Additional opportunities for using computer technologies in expert analysis of laboratory data

The presented work reflects the author’s algorithm of mathematical processing and possible interpretations of the results obtained when creating expert analytical systems using computer technology. As initial parameters for the construction of neural networks of the second level, it is proposed to use individual results of calculations of the ratios of a number of laboratory indicators capable of forming a single functional cluster (leukogram, indicators of water-electrolyte balance, protein fractions, etc.). Further, using the proposed calculation algorithm and the archive database, structural features in the ′deformation′ of the ratio panel were compared against the background of the growth of each indicator, a matrix table was built reflecting the degree (correlation coefficients, KCr) of the coincidence of the features of the formation of the structure of the obtained panels of the parameters determined in individual observations. At high values of KCr, a conclusion is made about their (determined parameters) unified participation in the mechanism of emerging disorders. Thus, the system allows you to establish a leading complex of associated relationships by changes in the structure of ratios in the selected panel, corresponding to the dynamics of deviation of the target (analyzed) indicator, thereby differentiating the different mechanisms of formation of pathological deviations in this patient, the manifestation and balance of their values in the system-wide response, to evaluate the specific value of the absolute indicator as the final result of such interaction at the time of examination of the patient. The approach used, proposed by the authors, allows us to evaluate not only quantitative relationships, but also the features of the manifestation of the functional properties of the evaluated indicators. All of the above significantly expands the informativeness of the obtained laboratory data, allowing us to build a reasonable paradigm of the connections of the emerging complex of pathological disorders in each individual case. In the list of references, the authors cite publications as concrete examples of the use of the proposed approach in assessing a complex of disorders with different pathological processes using different panels in calculations.

Comparative analysis of the content of heavy metals in raw materials of some representatives of the genus Paeonia L.

Currently, heavy metals are considered as priority soil pollutants. It is known that the vegetative mass of agricultural crops is capable of accumulating them in large quantities. Ornamental flower crops, which firmly occupy their ecological niche, are practically not considered from this point of view. The aim of this work is to study the features of the accumulation of heavy metals in the aboveground and underground organs of some representatives of the genus Paeonia L. in the urbanized environment of the city of Ufa. The objects of research were seven taxa of Paeonia (P. peregrina Mill., P. lactiflora Pall., P. lactiflora f. rosea, P. delavayi Franch., P. × hybrida Appassionata, Mustai Karim, Jeanne d’Arc). Methodology. The study of the elemental composition of the aboveground and underground parts was carried out according to the method No. M-02-1009-05 atomic spectroscopy. Mathematical data processing was carried out using generally accepted methods of variation statistics using the AgCStat software package in the form of an Excel add-in. Scientific novelty. For the first time, different taxa and parts of Paeonia plants were taken for research. Results. It was revealed that in the studied samples the copper content is 4,15–2520,00 times higher than that of other elements. It is noted that the minimum concentrations of arsenic, cadmium, chromium, manganese and iron are noted in the roots; lead and nickel – in flowers; copper – in the leaves of the studied paeonies. The maximum content of arsenic, lead, chromium is found in the leaves; cadmium, nickel, manganese – in the stems; iron – in flowers. That is, cutting paeonies in the autumn before retirement avoids the accumulation of these microelements in the soil. The results of the correlation analysis showed that the absolute values of the concentrations of the studied elements in the considered taxa of paeonies correlate with each other to a weak and medium degree. Correlation study of pairs of elements makes it possible to assess the synergism of accumulation and its absence, which is consistent with the opinion of other authors.

Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics

We performed an EEG graph analysis on data from 31 typical readers (22.27 ± 2.53 y/o) and 24 dyslexics (22.99 ± 2.29 y/o), recorded while they were engaged in an audiovisual task and during resting-state. The task simulates reading acquisition as participants learned new letter-sound mappings via feedback. EEG data was filtered for the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands. We computed the Phase Lag Index (PLI) to provide an estimate of the functional connectivity between all pairs of electrodes per band. Then, networks were constructed using a Minimum Spanning Tree (MST), a unique sub-graph connecting all nodes (electrodes) without loops, aimed at minimizing bias in between groups and conditions comparisons. Both groups showed a comparable accuracy increase during task blocks, indicating that they correctly learned the new associations. The EEG results revealed lower task-specific theta connectivity, and lower theta degree correlation over both rest and task recordings, indicating less network integration in dyslexics compared to typical readers. This pattern suggests a role of theta oscillations in dyslexia and may reflect differences in task engagement between the groups, although robust correlations between MST metrics and performance indices were lacking.

