the filtration of fine particles and chemical pollutants has been discussed. Finally, the challenges of their practical application and the future prospects have been summarized. Given that some advanced electrospun air filtration nanofibrous membranes exist for treating different contaminants from various types of polluted atmosphere, it is believed that they should make a significant contribution in protection against air pollution.
Various types and properties of the electrospun nanofibrous membranes for different contributions to remove airborne contaminants.
Causal discovery, the inference of causal relations among variables from data, is a fundamental problem of science. Nowadays, due to an increased awareness of data privacy concerns, there has been a ...shift towards distributed data collection, processing and storage. To meet the pressing need for distributed causal discovery, we propose a novel federated DAG learning method called distributed annealing on regularized likelihood score (DARLS) to learn a causal graph from data stored on multiple clients. DARLS simulates an annealing process to search over the space of topological sorts, where the optimal graphical structure compatible with a sort is found by distributed optimization. This distributed optimization relies on multiple rounds of communication between local clients and a central server to estimate the graphical structure. We establish its convergence to the solution obtained by an oracle with access to all the data. To the best of our knowledge, DARLS is the first distributed method for learning causal graphs with such finite-sample oracle guarantees. To establish the consistency of DARLS, we also derive new identifiability results for causal graphs parameterized by generalized linear models, which could be of independent interest. Through extensive simulation studies and a real-world application, we show that DARLS outperforms existing federated learning methods and is comparable to oracle methods on pooled data, demonstrating its great advantages in estimating causal networks from distributed data.
Q methodology was created as a means to explore and map subjective viewpoints in a systematic, relational and holistic manner. In this paper, we discuss Q methodology as a promising hybrid approach ...and present methodological takeaways from an online Q study on the meanings of reconciliation in Colombia, based on data obtained in 2021. Q is a method of capturing subjectivity that conveys an aura of objectivity, because researchers seldom explicitly engage subjectivity We provide a brief overview of our research project, showcase some results, and offer a lens through which to reflect on the entanglement of qualitative and quantitative moments in Q methodology. We spell out its interpretive layers, highlighting the role of subjectivity in two key phases of the research: the design of the study (image-based Q items) and the interpretive process (factor analysis). Although the quantitative moments of Q are seductive in their promise of objective factor analytical measurement, we argue that Q requires researchers to practice reflexivity and to explicitly engage with their subjectivity.
Bayesian networks are a class of popular graphical models that encode causal and conditional independence relations among variables by directed acyclic graphs (DAGs). We propose a novel structure ...learning method, annealing on regularized Cholesky score (ARCS), to search over topological sorts, or permutations of nodes, for a high-scoring Bayesian network. Our scoring function is derived from regularizing Gaussian DAG likelihood, and its optimization gives an alternative formulation of the sparse Cholesky factorization problem from a statistical viewpoint. We combine simulated annealing over permutation space with a fast proximal gradient algorithm, operating on triangular matrices of edge coefficients, to compute the score of any permutation. Combined, the two approaches allow us to quickly and effectively search over the space of DAGs without the need to verify the acyclicity constraint or to enumerate possible parent sets given a candidate topological sort. The annealing aspect of the optimization is able to consistently improve the accuracy of DAGs learned by greedy and deterministic search algorithms. In addition, we develop several techniques to facilitate the structure learning, including pre-annealing data-driven tuning parameter selection and post-annealing constraint-based structure refinement. Through extensive numerical comparisons, we show that ARCS outperformed existing methods by a substantial margin, demonstrating its great advantage in structure learning of Bayesian networks from both observational and experimental data. We also establish the consistency of our scoring function in estimating topological sorts and DAG structures in the large-sample limit. Source code of ARCS is available at https://github.com/yeqiaoling/arcs_bn .
2 mm: A new technique for sorting data Mubarak, Abbas; Iqbal, Sajid; Naeem, Tariq ...
Theoretical computer science,
04/2022, Letnik:
910
Journal Article
Recenzirano
•2 mm: a novel approach for sorting Data.•A Modification in MMBPSS.•Comparison based sorting.
In computation, sorting is highly essential to access and manipulate data efficiently. High-performance ...sorting algorithms have always been in demand so that computers may process data more quickly. Since the computer has become a vital tool in various domains of human life, the various researchers have investigated and presented numerous sorting algorithms to sort elements of list with minimal execution time and least space. As the volume of data increases, the urgency for efficient data processing algorithms also increases. In this novel work, we present a comparison-based sorting algorithm titled “2 mm” which is a modification of the sorting algorithm Min-Max Bidirectional Parallel Selection Sort (MMBPSS). The proposed algorithm follows divide and conquers method and uses constant space complexity i.e. O(n). Although 2 mm sort differs slightly from MMBPSS sort, its computational cost is very low and it reduces more than 50% comparison cost hence presents a more efficient solution to the sorting problems in the modern era. For performance evaluation and comparison, extensive experimentation has been performed that shows the better performance of the proposed method.
The reliability and validity of the Attachment Q Sort (AQS; Waters & Deane, 1985) was tested in a series of meta-analyses on 139 studies with 13,835 children. The observer AQS security score showed ...convergent validity with Strange Situation procedure (SSP) security (r = .31) and excellent predictive validity with sensitivity measures (r = .39). Its association with temperament was weaker (r = .16), which supports the discriminant validity of the observer AQS. Studies on the stability of the observer AQS are still relatively scarce but they have yielded promising results (mean r = .28; k = 4, n = 162). It is concluded that the observer AQS, but not the self-reported AQS, is a valid measure of attachment.
To assess the seismic failure risk of post electrical equipment, an assessment method considering different sorts of uncertainty of the post electrical equipment was proposed. The aleatory and ...epistemic uncertainties were considered in the assessment, and the parameters in seismic hazard function of different sites were fitted. To investigate the effects of the supporting structure on the seismic fragility and risk of post electrical equipment, case studies on ultra-high-voltage gas insulated switchgear bushings mounted on two different supporting frames were conducted. The results indicated that both the maximum tensile stress of the bushing and the maximum displacement of the supporting frames should be considered as the limit statuses of the post electrical equipment. The different sorts of uncertainty increase the seismic failure risk of the post electrical equipment, and should be considered in the assessment. Besides, for the pillar-type porcelain element equipment, the supporting frames with lower lateral stiffness generated higher seismic failure risk. In constrast to the case of retrofitting the supporting frame to increase the lateral stiffness, the annual seismic failure risk of the GIS bushing mounted on the retrofitted supporting frame decreased 101%. Besides, the seismic failure risk of the post electrical equipment is not positive correlated with the peak ground acceleration. In the performance-based seismic design of the electrical substation, the seismic failure risk of the electrical equipment should be considered.
This paper proposes a new technique to identify sets of branches that form heavily loaded and potentially vulnerable flowgates within power grids. To this end, a directed acyclic graph is used to ...model the instantaneous state of power grids. One of the advantages of directed acyclic graphs is they allow the identification of where power flows are coherent e.g where power flows in a uniform direction along a set of branches that partition the network into two islands. This paper uses topological sorts to identify many sets of branches having this property. Definitions are provided for two new concepts, termed coherent cut-sets and coherent crack-sets, which are particular sets of branches extracted from a specific topological sort. Notably, there are numerous possible topological sorts for a directed acyclic graph and calculating distinctive topological sorts is challenging. In this paper a novel optimization algorithm is proposed to find multiple, diverse topological sorts each of which implies many cut-sets. The effectiveness of the proposed methods for enhancing grid observability and situational awareness is demonstrated using two standard test networks.
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