Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated ...interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions &Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor's expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.
The fast and accurate prediction of Hansen solubility benefits many diverse fields such as pharmaceuticals, the food industry, and cosmetics. To estimate the individual HSP values (polar, dispersive, ...and hydrogen bonding components), we investigated the performance of using Mordred descriptors in multiple linear regressions and XGBoost modeling. For HSP predictions, we also tested a graph-based molecular representation with graph neural network (GNN) modeling. To select the optimal models for final training and predictions, we used nested cross-validation and hyper-parameter optimization. The models with the best predictive performance were selected through internal (R2train, RMSE, MEPcv) and external (RMSEP, CCC, MEP, R2test, ar2m, Δr2m) validation metrics using ∼1200 compounds from free-available database https://www.stevenabbott.co.uk. To confirm the practical reliability, we examined the agreement of experimentally obtained HSP data from the literature for 93 compounds and the data predicted by the created models. The results of GNN modeling showed the best predictive characteristics, which include a coefficient of determination between experimentally obtained and predicted HSP values greater than 0.76 for polar and hydrogen bond forces and greater than 0.66 for dispersive forces. Interpreting the fundamental basis of Hansen solubility using the created MLR equations and XGBoost models, HSP values were found to be influenced by van der Waals volume characteristics, 2D matrix molecular representation, and polarity. We elaborated on the practical benefits of using the selected GNN method through Hansen's solubility sphere as an example. This is the first study to demonstrate the advantages of GNN in predicting individual HSP components, as well as the first study to describe in detail their molecular basis using MLR and XGBoost modeling.
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•GNN, MLR and XGBoost modeling of three-dimensional Hansen solubility•Comparative analysis of the created QSRP models•Physico-chemical interpretation of the three-dimensional Hansen solubility•Demonstrating the practical applicability of the created models
Various mathematical frameworks play an essential role in understanding the economic systems and the emergence of crises in them. Understanding the relation between the structure of connections ...between the system’s constituents and the emergence of a crisis is of great importance. In this paper, we propose a novel method for the inference of economic systems’ structures based on complex networks theory utilizing the time series of prices. Our network is obtained from the correlation matrix between the time series of companies’ prices by imposing a threshold on the values of the correlation coefficients. The optimal value of the threshold is determined by comparing the spectral properties of the threshold network and the correlation matrix. We analyze the community structure of the obtained networks and the relation between communities’ inter and intra-connectivity as indicators of systemic risk. Our results show how an economic system’s behavior is related to its structure and how the crisis is reflected in changes in the structure. We show how regulation and deregulation affect the structure of the system. We demonstrate that our method can identify high systemic risks and measure the impact of the actions taken to increase the system’s stability.
Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel ...between locations: by direct observations that often involve privacy issues, e.g., tracking mobile phone locations, or by estimations from models. Typically, such models build on accurate knowledge of the population size at each location. However, when this information is not readily available, their applicability is rather limited. As mobile phones are ubiquitous, our aim is to investigate if mobility patterns can be inferred from aggregated mobile phone call data alone. Using data released by Orange for Ivory Coast, we show that human mobility is well predicted by a simple model based on the frequency of mobile phone calls between two locations and their geographical distance. We argue that the strength of the model comes from directly incorporating the social dimension of mobility. Furthermore, as only aggregated call data is required, the model helps to avoid potential privacy problems.
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•Ovomucoid CSP showed enantioselectivity for the separation of timolol enantiomers.•An enantioselective HPLC method was developed using AQbD methodology.•Achievement of a more ...ecologically friendly method than official one.•The validation studies confirmed adequacy of the method for its intended purpose.
Official method in Ph. Eur. for evaluation of timolol enantiomeric purity is normal-phase high performance liquid chromatography (NP-HPLC) method. Compared to other HPLC modes, NP is depicted as quite expensive with high consumption of organic solvents which leads to chronic exposure of analysts to toxic and carcinogenic effects. In order to overcome above-mentioned drawbacks, the aim of this study was to develop new method with better eco-friendly features. This was enabled by using protein type Chiral Stationary Phase (CSP) in reversed-phase mode that required up to 10 % (v/v) of organic solvent. Therefore, an enantioselective HPLC method was developed and validated for quantification of (S)-timolol and its chiral impurity, (R)-isomer. Optimized separation conditions on ovomucoid column were set using Analytical Quality by Design (AQbD) approach in method development. Optimization step was performed following the Box-Behnken experimental plan and the influence of three critical method parameters (CMPs) towards enantioseparation of the above-mentioned peak pair was examined. CMPs included variation of acetonitrile content in the mobile phase (5–10 %, v/v), pH value of the aqueous phase (6.0–7.0) and ammonium chloride concentration in the aqueous part of the mobile phase (10−30 mmol L−1). The most relevant critical method attributes (CMAs) in this case were the separation criterion between studied critical pair and retention factor of the second eluting peak, (S)-timolol. Qualitative Design Space (DS) was defined by Monte Carlo simulations providing adequate assurance of method’s qualitative robustness (π = 95 %). The selected working point situated in the middle of the DS was characterized by following combination of CMPs: acetonitrile content in the mobile phase 7 % (v/v), pH value of the aqueous phase 6.8 and concentration of ammonium chloride in aqueous phase 14 mmol L–1. In the next step, the quantitative robustness was tested by Plackett-Burman experimental design. The validation studies confirmed adequacy of the proposed method for its intended purpose. Finally, Analytical Eco-Scale metric tool was applied to confirm that developed method represents excellent green analytical method compared to the official one.