Who Ordered That? Unequal-mass Binary Black Hole Mergers Have Larger Effective Spins

Hierarchical analysis of binary black hole (BBH) detections by the Advanced LIGO and Virgo detectors has offered an increasingly clear picture of their mass, spin, and redshift distributions. Fully understanding the formation and evolution of BBH mergers will require not just the characterization of these marginal distributions, but the discovery of any correlations that exist between the properties of BBHs. Here, we hierarchically analyze the ensemble of BBHs discovered by LIGO and Virgo with a model that allows for intrinsic correlations between their mass ratios q and effective inspiral spins χ eff. At 98.7% credibility, we find that the mean of the χ eff distribution varies as a function of q, such that more unequa-mass BBHs exhibit systematically larger χ eff. We find a Bayesian odds ratio of 10.5 in favor of a model that allows for such a correlation over one that does not. Finally, we use simulated signals to verify that our results are robust against degeneracies in the measurements of q and χ eff for individual events. While many proposed astrophysical formation channels predict some degree correlation between spins and mass ratio, these predicted correlations typically act in an opposite sense to the trend we observationally identify in the data.

Heterogeneous Preferential Attachment in Key Ethereum-Based Cryptoassets

In this study, we analyse the aggregated transaction networks of Ether (the native cryptocurrency in Ethereum) and the three most market-capitalised ERC-20 tokens in this platform at the time of writing: Binance, USDT, and Chainlink. We analyse a comprehensive dataset from 2015 to 2020 (encompassing 87,780,546 nodes and 856,207,725 transactions) to understand the mechanism that drives their growth. In a seminal analysis, Kondor et al. (PLoS ONE, 2014, 9: e86197) showed that during its first year, the aggregated Bitcoin transaction network grew following linear preferential attachment. For the Ethereum-based cryptoassets, we find that they present in general super-linear preferential attachment, i.e., the probability for a node to receive a new incoming link is proportional to kα, where k is the node’s degree. Specifically, we find an exponent α = 1.2 for Binance and Chainlink, for Ether α = 1.1, and for USDT α = 1.05. These results reveal that few nodes become hubs rapidly. We then analyse wealth and degree correlation between tokens since many nodes are active simultaneously in different networks. We conclude that, similarly to what happens in Bitcoin, “the rich indeed get richer” in Ethereum and related tokens as well, with wealth much more concentrated than in-degree and out-degree.

Diagonal Degree Correlations vs. Epidemic Threshold in Scale-Free Networks

We prove that the presence of a diagonal assortative degree correlation, even if small, has the effect of dramatically lowering the epidemic threshold of large scale-free networks. The correlation matrix considered is P h | k = 1 − r P h k U + r δ h k , where P U is uncorrelated and r (the Newman assortativity coefficient) can be very small. The effect is uniform in the scale exponent γ if the network size is measured by the largest degree n . We also prove that it is possible to construct, via the Porto–Weber method, correlation matrices which have the same k n n as the P h | k above, but very different elements and spectra, and thus lead to different epidemic diffusion and threshold. Moreover, we study a subset of the admissible transformations of the form P h | k ⟶ P h | k + Φ h , k with Φ h , k depending on a parameter which leaves k n n invariant. Such transformations affect in general the epidemic threshold. We find, however, that this does not happen when they act between networks with constant k n n , i.e., networks in which the average neighbor degree is independent from the degree itself (a wider class than that of strictly uncorrelated networks).

Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network

The blockchain technology introduced by bitcoin, with its decentralised peer-to-peer network and cryptographic protocols, provides a public and accessible database of bitcoin transactions that have attracted interest from both economics and network science as an example of a complex evolving monetary network. Despite the known cryptographic guarantees present in the blockchain, there exists significant evidence of inconsistencies and suspicious behavior in the chain. In this paper, we examine the prevalence and evolution of two types of anomalies occurring in coinbase transactions in blockchain mining, which we reported on in earlier research. We further develop our techniques for investigating the impact of these anomalies on the blockchain transaction network, by building networks induced by anomalous coinbase transactions at regular intervals and calculating a range of network measures, including degree correlation and assortativity, as well as inequality in terms of wealth and anomaly ratio using the Gini coefficient. We obtain time series of network measures calculated over the full transaction network and three sub-networks. Inspecting trends in these time series allows us to identify a period in time with particularly strange transaction behavior. We then perform a frequency analysis of this time period to reveal several blocks of highly anomalous transactions. Our technique represents a novel way of using network science to detect and investigate cryptographic anomalies.

The Influence of Actual Appraisals of Peers on the Self-Appraisals of Personality Traits for Chinese Late Adolescents: The Mediating Effect of Reflected Appraisals

Reflected appraisals refer to the perceptions of individuals of how they are perceived by others. Numerous studies in cultural psychology have revealed that individuals in the Eastern collectivist culture show an interdependent self-construal, which depends much on the social culture. Hence, the research on reflected appraisals in the Eastern culture can improve the understanding of how the social environment shapes the self-perception of an individual. In this study, we aimed to explore the relationships among self-appraisals, reflected appraisals, and actual appraisals of peers of the Big Five personality for Chinese late adolescents. Participants were divided into 16 groups, with two to four people of each group who were familiar with each other. Each participant was told to fill out the questionnaires of reflected appraisals, actual appraisals of peers, and self-appraisals. Through analyzing 164 sets of data, the results showed the following: (a) The scores of reflected appraisals are significantly lower than that of the actual appraisals of peers. (b) The relationships among the reflected appraisals, actual appraisals of peers, and self-appraisals are distinct on different personalities. For extroversion, there are significant medium- to high-degree relationships among the three types of appraisals; while for the agreeableness, conscientiousness, emotional stability, and openness, self-appraisals are highly correlated with reflected appraisals, and reflected appraisals show a low-degree correlation with the actual appraisals of peers. (c) Reflected appraisals play a mediating role between actual appraisals of peers and self-appraisals. Our study suggests that individuals in Chinese culture generally underestimate how their peers perceive them. Furthermore, actual appraisals of peers affect the self-concepts of individuals through reflected appraisals. This study revealed the unique personality feature of self-modesty under the background of Chinese culture and the importance of peers on the development of self-concepts for Chinese late adolescents. This study can shed new light on the understanding of the development of self-concepts for late adolescents under different cultural backgrounds.

Role of travel and tourism sector in the attainment of Vision 2030 in Saudi Arabia: An analytical study

Tourism is the main service industry significantly developing in the world. It is recognized as the critical factor in economic improvement in various countries. Saudi Arabia is one of the oldest and most famous spots for pilgrimage tourism due to its Islamic heritage. The study analyzes data available on the websites of the Saudi government to specify the contribution of travel and tourism revenue to the economy and its trend, occupancy of residential, and transportation capacity. A tourism satisfaction questionnaire was administered online to get the responses of Saudi nationals and residents related to tourism infrastructure, facilities, and other tourism services in Saudi Arabia. Ranks and percentage analysis were applied to get the relational satisfaction of tourists. Index numbers, ratios, percentages, and coefficient of variations were applied to get the trend, yearly fluctuations, variations, weights, and contribution of tourism avenues. There is a positive but low degree correlation between tourism revenue and the GDP of Saudi Arabia for the period from 2010 to 2018. The results indicate either negative or negligibly positive revenue growth of the accommodation/hotel services, food services, and air transportation. Two-thirds of tourists are either strongly satisfied or satisfied with essential and other tourism services and facilities in Saudi Arabia. Apart from tourist satisfaction, the Saudi government may consider a variety of services as per the economic level of the targeted tourists, and softening of visiting visa procedures and fees to enhance tourism revenue of major contributors for the positive and progressive development to the economy. AcknowledgmentThe authors would like to thank the Deanship of Scientific Research, Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia, for providing financial support to complete this project (Project No: 2020/02/16978).