The file drawer effect – a long-lasting issue in science

Most of the scientific outputs produced by researchers are inaccessible since they are not published in scientific journals: they remain in the researchers' drawers, forming what we call the Dark Science. This is a long-standing issue in research, creating a misleading view of the scientific facts. Contrary to the current literature overfed with positive findings, the Dark Science is nurtured with null findings, replications, flawed experimental designs and other research outputs. Publishers, researchers, institutions and funders all play an important role in the accumulation of those unpublished works, but it is only once we understand the reasons and the benefits of publishing all the scientific findings that we can collectively act to solve the Dark Science problem. In this article, we discuss the causes and consequences of the Dark Science expansion, arguing that science and scientists would benefit from getting all their findings to the light of publication.

New Private Types for the Cubic-Quartic Optical Solitons in Birefringent Fibers in Its Four Forms of Nonlinear Refractive Index

From the point power of view of the extended simple equation method, multiple new private distinct types for the cubic-quartic optical soliton birefringent fibers with four forms nonlinear refractive index which have and play a vital effective effect in all modern telecommunications process have been extracted. The suggested method which continuously gives surprise accurate results for most nonlinear science problem has been implemented to extract multiple new accurate cubic-quartic soliton for the different forms of the NLSE which are, the cubic-quartic in polarization-preserving fibers with the kerr-low nonlinearity, quadratic-cubic law nonlinearity, parabolic law nonlinearity and non-local law nonlinearity. Actual comparison between the achieved results and that demonstrated by other authors has been established.

The History of the 1947 Monetary Reform of the USSR in Moscow and Leningrad

Introduction. World and domestic economic history are the history of ups and downs, the history of finding ways out of difficult, sometimes crisis and critical situations, most often manifested both during and after wars. The Great Patriotic War, which dealt a blow to all spheres of life of the belligerent countries, was no exception. Testing the viability of the country’s economic model, in particular the Union of Soviet Socialist Republics, began directly during the war and continued after the end of hostilities. The relevance of the topic under study lies in the study of a positive example of the country’s recovery from the economic crisis, as well as the study of the reaction of the general population to the measures taken. The purpose of this article is to retrospectively analyze the economic situation of those years, to model the reader’s understanding of the reaction of society at that time to events and the way of solving the problem chosen by the party, as well as to demonstrate the results of the government’s activities. Materials and Methods. This study is based on the traditional methods used in the national historical science: problem-chronological, systemic and comparative-historical. Research Results. The analysis of the measures taken in the financial and economic sphere showed the consistency of the methods chosen by the government, however, the general assessment of the measures among the population turned out to be versatile. The assessments of the researchers of this problem, both Soviet and modern, are generally positive. Discussion and Conclusion. As a result of the monetary reform of 1947, the Soviet Union managed to avoid the depreciation of the ruble, the surplus of banknotes issued during the war years was eliminated, the state’s internal debt on bonds was significantly reduced, and the salaries of the population were preserved. This money was used to rebuild the post-war country. The abolition of cards ensured a decrease in market prices for many groups of goods and significantly reduced the number of speculators.

Optimization of Spectral Wavelets for Persistence-Based Graph Classification

A graph's spectral wavelet signature determines a filtration, and consequently an associated set of extended persistence diagrams. We propose a framework that optimizes the choice of wavelet for a dataset of graphs, such that their associated persistence diagrams capture features of the graphs that are best suited to a given data science problem. Since the spectral wavelet signature of a graph is derived from its Laplacian, our framework encodes geometric properties of graphs in their associated persistence diagrams and can be applied to graphs without a priori node attributes. We apply our framework to graph classification problems and obtain performances competitive with other persistence-based architectures. To provide the underlying theoretical foundations, we extend the differentiability result for ordinary persistent homology to extended persistent homology.

Non-Gaussian tail in the force distribution: a hallmark of correlated disorder in the host media of elastic objects

Inferring the nature of disorder in the media where elastic objects are nucleated is of crucial importance for many applications but remains a challenging basic-science problem. Here we propose a method to discern whether weak-point or strong-correlated disorder dominates based on characterizing the distribution of the interaction forces between objects mapped in large fields-of-view. We illustrate our proposal with the case-study system of vortex structures nucleated in type-II superconductors with different pinning landscapes. Interaction force distributions are computed from individual vortex positions imaged in thousands-vortices fields-of-view in a two-orders-of-magnitude-wide vortex-density range. Vortex structures nucleated in point-disordered media present Gaussian distributions of the interaction force components. In contrast, if the media have dilute and randomly-distributed correlated disorder, these distributions present non-Gaussian algebraically-decaying tails for large force magnitudes. We propose that detecting this deviation from the Gaussian behavior is a fingerprint of strong disorder, in our case originated from a dilute distribution of correlated pinning centers.