Purpose:This research shows how the perception of quality differs through the table egg chain and highlights the main quality characteristics for each studied chain participant (farm, retail, ...consumer).Design/methodology/approach:Observing the change in perception starts from the farm, through retail to the end consumer using the customer–supplier interaction, while looking back from the consumer to the farm, the application of the quality function deployment (QFD) was used. The study included 30 farms, 50 retail stores, 1,000 customers and 300 households.Findings:The farm–retail comparison highlights the type of production as the dominant factor affecting egg quality for both of these participants, followed by hen diet and the type of laying hen hybrid from the farmer's point of view, while retail focuses on packaging and egg damage. Egg quality aspects from the retail–household perspective emphasize the shell appearance and the origin of the eggs, while shelf life and egg class are equally important characteristics for both participants. The application of the QFD throughout the entire egg chain emphasizes quality vs price as the most important characteristic.Originality/value:This study could serve to food policy makers as an introduction to further research and production orientation in relation to the set of quality requirements associated with the egg supply chain.
In many complex systems, self-organised criticality (SOC) provides a mechanism for the diversity of spatiotemporal scales that optimises the system’s response to omnipresent driving forces. ...Signatures of SOC are increasingly more evidenced in collective social behaviours. However, the spontaneous occurrence of critical states and their role in maintaining the system’s functional properties still need to be better understood; the reason can be related to the complexity of human interactions and the ubiquitous presence of cycles in social dynamics. In this work, we shed new light on these issues based on a critical survey and the extensive data analysis of online social dynamics. Firstly, we highlight prominent features of human activity patterns, conditioned by circadian cycles and content-related interactions, that can affect the course of the dynamics from the elemental to the global scale. We then analyse the prototypal time series of emotion-driven communications in the online social network MySpace to demonstrate the coexistence of SOC states with the modulated cyclical trends. Precisely, we determine avalanches of emotional comments exhibiting multifractal scaling, scale-invariant inter-avalanching behaviours and temporal correlations coexist with the cyclical trends of broad singularity spectra. We demonstrate that similar multi-harmonic cycles occur in entirely different datasets, particularly the negative emotion-driven Diggs and the infection-rate data from recent epidemics. Our results reveal the dynamical regime where the modulated cycles coexist with self-organised critical states; in contrast, in the cycles-dominated regime, exemplified by the infection time series, the nature of collective dynamics remains hidden behind the cycle modulation.
•Avalanches of emotional comments in online social systems are multifractal.•In online systemsmodulated cycles coexist with self-organised critical states.•In epidemics spreading collective dynamics remains hidden behind the cycle modulation.
A specific feature of dyslipidemia in pregnancy is increased high-density lipoprotein (HDL) cholesterol concentration, which is probably associated with maternal endothelium protection. However, ...preeclampsia is most often associated with low HDL cholesterol, and the mechanisms behind this change are scarcely explored. We aimed to investigate changes in HDL metabolism in risky pregnancies and those complicated by late-onset preeclampsia. We analyze cholesterol synthesis (cholesterol precursors: desmosterol, 7-dehydrocholesterol, and lathosterol) and absorption markers (phytosterols: campesterol and β-sitosterol) within HDL particles (NCS
), the activities of principal modulators of HDL cholesterol's content, and major HDL functional proteins levels in mid and late pregnancy. On the basis of the pregnancy outcome, participants were classified into the risk group (RG) (70 women) and the preeclampsia group (PG) (20 women). HDL cholesterol was lower in PG in the second trimester compared to RG (
< 0.05) and followed by lower levels of cholesterol absorption markers (
< 0.001 for campesterol
and
< 0.05 for β-sitosterol
). Lowering of HDL cholesterol between trimesters in RG (
< 0.05) was accompanied by a decrease in HDL phytosterol content (
< 0.001), apolipoprotein A-I (apoA-I) concentration (
< 0.05), and paraoxonase 1 (PON1) (
< 0.001), lecithin-cholesterol acyltransferase (LCAT) (
< 0.05), and cholesterol ester transfer protein (CETP) activities (
< 0.05). These longitudinal changes were absent in PG. Development of late-onset preeclampsia is preceded by the appearance of lower HDL cholesterol and NCS
in the second trimester. We propose that reduced capacity for intestinal HDL synthesis, decreased LCAT activity, and impaired capacity for HDL-mediated cholesterol efflux could be the contributing mechanisms resulting in lower HDL cholesterol.
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